diff --git a/.codex-input/.gitignore b/.codex-input/.gitignore deleted file mode 100644 index 4d861b12..00000000 --- a/.codex-input/.gitignore +++ /dev/null @@ -1,3 +0,0 @@ -# Local AI/import workspace. Never commit generated inputs, databases, archives or screenshots. -* -!.gitignore diff --git a/.gitignore b/.gitignore index c4dd2870..4e08732d 100644 --- a/.gitignore +++ b/.gitignore @@ -19,27 +19,8 @@ build/ # Local source-transfer archives; preserve them outside version control. /frontend-src.tar.gz -# Large local data -/artifacts/* -!/artifacts/evidence/ -/artifacts/evidence/* -!/artifacts/evidence/accuracy/ -/artifacts/evidence/accuracy/* -!/artifacts/evidence/accuracy/P1/ -!/artifacts/evidence/accuracy/P1/** -!/artifacts/evidence/accuracy/P3/ -!/artifacts/evidence/accuracy/P3/** -!/artifacts/evidence/accuracy/P4/ -/artifacts/evidence/accuracy/P4/* -!/artifacts/evidence/accuracy/P4/runs/ -/artifacts/evidence/accuracy/P4/runs/* -!/artifacts/evidence/accuracy/P4/runs/p4-2.0.1-9677d0ef37db82bcf39b/ -!/artifacts/evidence/accuracy/P4/runs/p4-2.0.1-9677d0ef37db82bcf39b/** -!/artifacts/evidence/accuracy/P2/ -!/artifacts/evidence/accuracy/P2/** -!/artifacts/evidence/accuracy/model-training/ -/artifacts/evidence/accuracy/model-training/* -!/artifacts/evidence/accuracy/model-training/20260830-independent-ai-visual-review.json +# Generated evidence, model output and operational snapshots stay outside Git. +/artifacts/ /.cache/ /datasets/raw/* /datasets/processed/* diff --git a/.gitleaks.toml b/.gitleaks.toml new file mode 100644 index 00000000..e4855c00 --- /dev/null +++ b/.gitleaks.toml @@ -0,0 +1,13 @@ +[extend] +useDefault = true + +[[allowlists]] +description = "Public registry identifiers that resemble generic API keys" +regexTarget = "match" +regexes = [ + '''key="population_density_2019"''', + '''source_key="inbo_bwk_natura2000"''', + '''product_key": "population_density_2019"''', + '''key="spw_flood_hazard_2021"''', + '''key="phase2-mutation"''', +] diff --git a/CHANGELOG.md b/CHANGELOG.md index fa1b70e4..1765b8d7 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -1,3162 +1,24 @@ -# M13 — Codex Optimization Pack - -- Added reusable Codex skills under `skills/`. -- Added prompt discipline, token/context budget policy, secrets policy and parallel-agent strategy. -- Added M13 day-one optimized master prompt and pass completion report prompt. -- Added M13 validation script and included it in readiness checks. - # Changelog -## Unreleased - Post-V1 capability completion (2026-07-19) - -- Enabled the restricted guest demo by default whenever the operator login gate is active. Compose, Unraid, environment examples and backend defaults now agree; operators can still disable it explicitly with `GEOINTEL_GUEST_ACCESS_ENABLED=false`. - -- Implemented the supplied Stitch landing-page direction as the real React - entry surface, with responsive navigation, accurate Belgian/North Sea - product copy, a project-owned optimized hero asset, loading/error states and - a direct transition into the existing map-first workbench. -- Added an optional single-operator login gate with PBKDF2-SHA256 password - verification, signed HttpOnly/SameSite sessions, expiry, brute-force - throttling, logout and API middleware enforcement. Plaintext credentials are - never committed or returned to the browser; trusted direct-loopback operator - scripts remain available without introducing multi-user persistence. - -- Added the official WALOUS 2018 GeoTIFF as a third live-provisioned Walloon - land-cover epoch. Its stable SPW artifact, archive/raster checksums, EPSG:3812 - identity and published stacked class codes are validated fail-closed. The - official view-class crosswalk normalizes stacked codes to the existing - 11-class series, while source value `0` is explicitly treated as background - nodata and never contributes to area metrics. -- Exposed governed WALOUS rasters to the map evolution workspace and scoped - temporal-series choices to the selected persisted Area. The Wallonia golden - area now shows one unambiguous 2018/2020/2023 series instead of unrelated - acquisitions from other geometries. -- Added bounded Walloon terrain acquisition from the official SPW MNT - 2021-2022 1 m GeoTIFF. Operator provisioning validates archive bounds, safe - extraction, CRS, resolution, band count, elevation samples and checksums; - selection persistence and terrain metrics retain DNG/EPSG:5710 instead of - incorrectly labelling Walloon elevations as TAW. -- Made terrain readiness fail closed on both the source raster and its valid - SHA-256 sidecar, wrote provisioning evidence atomically, and corrected the - persisted acquisition interval to the canonical `period` granularity with a - stable spatial series key. -- Extended detection-model capabilities with machine-readable training scope, - validation scope, validated regions, national-validation status and the - operator-review requirement. The configured local model remains bound to - Mol/Kempen evidence and cannot become nationally labelled through frontend - copy alone. -- Completed live WALOUS 2020/2023 provisioning and fixed signed `int8` source - reads with nodata `-128` across acquisition, analysis and PNG rendering. A - dedicated regression now proves conversion to the persisted `uint8`/`255` - contract, and live PostGIS/API/browser checks confirm real Walloon overlays, - hectare metrics and two-epoch temporal comparison on the deployed image. -- Added operational Walloon WALOUS 2020/2023 land-cover analysis: an - allowlisted checksum-validating provisioner, bounded EPSG:3812 window - persistence, semantic hectare metrics, governed map rendering and raster - temporal comparison. The map acquires comparable configured editions for - the same selection so 2020-2023 evolution becomes available without manual - dataset administration. -- Corrected WALOUS to the official non-contiguous raster code set - `1,2,3,4,5,6,7,8,9,80,90`, including class labels, colours, semantic area - aggregation and exact SPW observation ranges. Live provisioning now rejects - unknown values without rejecting valid low woody-cover codes 80 and 90. -- Added the current legal SPW Walloon flood-hazard polygons as a bounded - authoritative vector product with class-aware hectare metrics and canonical - persistence. No WMS pixels or modeled depths are fabricated. -- Selected the official 1 m Walloon MNT after a live capacity audit and kept - the officially listed circa 198 GB 0.5 m distribution outside V1 because it - adds no required analytical capability and would require still more working - space during extraction. The MDK endpoint still fails strict hostname - validation and remains fail-closed rather than being presented as measured - North Sea bathymetry. -- Extended the bounded all-in-one PostGIS recovery wait to 15 minutes and the - immutable deploy health gate to 16 minutes. This prevents a large persistent - data directory from being terminated mid-recovery by the former two- and - three-minute ceilings. -- Removed the unconditional recursive ownership rewrite of the persistent - PostGIS data directory. Startup now changes only the root directory owner; - the official PostgreSQL entrypoint retains its targeted ownership checks. - -- Made `Belgium and North Sea Workbench` the unconditional frontend startup - context, moved the initial MapLibre viewport to national extent and removed - Mol/Kempen defaults from project/area forms and end-user source copy. Mol and - Kempen remain golden regression data only. -- Added bounded official UrbIS Land Cover products for Brussels using the - live-validated `urbisvector:Blocks` WFS layer: total land-cover blocks, - FO/GB forest and park blocks, and WB permanent-water blocks. Persisted - geometries retain source class codes and expose real hectare metrics. -- Restricted the production model-asset catalog to the explicit - `YOLO_MODEL_PATH` file so training/smoke checkpoints no longer pollute the - end-user selector. The Detection Lab now states the local Mol/Kempen - validation scope and explicitly warns that the model is not nationally - validated. -- Made national map source presentation zone-aware: broad Belgium work areas - now show a neutral official-per-region source contract instead of presenting - the last Brussels product as if it covered the country. The concrete source - is still resolved from the drawn selection before acquisition. -- Serialized release deployment and DockerMan container replacement with file - locks, and wait for asynchronous container removal to finish before starting - the replacement. This prevents concurrent repo deployments from leaving the - Unraid container in a half-removed state. - -- Implemented real local segmentation inference: `YoloSegmentationAdapter` and - `SamSegmentationAdapter` (ultralytics interface) run over existing raster - tile manifests, georeference mask polygons to EPSG:4326, suppress duplicate - masks by IoU, compute geodesic areas and persist `Segmentation` rows with - local-inference provenance. The segmentation model registry now reports - `yolo-seg-configured` and `sam-configured` dynamically from - `YOLO_SEG_ENABLED`/`YOLO_SEG_MODEL_PATH` and `SAM_ENABLED`/`SAM_MODEL_PATH`. - Everything stays fail-closed: no weights are downloaded automatically and a - missing file or dependency reports an explicit unavailable status. -- Implemented bounded MDK Belgian North Sea bathymetry acquisition - (`POST /datasets/bathymetry/mdk/acquire`): WCS 1.0.0 GetCoverage behind the - existing strict-TLS readiness probe. Acquisition requires explicit - `MDK_BATHYMETRY_ACQUISITION_ENABLED=true`, a coverage id advertised by the - live capabilities document, a bounded EPSG:4326 bbox, GeoTIFF validation via - rasterio and persists LAT vertical-reference provenance. The bathymetry - source registry now reports `acquisition_supported=true` with - `configured=false` until the operator opts in. -- Added the live-validated `urbis_street_axes` product - (`urbisvector:StreetAxes`, INSPIRE_ID identity, LineString geometry) so the - Brussels roads theme becomes operational through the existing bounded UrbIS - WFS engine. The live capabilities advertise no hydrography feature type, so - Brussels surface water intentionally remains `not_configured`. -- Extended `.env.example` with the new segmentation and MDK acquisition - variables and updated `docs/KNOWN_LIMITATIONS.md` and `docs/TODO.md`. - -### Functional audit fixes (beyond documented scope) - -- Runs can no longer be orphaned in `running`: rejected fixture payloads, - unexpected inference errors and the unreachable model fall-through in both - `DetectionService.run_detection` and `SegmentationService.run_segmentation` - now mark the analysis run and job `failed` before propagating the error, and - `JobService.run_sync_job` marks the job failed on unexpected non-AppError - exceptions as well (`tests/test_run_state_consistency.py`). -- `/api/v1/system/capabilities` no longer hardcodes `sam=false`; it reports - the real configured state of the SAM segmentation capability. -- `POST /exports/geojson` fails closed with `INVALID_EXPORT_REQUEST` instead of - silently returning an empty envelope when no export target matches. -- The segmentation workbench now auto-selects a configured non-fixture - segmentation model when one exists, mirroring the detection workbench. -- Runtime parity: `YOLO_SEG_*`, `SAM_*`, `SEGMENTATION_*` and - `MDK_BATHYMETRY_ACQUISITION_*` are now wired through `docker-compose.yml`, - `docker-compose.unraid.yml`, `deploy/unraid/run-dockerman-container.sh`, - `deploy/unraid/geointel.env.example` and the DockerMan template. Without - this the new segmentation and bathymetry features could never be enabled in - the deployed runtimes. Compose deployments now also reconcile interrupted - runs after a restart (`GEOINTEL_RECONCILE_INTERRUPTED_RUNS_ON_STARTUP=true`), - matching the Unraid runtime. Guarded by - `test_segmentation_and_mdk_acquisition_are_configurable_in_every_runtime` - and `test_compose_reconciles_interrupted_runs_after_restart_like_unraid_runtime`. - -## 1.0.0 - Final Belgium and Belgian North Sea release (2026-07-19) - -- Fixed rectangle analysis so it materializes and reads all applicable - official sources instead of acquiring only the active theme and labelling - every other result `Bron ontbreekt`. Provider work is bounded to three - concurrent requests, persisted artifacts remain reusable and real failures - are shown as load failures. -- Registered VMM VHA historical profile points as the operational bounded - Flemish bathymetry-adjacent source and added them to the map product - catalogue. Continuous depth and water volume remain explicitly unsupported. -- Live-smoked a Mol rectangle through NGI, Statbel, GRB, Flemish thematic - rasters, DHMV, VMM flood hazard, BWK, DOV and VHA, including persisted - Dataset output and semantic vector/raster metrics. -- Classified both `Gemeente ...` and release-golden `... municipality` Areas - as local scope so a full municipality analysis cannot accidentally invoke - regional raster partition assembly. -- Prevented rasters marked `coverage_scope=bounded_selection` from being - reused outside their acquired bbox. A small selection can therefore no - longer masquerade as a full-municipality space, forest, terrain or flood - measurement. -- Rebuilt the complete frontend presentation as the Stitch-guided GeoIntel - Atlas Workbench. The new shell uses one compact icon navigation rail, one - context bar and task-specific work surfaces across Map, Sources, AI - Questions, Quality, Image Analysis, Downloads, Status and Administration. -- Completed a screen-by-screen Stitch parity pass with dedicated designs for - Quality, Image Analysis, Downloads and Status/Administration. Sources, - Quality, Image Analysis and Downloads now use the same master-detail and - inspector structures as their Stitch references instead of generic panel - stacks. -- Bundled Public Sans and Manrope locally and aligned the implementation with - the exact Stitch canvas, context, ink, border, teal, steel and amber tokens. - No API, persistence, GIS or AI behavior changed. -- Restored the normal desktop map to one stable theme/map/insight row, made - the map absorb ultrawide space, bounded the mobile theme list and removed - the duplicate workspace command bar. API, database, GIS and AI behavior are - unchanged. -- Promoted the nationally federated, map-first GeoIntel workbench from the - release candidate to the final `1.0.0` version. -- Added a restrained final visual polish pass for the map-first workbench: - clearer step hierarchy, an in-row results rail on wide screens, improved - widescreen use and explicit mobile header/navigation behavior. No workflow, - API, database or GIS behavior changed. -- Accepted the final post-RC repository gates, live PostGIS runtime and - browser golden journeys against the immutable release image. -- Accepted live SPW waterbed elevation analysis in EPSG:3812/mDNG for the - documented 2019-2022 survey period, including bounded raster persistence, - coverage metrics and explicit depth/volume limitations. -- Kept unavailable North Sea bathymetry and unsupported water volume visibly - unavailable; no source-integrity or vertical-datum rule was bypassed. - -## National history and governed SPW bathymetry (2026-07-19) - -- Accepted the two documented official Statbel geometry-archive variants: - internal member names with or without the repeated `31370` token and - situation dates in ISO or `YYYY/MM/DD` notation. CRS, release-year, schema, - join, topology, total and checksum validation remain fail-closed. -- Prepared the official Statbel 2021-2024 national snapshots so the existing - 2025 Belgium population layer can become one consistent five-edition - evolution series. -- Added a pinned SPW bathymetry operator for the official 2023-05-23 - 0.5-m GeoTIFF release. It validates SHA-256, archive safety, EPSG:3812, - Float32, nodata and value bounds, reads through `/vsizip/`, creates only a - bounded COG and persists through the canonical Dataset API. -- Added persisted SPW bathymetry selection and PNG routes, with waterbed-height - percentiles in mDNG, surveyed hectares and coverage. Current water depth, - volume and vertical-datum conversion remain explicitly unsupported. -- Integrated ready SPW rasters into the Waterbodem map theme, MapLibre image - overlay, rectangle analysis and source portfolio while excluding analytical - bathymetry rasters from detection imagery. -- Kept MDK North Sea acquisition blocked behind strict TLS and official - low-resolution data-request prerequisites; no certificate bypass or - synthesized North Sea depth was introduced. - -## Post-RC Belgium data federation (2026-07-19) - -- Made persisted NGI administrative, RBINS marine reporting and Belgian - marine-plan layers first-class analytical map themes with source-appropriate - selection metrics and truthful workbench readiness. -- Extended the governed Statbel operator from regional scopes to one reviewed - national Belgium edition while retaining plan, stage, named review, - checksum-confirmed apply and Mol baseline gates. -- Added bounded SPW/PICC building, road and hydrography acquisition for - Wallonia and bounded UrbIS building/cadastral acquisition for Brussels. - Regional output remains split by authority and persists only through the - existing DatasetService/vector pipeline. -- Made map-source choice depend on resolved coverage zones rather than the - active technical project, including split handling for cross-region - selections. -- Revalidated MDK bathymetry and kept acquisition fail-closed because the - official hostname still presents a mismatched TLS certificate. No - water-volume or fabricated bathymetry metric was added. -- Added Docker, single-container Unraid and Dockerman template controls for - SPW/PICC and UrbIS. -- Fixed the governed Statbel review gate so a new probe timestamp does not - masquerade as a changed publication; release URL, identifier, version and - catalog content hash remain mandatory stable identity fields. -- Kept Statbel population materialization theme-specific so it can never be - reported as an NGI administrative boundary layer. -- Made bounded API coverage spatially honest: a persisted provider selection - is operational only for selections contained by its retained source bbox. -- Kept reusable persisted datasets ahead of on-demand catalog placeholders in - the workbench, so national Statbel 2025 population data is no longer - mislabeled as a 2019 thematic raster. Selection-bounded SPW/UrbIS results - remain available through the exact on-demand acquisition path. -- Made a changed work area take viewport priority over a complete national - layer, so switching between Belgium, Wallonia, Brussels and the North Sea - visibly centers the map on the selected geography. -- Removed transient MapLibre `isStyleLoaded()` gates after the initial - `style.load`, so raster tile activity can no longer discard later Area, - dataset, selection or QA overlay updates. -- Bounded the two-column responsive explorer row independently from the long - theme list. The live map canvas is now 723 by 496 CSS pixels at the audited - desktop viewport instead of an invisible 1,891-pixel-tall canvas, while the - theme list scrolls inside its own panel. -- Passed the complete post-RC live journey with all seven golden Areas, - historical forest comparison, persisted export, grounded local Ollama - context and configured local YOLO map handoff. Browser console errors and - failed requests remained empty. -- Closed the autonomous post-RC gate with 1,042 backend tests, 20 frontend - tests, typecheck/build and the complete Alembic SQL chain passing. - -## Autonomous Belgium and North Sea RC program (2026-07-17) - -- Expanded the release-candidate geography from Mol/Kempen to all of Belgium - and the Belgian North Sea while retaining the existing areas as golden - regression references. -- Added an executable autonomous RC-0 through RC-11 roadmap and explicit - national/maritime scope freeze. -- Replaced the minimal smoke-only CI with complete Gitea and GitHub release - gates for readiness, offline migration evidence, Docker configuration, - dependency audits, a digest-pinned container scan and an SPDX SBOM. -- Added a hashed Linux/Python 3.11 GIS/dev lock with an enforced input - fingerprint while keeping PyTorch and Ultralytics out of base CI. -- Completed live SBOM and vulnerability-policy evidence for the configured AI - image. The final runtime replaces the Postgres base image's Go `gosu` - executable with an audited `setpriv` wrapper; the complete report still - retains the shadowed base-layer findings while the executable policy gate - reports zero reachable fixed HIGH/CRITICAL vulnerabilities. -- Folded fresh-install, upgrade, rollback and runtime proof into RC-5 and - RC-11 instead of creating a separate RC-12 phase. -- Completed RC-7 response hardening across every successful JSON route with - concrete Pydantic/OpenAPI schemas and the canonical data envelope. -- Added an executable OpenAPI contract audit covering 124 implemented routes - and 228 component schemas. The eight explicit non-envelope operations are - limited to health probes, persisted raster PNG responses and export - download. -- Passed the RC-7 release gate with 1,008 backend tests, frontend - typecheck/build, one Alembic head and offline migration SQL generation. -- Added 12 executable frontend unit tests for map selection, coverage, - temporal comparison and workbench bootstrap behavior. -- Added deterministic provisioning for seven Belgium/North Sea golden areas: - Mol, Kempen, Wallonia, Brussels, the language boundary, the coast and the - offshore multi-zone scope. -- Added a Playwright release runner that proves governed metrics/provenance, - historical comparison, no-data, partial/unsupported coverage, provider - failure, persisted export, real local Ollama context and an explicit - configured-YOLO run against live PostGIS. -- Fixed explicit demo provisioning so an archived technical demo project is - reactivated and remains selectable instead of being silently reused while - hidden. -- Passed the RC-8 release gate with 1,012 backend tests, 12 frontend unit - tests, frontend typecheck/build, one Alembic head and a clean live E2E - console/request audit. -- Replaced false initial `Ontbreekt` theme states with an explicit loading - state while projects, Areas and Datasets are still resolving. -- Added measured 4-second coverage and 15-second persisted map-analysis - budgets with visible completion time and over-budget warnings. -- Added keyboard-correct analysis tabs, reliable skip-link focus, live status - announcements and an accessible interactive-map region. -- Expanded the national map workbench across ultrawide screens while retaining - zero page-level overflow at 390, 1366 and 2560 pixels. -- Added an RC-9 Playwright UX audit covering delayed bootstrap, every - top-level workspace, accessible control names, keyboard behavior, viewport - layout and visible coverage timing. -- Passed the local RC-9 gate with 1,015 backend tests, 16 frontend unit tests, - frontend typecheck/build and a clean three-viewport browser audit. -- Deployed immutable RC-9 image `9b0239747d1f12d0c5dd3b7fa2d03cf672884dbd-ai`; - the live three-viewport audit passed with zero horizontal overflow, - console errors or failed requests and verified truthful delayed loading, - keyboard behavior, accessible control names and visible timing feedback. -- Added an RC-10 read-only data-operations audit covering storage lifecycle, - disk pressure, persisted-path integrity, old failed work and - national/regional/maritime source families. -- Added dry-run-first orphan/cache cleanup with fail-closed path categories, - an explicit delete ceiling, exact confirmation token and a recent - checksum-verified database plus SHA-256 storage-backup requirement. -- Mounted release backups read-only at `/app/backups` and applied the same - backup/confirmation guard to the older demo-export cleanup path. -- Added a live RC-10 audit that proves critical table counts remain unchanged - across the storage report and cleanup dry run. -- Deployed immutable RC-10 image - `22fb8d51a9fde39552cf06a789174441631842b6-ai` and repeated the audit against - its live PostGIS runtime. It found zero missing direct database artifact - references, reported 2,002 bounded dry-run candidates (218,263,512 bytes), - retained all data and classified disk pressure as healthy. -- Separated 224 unavailable historical manifest intermediates from current - database-reference integrity: they remain visible provenance warnings and - cannot become cleanup candidates. -- Classified fixed NGI and RBINS national/maritime editions explicitly. The - live source-freshness report now records three current sources, zero due - sources and zero integrity issues. -- Assigned semantic release version `1.0.0-rc.1` consistently to backend - health, frontend package metadata and the OCI image version label. -- Added a fail-closed release-package builder that requires a clean tagged - revision, exact image revision, evidence inventory, SHA-256 checksums and a - verified detached SSH signature. -- Replaced stale Mol/Kempen product-boundary navigation with the active - Belgium/North Sea scope while retaining Mol and the Kempen as golden - regression areas. -- Added the final release runbook for immutable deployment, fresh install, - backup, isolated restore/upgrade, rollback, browser journeys, SBOM, - vulnerability policy, signed manifest and safe shutdown. -- Passed the RC11 pre-tag gate with 1,030 backend tests, 16 frontend tests, - frontend typecheck/build, one Alembic head, isolated fresh install, a full - SHA-256 storage backup and count-reconciled isolated restore/upgrade. -- Proved real rollback to immutable build `22fb8d5`, live PostGIS compatibility - and forward deployment back to `1.0.0-rc.1` without changing persistent - volumes or downgrading Alembic. -- Passed all seven Belgium/North Sea browser journeys and the 390, 1366 and - 2560 pixel UX audit with no console errors, failed requests or horizontal - overflow. -- Generated the SPDX SBOM and full container vulnerability report; the - executable policy reports zero reachable fixed HIGH/CRITICAL findings. -- Added a current known-limitations register covering federated source - coverage, bbox semantics, historical provenance, AI scope and operations. -- Added a read-only release-evidence manifest command with Git, migration, - dependency, configuration checksum and optional live endpoint evidence. -- Replaced the obsolete pre-build status with the current implemented - foundation and active release blockers. -- Added atomic PostgreSQL release backup, read-only checksum verification and - isolated generated-database restore-smoke tooling. -- Split health into process liveness and fail-closed readiness covering - PostgreSQL, PostGIS, Alembic head and writable storage. -- Made system capabilities report real PostGIS and configured local YOLO - state, added request IDs and exception logging, reduced SQL engine logging, - and terminalized impossible orphaned work after all-in-one restarts. -- Added non-logging PostgreSQL credential rotation with atomic `.env` update, - role update, managed-container restart and health verification. -- Completed a current secure Tower backup and isolated restore drill with - PostGIS, Alembic and critical table-count reconciliation. -- Removed every implicit first-raster fallback from Detection Lab; raster - selection is now an explicit operator decision in normal runs, guided runs - and calibration. -- Added fail-closed detection source and QA temporal compatibility checks. - Historical orthophotos marked unsupported cannot run through the current - model, and historical QA requires an overlapping reference validity period. -- Persisted the temporal compatibility decision in existing QualityCheck - parameters/findings and added correlated request, job, analysis-run and - quality-check logging. -- Added a read-only stale-runtime report plus an explicitly confirmed - reconciliation mode. -- Deployed immutable build - `a28f2497e8d0da7d108828875ba9ffedda3c1688`; live readiness now exposes the - exact build identity and reports PostgreSQL, PostGIS 3.6, migration - `202607160001`, storage and local YOLO as ready. -- Completed live Detection Lab acceptance with an intentionally empty raster - choice, disabled start action and zero browser console errors. No stale - running Job or AnalysisRun remained after reconciliation. -- Added a separate national coverage registry with normalized themes, legal - land/sea zones and only four honest states: `operational`, `partial`, - `not_configured` and `unsupported`. -- Added canonical coverage catalog/resolve endpoints. Drawn bboxes are - resolved against persisted Areas, cross-zone output stays split and - `operational` requires a matching ready Dataset. -- Added the explicit Belgium/North Sea operator with fixed official NGI/RBINS - allowlists, strict TLS, size limits, safe archive extraction, complete WFS - pagination, checksums and API-only persistence. -- Added national-workspace preference and a compact selection coverage surface - to the Map UI without removing Mol/Kempen regression workspaces. -- Local RC-4 validation passed 986 backend tests, frontend typecheck/build, - the full readiness gate, one Alembic head and complete offline migration SQL. -- Fixed fail-closed AdminVector GeoJSON serialization for Pandas timestamp - properties exposed by the live NGI GeoPackage. -- Hardened shared AOI geometry normalization to persist valid 2D polygons when - an authoritative source supplies harmless zero-valued Z coordinates. -- Kept map rectangle and full-area selection available for coverage inspection - when a selected national theme has not yet been materialized, without - querying an unrelated active dataset. -- Hardened the all-in-one release path with commit-SHA image tags, OCI build - labels, previous-image preservation, automatic/manual rollback, an isolated - fresh-install smoke and dependency-cache-safe build metadata. -- Bound immutable release tags to both commit and dependency profile - (`-ai` or `-gis`) and reuse matching images instead of rebuilding - or overwriting an existing release tag. -- Preserved the actual prior rollback image across repeated no-op deploys of - the same immutable release. -- Exposed every operator-owned all-in-one runtime limit and local YOLO setting - through advanced Unraid edit fields while keeping deployment-only bridge - variables internal. -- Added a fail-safe isolated upgrade smoke that restores a verified backup to - a temporary database, runs the release image migration chain and removes the - temporary database without touching production. -- Made production startup reject known-default PostGIS passwords and apply the - configured upload limit consistently to nginx and FastAPI. - -## Sprint 240 Operational forest, agriculture, nature and soil themes (2026-07-17) - -- Extended the governed Landgebruik Vlaanderen 2025 raster registry with - binary forest (class 12) and agricultural-use (classes 13 and 14) products. -- Added bounded INBO BWK/Natura 2000 and DOV soil acquisition with exact - `bbox intersection Area` clipping, complete provider pagination, hard - response/feature limits, checksums, request-identity caching and canonical - Dataset/VectorFeature persistence. -- Added end-user hectare metrics for forest, agricultural land use, biological - value classes, habitat shares and historical soil classes. PHAB-derived - hectares remain visibly estimated. -- Exposed all four themes through the existing Flanders map selection flow. - Provider calls remain backend-only and full-Flanders monolithic requests - remain outside the bounded safety limits. -- Prevented bounded municipality rasters from being labelled as complete - Flanders coverage; every governed thematic card remains `Op aanvraag` until - the active selection has a measured result. -- Kept source semantics explicit: land-use agriculture is not the definitive - ALZ parcel declaration series, forest is not a legal forest boundary or - biomass model, and DOV soil is a 1949-1971 historical baseline rather than - a current site investigation. - -## Sprint 239 Governed bounded GRB map acquisition (2026-07-17) - -- Added a fixed four-product GRB registry for buildings, roads, water and - administrative parcels through the official OGC API Features service. -- Added bounded acquisition with exact `bbox ∩ Area` clipping, complete - allowlisted pagination, response/feature limits, request and artifact - checksums, 24-hour identity cache and canonical Job/Dataset/VectorFeature - persistence. -- Added semantic selection metrics for building footprint, road length, water - area/supporting line length and parcel area without fabricating traffic, - legal-boundary or water-volume data. -- Extended the Flanders map catalog and all-theme analysis so the four GRB - products are usable on demand without browser-side external calls. -- Prevented a single bounded municipality Dataset from being presented as - complete Flanders coverage; GRB cards remain `Op aanvraag` until the active - selection has produced its measured result, and stale previously opened - vector features are not rendered behind an on-demand theme. The global - context bar also reports `Op aanvraag` instead of the previous Dataset's - feature count. -- Updated the provider registry to report the bounded GRB integration as - configured while keeping the old generic import/fetch contract non-fetching - and directing callers to the governed project endpoint. - -## Sprint 238 Governed Flanders terrain and flood selection (2026-07-17) - -- Unified the Flanders map selection flow behind one official-raster - acquisition contract covering the five policy rasters, DHMV and VMM flood - hazard without adding browser-side provider calls. -- Added explicit DTM/DSM and twelve-scenario VMM registry selectors. Products - are acquired only for the selected municipality or rectangle, persisted as - ordinary Datasets and reused by exact request identity. -- Made one cross-domain area run include measured terrain and scenario-bound - flood metrics alongside the existing policy and bathymetry results. -- Corrected the default VMM request key from the invalid - `pluvial_current_t100` spelling to the governed - `pluviaal_current_t100` product. -- Kept whole-Flanders raster acquisition behind the existing bounded-area - safety gate and retained explicit source semantics: DHMV is height in TAW, - while VMM flood depth is modeled hazard rather than current water level or - bathymetry. - -## Sprint 237 Bounded Flanders cross-domain profile (2026-07-17) - -- Exposed the five existing governed MercatorNet policy rasters as - `Op aanvraag` in the Flanders map workbench without adding a new provider or - browser-side external fetch path. -- Made one explicit municipality or rectangle selection acquire/reuse, - persist and analyse space occupation, open space, population density, node - value and service level through the canonical Job and Dataset services. -- Automatically selects the usable ruimtebeslag theme when the Flanders - workspace inherits an unavailable theme, and displays annual policy products - by their governed reference year instead of a timezone-shifted timestamp. -- Kept whole-Flanders raster acquisition disabled behind the existing 60 km - and 30 million cell guardrails while preserving complete-region vector and - partitioned bathymetry analysis. -- Corrected thematic Dataset metadata so a regional Area is no longer - mislabelled as municipality coverage merely because an `area_id` was used. -- Added source-contract and metadata regression coverage for the complete - on-demand flow. - -## Sprint 236 Flemish bathymetry partitions and safe North Sea probe (2026-07-17) - -- Added dynamic provisioning of the complete official VRBG Flemish - municipality inventory, validated at 285 current Areas. -- Added an atomic, resumable VHA profile coordinator and server-side manifest - finalization that prevents partial partitions from appearing regional. -- Added a strict-TLS, size-bounded MDK WCS GetCapabilities readiness probe - without coverage download or insecure fallback. -- Exposed truthful MDK readiness and bathymetry partition-finalization API - contracts and packaged all operator scripts in the all-in-one image. -- Provisioned the live Flanders workbench with all 285 current municipalities - and 128,913 VHA profile points across 269 data-bearing partitions; 16 - municipalities are explicitly recorded as having no profiles. -- Made frontend Area loading exhaustive and bounded the Area/Dataset catalogs - with search and pagination so complete regional workspaces remain usable. -- Made VRBG boundary labels coverage-aware so Flanders is never presented as - the Kempen transport region. -- Replaced the regional Waterbodem representative-Dataset shortcut with a - manifest-aware PostGIS selection across all intersecting VHA municipality - partitions. Exact municipality selection, full-Flanders counts, configured - metrics, GeoJSON and server-side exports now use the same governed path. -- Made the Waterbodem theme report the actual regional totals and partition - count instead of the feature/document count of one arbitrary municipality. -- Made the global context bar and visible workspace labels use the same - regional totals and end-user label `Vlaanderen (285 gemeenten)`; technical - project names and one-partition map counts no longer leak into the Map flow. -- Removed the Kempen-only browser title now that the same workbench also - operates at Flemish scope. -- Let the geographic explorer switch to its two-row desktop layout before the - navigation rail makes the three-column map surface overflow. - -## Sprint 235 Governed bathymetry profiles and Belgian scale architecture (2026-07-17) - -- Added bounded official VHA cross-section acquisition with exact Area - clipping, complete paging, checksums and ordinary Dataset/VectorFeature - persistence. -- Added nullable structured depth/width metrics, official profile-document - evidence and explicit unsupported volume semantics. -- Added a bathymetry source registry covering operational VHA profiles and - audited MDK North Sea, SPW Walloon and port candidates without pretending - those future connectors are configured. -- Added the `Waterbodem` Map theme and a concise profile inspector. -- Added the Mol operator command and a staged expansion roadmap for Flanders, - Belgium, the territorial sea, EEZ and continental shelf with strict - TAW/LAT/mDNG separation. - -## Sprint 234 Full audit closure and workspace lifecycle cleanup (2026-07-17) - -- Added reversible active/archived project lifecycle handling and made active - workspaces the default project-list contract. -- Added a dry-run-first, strict-allowlist operator command for archiving - benchmark, calibration and smoke-test projects while preserving all related - persistence and both canonical operational workspaces. -- Moved overview orchestration, detection model management and pure map helpers - into focused modules without changing API or persistence behavior. -- Reduced end-user noise across Map, Quality, Detection and Segmentation by - using Dutch task language and placing UUIDs, paths, checksums and runtime - diagnostics behind technical disclosures. -- Replaced persisted AI run/model/class/tile internals with friendly labels in - the ordinary result tables while retaining the original provenance in - persistence and technical views. -- Added widescreen layout guardrails for AI workspaces and regression coverage - for project lifecycle, packaged cleanup and the new component boundaries. -- Bounded the 15-theme selector on narrow mobile screens so the primary map - and result flow is no longer displaced by the complete theme inventory. -- Hardened the packaged archive command for direct container execution and - added a subprocess regression for the documented operator invocation. - -## Sprint 233 Operational correctness and result completion (2026-07-17) - -- Fixed the map-first contract so drawn/manual selections use `bbox ∩ Area` - consistently for vector, raster, temporal, derived-dataset and export paths. - The full-Area fast path is used only when the bbox covers the complete Area. -- Made vector-selection exports Area-aware and added a canonical server-side - map-result export for current vector/raster measurements and historical - comparisons. -- Changed the result handoff to persist the server-recomputed artifact before - opening Downloads; map analyses, evolution results and vector selections now - appear in the latest-download surface. -- Added exact-name project filtering and canonical regional-workspace lookup, - removing the dependency on the first 50 newest operator projects. -- Improved source failure messages, workspace scroll reset, map viewport - ergonomics, Detection Lab flow, QA score interpretation and Dutch download - terminology. -- Removed governed terrain, flood-hazard and thematic rasters from the - Detection Lab luchtbeeld selector while keeping them available on the map. -- Added focused regression coverage for selection scope, export persistence, - canonical workspace lookup and the usability guardrails. - -## Sprint 232 V1 user-flow completion (2026-07-17) - -- Completed the primary end-user handoff from map analysis to a usable result, - local AI question and downloads without exposing technical project or model - setup in the normal path. -- Added explicit metric names to the all-theme summary so values such as a - station water level are no longer shown without their measured meaning. -- Kept vector selections downloadable as GeoJSON and added JSON downloads for - governed raster analyses and complete historical comparisons. -- Added compact post-analysis actions for the local grounded Ollama assistant - and the existing Downloads workspace, preserving the active area context. -- Kept the map workspace mounted while visiting AI, Downloads or another - workspace so the selected theme, computed result and evolution comparison - remain available when the operator returns to the map. -- Replaced the accumulated TODO lists as the product roadmap with one current - V1 completion board; historical sprint checklists remain retained as - implementation evidence. - -## Sprint 231 Governed orthophoto release promotion (2026-07-17) - -- Added an operator-only `plan -> stage -> review -> apply` coordinator for one - bounded current Digitaal Vlaanderen orthophoto selection. It reuses and - revalidates the Sprint 230 catalog, WMS, WCS and flight-day preflight. -- Stage performs exactly one bounded allowlisted WMS `GetMap`, retains the raw - response, normalizes a three-band EPSG:31370 GeoTIFF and creates a PNG review - preview. Every source, raster, preview, request and preflight identity is - SHA-256-bound under persistent operator evidence. -- Review requires a named explicit approval. Apply requires exact plan and - review hashes, rechecks remote and local state, and uploads only the approved - GeoTIFF through the existing dataset upload/DatasetService transaction. -- Added an explicit first-baseline transition for legacy - `most_recent_at_*` markers. It requires both the exact legacy marker and the - official edition; no existing Dataset is rewritten or deleted. -- Made official `YYYY.NN` orthophoto Datasets take precedence over rolling - acquisition markers in source-catalog comparison. No API, migration, - scheduler, browser fetch or automatic refresh was added. -- Made staged, reviewed and applied release evidence write-once. An idempotent - apply validates and reuses the existing evidence instead of changing its - timestamp or authorization history. -- Made the read-only source-freshness audit prefer the governed official - `YYYY.NN` orthophoto edition over retained legacy `most_recent_at_*` labels, - while preserving the existing rolling-source review interval. - -## Sprint 230 Governed orthophoto release preflight (2026-07-17) - -- Added an operator-only, read-only preflight for the current Digitaal - Vlaanderen orthophoto product. It binds the canonical product and catalog - envelopes to exact official WMS capabilities and ISO edition evidence. -- Added metadata-only WCS `DescribeCoverage` validation for the governed - EPSG:31370, 15 cm, three-band `Ortho` raster domain and deterministic bounded - `Vliegdagcontour` sampling for selected-area flight-year evidence. -- Classified local official editions as current/update/baseline/remote-older - and kept legacy `most_recent_at_*` values explicitly non-comparable. No - raster pixels, Datasets, Jobs, migrations or automatic refresh were added. -- Added trust-boundary, hash-drift, product, coverage, flight-year, bounds and - runtime-packaging tests plus readiness compilation and operator docs. - -## Sprint 229 Governed ALZ definitive release promotion (2026-07-17) - -- Added an operator-only `plan -> stage -> review -> apply` coordinator for - future definitive ALZ agricultural-use parcel editions. A provisional v1/v2 - campaign snapshot remains visible release evidence but is never importable. -- Derived the exact archive identity from the allowlisted publication year and - date reported by the existing source-catalog probe. Arbitrary provider URLs, - current/older releases, catalog drift and changed staged bytes fail closed. -- Extended the existing agricultural provisioner to accept exactly one - explicitly governed future edition, validate final download identity, keep - streamed size bounds and read every paginated workspace Dataset consistently. -- Bound archive, normalized GeoJSON, GeoPackage schema/CRS, crop-code list, - scope totals and previous-edition deltas into named human review evidence. - Apply still creates only an immutable Dataset through DatasetService. -- Added focused trust-boundary, tamper, drift, approval, apply and packaging - tests without adding an API route, migration, scheduler or frontend action. - -## Sprint 228 Governed Statbel population release promotion (2026-07-17) - -- Added an operator-only `plan -> stage -> review -> apply` coordinator for - future official Statbel population editions. Plan is read-only, stage is - preflight/filesystem-only, review requires a named approval and apply - requires exact plan plus review SHA-256 values. -- Derived population and matching geometry URLs only from the allowlisted - catalog year/layout contract. Current, older, unavailable, ambiguous or - catalog-drifted releases fail closed; the coordinator accepts no arbitrary - provider URL and creates no scheduler or background fetch. -- Extended the existing population provisioner to accept one complete - explicitly governed future release, bound downloads before buffering and - discover the latest retained baseline across dynamically added years. -- Revalidated every source, manifest and snapshot byte immediately before the - canonical DatasetService upload. Dataset discovery now paginates completely, - preserving idempotence in workspaces with more than 200 datasets. -- Added focused release-state, trust-boundary, tamper, review and apply tests, - Docker packaging and readiness compilation without API or migration changes. - -## Sprint 227 Statbel population import compatibility preflight (2026-07-16) - -- Added a local, fail-closed preflight for staged official Statbel population - and matching statistical-sector archives. It validates exact source - identity, bounded ZIP contents, table/geometry schemas, REDEGEO layout, - EPSG:31370, situation date, geometry validity, scope coverage, joins and - reconciled national/scope totals before a new import is eligible. -- Replaced the historical sector-prefix municipality assumption with explicit - population/geometry municipality-field reconciliation, which supports the - 2025 REDEGEO municipal-merger contract without weakening identity checks. -- Accounted for official `ZZZZ` unlocated population separately from map-ready - sectors and bounded lossless `make_valid` normalization of reported source - topology errors. Both conditions are visible in the evidence manifest. -- Hardened the existing population operator to retain official source ZIPs, - atomically write derived evidence, require a passed manifest for new imports - and revalidate source plus derived SHA-256 values immediately before upload. -- Added negative regression coverage and packaged the preflight in the - all-in-one image and release readiness compile gate. No API, migration, - automatic import or existing Dataset was changed. - -## Sprint 226 Governed Statbel population edition probe (2026-07-16) - -- Extended the explicit read-only source catalog audit with the official - Statbel DCAT Turtle catalog and the latest uniquely identified Dutch - population-by-statistical-sector release. -- Added strict catalog, redirect, landing-page, license and distribution URL - validation with a separate 5 MiB bound. Distribution ZIP/XLSX files are - never downloaded and no Dataset is imported or replaced. -- Kept population year, statistical-sector geometry year and REDEGEO layout - separate. The 2025 new layout is current; the old-layout file is transition - evidence only, and 2026 sector geometry is not treated as 2026 population. -- Reused the canonical source-catalog envelope, cache, operator command and - Status UI, and propagated configuration through Compose and Unraid. -- Added RDF/Turtle parser, ordering, trust-boundary, size-limit, redirect and - no-distribution-fetch regression coverage without migrations. - -## Sprint 225 Governed ALZ edition probe (2026-07-16) - -- Extended the explicit read-only source catalog audit with the official ALZ - agricultural-use parcel publication page without adding an importer, - scheduler or background provider request. -- Added strict release-page, redirect and archive-link allowlists and bounded - HTML parsing; the probe never downloads the referenced ALZ ZIP archives. -- Normalized only definitive third snapshots as comparable editions, so local - `2025-definitive` evidence matches official `2025-v3` while current - `2026-v1` remains visibly provisional. -- Reused the canonical source-catalog envelope, Status UI and operator command, - and propagated the fixed release URL through Docker and Unraid runtime - configuration. -- Added focused release parsing, version ordering, cache, failure-isolation and - trust-boundary regression coverage without changing persistence or - migrations. - -## Sprint 224 Governed GRB evolution (2026-07-16) - -- Enabled fail-closed object evolution between the retained regional GRB - snapshots by validating official OGC feature identities, approved operator - provenance, completeness and collection-specific prefixes. -- Removed geometry-hash identity fallbacks from future regional GRB imports; - a provider feature without an official identity now aborts acquisition. -- Added explicit identity contracts to future buildings, roads, water and - parcel snapshots while retaining compatibility with the two already - persisted governed editions. -- Improved daily temporal labels and added a clear distinction between an - official registration change and the unknown date of a physical change. -- Documented a source-wide refresh-readiness matrix without enabling browser - fetches, schedulers, migrations or automatic Dataset replacement. - -## Sprint 223 Governed regional GRB refresh (2026-07-16) - -- Added a canonical, read-only regional GRB refresh plan for buildings, roads, - water and parcels, derived from the official catalog edition and persisted - temporal snapshots. -- Added an explicit operator coordinator with separate `plan`, `stage` and - SHA-256-confirmed `apply` phases. Staging validates every municipality - partition before PostGIS persistence is possible. -- Kept all provider URLs and collections allowlisted, reused the existing - resumable regional operators and DatasetService/VectorFeatureService import - path, and retained every older snapshot. -- Added compact Status UI, deterministic guardrail tests and readiness syntax - coverage without changing migrations or enabling automatic refresh. -- Fixed map theme ranking so a newer official observation always wins over an - older snapshot with a marginally larger feature count. -- Restored the active map theme from the selected dataset when returning to the - Map workspace, keeping viewport queries, legends and zoom guidance aligned. - -## Sprint 222 Official source edition probes (2026-07-16) - -- Added explicit, read-only GRB and most-recent orthophoto catalog probes using - official WFS/WMS capabilities and linked ISO 19139 CSW metadata records. -- Added bounded response sizes, timeouts, provider-isolated failures, a short - cache and strict metadata-host/path validation. No provider features, raster - pixels or application data are fetched or modified. -- Added canonical API, compact opt-in Status UI and operator CLI support. The - local source-freshness audit remains automatic and provider-free. -- Added deterministic XML/network-boundary tests and editable Compose/Unraid - controls without changing migrations or persistence contracts. - -## Sprint 221 Governed source freshness audit (2026-07-16) - -- Added a project-wide read-only source report derived from Dataset, - DatasetVersion and local storage evidence, with canonical API envelope. -- Classified rolling snapshots, annual releases, fixed editions, scenarios, - archives and local artifacts separately so historical publications are not - mislabeled as stale. -- Added integrity checks for missing versions, checksum disagreement, missing - local files and size mismatches without changing persistence or migrations. -- Added a compact frontend source-status panel and a packaged cron-compatible - operator command. Neither path contacts providers, downloads files or - performs automatic refreshes. - -## Sprint 218 Regional terrain and flood completion (2026-07-16) - -- Provisioned and audited the complete governed Kempen matrices: 56 DHMV - DTM/DSM rasters and 336 VMM flood-scenario rasters across all 28 approved - municipalities, each with one DatasetVersion and a non-empty checksum-bound - GeoTIFF. -- Bounded official WCS edge-grid rounding to at most 5%/0.25 m for DHMV and - VMM tile assembly, resampled accepted edge tiles to the exact 5 m analysis - grid and retained every source resolution and harmonized tile index in - provenance. Larger mismatches still fail closed. -- Added exact regional raster-selection endpoints. They open only intersecting - persisted municipality partitions, mosaic the selected windows in memory - and calculate global cell statistics under the existing 12-million-cell - guard; no monolithic or hidden authoritative raster is created. -- Updated the Map workspace to expose DHMV and VMM on the complete Kempen Area, - render all 28 matching MapLibre partitions, deduplicate VMM into twelve - scenario choices and analyse a drawn cross-boundary rectangle without first - selecting a municipality. -- Forwarded the active Area through drawn, coordinate, manual, temporal, - derived-dataset and full-workflow selections so every result remains clipped - to the chosen municipality or approved regional boundary. -- Preserved the distinction between DHMV height, modeled VMM scenario depth, - permanent water, bathymetry and concurrent flood volume. - -## Sprint 217 Regional DOV soil coverage (2026-07-16) - -- Added a governed regional DOV soil operator for all 28 approved Kempen - municipalities. It validates the official scope artifact, clips in Lambert - 72, retains deterministic gzip WFS responses and imports through the existing - DatasetService/vector-feature flow. -- Added NIS-suffixed persisted feature ids for source polygons split by - municipality boundaries, while retaining the original DOV source id in - provenance properties. -- Persisted one complete regional snapshot with 27,200 valid soil polygons - assembled from 62 source responses and 46,134 bounded source features. -- Kept the 1949-1971 survey period, 1:20,000 scale and historical drainage - limitation visible in map results and assistant context. -- Disabled preclipped metric shortcuts for the regional snapshot. Exact - PostGIS intersections remain mandatory because CRS round trips can create - negligible coordinate-rounding slivers at administrative boundaries. -- No migration, new endpoint, direct database write or current-soil claim was - introduced. - -## Sprint 216 Regional thematic coverage (2026-07-16) - -- Provisioned all five governed Departement Omgeving thematic rasters for all - 28 approved Kempen municipalities and for the complete persisted transport - region. The resulting 145 ready Datasets remain linked to exact Areas and - contain no duplicate area/product pairs. -- Raised only the thematic-raster acquisition envelope to the measured Kempen - extent: 60 km per side and 30 million output pixels. Official WCS reads stay - partitioned into fixed 10 km tiles; orthophoto, DHMV and flood limits were not - changed. -- Added bounded retries for interrupted or transient official WCS tile - responses. Partial bytes are never accepted and three failed attempts still - produce the canonical provider-unavailable error. -- Hardened the local assistant prompt so year, source and measurement quality - must remain attached to the same Dataset when one requested theme has - multiple official observations. -- Verified the complete regional map workflow against live PostGIS. A full - Kempen selection reports 45,126.87 ha space occupation, 97,375.81 ha open - space, an estimated 484,146.70 inhabitants from the 2019 density raster and - the persisted 2022 accessibility and service scores. -- No migration, live provider integration, synthetic metric or direct database - write was introduced. - -## Sprint 215 Grounded assistant cross-domain reliability (2026-07-16) - -- Raised the bounded local Ollama answer budget from 700 to 1,200 tokens after - a live Mol profile exhausted the smaller limit; `done_reason=length` remains - a hard error and incomplete text is still never returned. -- Required listed themes to be covered without adding unrelated themes and - kept cross-domain answers compact without weakening source, unit, estimate, - chronology or unsupported-metric rules. -- Exposed the output limit in the Unraid DockerMan template and aligned all - Compose, runtime, example and operator documentation defaults. -- Limited expensive PostGIS summaries to explicitly requested themes while - preserving full context for general overview/source questions. This keeps a - six-theme Mol profile from calculating unrelated agricultural subclasses. -- Provisioned the five official thematic products and the 1,159-feature DOV - soil map into Mol's Area in the central 28-municipality workbench, removing - the mismatch with the earlier standalone Mol project. -- Added deterministic semantic rounding for model context and normalized model - Markdown to the existing plain-text renderer so hectare, population and - score answers remain readable without exposing raw floating-point tails. -- Prevented an area-weighted population estimate from retaining model phrases - such as "official count" when its persisted metric is marked as estimated. -- Preserved Dutch sentence casing and word order when the estimate guard - rewrites contradictory population wording in a generated answer. -- Fixed the narrow-screen geographic explorer cascade so the theme selector, - map and results stack at their container width instead of retaining the - generic section grid and clipping the map horizontally. -- Recognized Dutch compound GIS terms such as `bodemdetails`, - `bevolkingsontwikkeling` and `perceeloppervlaktes` when selecting the - minimal grounded assistant context. -- Kept supporting object counts in the canonical response evidence but omitted - them from the model prompt whenever more meaningful area, length, population - or score metrics exist. This prevents a model typo from competing with the - authoritative semantic measurement. - -## Sprint 213-214 Cross-domain area profile (2026-07-16) - -- Implemented one allowlisted MercatorNet WCS registry for official Flemish - space occupation 2025, open space 2022, population density 2019, public - transport node value 2022 and total service level 2022 rasters. -- Added bounded tiled acquisition, exact Area clipping in EPSG:31370, raster - value/unit validation, checksummed Dataset/DatasetVersion provenance and - source-correct selection metrics without accepting arbitrary service URLs or - coverage identifiers. -- Added MapLibre image overlays, legends and current-state selection for all - five products. Raster cell values are presented as hectares, an explicitly - estimated population total/density or source scores, never as object counts. -- Grounded local Ollama answers in the persisted thematic measurements and - retained unsupported-current-count, live-timetable and causal limitations. -- Added the official DOV digital soil map as an explicit Mol operator. It - paginates all bounded `bodemkaart:bodemtypes` features, stores checksummed raw - evidence, clips exactly in Lambert 72 and imports through DatasetService. -- Added a Soil map theme with mapped hectares and inspectable soil type, - texture and drainage fields. The 1949-1971 survey period and 1:20,000 scale - remain visible; current drainage is never inferred. -- Added focused acquisition, GIS, analysis, API, AI-context, operator, - packaging and frontend-contract tests. No migration or direct database write - was introduced. - -## Sprint 212 Platform-wide official source portfolio (2026-07-16) - -- Rebalanced the source strategy across six user-facing domains: space and - buildings, nature and agriculture, soil and relief, mobility and - accessibility, population and services, and climate and living environment. -- Added a central frontend source portfolio with official catalogue links, - measurable outcomes, priorities and dataset matchers. A source is labelled - operational only when a matching ready Dataset really exists. -- Simplified the Sources inventory to six compact domain cards. Theme/time - detail, active-source limitations and the complete candidate list now use - progressive disclosure instead of competing for attention. -- Stacked the source heading, explanation and operational-status badge on - narrow viewports so the introduction remains readable on mobile. -- Expanded the Datavindplaats roadmap beyond hydrology with land use, space - occupation, soil, population, services, accessibility, business parks, - mobility hubs, cycle highways, heat and air quality. -- Recommended a governed allowlisted Mercator thematic-raster registry as the - next implementation wave so one safe acquisition path unlocks several - platform domains without arbitrary provider URLs or schema changes. - -## Sprint 211 Regional VMM flood-hazard provisioning support (2026-07-16) - -- Added `provision_regional_flood_hazards.py`, an explicit operator for the - approved 28-municipality Kempen scope that provisions official VMM - flood-depth scenarios per municipality Area through the existing canonical - flood-hazard API. -- Kept persistence inside the existing Dataset/DatasetVersion/Job raster flow; - no direct PostGIS writes, no browser-side provider fetches, no startup fetches - and no new schema/API contract were introduced. -- Added dry-run, member/product subset, resume/reuse and failure-reporting - controls so operators can validate Mol or selected municipalities before the - full 336 municipality/scenario matrix. -- Updated Unraid packaging, readiness checks, tests and docs. The semantic - limitation remains explicit: VMM water depth is modeled scenario depth, not - permanent water volume, current water level or bathymetry. -- Fixed live operator pagination to respect the canonical Area list limit and - verified the redeployed Tower runtime with a Mol `pluviaal_current_t100` - reuse/acquisition smoke. -- Added a Datavindplaats source roadmap for the next governed public Vlaamse - datasets: VHA waterlopen, afstromingskaart, bodem/erosion, ruimtebeslag/open - ruimte, morphology and accessibility/service-score layers. - -## Sprint 210 Regional BWK/Natura 2000 expansion (2026-07-16) - -- Added an explicit 28-municipality operator for the official INBO BWK/Natura - 2000 state-2025 WFS, reusing the governed Mol normalization and metrics. -- Added exact EPSG:31370 municipality clipping, partition-unique source ids, - deterministic gzip source evidence, checksum-bound cache reuse and one - canonical regional Dataset upload. -- Made map dataset selection prefer an exact Area snapshot over a broader - compatible layer and changed the source inventory to report overlapping - area snapshots without summing duplicate coverage. -- Added a matching ORM/Alembic municipality expression index for fast regional - fallback selection; live Mol and Geel reads now complete in 0.989 and 0.529 - seconds respectively. -- Provisioned the live 28-municipality Dataset with 72,933 valid EPSG:4326 - features from 147 retained source responses. Idempotency, checksums and the - single DatasetVersion were verified against PostGIS. -- Live map results now expose 138,701.35 ha BWK-mapped surface, 6,580.43 ha - Natura 2000 habitat and the governed BWK value classes across the Kempen; - Mol continues to use its exact 4,668-feature snapshot. -- Added focused GIS, persistence-contract, packaging and UI regression tests. - No API contract, AI model or product scope changed. - -## Sprint 209 Regional historical land-use expansion (2026-07-15) - -- Added an explicit operator for the official 1778, 1873 and 1969 historical - building, water and road land-use classes across all 28 approved Kempen - transport-region municipalities. -- Avoided the official WFS 10,000-result regional cap through resumable VRBG - municipality partitions, exact raw-response gzip retention and SHA256 - source/output manifests. -- Added exact municipality clipping, partition-unique evidence ids, bounded - feature limits and one canonical regional Dataset upload per theme/year. -- Extended the regional time-series coordinator and release packaging without - changing API contracts, database migrations or frontend architecture. -- Provisioned all nine snapshots on live Tower/PostGIS: 207,717 persisted - polygon features across three complete 28-municipality temporal series. - Every Dataset is ready, has one immutable DatasetVersion and was reused by - the idempotency run without duplicate persistence. -- Added the exact-area fast path for these already-clipped regional artifacts, - reducing complete-Kempen comparisons from minutes to 0.9-4.1 seconds in the - live audit while preserving the calculated values. -- Suppressed inapplicable generic line metrics for historical polygon classes; - results now show governed hectares plus object counts, never artificial - `0 km` road/watercourse measurements. -- Kept the top workbench source context synchronized with the selected - Evolution series. Browser verification covered complete Kempen, Mol and a - 3440 x 1440 viewport with no console warnings or errors. - -## Sprint 208 Governed VMM flood-hazard scenarios (2026-07-15) - -- Audited official water-depth and bathymetry sources and found no public, - municipality-wide inland bathymetry suitable for permanent Mol waterbody - volume; coastal and North Sea products are outside scope. -- Added a fixed twelve-product VMM OGRK WCS registry for fluvial/pluvial, - current climate/climate projection 2050 and T10/T100/T1000 depth scenarios. -- Added bounded tiled WCS 1.1 acquisition, multipart GeoTIFF extraction, exact - Area clipping, centimetre-to-metre normalization and immutable provenance - through existing Dataset, DatasetVersion and Job persistence. -- Aligned WCS tiles to the observed VMM 4.88 MB generated-coverage limit by - using provider-safe 5 km requests and retaining readable XML exception text. -- Added raster selection metrics for mapped inundated hectares/share, - mean/P90/maximum local modeled depth and a strictly named maximum-depth area - integral; permanent and concurrent water volume remain unsupported. -- Added a separate `Overstroming` map theme, scenario selector, transparent - MapLibre overlay, source inventory and source-grounded Ollama context. -- Added the full-Mol operator, Unraid/runtime settings, focused GIS/API/UI/AI - tests and documentation without a migration or new dependency. -- Provisioned all twelve official scenarios on live Tower/PostGIS. Each ready - Mol Dataset has one immutable DatasetVersion; a second operator run reused - all twelve without duplicate persistence. -- Browser validation confirmed the twelve-option scenario selector, raster - overlay, exact full-Mol metrics, no console errors or horizontal overflow at - 1280 px and 3440 px, and strict separation between surface water and flood - hazard themes. - -## Sprint 207 Governed DHMV II terrain foundation (2026-07-15) - -- Added a fixed official Digitaal Vlaanderen DHMV II DTM/DSM WCS registry, - rate-limited 10 km multipart GeoTIFF acquisition, georeferenced mosaicking - and exact persisted-Area clipping. -- Validates and retains native 1 m product identity, 5 m analysis resolution, - EPSG:31370, Float32 nodata, TAW, acquisition period and source/output - checksums through ordinary Dataset, DatasetVersion and Job persistence. -- Added exact raster-selection metrics for mean/min/max/P10/P90 height, relief - and slope, with explicit valid-cell coverage and computation methods. -- Added a Mol operator and a `Hoogte & reliëf` map theme with colour-relief - MapLibre overlay over the existing OpenStreetMap context. -- Explicitly keeps drainage as a future derived analysis and prohibits - presenting DHMV terrain/surface height as water depth or volume. -- Added runtime/Unraid configuration and focused acquisition, GIS formula, - persistence, API, frontend and packaging tests without a migration. -- Live Mol DTM/DSM provisioning now persists 4,581,867 valid 5 m cells per - product with complete Area coverage and immutable cache reuse. Browser - validation confirmed the MapLibre relief overlay and full-Area metrics. -- Scoped the orthophoto building-recognition prompt to the building theme so - terrain results remain focused on elevation, relief and slope. - -## Sprint 206 Governed Buildings and Addresses Register snapshot (2026-07-15) - -- Added an explicit operator for the current official Digitaal Vlaanderen - building, building-unit and address OGC collections with complete pagination, - safety limits, retries and retained raw SHA256 evidence. -- Hardened completeness against the production address service's omitted - `next` link by continuing full pages with an explicit `startIndex` until a - short terminal page is observed. -- Added exact EPSG:31370 Area clipping, EPSG:4326 building persistence and - classified reconciliation against checksummed persisted GRB partitions. -- Persisted only building lifecycle data and aggregate unit/address counts; - full addresses, street names and house/box numbers remain outside queryable - output, and ambiguous address/GRB relations are never forced. -- Added exact footprint, lifecycle, unit, address-status and confirmed-GRB - selection metrics, including correct filtered `feature_count` execution. -- Made the Map workspace prefer the richer Mol register snapshot only for the - matching Mol Area and retain regional GRB coverage everywhere else. -- Added source-inventory presentation, runtime packaging and focused operator, - privacy, reconciliation, metric and UI tests. -- Live Mol validation retained 43,945 exact building polygons, 30,382 units - and 21,388 unambiguous address relations. It found a 98.45% realized-building - GRB match rate, zero invalid geometries and zero prohibited address fields. - -## Sprint 205 Governed agricultural-use parcel history (2026-07-15) - -- Added an explicit ALZ operator for the definitive 2008-2025 annual - agricultural-use parcel archives, with a fixed source allowlist, streamed - size limit, ZIP safety checks and EPSG:31370 schema validation. -- Retained official archives, annual crop-code lists and checksum manifests; - exact scope clipping produces ordinary Dataset/vector_feature persistence - only through the existing upload service. -- Added a separate Agriculture map theme with exact declared-use hectares and - server-owned official main-crop-group hectare metrics. -- Added a scope-specific 18-edition temporal series while explicitly disabling - parcel-level lineage and excluding the provisional current campaign. -- Added focused source, clipping, metric, pagination, packaging and UI tests. -- Added compatibility for the official comma-separated grain and horticulture - group labels after live source validation exposed their exact wording. -- Replaced internal agriculture/BWK/Waterinfo source identifiers with concise - authority labels in the shared end-user dataset display path. - -## Sprint 204 Governed BWK and Natura 2000 for Mol (2026-07-15) - -- Added an explicit operator for the official INBO BWK/Natura 2000 state 2025 - WFS with complete link/start-index pagination, retained raw page checksums and - exact Mol clipping in EPSG:31370. -- Preserved original BWK evaluation, mapping-unit, origin, habitat, percentage - and habitat-origin fields while adding readable, source-faithful properties. -- Added filtered PostGIS selection metrics for each official BWK value class, - Natura 2000 habitat shares, regional biotopes and uncertain habitat gaps. -- Added Nature Value as a seventh map theme and moved BWK/Natura 2000 from the - follow-up catalogue to loaded evidence only after a real Dataset exists. -- Kept the 2025 edition honest: it is a map state rather than one uniform 2025 - survey, and PHAB-based partial-selection hectares remain labelled estimates. - -## Sprint 203 Governed hydrology and historical imagery (2026-07-15) - -- Added an explicit Waterinfo KiWIS operator for annual water-level and - discharge station histories. It filters against the persisted Area, retains - raw JSON/checksums and imports each real station/year through DatasetService. -- Added numeric `mean` selection aggregation for station measurements while - keeping every station in an independent temporal series with an explicit - point-versus-area/volume limitation. -- Added a fixed official orthophoto product registry covering current, annual - 2012-2025, older winter periods, RGB 1979-1990 and panchromatic 1971. -- Added historical raster temporal provenance, a constrained browser PNG - endpoint and a MapLibre image overlay/product selector. -- Kept configured-YOLO/current-GRB QA exclusive to the most-recent product; - historical imagery never produces fake current-state quality metrics. -- Converted BWK/Natura 2000, agricultural parcels, Buildings Register, DHMV - and bathymetry into an ordered acceptance-criteria backlog. -- Made the frontend dataset client exhaust canonical 200-row pages. Real - Waterinfo persistence pushed the regional project beyond the old 50-row - default and exposed that older sources otherwise disappeared from the UI. -- Restored the source inventory as a full-width, naturally flowing overview - band after the premium desktop grid rules had compressed it into a narrow, - internally scrolling column. - -## Sprint 202 Source intelligence, full evolution metrics and local assistant (2026-07-15) - -- Extended temporal comparisons with exact persisted-Area filtering, every - compatible semantic metric and a complete observation timeline. -- Expanded the official 2013-2025 land-use operator to derive water, built - functions and transport surface alongside forest from one retained 10 m - source raster per year. -- Added a source inventory that distinguishes loaded datasets from official - follow-up sources such as historical orthophotos, BWK, agricultural parcels, - the Buildings Register, DHMV and Waterinfo. -- Added a source-grounded local GIS assistant through Ollama. The backend lists - only installed models, supplies persisted GeoIntel metrics as context and - refuses to infer unavailable values such as water volume. -- Added editable Unraid environment/template settings and a Docker host-gateway - mapping for the Ollama service running on the server. -- Added an explicit 16,384-token Ollama context window and reject truncated - `done_reason=length` responses instead of showing an incomplete answer. -- Tightened generated answers to descriptive source evidence: estimates must - remain labelled, unsupported causal/forecast claims are forbidden and plain - text is requested for the existing chat renderer. -- Added deterministic estimate disclosure for population answers and instructed - the local model to copy governed values literally instead of inventing - averages, rates or derived trends. -- Clarified the source inventory so current GRB layers are shown as a different - methodology beside, rather than as part of, the comparable 2013-2025 land-use - time series. - -## Sprint 201 Semantic area-selection metrics (2026-07-15) - -- Replaced count-only primary results for known regional themes with meaningful - PostGIS measurements: building footprint, forest, water and parcel area in - hectares; road and watercourse length in kilometres; and population in - inhabitants. -- Kept intersecting feature counts as supporting evidence and added an additive - metric list without removing the existing primary summary fields. -- Added explicit source limitations: building footprint is not floor area or - volume, road length is not traffic capacity and water volume is unavailable - without reliable depth or bathymetry. -- Updated future regional GRB provisioning metadata so new imports persist the - semantic primary aggregation directly. - -## Sprint 200 Operational time-series handoff (2026-07-15) - -- Removed the dead-end Evolution state that appeared when the current building - theme had only one regional snapshot while real historical series existed. -- Evolution now opens the first available persisted series automatically and - loads its latest snapshot on the map. -- Theme cards distinguish genuine multi-snapshot series from current-only - sources, including observation counts and year ranges. -- Confirmed the deployed PostGIS temporal path with a real Statbel 2021-2025 - comparison; no synthetic values or parallel frontend calculations were added. - -## Sprint 199 Reviewed accuracy expansion (2026-07-15) - -- Added six leakage-free training AOIs in Arendonk, Dessel, Meerhout, Laakdal, - Nijlen and Hulshout, backed by 9,964 paged GRB building references. -- Exported and audited a 252-tile, 79,192-label corpus; the configured audit and - balanced 64-tile visual review found no invalid, missing or low-variance - selections. -- Fine-tuned one inactive local YOLOv8s challenger for 20 CPU epochs without - downloads. Its best checkpoint SHA256 is - `038f1f97a6afd534f29e1f392a730a58207b928ca01e31ab8d8fed6106705820`. -- Re-ran active and challenger models through the same current persisted QA/QC - pipeline on four Mol and three regional holdouts. The challenger improved - mean F1 from `0.6069` to `0.6248` and improved every zone. -- Retained the active model because the challenger produced two detections in - empty Postel-bos; the active profile remained zero across all three empty - controls. No runtime model or `.env` setting was changed. -- Replaced stale Detection Lab profile averages with coverage-aligned active - evidence: precision `0.6141`, recall `0.6062`, F1 `0.6069`. - -## Sprint 198 Evidence-closed model review (2026-07-15) - -- Completed visual and geometric review of 48 persisted false-positive and 48 - false-negative cards from Geel, Herentals and Turnhout. Only 5 FP and 10 FN - records were confirmed model errors; 59 records were QA alignment effects and - 22 were reference, imagery or uncertainty cases excluded from training. -- Added a symmetric fail-closed false-negative decision validator and readiness - compilation gate. It exports only explicit confirmed misses and rejects - incomplete, mismatched or invalid decision sets. -- Packaged the validator in the all-in-one Unraid image and covered that runtime - file contract with the existing Docker configuration regression. -- Audited the confirmed evidence against the active tile corpus and holdouts. - Geel/Herentals evidence already belongs to the training source and Turnhout - remains excluded, leaving zero novel leakage-free labels. No model was - trained, downloaded, activated or reconfigured. -- Clarified map quality output with strict match counts and the existing - diagnostic reference-envelope match, without changing canonical QA metrics. -- Live Mol proof measured 282 candidates, 209 strict matches, precision 74.1%, - recall 68.5% and F1 71.2%; 212 diagnostic envelope matches made the remaining - three possible box/footprint differences explicit. - -## Sprint 197 Measured detection accuracy and durable review (2026-07-15) - -- Re-ran the active local building model at confidence thresholds `0.10` and - `0.15` over independent Mol holdouts in Achterbos, Gompel, Donk and Postel, - plus the pure-empty Postel forest control. Threshold `0.15` retained the best - F1 in every positive zone and both thresholds produced zero forest-control - detections, so no speculative threshold or model promotion was made. -- Aligned the map-driven building QA flow with the documented operational - footprint match IoU `0.25`. The map now reports candidate count, matches, - precision, recall, F1, false positives and false negatives instead of - presenting every model box as a recognized building. -- Added first-class `detection_reviews` persistence and canonical project QA - endpoints for paginated false-positive/false-negative review decisions. -- Added a focused frontend review queue with role/status filters, notes, - pagination and map handoff. Unreviewed or alignment-mismatch evidence cannot - silently become hard-negative training data. -- Bounded QA evidence resolution to the persisted evidence identifiers instead - of loading complete regional reference datasets into application memory. -- Added regression coverage for migration alignment, decision validation, API - envelopes, bounded evidence access and the map QA threshold. -- Passed the complete readiness gate with 592 backend tests, 88 documented API - routes, one Alembic head and a green frontend typecheck/production build. -- Live browser validation caught and fixed cramped map-result metric cells; - quality values now use a readable two-column layout and the map legend calls - unverified model output `AI-kandidaten`. - -## Sprint 196 Map-driven official orthophoto analysis (2026-07-15) - -- Added an explicit bounded endpoint for the official Digitaal Vlaanderen - most-recent winter orthophoto WMS, with EPSG:31370 georeferencing, 128-1,024 - metre side limits, response guards, exact-request reuse and complete - Dataset/DatasetVersion provenance through DatasetService. -- Connected a drawn map rectangle to one building-analysis action: official - raster acquisition, canonical tiling, active local YOLO inference, persisted - detections, existing GRB QA and MapLibre output. -- Kept all fetches user-triggered and backend-only. No startup fetch, - browser-side WMS call, model download, direct persistence write or fabricated - detection/QA value was introduced. -- Added Docker/Unraid controls and focused service, CRS, persistence, - safety-bound and canonical-envelope regressions. -- Scoped the acquisition guard to the approved Kempen regional boundary while - retaining the selected municipality as a map filter, and translated known - acquisition/model failures into concise Dutch operator feedback. -- Proved the complete flow live on Tower: one 244 x 207 orthophoto request, - one immutable DatasetVersion, one configured-YOLO run with 78 persisted - detections and one persisted six-metric GRB quality check. At IoU 0.50 the - run measured precision 0.5641, recall 0.3761, F1 0.4513 and mean IoU 0.6622. - -## Sprint 195 Guided raster-to-detection workflow (2026-07-14) - -- Replaced the Detection Lab's manual manifest-path prerequisite with one guided action that creates canonical 512 px raster tiles with 64 px overlap, reuses an existing manifest, validates raster size and the local YOLO runtime, runs persisted detection and loads the persisted GeoJSON result on the existing MapLibre map. -- Added direct, explicit georeferenced GeoTIFF upload in Detection Lab through the existing dataset upload boundary; no browser-side provider fetch, model download or alternate persistence path was introduced. -- Kept manual manifest execution, model assets, preflight and calibration available under technical/management disclosures while making persisted detection QA a primary user step. -- Added clear preparation progress, understandable Dutch QA diagnostics, result-to-map navigation and focused regression coverage. -- Did not change API contracts, database migrations, model dependencies or backend inference behavior. -- Live Mol validation persisted 1,953 configured-YOLO detections from nine georeferenced tiles and exposed a regional QA scaling defect before release. -- Detection QA now applies the persisted tile coverage through the existing GiST-indexed PostGIS geometry column before loading reference rows, while retaining the complete reference population in audit counts. -- The unchanged exact IoU matcher now uses a Shapely spatial index to avoid testing geometries whose envelopes cannot intersect. -- Clarified the primary map source and legend whenever an AI result is active so detections are never presented as the underlying official GRB source. -- Made the fixed workbench context bar follow the active AI layer and exposed the IoU match threshold beside every detection-QA score. - -## Sprint 194 Regional official time-series synchronization (2026-07-14) - -- Generalized the proven Statbel population operator from a hardcoded Mol import to an approved geographic scope while keeping Mol as the backwards-compatible default. -- Added one explicit regional synchronization command for official 2021-2025 population and 2013-2025 modern forest snapshots. -- Added resumable municipality-partitioned WCS retrieval and native-resolution raster mosaicking after the upstream service rejected the complete regional response at its documented size limit. -- Kept every fetch operator-triggered, idempotent and behind the canonical DatasetService upload path; no startup fetch, migration or API contract change was introduced. -- Preserved separate Mol/regional series keys and honest partial-sector population and 10 m forest-area limitations. -- Replaced internal provider identifiers with readable source labels in the primary map. -- Added a provenance-gated full-Area query path for official pre-clipped datasets, avoiding redundant intersection of every feature against the same detailed municipal/regional boundary while preserving exact rectangle selection behavior. -- Reduced a live complete-Kempen population/forest analysis from roughly 92 seconds to 2.8 seconds of API work while retaining the exact official totals. -- Grouped dated population and forest snapshots into one current source plus an optional historical disclosure, translated remaining user-facing status/download/model-evaluation text and made municipality selection explicitly optional. -- Replaced the last primary-map `features`/`PostGIS` delivery message with a plain Dutch zoom instruction and user-facing object counts. -- Added focused scope filtering, command construction, boundary resolution, multi-NIS provenance, full-Area correctness, temporal-language and frontend-label tests; the full readiness gate now passes with 571 tests. - -## Sprint 193 End-user regional workbench simplification (2026-07-14) - -- Made the complete `Kempen Regional Workbench` the automatic fresh-session data context and removed the redundant region selector from the primary map. -- Kept all available regional datasets loaded while treating Mol, the other 27 municipalities and the complete region as spatial work-area filters. -- Replaced technical dataset names with theme/source labels and moved benchmark projects, raw source metadata, provider internals, QA evidence and model diagnostics behind advanced disclosures. -- Defaulted Detection Lab to the configured local YOLO asset, active local model profile and measured operating threshold; model quality remains explicitly review-required rather than presented as production-perfect. -- Simplified Quality, Downloads, Status and Beheer around end-user tasks without changing API contracts, migrations, persistence or inference behavior. -- Followed the live browser audit by moving the legacy Mol-only workspace under advanced management, adding friendly regional-boundary dataset names, translating the active model profiles and replacing the empty `waiting` quality status with end-user language. -- Completed the visible-language sweep for the details control, export preview and provider layer names. - -## Sprint 192 Regional map state correctness (2026-07-14) - -- Fixed the map-first work-area selector so changing from the complete Kempen region to a municipality clears the old bbox, theme totals and result geometry before switching Areas. -- Invalidated outstanding single-theme and multi-theme selection requests on reset, preventing a slow previous-area response from restoring stale results after a scope change. -- Replaced the hardcoded viewport instruction for `buildings` with the active dataset's reference layer name. -- Added focused state/race/status regressions and passed the complete 556-test release gate plus frontend typecheck/build. -- Deployed commit `7997a72` and verified the exact Kempen-to-Mol switch, a fresh 33,038-parcel Mol result, a 525-feature PostGIS detail viewport, clean browser logs and no horizontal overflow at 1280x720 or 3440x1440. - -## Sprint 191 Regional Kempen GRB context foundation (2026-07-14) - -- Added one explicit regional operator for current GRB roads, water and parcels, with independent resumable municipality partitions and one normal PostGIS dataset per theme. -- Preserved official source geometry dimensions across `Wegsegment`, `WTZ`, `WLAS`, `WGR` and `ADP`; collection-qualified source IDs prevent collisions inside the combined water layer. -- Assigned cross-boundary polygons by maximum overlap area and lines by maximum overlap length, with deterministic NIS-code tie breaking and clipping only to the complete approved region. -- Reused DatasetService, VectorFeatureService, immutable dataset versions, exact selection aggregation and existing Area/bbox APIs; no API contract, migration or direct vector-feature write was added. -- Added truncation guards, atomic manifests, checksum reuse, duplicate rejection, Docker packaging, readiness compilation and focused geometry/persistence tests. -- Documented source semantics honestly: road objects are not traffic data, heterogeneous water objects are not volume metrics and ADP is not a legal cadastral survey. -- Kept all source access operator-only; the browser, startup path and public `not_configured` GRB provider perform no external fetch. -- Provisioned the live Tower snapshot: 84,504 roads, 88,332 water objects and 415,288 parcels across 28 complete partitions per theme; immediate repeat runs reused all artifacts and datasets. -- Verified exact manifest/PostGIS/distinct-ID parity, valid non-empty EPSG:4326 geometries, one immutable DatasetVersion per snapshot and canonical full-region/Mol Area selection responses. - -## Sprint 190 Regional Kempen GRB buildings (2026-07-14) - -- Added an explicit regional GRB building operator that fetches the approved Kempen scope in 28 resumable municipality partitions and follows every OGC API pagination link. -- Assigned boundary-crossing GRB features to exactly one partition using maximum municipality intersection, with deterministic NIS-code tie breaking and one retained source identity. -- Added a covered-by-member fast path so ordinary interior buildings avoid the regional boundary-owner scan while true border cases retain the exact overlap rule. -- Added streaming artifact copy and batch-wise partition indexing through `DatasetService` and `VectorFeatureService`, avoiding one giant multipart parse while preserving one normal regional dataset for existing map and PostGIS selection flows. -- Added truncation guards, source/checksum manifests, immutable observation dates, duplicate-source rejection and focused service/operator tests. -- Kept the provider endpoint contract unchanged and retained explicit operator-only fetching; no source request runs during application startup or interactive map use. -- Provisioned the live 2026-07-14 regional snapshot on Tower: 466,078 unique GRB buildings from 879 source pages, 28 retained municipality partitions and one 478,143,249-byte managed artifact with `reference_truncated=false`. -- Added optional persisted-Area filtering to the existing vector-selection contract so a full municipality or regional work area uses its exact PostGIS polygon instead of counting surrounding bbox corners. -- Verified exact live selections of 36,941 buildings for Mol and 466,078 for the complete transport region, plus an interactive rectangle query and a 730-feature detail viewport with no browser errors or horizontal overflow. - -## Sprint 189 Official Kempen operational scope (2026-07-14) - -- Defined `Kempen` operationally as the official 28-municipality Vlaamse vervoerregio, with an explicit warning that this policy boundary is not the wider cultural or landscape Kempen. -- Added a central operator scope registry with current municipality names and NIS codes, including Mol `13025` and Nijlen `12026`. -- Added an explicit, idempotent VRBG scope provisioner that creates one regional boundary, 28 member boundaries, one regional Area, 28 municipality Areas and canonical source datasets through the existing API. -- Added a compact Mol/Kempen region selector to the map-first explorer and made its heading and full-area action scope-neutral. -- Made region switches clear all project-bound state, ignore stale project-data responses and prefer the regional boundary/AOI, preventing Mol context from leaking into the Kempen workbench. -- Kept thematic regional ingestion separate from the boundary pass so large GRB/WCS sources can be partitioned and validated without hidden startup fetches or truncated datasets. -- Provisioned and verified the complete boundary foundation on Tower: 29 Areas, two canonical VRBG datasets, idempotent reruns, correct Mol/Kempen switching and a clean 1280/3440 px browser audit. - -## Sprint 188 Official modern Mol land-use series (2026-07-14) - -- Added an explicit, reusable MercatorNet WCS operator for official Departement Omgeving land-use snapshots in 2013, 2016, 2019, 2022 and 2025. -- Validated categorical integer GeoTIFF input at 10 m in EPSG:31370, retained raw rasters/checksums/manifests and polygonized only documented class 12 (`Bos`). -- Imported forest polygons through the existing DatasetService/VectorFeatureService path with canonical EPSG:4326 geometry and hectare intersection metrics; no startup fetch or direct PostGIS write was added. -- Kept the modern 2013-2025 series separate from historical 1778/1873/1969 cartography and added a compact temporal-series selector when both are available. -- Made the map-first forest theme prefer the authoritative modern source and its latest 2025 snapshot while preserving historical access. -- Added focused raster, CRS, class, provenance, packaging and frontend contract tests plus readiness compilation coverage. -- Provisioned all five snapshots in the live Tower/PostGIS workspace and verified idempotent reruns, canonical provenance and full-Mol temporal selection. -- Aligned MapLibre layer and legend colors with the selected data theme and let the primary geographic explorer use the full available ultrawide width. - -## Sprint 187 Temporal Mol explorer (2026-07-14) - -- Added first-class temporal dataset metadata and immutable dataset-version provenance for uploaded and derived vector/raster datasets. -- Added project temporal-series discovery and bounded snapshot comparison APIs with explicit observation dates, metric deltas, warnings and optional stable-identity object changes. -- Extended bbox selection with source-governed PostGIS aggregations so population is reported as inhabitants and land cover as intersected hectares instead of misleading feature counts. -- Added a calm Latest state/Evolution flow to the map-first explorer, including period selection, metric comparison and added/removed/modified overlays where source identities support them. -- Added explicit operator provisioners for official Statbel Mol population snapshots (2021-2025) and Digitaal Vlaanderen historical land-use snapshots (1778, 1873 and 1969); no source is fetched during application startup. -- Preserved methodological honesty: partial statistical sectors are labelled area-weighted estimates, historical land-use identity changes are not fabricated and all source URLs, versions and processing limitations are persisted. -- Serialized Tower startup and migration-smoke validation by waiting for container health, preventing concurrent Alembic upgrades from racing on the same PostGIS schema. -- Normalized valid source Z coordinates to the canonical 2D PostGIS vector store while retaining the original uploaded GeoJSON and reporting the source Z-feature count in metadata. -- Made vector dataset, version and feature persistence one transaction, with file cleanup on rollback, so an indexing error cannot leave a ready dataset without persisted features. -- Hardened MapLibre resizing and responsive fit behavior so the Mol boundary and road basemap fill the complete GIS stage on standard and 3440x1440 ultrawide viewports. -- Completed live browser validation of full-municipality, rectangle and temporal population flows against the deployed Tower/PostGIS runtime with no console errors. - -## Sprint 186 Map-first Mol geographic explorer (2026-07-14) - -- Replaced the default dashboard entry with a calm map-first workflow: choose a real data theme, drag a rectangle, query PostGIS automatically and review results. -- Kept the previous technical map, QA, export and AI controls available behind the advanced workbench instead of mixing them into the primary path. -- Added explicit source availability for buildings, population, forest, water, roads and parcels; unavailable themes never receive simulated values. -- Added true drag-to-select behavior in MapLibre and exact total intersection counts alongside the bounded 1,000-feature map preview. -- Made the official full Mol municipality area and the largest authoritative building layer the initial map context. -- Added an idempotent operator provisioner for official Mol GRB roads, water and parcels through the existing API/DatasetService/PostGIS persistence flow. -- Prevented stale asynchronous dataset-detail responses from replacing the latest selected map layer and its visible context. -- Kept GeoJSON download/copy actions attached to the active theme result when switching themes after a rectangle analysis. - -## Sprint 185 Coverage-aware Mol operational benchmark (2026-07-14) - -- Extended real detection quality-matrix evidence with persisted inference coverage, raw/evaluated/excluded/clipped populations and diagnostic-only box-to-footprint mismatch counts. -- Preserved municipality, operational-zone, split and source-reference metadata in combined multi-sample summaries. -- Added a fail-closed Mol benchmark report that groups exact model/tile/overlap/threshold candidates and gates four independent positive holdouts plus a pure-empty background control. -- Kept canonical footprint-IoU metrics authoritative and made model-quality rejection a reported evidence outcome rather than a hidden runner failure or automatic model mutation. -- Added readiness, all-in-one image and focused pass/reject regression coverage without changing APIs, migrations, inference behavior or dependencies. -- Executed the active small-building model over Achterbos, Gompel, Donk and Postel plus the Postel-bos pure-empty control: mean F1 `0.5975`, minimum zone F1 `0.4749`, micro F1 `0.6338` and zero background detections. -- Accepted the active candidate for bounded operator use after evaluating 3,624 of 3,829 raw references; kept 205 outside-coverage references and 101 box-to-footprint diagnostic matches explicit rather than inflating canonical metrics. -- Exported 7,078 persisted evidence features, audited 1,381 false negatives and 1,211 false positives, and rendered 96 balanced review cards across all four zones with no missing source tiles. - -## Sprint 184 Detection QA coverage and matching diagnostics (2026-07-14) - -- Clipped configured-YOLO candidate and reference QA populations to the union of the exact persisted inference tile footprints before canonical IoU matching. -- Added fail-closed validation for missing, invalid or cross-dataset tile-manifest provenance while retaining the existing unbounded behavior for explicit fixture and legacy runs without a manifest. -- Kept precision, recall, F1 and mean IoU strictly based on candidate polygons versus persisted reference footprints; added a separately labelled reference-envelope comparison as diagnostic evidence only. -- Persisted raw/evaluated/excluded/clipped population counts and diagnostic matching evidence in the existing `quality_checks.findings_json` structure without changing migrations or canonical metric rows. -- Surfaced inference coverage and box-to-footprint diagnostics in Detection Lab and hardened the real-data workflow assertions, documentation and regression coverage. -- Live Tower/PostGIS validation on the persisted Mol-center run evaluated 304 of 374 GRB references, excluded 70 outside the inference tile, persisted six canonical Metric rows and exposed 14 possible box-to-footprint artifacts without inflating the strict scores. -- Updated the API contract audit to use the canonical OpenAPI path map after FastAPI 0.139 introduced grouped top-level routers; this keeps all 81 operations audited across clean framework installations. -- Kept Starlette on its supported pre-1.0 compatibility line until GeoIntel deliberately migrates its test client from `httpx` to `httpx2`; this removes the new framework deprecation warning without taking an unrelated test-stack upgrade. -- Upgraded the build-only frontend toolchain to Vite 7.3.6 and React plugin 5.2, declared the Node 20.19+/22.12+ engine contract and reduced `npm audit` from one high plus one moderate finding to zero without changing React, MapLibre or runtime behavior. - -## Sprint 183 Mol map source clarity and live AI validation (2026-07-14) - -- Added an explicit Database/Analysis result map-content mode so an automatically loaded detection result can no longer mask a newly selected persisted municipality layer. -- Kept the Map workspace database-first and made dataset selection switch back to the selected PostGIS layer without discarding available detection, segmentation or change-analysis results. -- Restored the premium UI's viewport status row so visible/total feature counts and the 1,000-feature truncation warning remain readable. -- Rebuilt and deployed the all-in-one Tower runtime, then passed PostGIS 3.6 connectivity, schema/index, single-head migration, frontend proxy and browser runtime checks. -- Ran the bounded Mol-center raster -> tiles -> configured YOLO -> persisted Detection -> GRB QA -> export chain against the live runtime: 36 detections, 17 matches, precision 0.4722, recall 0.0455, F1 0.0829 and mean IoU 0.5958. These honest metrics confirm the workflow while keeping the current model below production-quality acceptance. - -## Sprint 182 Municipality viewport delivery and bounded AI handoff (2026-07-14) - -- Replaced full-file loading for vector datasets above 5,000 features with debounced, zoom-aware requests to the existing persisted PostGIS bbox-selection endpoint. -- Kept each viewport response bounded to the canonical 1,000-feature maximum and made zoom-required, loading, visible/total, truncation and error states explicit in the Map workspace. -- Prevented viewport responses from repeatedly fitting the map back to their own bounds while preserving AOI framing and existing behavior for small vectors, detection/segmentation results, selections and QA evidence. -- Hardened the real raster/detection/QA operator smoke so it can reuse a validated existing project, attach both uploads to a persisted analysis Area and apply safe distinct upload filenames. -- Added focused contract and frontend-wiring regression coverage. No migration, model dependency, provider fetch behavior or persistence schema changed. - -## Sprint 181 Complete Mol municipality workspace (2026-07-14) - -- Added an explicit operator provisioner for the official Digitaal Vlaanderen Mol municipality boundary (NIS `13025`) and the complete GRB GBG building population clipped to that boundary. -- Added auditable source artifacts and a manifest with page count, checksums, exact WGS84 bounds, municipality area, feature totals and truncation state; incomplete pagination now fails closed. -- Declared EPSG:4326 explicitly in both official GeoJSON artifacts so downstream QA does not downgrade known OGC provenance to an inferred CRS. -- Added bounded exponential retries for safe official-source GET requests after a live transient GRB page failure; upload POST requests are never retried automatically. -- Provisioning remains explicit and imports Project, Area and Dataset records through existing canonical API routes and DatasetService/VectorFeatureService persistence rather than writing directly to PostGIS. -- Made the complete `Mol Municipality Workbench` the preferred fresh-session context and the official municipality boundary its lightweight default layer, ahead of historical Postel validation projects. -- Replaced large coordinate arrays and spread-based bounds calculations with streaming, memoized GeoJSON bounds so municipality-scale vector layers remain safe in MapLibre. -- Removed per-feature ORM refreshes after vector import while retaining one flush and commit, avoiding tens of thousands of redundant queries for full-municipality datasets. -- Added focused municipality clipping, truncation, persistence-scaling, runtime wiring and frontend-priority regression coverage. No migration or API contract changed. - -## Sprint 180 Premium workbench UX hardening (2026-07-14) - -- Rebuilt the workbench presentation hierarchy around grouped task navigation, a compact Mol context header and an optional selection-detail drawer instead of a permanent third column. -- Fixed the narrow-screen shell so navigation is horizontal and the active workspace receives the full viewport width; desktop and ultrawide content now use stable, centered work areas. -- Reworked Overview into one operational status band, one workflow rail and compact quick actions without changing readiness calculations or routing. -- Made Data operational with three bounded project/AOI/dataset columns, scroll-safe populated catalogs and progressively disclosed create/upload forms. -- Made Map controls and MapLibre the primary surface while collapsing provenance, BBox inputs and raw feature inspection into explicit detail disclosures. -- Made AI Labs task-first by placing detection/segmentation run controls before model-registry diagnostics and collapsing registry/preflight detail. -- Added focused UI regression coverage; no API contract, migration, persistence, GIS operation, QA metric, model dependency or inference behavior changed. - -## Sprint 179 Mol detection evidence diagnosis (2026-07-13) - -- Added a read-only, storage-confined false-negative contact-sheet renderer that projects persisted missed GRB geometries onto the exact source tile manifest recorded by the analysis run. -- Added AOI/area-stratified review selection, nearby persisted candidate/reference overlays, explicit manual decision CSVs and separate GeoJSON evidence for references outside inference-tile coverage. -- Added focused rendering, manifest-resolution, decision-default and path-confinement regression coverage plus all-in-one/readiness wiring. -- Completed explicit Donk/Postel visual review: QA alignment dominated 37/48 false-positive and 27/48 false-negative samples; only 7 and 6 respectively were confirmed model errors. -- Found 41 of 638 Donk/Postel false-negative evidence records outside all persisted inference tiles and kept coverage-adjusted recall as a diagnostic only; persisted QA metrics were not changed. -- Recorded a NO-GO for immediate retraining. QA population clipping and box-to-footprint matching diagnostics are the required next pass. - -## Sprint 178 Mol multi-zone operational validation (2026-07-13) - -- Added documented Mol center, Achterbos, Gompel, Donk and Postel operator zones with municipality and operational-zone provenance. -- Protected the four new positive zones as validation holdouts; they are not silently eligible for model training. -- Hardened real-data quality workflows to persist manifest-backed EPSG:4326 Areas and Mol project regions alongside datasets and analysis evidence. -- Added a single Mol operator runner that composes existing positive QA/QC and background detection-pressure workflows without fake metrics or model downloads. -- Made the all-in-one runner's default evidence output persistent under `/app/storage/operator-evidence` and fixed manifest path handling in multi-sample aggregation. -- Added all-in-one image/readiness wiring and focused regression coverage; APIs, migrations, model activation and frontend behavior remain unchanged. - -## Sprint 177 Mol-first operating context (2026-07-13) - -- Made Mol the explicit primary operating focus while retaining the broader Kempen as the validation and interoperability region. -- Added one centralized frontend focus definition for the empty-map center, new-project region, default AOI and persisted project/dataset recognition. -- Initial workbench selection now prefers real persisted Mol data without overriding an explicit current or newly created project selection. -- Moved Mol to the front of default operator sample preparation and added AOI slugs to future detection quality-matrix project names. -- Kept APIs, migrations, persistence, providers, AI dependencies and model behavior unchanged. - -## Sprint 176 Detection false-positive visual review gate (2026-07-13) - -- Enriched existing QA evidence GeoJSON with persisted detection and segmentation provenance without changing its endpoint or canonical envelope. -- Added a read-only, storage-root-confined false-positive contact-sheet renderer with deterministic AOI/area/confidence stratification and persisted reference overlays. -- Candidate-centred crops preserve non-square edge-tile aspect ratios and limit reference overlays to the local review context. -- Added an explicit five-state operator review contract; incomplete reviews fail the completion gate and no decision is inferred. -- Exported only manually confirmed model false-positives as possible review input, keeping reference gaps, QA alignment issues and uncertain cases separate. -- Added focused provenance, visual rendering, path-confinement, incomplete-review and confirmed-export regression coverage plus all-in-one/readiness wiring. -- Kept database migrations, model activation, inference, training and provider behavior unchanged. - -## Sprint 175 Detection result scale and false-positive evidence review (2026-07-13) - -- Bounded Detection Lab table rendering with client-side 25/50/100-row pagination while preserving the complete persisted detection set for MapLibre and QA/QC. -- Compacted source-tile cells to filenames while preserving full persisted paths in tooltips. -- Added a strict read-only false-positive evidence audit with role-count drift checks, polygon validation, WGS84 geodesic areas, size buckets, AOI/class/tile summaries and combined review GeoJSON. -- Audited the active seven-AOI portfolio: 5,568 false positives among 13,613 candidates, median geometry area 184.5 m2, and 25.8% below 100 m2; Turnhout, Herentals and Geel carry the largest review volumes. -- Recorded that existing QA evidence has no per-detection confidence values; the audit reports zero confidence coverage and does not infer scores from the run threshold. -- Kept API contracts, database migrations, model activation, provider behavior and inference behavior unchanged. - -## Sprint 174 Focused small-building model promotion (2026-07-13) - -- Expanded the real operator corpus with four focused training AOIs and two independent validation AOIs, while keeping Turnhout, Retie and Westerlo outside the tile-training corpus as operation-level holdouts. -- Exported and visually audited 198 tiles with 58,820 real GRB-derived labels; the accepted corpus contained no invalid labels, missing files or low-variance review selections. -- Trained `geointel-building-yolov8s-smallbld-minpx3-img640-ft30-pt` from the previous active local model without downloading weights; the trained asset SHA256 is `a9088b8491dfae36694b53e9e9406cb4e3511d334a5712fa34f75078a47759c1`. -- At tile `512`, overlap `64`, threshold `0.15` and QA match IoU `0.25`, seven persisted AOIs reached mean precision `0.5898`, recall `0.5770`, F1 `0.5825` and minimum F1 `0.5528`; all three pure-empty controls remained at zero detections. -- Fixed-reference evidence reduced false negatives from 7,753 to 6,182, including 745 fewer 25-100 m2 misses and 181 fewer sub-25 m2 misses. Precision is lower, so the UI states the increased false-positive review load explicitly. -- Added persistent false-negative area summaries/GeoJSON, explicit tile-corpus sample selection provenance, missing runtime evaluation scripts, Docker COPY-source regression checks and warning-free Pydantic model-field schemas. -- Fixed ultrawide two-panel workspaces so AI Labs, QA/QC and Exports use the available main width instead of leaving empty third/fourth columns, and decoupled backend README edits from the expensive all-in-one GIS/AI dependency cache layer. -- Guarded activation updated only the Tower AI/model environment values; no fake outputs, provider fetching, API contract or database migration changed. - -## Sprint 173 Expanded building model promotion (2026-07-13) - -- Trained and fully gated the inactive `geointel-building-yolov8s-aoi1024expandedminpx4vis035e50-pt` candidate from the 20-source expanded real-data corpus. -- The recommended `512` tile / `64` overlap / `0.15` confidence profile reached mean precision `0.6471`, recall `0.4700` and F1 `0.5433` across seven positive AOIs; all three pure-empty background AOIs remained at zero detections. -- Compared fixed-threshold persisted evidence against the previous active model and reduced the false-negative rate in every validated positive AOI. -- Activated the exact promoted local model through the guarded dry-run-first helper; no model was downloaded and no fake inference or QA result was introduced. -- Updated Detection Lab operator profiles so the promoted expanded model is the recommended balanced review choice while the previous high-precision model remains available as a legacy conservative profile. -- Redeployed the all-in-one Tower runtime with CPU-only Torch `2.13.0+cpu`, verified a real local model load against a nine-tile manifest, and passed PostGIS, API, health and browser checks. -- Persistent small-building misses remain the primary model-quality limitation and still require operator QA/QC. - -## Sprint 172 CPU AI image build hardening (2026-07-12) - -- Reordered the Unraid all-in-one Docker build so backend source changes reuse the Python/GIS/AI dependency layer. -- Pinned the opt-in CPU runtime to PyTorch 2.13.0 and torchvision 0.28.0 from the official CPU wheel index, avoiding unused CUDA runtime packages while preserving the currently validated framework versions. -- Kept AI dependencies opt-in and model weights local-only; no API, migration, model activation or inference contract changed. - -## Sprint 171.1 Validation coverage provenance (2026-07-12) - -- Added explicit retained and empty validation sample lists to generated YOLO tile summaries. -- Quality-filtered holdouts such as Arendonk-heide remain visible in provenance without being counted as actual retained validation coverage. - -## Sprint 171 Positive AOI expansion and split safety (2026-07-12) - -- Added four explicit, real-reference Kempen training AOIs: Olen, Lille, Oud-Turnhout and Kasterlee center. -- Preserved Turnhout, Retie, Westerlo and Arendonk-heide as manifest-backed validation holdouts and made the tile exporter reject unknown samples or holdout leakage. -- Added `recommended_split` provenance to generated sample/reference/tile metadata and recorded the validation split in dataset summaries. -- Hardened persistent false-negative comparison so portfolios with different reference feature identities cannot be compared. -- Generated and audited the 20-source expanded dataset on Tower: 171 retained tiles, 45,892 valid labels, 9 low-variance negatives removed and no structural audit warnings. -- Balanced visual label QA by source sample before selecting repeated dense tiles; the live pass covered all 19 retained sources without invalid labels, missing images or blank selections. -- No model was activated and no product API or migration changed. - -## Sprint 170 Persistent false-negative evidence audit (2026-07-12) - -- Added fixed-threshold evidence portfolio input generation so model comparisons use exactly one matching model/tile/threshold run per AOI. -- Added GIS-aware false-negative audit tooling with WGS84 geodetic areas, building-size buckets and persistent miss detection across multiple persisted QA portfolios. -- Missing, invalid or non-polygon evidence geometry now fails the operator audit explicitly. -- Added readiness compilation and focused regression coverage. -- No API contract, migration, model activation, provider fetching, fake QA output or model download behavior changed. - -## Sprint 169 Filtered YOLO candidate gate and operator hardening (2026-07-12) - -- Trained and fully gated inactive `geointel-building-yolov8s-aoi1024cleanpx12vis035lowvar512e50-pt` against seven positive AOIs and split pure-empty/sparse-context backgrounds. -- Rejected the candidate for default promotion: best mean positive F1 was approximately `0.154`, below the `0.25` gate; threshold `0.05` also produced one pure-empty background detection. -- Preserved the current active `aoi1024bg512r3e50` model and all runtime defaults. -- Added SHA256 provenance to future YOLO training summaries. -- Improved long project/dataset/AOI readability with matching tooltips and compact two-line readiness values. -- No API contract, migration, provider fetching, fake output, model download or automatic model activation changed. - -## Sprint 164 Tower AI deploy env hardening (2026-07-11) - -- Fixed Tower deploy automation so `scripts/deploy_tower.sh` and `scripts/deploy_tower.ps1` source the remote `.env` before building the all-in-one image. -- Hardened the PowerShell deploy wrapper to stream the remote script through `bash -s`, matching the Bash deploy path and preserving remote shell variable expansion. -- The PowerShell wrapper now writes a UTF-8-without-BOM temporary script, copies it with `scp`, runs it with `bash` on Tower and removes the remote temp file while preserving the deploy exit code. -- Remote `.env` now controls `GEOINTEL_INSTALL_AI=true` by default, with explicit local deploy overrides still supported. -- Added regression coverage so future deploy changes cannot silently build a GIS-only image while runtime YOLO settings are enabled. -- No API contract, database migration, provider fetching, fake detections, model download or product feature changed. - -## Sprint 163 Guarded YOLO candidate activation (2026-07-11) - -- Added `scripts/activate_promoted_yolo_candidate.py` to validate a promotion report and exact candidate key before emitting YOLO `.env` activation updates. -- The helper supports dry-run by default and writes `.env` only with `--apply`; it does not download weights, load models or run inference. -- Updated Detection Lab operator profiles: balanced `0.15` remains candidate-only, while conservative `0.35` is marked as the promoted profile backed by the split-background pure-empty gate. -- Added tests for dry-run activation, `.env` apply behavior, rejected report handling and promoted UI profile status. -- No API contract, database migration, provider fetching, fake detections, model file mutation or automatic runtime activation was introduced. - -## Sprint 162 Split-background promotion runtime pass (2026-07-11) - -- Hardened split-background preflight compatibility for legacy operator manifests by deriving missing background categories from `reference_feature_count`. -- Ran Tower split-background promotion evidence against `http://192.0.2.10:1202`. -- Produced a high-threshold promote candidate: `geointel-building-yolov8s-aoi1024bg512r3e50-pt|512|64|0.35`. -- Verified the strict pure-empty background gate: 3 samples, 9 runs, 0 detections. -- Preserved the current model default; no automatic activation, provider fetching, fake outputs, model downloads, API contracts or migrations changed. - -## Sprint 161 Widescreen workbench support (2026-07-10) - -- Added dedicated `1800px` and `2200px` frontend layout breakpoints for wide and ultrawide monitors. -- Expanded the workbench shell, inspector and MapLibre review frame while preserving the existing Map/Data/QA/AI/Export workflows and API contracts. -- Added regression tests for widescreen grid, map-height and ultrawide layout contracts. -- No backend API, database migration, model default, provider fetching, fake detection output or model download behavior changed. - -## Sprint 160 Split-background promotion preflight (2026-07-10) - -- Added `--preflight-only` to `scripts/run_split_background_promotion_workflow.sh`. -- Preflight validates local positive portfolio and operator manifest files, confirms required `pure_empty_negative` and `sparse_building_context` background categories, checks Python/curl availability and verifies the runtime API proxy returns the canonical envelope. -- Hardened preflight compatibility for older operator manifests by deriving missing background categories from `reference_feature_count`, matching the existing matrix-runner behavior. -- Documented the quick post-redeploy preflight command before starting long configured-YOLO matrix inference. -- No model default, backend API, database migration, provider fetching, fake detection output or model download behavior changed. - -## Sprint 159 Split-background promotion workflow wrapper (2026-07-10) - -- Added `scripts/run_split_background_promotion_workflow.sh` to run the split background matrix and split-aware promotion report from one operator command. -- Added readiness syntax coverage and regression tests for the wrapper contract. -- Documented the one-command Tower/runtime flow for the inactive AOI1024 background-aware model candidate. -- No model default, backend API, database migration, provider fetching, fake detection output or model download behavior changed. - -## Sprint 158 Split-aware promotion report (2026-07-10) - -- Added `--background-split-summary` support to `scripts/build_detection_model_promotion_report.py`. -- The promotion report now resolves the split summary's `pure_empty_negative` source as the strict default-promotion background gate and records `sparse_building_context` as review-only evidence. -- Added regression coverage proving sparse-context detections do not block default promotion when the pure-empty gate passes. -- No model default, backend API, database migration, provider fetching, fake detection output or model download behavior changed. - -## Sprint 157 Background split matrix runner (2026-07-10) - -- Added `scripts/run_background_corpus_split_matrix.sh` to run pure-empty and sparse-context hard-negative matrices separately from one operator command. -- Added `scripts/build_background_corpus_split_report.py` to combine both hard-negative summaries into `background_corpus_split_summary.json` and `.md`. -- Added readiness coverage and tests for the split runner/report contract. -- No model default, backend API, database migration, provider fetching, fake detection output or model download behavior changed. - -## Sprint 156 Background corpus classification (2026-07-10) - -- Added explicit operator background categories to prepared sample manifests: `pure_empty_negative` when GRB returns zero reference buildings and `sparse_building_context` when contextual GRB buildings are present. -- Added `OPERATOR_BACKGROUND_CATEGORIES` to `scripts/run_operator_hard_negative_detection_matrix.sh` so strict default-promotion false-positive gates can run on pure-empty negatives separately from sparse-context review samples. -- Preserved `background_category` in exported YOLO tile metadata for training auditability. -- No model default, backend API, database migration, provider fetching, fake detection output or model download behavior changed. - -## Sprint 155 Detection operator profiles (2026-07-09) - -- Added explicit Detection Lab operator profiles for the inactive `geointel-building-yolov8s-aoi1024bg512r3e50-pt` local model asset. -- Added a balanced review profile at confidence threshold `0.15` and a conservative review profile at `0.35`, with persisted gate metrics shown in the UI. -- Kept both profiles clearly marked as candidate-only and not default-approved because the promotion recommendation remains `none` and background false-positive pressure still blocks automatic activation. -- No model download behavior, API contract, migration, provider fetching, fake detection output or active runtime default changed. - -## Sprint 154 Background-aware AOI1024 YOLOv8s candidate gate (2026-07-09) - -- Exported and audited background-aware AOI1024 training dataset `/app/storage/operator-data/yolo-building-aoi1024-bgaware512r3`; the audit passed with 162 tiles, 117 positive tiles, 45 negative tiles, 21,530 labels and no warnings. -- Trained inactive local model asset `geointel-building-yolov8s-aoi1024bg512r3e50-pt` from the background-aware dataset. The Tower catalog reports SHA256 `e0980572aac90e7efc514608eb16d7de5bfbf27a4bbec04e7bc1bc8c02f9601f`, `status=available`, `active=false` and `will_download_models=false`. -- Ultralytics validation for the completed 50-epoch CPU run ended at approximately precision `0.440`, recall `0.362`, mAP50 `0.251` and mAP50-95 `0.0878`. -- Ran the seven-reference AOI1024 persisted QA matrix at tile `512`, overlap `64` and thresholds `0.25`, `0.15` and `0.05`. Mean positive F1 improved to `0.4908049127242224` at threshold `0.05`, `0.5074022485589402` at `0.15` and `0.44378879337957716` at `0.25`. -- Ran an additional conservative-threshold positive matrix at thresholds `0.35`, `0.45` and `0.60`. Threshold `0.35` produced mean F1 `0.32086574003576274`, mean precision `0.840006` and mean recall `0.202135`. -- Ran full hard-negative/background matrices. The candidate still fails automatic default promotion because mixed background-candidate AOIs keep false-positive pressure: max detections were `184` at threshold `0.05`, `103` at `0.15`, `75` at `0.25`, `55` at `0.35`, `38` at `0.45` and `18` at `0.60`. -- Generated promotion reports at `artifacts/detection-model-promotion/aoi1024bg512r3e50-full/detection_model_promotion_report.md` and `artifacts/detection-model-promotion/aoi1024bg512r3e50-high-threshold/detection_model_promotion_report.md`; recommendation remains `none`. -- No API contract, migration, provider fetching, fake detection data, model download behavior or active model default changed. - -## Sprint 153 AOI1024 clean-label YOLOv8s candidate gate (2026-07-09) - -- Audited AOI1024 label-quality variants after paged GRB reference regeneration and selected `/app/storage/operator-data/yolo-building-aoi1024-visible050-minpx8` for training because it passed the dataset audit while keeping the 512px runtime scale. -- Trained inactive local model asset `geointel-building-yolov8s-aoi1024clean512e50-pt` from the cleaned 512px tile dataset. The Tower catalog reports SHA256 `7cfadb684dd56623d2e35ebd65593211d3051908c87121bef438b231d3e47cce`, `status=available`, `active=false` and `will_download_models=false`. -- Ultralytics validation for the completed 50-epoch CPU run ended at approximately precision `0.441`, recall `0.380`, mAP50 `0.265` and mAP50-95 `0.096`. -- Ran the full seven-reference AOI1024 persisted QA matrix at tile `512`, overlap `64` and thresholds `0.25`, `0.15` and `0.05`. Mean positive F1 improved materially: `0.4723513253430784` at threshold `0.05`, `0.4753322215541376` at `0.15` and `0.31021575247724875` at `0.25`. -- Ran the full nine-sample hard-negative/background matrix. Background false-positive pressure still blocks default promotion: max detections were `137` at threshold `0.05`, `75` at `0.15` and `55` at `0.25`. -- Generated the promotion report at `artifacts/detection-model-promotion/aoi1024clean512e50-full/detection_model_promotion_report.md`; recommendation remains `none` because every threshold fails `background_false_positive_pressure`. -- No API contract, migration, provider fetching, fake detection data, model download behavior or active model default changed. - -## Sprint 152 GRB reference paging for operator samples (2026-07-09) - -- Fixed the operator real-data sample preparer so GRB GBG reference GeoJSON is fetched through OGC API `rel=next` pagination links instead of stopping at the first `limit=1000` page. -- Added `--reference-page-limit` / `OPERATOR_GRB_PAGE_LIMIT` and `--reference-max-features` / `OPERATOR_GRB_MAX_FEATURES` safeguards for dense reference AOIs. -- Generated reference GeoJSON now records fetched page URLs, page count, truncation state and paging limits for auditability. -- Added regression coverage for paged GRB responses and the new CLI help options. -- Redeployed Tower, regenerated AOI1024 operator samples with paged GRB references and re-exported `yolo-building-aoi1024-visible025`; dense reference counts now exceed the old cap where expected, including Geel 2,268, Mol 1,993, Turnhout 3,278, Herentals 2,478, Balen 1,343, Retie 1,734 and Westerlo 1,133 features. -- The refreshed AOI1024 tile dataset now has 29,170 labels with 0 missing label files and 0 invalid rows; audit status remains `needs_attention` because small-box share is still high. -- No application provider endpoint, migration, API contract, live GRB product import, model download or active YOLO model changed. - -## Sprint 151 runtime GIS upload and AOI1024 YOLO candidate (2026-07-09) - -- Fixed the operator YOLO training wrapper so the all-in-one runtime defaults to `/opt/geointel/venv/bin/python` when present, while still falling back to `python3` for local shells. -- Raised the Nginx upload limit to `250m` in both the compose frontend proxy and Unraid all-in-one proxy after a live 1024px GeoTIFF QA upload hit `413 Request Entity Too Large`. -- Raised Nginx proxy read/send timeouts to `600s` after a long low-threshold persisted YOLO/QA run hit `504 Gateway Timeout`. -- Hardened `build_detection_model_promotion_report.py` so it correctly accepts both calibration evidence portfolios and multi-sample quality summaries as positive evidence inputs. -- Prepared a larger Tower operator sample manifest at `/app/storage/operator-data/operator-samples-1024` using explicit `1024x1024` rasters and doubled AOI half-size. -- Exported and audited `/app/storage/operator-data/yolo-building-aoi1024-visible025`: 144 tiles, 117 positive tiles, 27 negative tiles, 15,079 labels and `min_label_visible_ratio=0.25`; audit remains `needs_attention` because median label area is still below gate. -- Trained inactive local model asset `geointel-building-yolov8s-aoi1024visible025e50-pt` from the AOI1024 dataset. Ultralytics validation ended at approximately precision `0.275`, recall `0.331`, mAP50 `0.188` and mAP50-95 `0.0716`. -- Redeployed Tower and verified the previously failing Geel low-threshold persisted YOLO/QA path now completes instead of returning `504`; the run produced F1 `0.09136212624584718`, so the model remains rejected for default use. -- Ran the full four-sample AOI1024 positive matrix and nine-sample hard-negative matrix. Best positive result was Westerlo threshold `0.15` with F1 `0.28703703703703703`; background pressure still reached 59 detections at threshold `0.25`, 107 at `0.15` and 226 at `0.05`. -- Generated the AOI1024 promotion report after the parser fix; recommended candidate remains `none`. Mean positive F1 stayed below gate for all thresholds: `0.13307746028311157` at `0.05`, `0.13900227809255514` at `0.15` and `0.09694707724016788` at `0.25`. -- The candidate remains inactive and must pass persisted detection QA/QC plus background/hard-negative promotion gates before default activation. -- No API contract, migration, product feature, provider fetching, fake detection data or active model default changed. - -## Sprint 150 YOLO label visible-ratio gate (2026-07-09) - -- Added `--min-label-visible-ratio` / `OPERATOR_YOLO_MIN_LABEL_VISIBLE_RATIO` to the operator YOLO tile dataset exporter. -- The exporter can now drop clipped building labels where only a small share of the original object bbox is visible in an overlapping tile. -- Tile dataset summaries and audit reports now retain/report `min_label_visible_ratio`. -- Added operator-only `--width`, `--height` and `--half-size-scale` options to `prepare_operator_real_data_samples.py` so larger training AOIs can be prepared explicitly. -- Updated operator documentation for the recommended next dataset pass. -- No model was activated, no detections were faked, no provider fetching was introduced and no migration changed. - -## Sprint 149 YOLO duplicate suppression evidence (2026-07-09) - -- Added configured-YOLO cross-tile duplicate suppression before `Detection` rows are persisted. -- Added `YOLO_DUPLICATE_IOU_THRESHOLD` with default `0.5`; `0` disables the GeoIntel-side pass for debugging. -- Detection run result metadata now records raw candidate count, suppressed duplicate count and duplicate IoU threshold. -- Calibration and quality matrix scripts now fetch detection run details and include raw/suppressed counts in summaries. -- Updated Docker/Unraid env examples, API/AI/backend docs and detection pipeline notes. -- Redeployed Tower and reran Westerlo/Turnhout dense-AOI sweeps; duplicate suppression improved F1 but the AOI512 YOLOv8s candidate remains rejected for default use. -- No model was activated, no detections were faked, and no migration changed. - -## Sprint 148 YOLO max-detection cap hardening (2026-07-09) - -- Added `YOLO_MAX_DETECTIONS` with default `1000` and forward it to Ultralytics as `max_det`. -- Wired the setting through `.env.example`, Docker Compose, Unraid env examples and the Dockerman run script. -- Documented why dense building AOIs should not inherit the Ultralytics default cap of 300 detections before persisted QA/QC. -- Added regression coverage for adapter forwarding and Docker/Unraid runtime exposure. -- Redeployed the Tower all-in-one runtime and verified live dense-AOI sweeps can exceed 300 persisted detection candidates: Westerlo reached 523/1000 detections and Turnhout reached 822/1000 at tested thresholds. -- The current AOI512 YOLOv8s candidate remains rejected for default use because persisted QA/QC F1 remains too low despite the runtime cap fix. -- No model was activated, no detections were faked, and no API route or migration changed. - -## Sprint 147 AOI512 YOLOv8s scale-match candidate gate (2026-07-09) - -- Built and audited an AOI-scale YOLO dataset at `512px` tile size to test whether the previous `160px` training scale was the main quality blocker. -- Trained Tower-local model asset `geointel-building-yolov8s-aoi512e80-pt` from `/app/storage/operator-data/yolo-building-aoi512-uniquehardneg`. -- Ran 7 positive AOI sweeps, a 17,156-feature evidence portfolio, a 9-sample hard-negative/background matrix and a promotion report. -- Result: the candidate is rejected. The best threshold `0.25` reached mean positive F1 `0.13511851520077328` and still produced max background detections `56`. -- Conclusion: scale-match training helps the training validation curve but does not solve operational persisted QA/QC quality. The next model pass needs better positive AOI coverage and label strategy, not only more epochs or another threshold. -- No API contract, migration, frontend behavior, provider fetching, model download or active model configuration changed. - -## Sprint 146 Unique hard-negative YOLOv8s candidate gate (2026-07-09) - -- Fixed the all-in-one Docker image so the operator YOLO training wrapper is available at `/app/scripts/train_operator_yolo_detector.sh`. -- Trained the Tower-local `geointel-building-yolov8s-uniquehardneg160e50-pt` candidate from the `yolo-building-tile-uniquehardneg160` dataset and preserved it as an explicit local model asset. -- Ran 7 positive AOI calibration sweeps, a 17,008-feature evidence portfolio, a 9-sample hard-negative/background matrix and a promotion report. -- Result: the candidate is rejected. Mean positive F1 remains around `0.16` and background false-positive pressure reaches `58` detections at threshold `0.25`, `85` at `0.15` and `172` at `0.05`. -- Hardened the operator promotion report so older positive evidence portfolios can be compared with explicit positive tile-size/overlap defaults. -- No API contract, migration, frontend behavior, model download, provider-fetching behavior or active model configuration changed. - -## Sprint 145 YOLOv8s hardneg r8 e60 full candidate evaluation (2026-07-08) - -- Completed the Tower-local YOLOv8s hard-negative r8 training run through 60 CPU epochs and published local model asset `geointel-building-yolov8s-hardneg160r8e60-pt`. -- Ran the full 7-AOI positive matrix, hard-negative matrix, evidence portfolio and promotion report for the completed e60 artifact. -- Result: the model is rejected. It reduces Kasterlee-bos background detections versus `expanded160e50` at threshold `0.15` (`11` versus `46`), but mean positive F1 remains too low (`0.07870592446136859` at threshold `0.15`). -- No backend API, migration, frontend runtime, model download, provider-fetching behavior or active model configuration changed. - -## Sprint 144 YOLOv8s hardneg r8 partial candidate evaluation (2026-07-08) - -- Started a Tower-local YOLOv8s training run on the `yolo-building-tile-hardneg160r8` dataset with requested 60 epochs. -- Preserved the 12-epoch `best.pt` artifact as explicit partial model asset `geointel-building-yolov8s-hardneg160r8e12partial-pt` after the CPU training command reached the 1-hour command limit. -- Ran the partial candidate through the 7-AOI positive matrix, hard-negative matrix, evidence portfolio and promotion report. -- Result: the partial candidate is rejected. Best positive F1 was Westerlo at `0.14826498422712936`, mean positive F1 at threshold `0.05` was `0.05026994383963278`, and Kasterlee-bos still produced 18 detections at threshold `0.05`. -- No backend API, migration, frontend runtime, model download, provider-fetching behavior or active model configuration changed. - -## Sprint 143 Detection model promotion decision report (2026-07-08) - -- Added `scripts/build_detection_model_promotion_report.py` for operator-only model promotion review. -- The report combines positive-AOI calibration evidence portfolios with hard-negative/background matrix summaries. -- Candidate decisions are grouped by model asset, tile size, overlap and threshold, then gated by positive sample count, background sample count, mean F1 and maximum background detections per sample. -- Added regression coverage for promoting a clean candidate and rejecting a candidate with background false-positive pressure. -- Ran the report on Tower against the regenerated 7-AOI positive portfolio and live hard-negative summaries; it evaluated 15 candidates and recommended none for default promotion. -- No backend API, migration, frontend runtime, model weight, model download, inference or provider-fetching behavior changed. - -## Sprint 141 Expanded positive-AOI matrix and portfolio metadata hardening (2026-07-08) - -- Ran a fresh Tower quality matrix for Balen, Herentals and Westerlo using `geointel-building-yolov8n-expanded160e50-pt` and `geointel-building-yolov8n-hardneg160r8e40-pt`. -- Assembled an expanded 7-AOI positive evidence portfolio across Geel, Mol, Turnhout, Retie, Balen, Herentals and Westerlo. -- Hardened calibration evidence exports so model asset id, model request, tile size and tile overlap survive into evidence bundle summaries and GeoJSON properties. -- Result: expanded160e50 is stronger on positive AOIs, with Westerlo reaching F1 `0.3659305993690852`, but hard-negative matrices still show false-positive pressure tradeoffs that prevent blind default promotion. -- No backend API, migration, frontend runtime, model weight, provider fetching or Docker runtime change was introduced. - -## Sprint 140 Live multi-AOI calibration portfolio run (2026-07-08) - -- Ran the new multi-AOI calibration evidence portfolio assembler on Tower against existing persisted quality-matrix summaries for Geel, Mol and Turnhout. -- Produced a real operator handoff under `/mnt/user/appdata/geointel/artifacts/detection-calibration-portfolio/live-20260708/output/` with portfolio JSON, Markdown and per-AOI evidence GeoJSON/HTML review artifacts. -- Portfolio evidence contains 5,509 persisted QA evidence features across 3 AOIs: 5,239 false negatives, 164 false positives, 53 matched detections and 53 matched references. -- Result: the evidence pipeline works, but the evaluated model/threshold set should not be promoted because recall remains very low across the AOIs. -- No app rebuild, API change, migration, inference rerun, model training, model download, provider fetch or frontend runtime change was introduced. - -## Sprint 139 Multi-AOI calibration evidence portfolio (2026-07-08) - -- Added `scripts/assemble_detection_calibration_evidence_portfolio.sh` to package multiple AOI calibration summaries and their persisted QA evidence bundles into one model-review portfolio. -- The assembler copies each summary into a sample folder, runs the existing evidence exporter per AOI and writes `calibration_evidence_portfolio.json` plus `calibration_evidence_portfolio.md`. -- Added readiness syntax coverage and a mocked-endpoint regression test for the portfolio convention. -- No backend API, migration, inference, provider fetching, model download, live data mutation or frontend runtime behavior changed. - -## Sprint 138 Browser calibration evidence bundle smoke (2026-07-08) - -- Added `scripts/smoke_detection_calibration_evidence_bundle.sh` to exercise the browser `detection-calibration-summary.json` -> QA evidence bundle path locally. -- The smoke uses mocked canonical QA evidence endpoint responses, runs the real `export_detection_calibration_evidence.sh` script and verifies the emitted GeoJSON, summary JSON and HTML review artifacts. -- Added readiness syntax coverage and regression coverage for the smoke. -- No backend API, migration, inference, provider fetching, model download, live data mutation or frontend runtime behavior changed. - -## Sprint 137 Browser calibration summary evidence bundle handoff (2026-07-08) - -- Extended `scripts/export_detection_calibration_evidence.sh` so it accepts Detection Lab `detection-calibration-summary.json` browser exports in addition to the older operator calibration summary format. -- Added summary normalization for browser-exported `rows`, root `project_id`, persisted `quality_check_id` values and best-mode fallback selection. -- Updated operator docs with the direct browser summary command. -- No backend API, migration, inference, provider fetching, model download or frontend runtime behavior changed. - -## Sprint 136 Guided calibration summary export (2026-07-08) - -- Added a Detection Lab `Download calibration summary` action for guided calibration rows. -- The exported JSON includes thresholds, persisted analysis run IDs, job IDs, quality check IDs, metrics and evidence GeoJSON URLs for successful rows. -- Reused browser-side JSON download behavior only; no backend endpoint, API contract, migration, model, provider or inference behavior changed. -- Added regression coverage for the summary export wiring. - -## Sprint 135 Calibration evidence handoff (2026-07-08) - -- Added a guided-calibration table action that opens the persisted QA/QC evidence map for successful threshold rows. -- Reused the existing quality-check evidence API and Map workspace overlay flow; no backend route, migration, model, provider or inference behavior changed. -- Kept unsuccessful/queued calibration rows read-only by disabling evidence actions until a persisted `quality_check_id` exists. -- Added regression coverage for the Detection Lab wiring and TODO tracking. - -## Sprint 134 External remote-sensing YOLO candidate benchmark (2026-07-07) - -- Evaluated the Hugging Face `agademer/yolo-remote-sensing-photovoltaic` YOLOv8l detection checkpoint as an explicit operator-provided runtime model asset. -- Downloaded `yolo-remote-sensing-photovoltaic-v8l-solar-farms-and-cities-v20260331-detect-1000_epochs.pt` to the Tower runtime as `/app/models/yolo-remote-sensing-photovoltaic-v8l-detect-1000.pt`; the model file is not committed to Git. -- The model catalog exposes it as `yolo-remote-sensing-photovoltaic-v8l-detect-1000-pt` with SHA256 `242ff4ab889569278f0eb9fcd22eb2c4bf2a52e48d05d89cc7cfa7941165d203`. -- Live YOLO preflight loaded the model successfully with `status=ready`, `model_load_ok=true`, `manifest_valid=true`, `tile_paths_exist=true`, `will_download_models=false` and `will_run_inference=false`. -- Live 45-run dense QA matrix compared the external YOLOv8l candidate with `geointel-building-yolov8n-expanded160e50-pt` and `geointel-building-yolov8n-hardneg160r8e40-pt` across Geel, Mol, Turnhout, Retie and Kasterlee-bos. -- Result: the external candidate was very conservative and missed most dense GRB buildings. It scored F1 `0.0` on Geel, `0.010582010582010581` on Mol, `0.019070321811680575` on Turnhout and `0.0` on Retie, while expanded160e50 remained the dense-AOI winner. -- Live 27-run background matrix showed the external candidate was cleaner on Kasterlee-bos than local YOLOv8n candidates, with 1/2/5 detections at thresholds `0.25`/`0.15`/`0.05`, but it leaked 0/1/3 detections on Postel-bos and was therefore not uniformly cleaner than hardneg160r8e40. -- Decision: keep the model as runtime evidence only. It should not become the V1 default because recall is too low for operational extraction. The next pass should train a higher-capacity local model, starting from a stronger base and using the existing dense plus hard-negative benchmark gates. -- No API contract change, provider fetching, fake detections, model auto-provisioning, repository-stored weights or app-side model training behavior was introduced. - -## Sprint 133 Hard-negative-balanced YOLO candidate (2026-07-07) - -- Added `--background-negative-repeat` / `OPERATOR_YOLO_BACKGROUND_NEGATIVE_REPEAT` support to `scripts/export_operator_yolo_tile_dataset.py` so train-split background-candidate negative tiles can be repeated deterministically without duplicating validation tiles. -- Added exported tile provenance fields `sample_role`, `repeat_index` and `is_repeated_background_negative` plus regression coverage in `backend/tests/test_sprint130_operator_yolo_tile_dataset.py`. -- Live Tower export produced `/app/storage/operator-data/yolo-building-tile-hardneg160r8` with tile size `160`, stride `80`, background repeat `8`, 864 tiles, 260 positive tiles, 604 negative tiles, 11213 labels, 756 train tiles and 108 validation tiles. -- Live Tower 40-epoch CPU training produced `/app/models/geointel-building-yolov8n-hardneg160r8e40.pt`; the model catalog exposes it as `geointel-building-yolov8n-hardneg160r8e40-pt` with SHA256 `7a77bd9f68e4c3927ffc8a8cd978a81067b02f42cffe77ada5334b5f8dbb6b50`. -- Live YOLO preflight loaded the model successfully with `status=ready`, `model_load_ok=true`, `manifest_valid=true`, `tile_paths_exist=true`, `will_download_models=false` and `will_run_inference=false`. -- Live 60-run dense QA matrix showed `geointel-building-yolov8n-expanded160e50-pt` remains the better dense-AOI candidate; hardneg160r8e40 underperformed it on Geel, Mol, Turnhout and Retie. -- Live 36-run background matrix showed hardneg160r8e40 materially reduced false-positive pressure: Kasterlee-bos dropped from expanded160e50's 38/46/76 detections to 5/9/25 at thresholds `0.25`/`0.15`/`0.05`, and Postel-bos/Lommel-heide stayed at 0 detections across all thresholds. -- Decision: hardneg160r8e40 is useful evidence for a low-false-positive training direction, but it should not become the V1 default because dense-AOI recall/F1 regressed. The next model pass should combine stronger positive coverage with hard-negative balancing or test a stronger aerial-building architecture. -- No Training Studio UI, API contract change, provider fetching, model auto-provisioning, fake detections or app-side model training behavior was introduced. - -## Sprint 132 Operator hard-negative detection matrix (2026-07-07) - -- Added `scripts/run_operator_hard_negative_detection_matrix.sh` to score configured-YOLO false-positive pressure on documented background-candidate operator AOIs without uploading reference vectors or running QA/QC. -- Added readiness shell-syntax coverage and regression coverage in `backend/tests/test_sprint132_operator_hard_negative_matrix.py`. -- Live Tower 27-run hard-negative matrix compared `geointel-building-yolov8n-expanded160e50-pt`, `geointel-building-yolov8n-tile30-pt` and `yolov8s-building-segmentation-pt` on Postel-bos, Lommel-heide and Kasterlee-bos at thresholds `0.25`/`0.15`/`0.05`. -- Result: `geointel-building-yolov8n-expanded160e50-pt` produced 0 detections on Postel-bos and Lommel-heide at thresholds `0.25` and `0.15`, but produced 38/46/76 detections on Kasterlee-bos at thresholds `0.25`/`0.15`/`0.05`. -- Decision: the expanded local model remains the best dense-AOI candidate, but Kasterlee-bos false-positive pressure blocks it from becoming a V1 default. The next model pass must train against stronger hard-negative coverage or tune per-model threshold/max-detection policy. -- No QA metrics were faked; background scoring is detection-count based only. No provider fetching, fixture detections, model downloads, API contract changes or app-side training behavior were introduced. - -## Sprint 131 Operator sample expansion and negative-tile YOLO candidate (2026-07-07) - -- Expanded `scripts/prepare_operator_real_data_samples.py` from the original Geel/Mol/Turnhout corpus to 7 reference AOIs plus 3 background-candidate AOIs. -- Added `sample_role` and `allow_empty_reference` metadata so deliberate background candidates can be prepared without weakening the empty-GRB guard for normal reference samples. -- Added regression coverage in `backend/tests/test_sprint131_operator_sample_expansion.py` for the expanded sample registry, empty-reference background candidates and normal reference-sample rejection. -- Live Tower preparation produced 10 operator samples: Geel, Mol, Turnhout, Herentals, Balen, Retie, Westerlo, Postel-bos, Lommel-heide and Kasterlee-bos. -- Live Tower tile export produced `/app/storage/operator-data/yolo-building-tile-expanded160` with 360 tiles, 260 positive tiles, 100 negative tiles and 11213 clipped building labels. -- Live Tower 50-epoch CPU training produced `/app/models/geointel-building-yolov8n-expanded160e50.pt`; the model catalog exposes it as `geointel-building-yolov8n-expanded160e50-pt` with SHA256 `bf6a5e8d25a62d784ee53764ea11d7ce89c4e7aeeac7588010e497b8d7dafb2b`. -- Live YOLO preflight loaded `geointel-building-yolov8n-expanded160e50-pt` successfully with `status=ready`, `model_load_ok=true`, `manifest_valid=true`, `tile_paths_exist=true`, `will_download_models=false` and `will_run_inference=false`. -- Live 45-run Geel/Mol/Turnhout/Retie/Kasterlee-bos QA matrix showed the expanded model is the best current candidate on dense building AOIs: best overall score was Geel at tile `640`, threshold `0.05`, precision `0.30333333333333334`, recall `0.14748784440842788`, F1 `0.1984732824427481`. -- Hard-negative finding: on the sparse Kasterlee-bos sample, `yolov8s-building-segmentation-pt` remained cleaner, while the expanded local model produced too many false positives. The model is therefore improved but still experimental, not a V1 default. -- No Training Studio UI, API contract change, provider fetching, model auto-provisioning, fake detections or app-side model training behavior was introduced. - -## Sprint 130 Operator YOLO tile-level dataset tooling (2026-07-07) - -- Added `scripts/export_operator_yolo_tile_dataset.py` to convert prepared operator samples into overlapping YOLO tile datasets with clipped building labels and deterministic negative tile retention. -- Added readiness coverage for the tile exporter Python compile check. -- Added regression coverage in `backend/tests/test_sprint130_operator_yolo_tile_dataset.py` for script contract, help behavior without GIS imports, edge-covering tile windows and deterministic negative-tile selection. -- Updated operator documentation for tile-level dataset export and reuse of the existing local training wrapper. -- Live Tower tile export produced `/app/storage/operator-data/yolo-building-tile-dataset` with 75 overlapping tiles and 5321 clipped building labels from the Geel/Mol/Turnhout operator samples. -- Live Tower 30-epoch CPU training produced `/app/models/geointel-building-yolov8n-tile30.pt`; the model catalog exposes it as `geointel-building-yolov8n-tile30-pt` with SHA256 `b9e228202500d7c85836d12a72e320f4f2f0cef24cbb1b5bf7fa78a6778390af`. -- Live YOLO preflight loaded `geointel-building-yolov8n-tile30-pt` successfully with `status=ready`, `model_load_ok=true`, `manifest_valid=true`, `tile_paths_exist=true`, `will_download_models=false` and `will_run_inference=false`. -- Live 48-run Geel/Mol/Turnhout QA matrix compared `geointel-building-yolov8n-tile30-pt` with `yolov8s-building-segmentation-pt`; best overall score was Mol with the tile model, tile `640`, threshold `0.15`, precision `0.13602941176470587`, recall `0.09893048128342247`, F1 `0.11455108359133127`. -- Result decision: the tile-trained local model is now the best tested candidate on Geel/Mol and best overall, but remains experimental and should not become the V1 default until more AOIs and negative/background samples materially improve recall and false-positive behavior. -- No Training Studio UI, API contract change, provider fetching, model auto-provisioning or app-side model training behavior was introduced. - -## Sprint 129 Operator YOLO training dataset tooling (2026-07-07) - -- Added `scripts/export_operator_yolo_dataset.py` to convert prepared operator orthophoto/GRB sample pairs into a standard local YOLO detection dataset with `dataset.yaml`, train/validation image folders, label folders and `yolo_dataset_summary.json`. -- Added `scripts/train_operator_yolo_detector.sh` as an operator-only training smoke wrapper that uses an existing local base `.pt` model and writes a trained local `.pt` artifact plus `training_summary.json`. -- Disabled Ultralytics plot generation in the training wrapper so the smoke path avoids auxiliary plot/font network behavior. -- Added readiness coverage for the exporter Python compile check and training wrapper shell syntax. -- Added regression coverage in `backend/tests/test_sprint129_operator_yolo_training_dataset.py`. -- Updated operator documentation for dataset export, training smoke usage and the requirement to benchmark any trained model through the existing real-data Detection + QA matrix before treating it as useful. -- Live Tower export produced a YOLO dataset with 3 operator samples and 1427 labels; a clean 8-epoch CPU training smoke produced `/app/models/geointel-building-yolov8n-operator8.pt`. -- Live preflight loaded `geointel-building-yolov8n-operator8-pt` successfully with `will_download_models=false` and `will_run_inference=false`. -- Live multi-sample QA matrix showed the 8-epoch operator model is not useful yet: it produced zero detections at thresholds `0.15`-`0.50`, and the low-threshold `0.01` run produced mostly false positives with best F1 `0.003798670465337132`. -- `yolov8s-building-segmentation-pt` remains the best tested model, with best overall F1 `0.04195804195804196` on Mol at tile `640`, threshold `0.15`; still not sufficient for V1 default extraction. -- No Training Studio UI, API contract change, provider fetching, model auto-provisioning or app-side model training behavior was introduced. - -## Sprint 128 Stronger building model runtime benchmark (2026-07-07) - -- Added `keremberke/yolov8s-building-segmentation` as an explicit Tower runtime model asset at `/mnt/user/appdata/geointel/models/yolov8s-building-segmentation.pt`; the file is not committed to Git. -- Verified the live model catalog exposes `yolov8s-building-segmentation-pt` with `will_download_models=false` and SHA256 `a27af31654c6a4edbdc85581c33d93c13986b5919de7de410f8d85d801b3bb34`. -- YOLO preflight loaded the model locally with `model_load_ok=true` and no automatic download. -- Ran a 36-run Geel/Mol/Turnhout matrix comparing `yolov8n-building-segmentation-pt` and `yolov8s-building-segmentation-pt` across tile sizes `512`/`640` and thresholds `0.50`/`0.25`/`0.15`. -- Best overall score was Mol with `yolov8s-building-segmentation-pt`, tile `640`, threshold `0.15`: 55 detections, 9 matches, 46 false positives, 365 false negatives, precision `0.16363636363636364`, recall `0.02406417112299465`, F1 `0.04195804195804196`. -- Conclusion: `yolov8s` is cleaner than `yolov8n` on some samples, but still misses most GRB buildings; it is not a sufficient V1 default. - -## Sprint 127 Multi-sample detection quality calibration tooling (2026-07-07) - -- Added `scripts/prepare_operator_real_data_samples.py` to prepare documented Geel, Mol and Turnhout orthophoto/GRB GBG building sample pairs as explicit runtime artifacts. -- Added `scripts/run_multi_sample_detection_quality_matrix.sh` to run the existing real-data quality matrix for every prepared sample and combine the results. -- The combined summary writes `multi_sample_quality_summary.json` with overall score/recall/precision rankings and per-sample best configurations. -- Added readiness coverage and regression tests for the sample-preparation and multi-sample matrix contracts. -- Ran the full 24-run Tower matrix for Geel, Mol and Turnhout. Best overall score/recall was Turnhout with `yolov8n-building-segmentation-pt`, tile `512`, overlap `64`, threshold `0.15`, 142 detections, 18 matches, 124 false positives, 755 false negatives and F1 `0.03934426229508197`; generic `yolov8n-pt` produced zero building detections across all samples. - -## Sprint 126 Detection quality matrix tooling (2026-07-07) - -- Added `scripts/run_detection_quality_matrix.sh` to compare local model assets, raster tile sizes, tile overlaps and confidence thresholds through the existing real-data detection + QA workflow. -- The script writes per-run logs and a `quality_matrix_summary.json` with detection count, QA score, precision, recall, F1, mean IoU, matches, false positives and false negatives. -- The summary ranks `best_by_score`, `best_by_recall` and `best_by_precision` for operator model-quality decisions. -- Added readiness syntax coverage and static regression coverage for the quality matrix contract. -- Ran the matrix on Tower against the Geel operator sample: `yolov8n-building-segmentation-pt` with tile `512`, overlap `64` and threshold `0.15` ranked best by score/recall with 80 detections, 6 matches, 74 false positives, 611 false negatives and F1 `0.017216642754662843`; generic `yolov8n-pt` produced zero building detections. - -## Sprint 125 Detection calibration evidence bundle (2026-07-07) - -- Added `scripts/export_detection_calibration_evidence.sh` to export persisted QA evidence from a detection calibration summary. -- The script writes combined `calibration_evidence.geojson`, `calibration_evidence_summary.json` and a standalone `calibration_evidence_review.html` SVG artifact for matched detections, matched references, false positives and false negatives. -- Added readiness syntax coverage and regression coverage for the evidence bundle contract. -- Ran the export on Tower for the latest Geel calibration sweep; the bundle contained 2555 evidence features: 2460 false negatives, 79 false positives, 8 matched detections and 8 matched references. -- No inference, model dependency, provider fetching, fake data, API contract or frontend runtime behavior changed. - -## Sprint 124 Detection calibration sweep tooling (2026-07-07) - -- Added `scripts/run_detection_calibration_sweep.sh` to run the existing real-data detection + QA workflow across multiple configured-YOLO confidence thresholds. -- The sweep writes per-threshold logs and a `calibration_summary.json` with persisted detection count, QA score, precision, recall, F1, mean IoU, matches, false positives and false negatives. -- Added readiness syntax coverage and static regression coverage for the calibration sweep contract. -- Ran the sweep on Tower against the Geel operator sample; threshold `0.15` ranked best among `0.50`, `0.35`, `0.25` and `0.15`, but recall remained below 1%, confirming the next problem is model/data calibration rather than runtime availability. -- No new model dependencies, provider fetching, fake detections, API contracts or product UI behavior were introduced. - -## Sprint 123 YOLO class and tile CRS normalization (2026-07-07) - -- Fixed configured-YOLO class filtering so model labels such as `Building` match operator/domain filters such as `building`. -- Persisted configured-YOLO class names as canonical lowercase values while preserving the original model label in detection provenance. -- Added regression coverage for the mixed-case YOLO class route that caused the Geel real-data smoke to persist zero detections. -- Confirmed through direct Tower inference that the active local building model returns raw detections on the prepared Geel orthophoto tile; the remaining work is threshold/QA calibration rather than model availability. -- Fixed raster tile manifest CRS propagation so generated tile manifests include source CRS metadata required to convert YOLO pixel boxes to WGS84 Detection GeoJSON coordinates. -- Deployed the class-normalization and tile-CRS fixes to Tower, reran the real-data detection + QA workflow, confirmed 4 persisted detections and verified Detection GeoJSON now returns WGS84 coordinates around Geel. - -## Sprint 122 Real operator data availability and raster metadata fix (2026-07-07) - -- Created Tower operator sample artifacts under `/mnt/user/appdata/geointel/storage/operator-data`: - - `geel_orthophoto_wms_512.tif` from the Digitaal Vlaanderen OMWRGBMRVL WMS `Ortho` layer. - - `geel_grb_gbg_buildings.geojson` from the Digitaal Vlaanderen GRB OGC API Features `GBG` collection. -- Fixed raster upload metadata mapping so uploaded rasters persist canonical `bounds_json`, `resolution_json` and `bands_json` from extracted raster metadata. -- Added regression coverage for raster upload metadata mapping. -- Deployed the fix to Tower and ran the real-data detection + QA workflow against `http://192.0.2.10:1202`. -- The workflow passed with persisted raster/reference datasets, tile manifest, AnalysisRun, QualityCheck and detection GeoJSON export. A follow-up pass identified case-sensitive class filtering as the reason the initial Geel run persisted zero detections. - -## Sprint 121 Real data detection and QA workflow smoke (2026-07-07) - -- Added `scripts/verify_real_data_detection_qa_workflow.sh` for operator-provided GeoTIFF/reference-vector validation against a live runtime. -- The smoke uploads a real raster source dataset and real reference building vector, validates GIS metadata, tiles the raster, selects a mounted local model asset, runs configured YOLO detection, runs persisted detection QA/QC and exports detection GeoJSON. -- Registered the script in the readiness gate as a syntax check so normal development remains green without real local imagery or model files. -- Documented exact Tower usage in `scripts/README.md`, `backend/README.md`, `docs/AI_PIPELINES.md` and `docs/TODO.md`. -- The script refuses missing files, unsupported formats, demo workflow seeding, fixture detections, live provider fetching and model downloads. - -## Sprint 120 Model asset detection workflow smoke (2026-07-06) - -- Added `scripts/verify_model_asset_detection_workflow.sh` for live Docker/Tower validation of the configured-YOLO path with a selected local model asset. -- The smoke seeds the explicit demo raster, generates a tile manifest, selects a cataloged model asset, checks read-only YOLO preflight, runs the existing detection endpoint and verifies persisted AnalysisRun, Detection list and Detection GeoJSON outputs. -- Registered the new smoke script in the readiness gate as a syntax check so ordinary CI/dev runs do not require AI dependencies or model files. -- Documented that the smoke validates operational routing/provenance only; zero detections are acceptable on the synthetic demo raster and real GIS quality still requires local orthophoto/reference validation. - -## Sprint 118 Local model and reference catalog clarity (2026-07-06) - -- Added a read-only local model asset catalog endpoint at `GET /api/v1/detection/model-assets`. -- Added `YOLO_MODELS_DIR` so Docker/Unraid runtimes can expose mounted model files as selectable assets without downloading weights. -- Detection runs and YOLO preflight can now accept `model_asset_id` for `yolo-configured`, with backend-side resolution to a cataloged local file. -- Detection Lab now shows a local model asset picker with active-file, size and checksum context. -- Provider Capabilities now explicitly labels GRB/OSM/manual/fixture as reference-data source capabilities, not AI model choices. -- Added regression coverage for the backend model asset catalog and frontend model asset wiring. - -## Sprint 117 Safe local YOLO model activation (2026-07-06) - -- Added `scripts/configure_yolo_model.py` to configure an existing local YOLO model into the Unraid/Tower `.env` file without downloading weights, loading a model or running inference. -- The helper refuses no-model and ambiguous multi-model states, and only applies env changes when `--apply` is provided. -- Documented the Tower flow for placing model files under `/mnt/user/appdata/geointel/models`, applying the env update and restarting/redeploying the all-in-one container. -- Added regression coverage for no-model, multi-model, dry-run and env-file apply behavior. -- Hardened configured YOLO inference so single-band raster tiles are converted to temporary RGB prediction images and model runtime errors are returned as typed detection failures instead of raw server errors. - -## Sprint 116 Operational GIS map workflow (2026-07-04) - -- Switched the default MapLibre basemap from demo tiles to an OpenStreetMap road raster basemap with visible attribution while keeping `VITE_MAP_STYLE_URL` as the production override. -- Added a persisted database layer selector to the Map workspace so users can directly load a ready vector dataset from stored project data. -- Added an Operational GIS run panel that reuses AOI or active layer extents to query persisted PostGIS `vector_features` through the existing bbox selection flow. -- Added a basemap policy notice when the public OpenStreetMap fallback is active and a guided operational workflow for query, derived dataset, QA/QC and export handoff. -- Added a one-click full GIS workflow action that runs persisted selection, saves the derived dataset, saves a GeoJSON export and optionally runs QA/QC against the selected reference dataset. -- Added a full-workflow run mode selector so repeated Map QA/QC runs can reuse the latest saved derived dataset instead of creating duplicate dataset/export artifacts. -- Added an opt-in Docker/Unraid AI build path (`GEOINTEL_INSTALL_AI=true`) for installing optional PyTorch/Ultralytics dependencies while keeping the default GIS runtime lightweight and import-safe. -- Hardened the AI Docker runtime with OpenCV native libraries required by Ultralytics and made YOLO dependency detection use real imports instead of optimistic module discovery. -- Added a writable `YOLO_CONFIG_DIR` default under application storage so Ultralytics does not fall back to root user config paths in Docker/Unraid. -- Added YOLO preflight runtime diagnostics for dependency assumption state, model directory, `YOLO_CONFIG_DIR`, installed `torch`/`ultralytics` versions and CUDA availability without running inference or downloading weights. -- Added a canonical `GET /api/v1/detection/yolo/preflight` endpoint and Detection Lab panel so operators can inspect live YOLO runtime readiness from the web UI. -- Added static regression coverage for the road basemap, attribution, basemap policy notice, database layer selector and persisted operational GIS workflow wiring. - -## Sprint 115 QA/QC and Exports usability layout pass (2026-07-04) - -- Made the QA/QC workspace calmer by compacting summary, handoff, drilldown, feature evidence and metric history surfaces. -- Reduced raw QA provenance height so JSON evidence remains available without dominating the screen. -- Rebalanced QA/QC and Exports workspace columns for review-first usage. -- Made export handoff cards, latest artifact cards and export history controls denser and easier to scan. -- Added static regression coverage for compact QA evidence review and export handoff layouts. - -## Sprint 114 Data and Map usability layout pass (2026-07-04) - -- Made the Data workspace catalog more compact with quieter upload controls, denser role summaries and shorter dataset action buttons. -- Rebalanced the Data workspace columns so catalog review has more room while setup panels remain available. -- Made the Map workspace more map-first by placing the MapLibre frame before dense layer controls and increasing the desktop map height. -- Reduced Map context, provenance, bbox selection and feature extraction density while keeping existing selection/export/QA actions unchanged. -- Added static regression coverage for the compact Data catalog and map-first workspace ordering. - -## Sprint 113 Calm workbench layout pass (2026-07-04) - -- Reduced visual density in the workbench shell without changing API contracts or workflows. -- Softened the base palette, borders and shadows so panels read as a work surface instead of stacked cards. -- Made the top context bar, sidebar navigation, workspace heading, status tiles and inspector more compact. -- Hid the duplicated workspace command bar because the persistent sidebar already provides primary navigation. -- Added static regression coverage for the calmer shell density and mobile-safe navigation rules. - -## Sprint 112 QA evidence map overlay (2026-06-25) - -- Added a read-only QA/QC evidence GeoJSON endpoint for persisted quality checks. -- The endpoint resolves `match_evidence`, `false_positive_evidence` and `false_negative_evidence` ids back to persisted vector, detection or segmentation geometries where available. -- Added QA/QC actions to render evidence overlays in the existing MapLibre workspace with distinct match, false-positive and false-negative styling. -- Added frontend loading/error/clear states for the QA evidence overlay and a compact map legend. -- No migration, new table, provider fetching, AI behavior or new product domain was introduced. - -## Sprint 111 QA feature evidence persistence (2026-06-25) - -- Added feature-level QA evidence to dataset, detection and segmentation QA matching. -- Persisted matched feature ids, false-positive feature ids and false-negative feature ids inside `quality_checks.findings_json`. -- Extended QA/QC drilldown with compact matched/false-positive/false-negative feature id lists beside the existing metrics and raw findings JSON. -- Updated API contracts to document `match_evidence`, `false_positive_evidence` and `false_negative_evidence`. -- No migration, new table, provider fetching, AI behavior or new product domain was introduced. - -## Sprint 110 Map QA evidence drilldown (2026-06-25) - -- Extended the Map workspace QA/QC shortcut with inline evidence after comparing a saved derived selection dataset. -- The result now shows quality-check id, matches, false positives, false negatives, mean IoU and QA warnings beside precision/recall/F1. -- Added an `Open QA/QC evidence` handoff to the existing QA/QC workspace drilldown instead of creating a parallel QA detail system. -- No backend API contracts, migrations, provider fetching, AI behavior or new product domains were introduced. - -## Sprint 109 Map selection QA shortcut (2026-06-25) - -- Added a Map workspace QA/QC shortcut for saved derived selection datasets. -- The shortcut reuses the existing QA comparison workflow and persists `QualityCheck`/`Metric` rows through the existing backend route. -- Added reference dataset selection, loading/error state and compact precision/recall/F1/status feedback beside the saved map selection. -- Kept QA orchestration in a dedicated frontend hook so `App.tsx` remains an orchestrator and API calls stay out of the shell component. -- No backend API contracts, migrations, provider fetching, AI behavior or new product domains were introduced. - -## Sprint 108 Map selection derived datasets (2026-06-25) - -- Added `POST /api/v1/projects/{project_id}/datasets/{dataset_id}/vector/select/derive` to persist a map bbox selection as a reusable derived vector dataset. -- Derived selection datasets keep source provenance, write a GeoJSON artifact and index their features back into `vector_features`. -- Added `Save as dataset` to the Map workspace after area extract, including loading/error/latest dataset feedback. -- Added regression coverage for service persistence, empty-selection failure, canonical API envelope and frontend wiring. - -## Sprint 107 Map selection export handoff (2026-06-25) - -- Added `vector_selection` GeoJSON export support to persist bbox-selected map features as normal export artifacts. -- Selection exports query persisted PostGIS `vector_features`, write a `vector_selection_geojson` FeatureCollection and store selection bbox/count metadata in the export record. -- Added `Save area export` to the Map workspace after an area extract, including loading/error state and latest artifact path feedback. -- Updated frontend export typing/API hook wiring so saved selections appear in the existing Export Center history. -- No migrations, provider fetching, AI behavior, real model dependencies or new product domains were introduced. - -## Sprint 106 Map area selection extract (2026-06-25) - -- Added a read-only bbox selection endpoint for vector datasets: `POST /api/v1/projects/{project_id}/datasets/{dataset_id}/vector/select`. -- The endpoint queries persisted PostGIS `vector_features` and returns a canonical-envelope GeoJSON FeatureCollection with selection bbox, feature count, limit and truncation state. -- Added Map workspace area selection with two-click bbox drawing, manual EPSG:4326 bbox inputs, selected-feature/AOI/layer bbox shortcuts and client-side GeoJSON download/copy. -- Added MapLibre overlays for the active bbox and extracted selection result. -- Added regression coverage for backend selection behavior, route envelope and frontend wiring. -- No migrations, provider fetching, AI behavior, real model dependencies or new product domains were introduced. - -## Sprint 105 Map feature extract (2026-06-25) - -- Added a `Selection & extract` panel to the Map workspace for clicked map features. -- Selected features are highlighted through a dedicated MapLibre GeoJSON source/layer. -- The extract panel now shows geometry type, coordinate count, EPSG:4326 bbox and a property table. -- Added client-side `Download selected GeoJSON`, `Copy selected properties` and `Clear selection` actions for the clicked feature. -- No backend API contracts, migrations, provider fetching, AI behavior or database persistence changed. - -## Sprint 102 Detection Lab handoff polish (2026-06-24) - -- Updated the raster tile manifest handoff to Detection Lab so it automatically selects `yolo-configured`. -- Tightened the AI handoff browser smoke so it now verifies that the model selection is set by the UI handoff rather than by the test. -- Added regression coverage for the automatic model handoff. -- No backend API, persistence, migration, provider fetching or AI dependency behavior changed. - -## Sprint 101 AI Lab handoff browser smoke (2026-06-24) - -- Added `scripts/verify_ai_handoff_interactions.sh` to exercise the browser click path from raster tiling into Detection Lab and Segmentation Lab. -- The smoke seeds the explicit offline demo workflow, generates a small raster tile manifest, clicks both AI handoff buttons and verifies the selected raster dataset plus manifest path are preserved. -- Added readiness syntax coverage for the new browser interaction smoke and documented its optional Playwright requirement. -- Added regression coverage for the script/readiness contract. -- No product behavior, API contract, migration, AI dependency or provider-fetching changes were introduced. - -## Sprint 100 raster tile Segmentation Lab handoff (2026-06-24) - -- Added Segmentation Lab tile manifest state and wired it into the existing segmentation run request `tile_manifest_path`. -- Added a raster inspector handoff action that fills the selected raster dataset and tile manifest path in Segmentation Lab. -- Mirrored the existing Detection Lab manifest input pattern without adding new backend routes, migrations, AI dependencies or model behavior. -- Added regression coverage for the segmentation handoff wiring. - -## Sprint 99 raster tile Detection Lab handoff (2026-06-23) - -- Surfaced the latest persisted `raster.tile` manifest path in the raster dataset inspector. -- Added a direct Detection Lab handoff action that fills the selected raster dataset and tile manifest path from the existing raster tile job result. -- Preserved existing raster, detection and segmentation API contracts; no AI inference, provider fetching, migrations or backend route changes were introduced. -- Added regression coverage for the frontend handoff wiring. - -## Sprint 98 demo raster workflow smoke (2026-06-23) - -- Added `scripts/verify_demo_raster_workflow.sh` to validate the browser-facing demo raster happy path: inspect, preview, stats and tile manifest generation. -- Added readiness syntax coverage for the raster workflow smoke. -- Fixed raster tiling manifest generation for Rasterio versions that return window bounds as tuples instead of bound objects. -- Added regression coverage for tuple-based raster window bounds and the new raster smoke contract. -- No AI inference, external provider fetching, migrations or API route changes were introduced. - -## Sprint 97 demo raster fixture workflow (2026-06-23) - -- Added a deterministic local GeoTIFF raster fixture to the offline demo workflow so raster controls and AI Lab dataset prerequisites have usable V1 context. -- Returned `raster_dataset_id` from the canonical demo workflow response and wired the frontend demo loader to select it for Detection and Segmentation Labs. -- Kept the candidate vector dataset as the default Data/Map/Export context after demo load. -- Hardened workbench default/interactions smoke scripts to require the candidate vector, reference vector and raster fixture datasets as `3/3 ready`. -- No external provider fetching, real AI inference, migrations or API behavior outside the demo response contract changed. - -## Sprint 96 useful default context (2026-06-22) - -- Auto-open the first ready vector dataset after project data loads so Data, Map and Exports start with usable context. -- Kept user-driven dataset selection intact; the default is only applied when no dataset is selected. -- Added explicit Detection/Segmentation Lab guidance when no raster datasets are available. -- Added regression coverage for useful default dataset selection and AI Lab raster prerequisite messaging. -- No API contracts, migrations, provider fetching or AI/model behavior changed. - -## Sprint 95 raster pipeline hardening (2026-06-22) - -- Added a raster pipeline readiness surface to the dataset inspector. -- Surfaced metadata profile, CRS readiness, preview artifact, tile manifest handoff and clip AOI state before raster operations. -- Added processing guardrails for missing metadata, missing CRS, missing preview, invalid tile parameters, unavailable rasters and missing clip areas. -- Added responsive styling and regression coverage for the raster readiness/handoff structure. -- No API contracts, migrations, provider fetching or AI/model behavior changed. - -## Sprint 94 QA/QC evidence drilldown (2026-06-22) - -- Added a selected QA/QC evidence drilldown to the Quality Results panel. -- Surfaced candidate/reference layer names, analysis run/job provenance, status, score and completed/created timestamps for the selected persisted quality check. -- Added false-positive, false-negative and map-evidence handoff cards from persisted metric rows. -- Added parameter/findings JSON panes for persisted QA/QC provenance. -- Added regression coverage for drilldown structure, metric evidence and responsive styles. -- No API contracts, migrations, provider fetching or AI/model behavior changed. - -## Sprint 93 export handoff artifact polish (2026-06-21) - -- Added a latest handoff artifacts section to the Export Center for project reports, project metadata, dataset GeoJSON, detection GeoJSON and segmentation GeoJSON. -- Reused existing preview/download export actions from each latest artifact card without changing export API contracts or persistence. -- Added responsive styling for latest artifact cards, empty artifact states and compact artifact actions. -- Added regression coverage for grouped latest artifact surfaces and preserved preview/download controls. -- No API contracts, migrations, provider fetching or AI/model behavior changed. - -## Sprint 92 workflow rail interaction polish (2026-06-21) - -- Audited the live Overview workflow rail click path from Overview to Data, Map, QA/QC and Exports. -- Hardened the Map workflow step to reuse the first ready vector/GeoJSON dataset through the existing map-open flow when no layer is active. -- Hardened the Export workflow step to reuse the first ready vector/GeoJSON dataset through the existing export-open flow when no dataset is selected. -- Added regression coverage for the context-aware rail handler and fallback workspace navigation. -- No API contracts, migrations, backend behavior, provider fetching or AI model behavior changed. - -## Sprint 91 populated workflow audit polish (2026-06-21) - -- Audited the live populated demo workflow on `http://192.0.2.10:1202` across Overview, Data, Map, QA/QC, AI Labs and Exports. -- Tightened the Overview workflow guidance complete state so a fully populated flow shows `Ready for handoff` instead of another next-step prompt. -- Clarified the Map guidance detail by separating rendered layer feature count from AOI context. -- Added regression coverage for complete-state copy and precise Map guidance copy. -- No API contracts, migrations, backend behavior, provider fetching or AI model behavior changed. - -## Sprint 90 workflow guidance polish (2026-06-20) - -- Added an Overview workflow guidance rail for the V1 path: Project & AOI, Data, Map, QA / AI and Export. -- The guidance rail uses existing workspace navigation only; it does not add API calls, backend behavior or persistence. -- Added compact ready/waiting/next visual states based on already loaded project, dataset, map, QA/AI and export state. -- Added regression coverage for the guidance rail, existing workspace routing and responsive CSS contracts. -- No API contracts, migrations, backend behavior, provider fetching or AI model behavior changed. - -## Sprint 89 Export/System density polish (2026-06-20) - -- Grouped Export Center summary, handoff readiness, artifact actions, state cards and history into focused surfaces. -- Grouped Provider Capabilities into a system shell with registry state cards, capability cards and attribution/license provenance cards. -- Preserved existing export action, filter, preview/download and provider refresh workflows without API or persistence changes. -- Added static regression coverage for Export/System hierarchy and density contracts. -- No API contracts, migrations, backend behavior, provider fetching or AI model behavior changed. - -## Sprint 88 AI Labs density polish (2026-06-20) - -- Grouped Detection Lab and Segmentation Lab model registry, run controls, result loading and QA controls into focused surfaces. -- Added shared AI Lab density CSS for model lists, run forms, result/QA summaries and mobile-safe grids. -- Preserved existing detection/segmentation model loading, run, result filtering and QA callbacks without API or persistence changes. -- Added static regression coverage for AI Lab hierarchy and density contracts. -- No API contracts, migrations, backend behavior, provider fetching or AI model behavior changed. - -## Sprint 87 Change Detection density polish (2026-06-20) - -- Grouped Change Detection heading, input controls, result states, summary and warnings into focused surfaces. -- Reused shared result-state cards for not-enough-data and error states. -- Added compact desktop/mobile grids for vector inputs and change summary metrics. -- Added static regression coverage for Change Detection hierarchy and density contracts. -- No API contracts, migrations, backend behavior, provider fetching or AI model behavior changed. - -## Sprint 86 QA/QC workspace density polish (2026-06-20) - -- Grouped QA/QC summary, dataset evidence, refresh/filter controls and result history into focused surfaces. -- Kept existing persisted quality check filters, refresh behavior, metric cards and history rendering unchanged. -- Added compact mobile breakpoint grids for QA/QC summary, handoff evidence, filters and metric/history rows. -- Added static regression coverage for QA/QC workspace hierarchy and density contracts. -- No API contracts, migrations, backend behavior, provider fetching or AI model behavior changed. - -## Sprint 85 Map workspace density polish (2026-06-20) - -- Added a compact Map workspace context summary for selected AOI, active layer and rendered feature state. -- Grouped map controls, provenance, map frame and feature inspector into clearer surfaces without changing MapLibre behavior. -- Tightened map toolbar/provenance spacing and mobile breakpoint grids so Map workspace scans better on desktop and narrow screens. -- Added static regression coverage for Map workspace hierarchy and density contracts. -- No API contracts, migrations, backend behavior, provider fetching or AI model behavior changed. - -## Sprint 84 Data workspace density polish (2026-06-20) - -- Added selected-summary regions to Project, AOI and Dataset panels so active context is visible before forms. -- Split Data workspace panels into named form/list/catalog blocks to reduce form-first scanning friction. -- Restyled dataset upload as an embedded source-data block while preserving the existing upload flow. -- Added static regression coverage for Data workspace selected-summary, upload and catalog density contracts. -- No API contracts, migrations, backend behavior, provider fetching or AI model behavior changed. - -## Sprint 83 Workspace panel hierarchy polish (2026-06-20) - -- Made the Overview readiness strip a calmer section surface with tighter status tiles. -- Added explicit Overview action-copy and recommended-action regions for easier scanning and future UI regression coverage. -- Restyled recommended next actions as a lighter callout instead of another equally weighted white card. -- Added static regression coverage for Overview hierarchy regions, compact status tiles and secondary action-callout styling. -- No API contracts, migrations, backend behavior, provider fetching or AI model behavior changed. - -## Sprint 82 Shell density polish (2026-06-20) - -- Added a keyboard skip link to jump directly from the workbench shell to active workspace content. -- Added an explicit primary workspace navigation label and main focus target. -- Made narrow-view context chips, sidebar navigation and workspace shortcuts more compact and scroll-safe. -- Locked the smallest mobile breakpoint so the topbar context remains a horizontal rail instead of expanding into a tall preamble. -- Added static regression coverage for shell density, skip-link and mobile navigation contracts. -- No API contracts, migrations, backend behavior, provider fetching or AI model behavior changed. - -## Sprint 81 Result state consistency polish (2026-06-20) - -- Added shared result-state styling for compact loading, error, empty and ready states. -- Applied consistent state blocks to QA/QC results, export history and AI lab model/result panels. -- Replaced loose text/error rows in Detection and Segmentation Labs with scan-friendly state cards. -- Added static regression coverage for result-state CSS and panel usage contracts. -- No API contracts, migrations, backend behavior, provider fetching or AI model behavior changed. - -## Sprint 80 Operation form readability polish (2026-06-20) - -- Added structured headings, helper text, field wrappers and action rows to dense raster operation controls. -- Added the same form readability structure to vector clip, buffer and intersect controls. -- Added compact CSS contracts for dataset tool headings, helper text, field grids, action rows and inline error blocks. -- Added static regression coverage for raster/vector operation form readability contracts. -- No API contracts, migrations, backend behavior, provider fetching or AI model behavior changed. - -## Sprint 79 Accessibility focus polish (2026-06-20) - -- Added a shared visible focus-ring contract for primary buttons, workspace navigation, command chips, inspector tabs and dataset action buttons. -- Added explicit ARIA labels to workspace navigation, command chips and overview quick actions. -- Bound inspector tabs to their active tab panels with `aria-controls`, tab ids and `tabpanel` metadata. -- Added static regression coverage for keyboard focus and inspector tab accessibility contracts. -- No API contracts, migrations, backend behavior, provider fetching or AI model behavior changed. - -## Sprint 78 Export preview readability polish (2026-06-20) - -- Added compact preview summary cards for JSON/GeoJSON export payloads. -- Wrapped export preview JSON in a scroll-contained shell with a lightweight toolbar. -- Improved long key/value wrapping for large handoff artifacts while preserving the stored payload. -- Added static regression coverage for export preview readability contracts. -- No API contracts, migrations, backend behavior, provider fetching or AI model behavior changed. - -## Sprint 77 Inspector mobile visual polish (2026-06-20) - -- Added compact inspector action button grids for narrow screens. -- Added mobile-safe wrapping for dataset filenames, checksums, bounds, persisted export paths and loaded feature/job JSON. -- Added structured raster/vector tool panel classes so operation inputs and buttons stay inside the inspector. -- Added static regression coverage for inspector mobile CSS and dataset tool markup contracts. -- No API contracts, migrations, backend behavior, provider fetching or AI model behavior changed. - -## Sprint 76 Export/System mobile visual polish (2026-06-20) - -- Added scan-friendly Provider Capabilities cards with structured status, authority, geometry, query mode and layer chips. -- Tightened mobile export action cards, export history controls and export card headers. -- Added overflow wrapping for long provider limitations, attribution text, export ids and artifact paths. -- Added static regression coverage for Export/System mobile CSS and workflow markup contracts. -- No API contracts, migrations, backend behavior, provider fetching or AI model behavior changed. - -## Sprint 75 AI Labs mobile visual polish (2026-06-20) - -- Tightened mobile Detection and Segmentation Lab model card, form and result-summary sizing. -- Added overflow wrapping for long model ids, source tile paths, mask paths and QA summary values. -- Kept result tables scroll-contained instead of allowing them to widen the workbench. -- Added static regression coverage for AI Labs mobile CSS and workflow markup contracts. -- No API contracts, migrations, backend behavior, provider fetching or AI model behavior changed. - -## Sprint 74 Data/Map mobile visual polish (2026-06-20) - -- Tightened mobile Data workspace upload form, file input and dataset action button sizing. -- Kept desktop dataset action grid width contract while adding compact mobile tracks. -- Tightened Map toolbar, layer control sliders and empty-map quick actions for narrow screens. -- Added static regression coverage for Data/Map mobile CSS contracts. -- No API contracts, migrations, backend behavior, provider fetching or AI model behavior changed. - -## Sprint 73 QA/QC result filtering (2026-06-20) - -- Added client-side QA/QC result search, status and check-type filters. -- Added latest-eight density control with a show-all toggle for long-lived demo projects. -- Added a no-match empty state and reset action for filtered QA/QC result views. -- Kept metric evidence cards and raw persisted metrics unchanged. -- Added static regression coverage for QA/QC filtering and dense history styles. -- No API contracts, migrations, backend behavior, provider fetching or AI model behavior changed. - -## Sprint 72 Mobile overflow hardening (2026-06-20) - -- Clamped page-level horizontal overflow for the workbench shell on mobile. -- Kept sidebar navigation and workspace shortcut chips as contained horizontal scroll areas. -- Added wrapping/containment for long QA identifiers, dataset links and inspector values. -- Made inspector tabs two-column on narrow screens to avoid header overflow. -- Added static regression coverage for mobile overflow and long-identifier wrapping contracts. -- No API contracts, migrations, backend behavior, provider fetching or AI model behavior changed. - -## Sprint 71 QA/QC metric card polish (2026-06-19) - -- Added core metric evidence cards for precision, recall, F1, mean IoU and false positive/negative counts. -- Kept the raw persisted metric list available below the promoted metric evidence. -- Added number formatting for compact metric display while preserving persisted metric values. -- Added static regression coverage for metric promotion and responsive metric-card styles. -- No API contracts, migrations, backend behavior, provider fetching or AI model behavior changed. - -## Sprint 70 QA/QC handoff polish (2026-06-19) - -- Added candidate/reference handoff cards to the QA/QC workspace. -- Resolved persisted quality-check candidate/reference dataset IDs back to loaded dataset names where available. -- Filtered QA candidate context to non-reference vector/GeoJSON datasets while keeping persisted dataset roles unchanged. -- Added static regression coverage for QA handoff props, App wiring and responsive handoff styles. -- No API contracts, migrations, backend behavior, provider fetching or AI model behavior changed. - -## Sprint 69 Data catalog action polish (2026-06-19) - -- Added recommended-action hints to each dataset card so reference and candidate layers explain their QA role. -- Reworked dataset card actions into compact two-line buttons for Inspect, Map, Export / QA and Metadata. -- Preserved existing handlers, API contracts and persistence behavior; this is UI affordance polish only. -- Added static regression coverage for the action hints, disabled-action copy and responsive action grid. -- No API contracts, migrations, backend behavior, provider fetching or AI model behavior changed. - -## Sprint 68 Data catalog density polish (2026-06-19) - -- Added a compact Data catalog summary for Selected, Reference, Candidate and Source layers. -- Added scan-friendly dataset role badges, source/layer/CRS context and safer title wrapping to dataset cards. -- Kept candidate as a frontend workbench display role only: persisted dataset roles and API contracts remain unchanged. -- Added static regression coverage for the dataset catalog density structure and responsive CSS. -- No API contracts, migrations, backend behavior, provider fetching or AI model behavior changed. - -## Sprint 63 Map overlay ergonomics (2026-06-18) - -- Added an active layer provenance rail to the Map workspace, showing layer source, provenance and draw state from existing frontend state. -- Added clear empty guidance when no vector/result layer is active on the map. -- Added scan-friendly selected-feature property chips before the raw JSON inspector. -- Tightened panel title alignment after the visual polish pass exposed a generic CSS selector specificity issue. -- Added static regression coverage for the map provenance and feature-summary UI contracts. -- No API contracts, migrations, backend behavior, provider fetching or AI model behavior changed. - -## Sprint 62 Workbench visual polish (2026-06-18) - -- Added a compact workspace command bar for fast switching between the primary workbench surfaces. -- Polished the shell visual system with raised/sunken surfaces, softer shadows, tighter topbar spacing and more consistent panel styling. -- Replaced raw empty-state text in project/dataset panels with structured empty-state blocks. -- Improved Detection Lab and Segmentation Lab result summaries and wrapped long result tables in scroll-safe containers. -- Improved mobile workbench navigation by using horizontal rails for the primary nav and command chips, reducing vertical crowding without adding new behavior. -- Added static regression coverage for the visual polish contracts. -- No API contracts, migrations, backend behavior, provider fetching or AI model behavior changed. - -## Sprint 61 Golden QA scenario expansion (2026-06-18) - -- Expanded the deterministic QA/QC golden benchmark from one building scenario to four local fixture scenarios: partial match, perfect match, no-overlap and MultiPolygon match. -- Added `fixtures/golden/golden_qa_benchmarks.json` as the scenario manifest while preserving the original `expected_qa_metrics.json` baseline for existing demo workflow checks. -- Updated `scripts/run_golden_qa_benchmark.py` to run every scenario, verify metric drift and report aggregate `QualityCheck`/`Metric` persistence expectations. -- Added regression coverage for the multi-scenario manifest and aggregate benchmark output. -- No product behavior, API contract, migration, provider fetching or AI model behavior changed. - -## Sprint 49 Workbench shell UI refactor (2026-06-17) - -- Replaced the one-page workbench panel stack with a task-based UI shell. -- Added primary workspaces for Overview, Data, Map, QA/QC, AI Labs, Exports and System. -- Added a persistent top context bar for active project, AOI, dataset and layer state. -- Moved dataset details into a persistent right-side inspector instead of leaving them below the full workflow. -- Kept existing hooks, API contracts, backend behavior, migrations, provider behavior and AI configuration unchanged. -- Added static regression coverage for the new shell regions and workspace navigation anchors. - -## Sprint 50 Workspace usability polish (2026-06-17) - -- Reworked the Data workspace panels into compact operator forms and scan-friendly project/AOI/dataset cards. -- Reworked the Map workspace controls into a layer toolbar with clearer AOI/layer status. -- Reworked Detection Lab and Segmentation Lab into model, run, result and QA blocks instead of raw stacked controls. -- Added responsive card/form styling so nested workspaces do not overflow inside the shell. -- Added static regression coverage for the polished workspace structure. -- No API contracts, migrations, backend behavior, provider fetching or AI model behavior changed. - -## Sprint 48 Backend API contract audit (2026-06-17) - -- Added `scripts/audit_api_contracts.py` to compare the active FastAPI route surface with `docs/API_CONTRACTS.md`. -- Added the API contract audit to the readiness gate so undocumented routes and stale documented routes fail release checks. -- Corrected API contract drift for area detail/update, vector stats, dataset content and future analysis/YOLO export placeholders. -- Added regression tests for the contract audit and readiness integration. - -## Sprint 47 Workbench interaction smoke (2026-06-17) - -- Added stable `data-testid` anchors to the existing project, area, map, dataset, QA/QC and export controls for browser regression checks. -- Added `scripts/verify_workbench_interactions.sh` to verify the live backing state for project switching, AOI/map selection, dataset readiness, QA refresh and export refresh. -- Added readiness syntax coverage and static regression tests for the new interaction smoke. -- No API contracts, migrations, provider fetching, AI behavior or product capabilities changed. - -## Sprint 46 Workbench default-state smoke (2026-06-17) - -- Added `scripts/verify_workbench_default_state.sh` to verify the live frontend/API default demo state through the browser-facing URL. -- The smoke seeds the offline demo workflow and verifies the demo project, AOI geometry, ready candidate/reference datasets and persisted QA/QC result via canonical envelopes. -- Added readiness coverage for the new smoke script syntax and static tests for its expected contract checks. -- No API contracts, migrations, provider fetching, AI behavior or product capabilities changed. - -## Sprint 45 Default demo selection polish (2026-06-17) - -- Improved frontend project selection so a cold start prefers a populated demo/workbench project over an empty first project. -- Preserved the current project selection when it still exists and selected newly created projects immediately after creation. -- Updated the demo workflow hook to pass the seeded project as the preferred project during refresh. -- Added static regression coverage for the smarter project selection and demo refresh behavior. -- No API contracts, migrations, provider fetching, AI behavior or product capabilities changed. - -## Sprint 44 Workbench UI polish pass (2026-06-17) - -- Reworked the frontend workbench styling into a cleaner operational GIS interface with compact panels, modern controls, restrained green/neutral accents and scroll-contained long sections. -- Promoted `MapWorkspace` above the dense workflow grid so the map is visible early in the workbench flow. -- Moved `DatasetPanel` into the first workflow row beside project/area/provider setup. -- Added a static layout regression test for map-first ordering and scroll-contained workflow panels. -- No API contracts, migrations, provider fetching, AI behavior or product capabilities changed. - -## Sprint 43 Workbench bootstrap hook decomposition (2026-06-17) - -- Moved frontend bootstrap/project/result reload effects from `App.tsx` into `frontend/src/hooks/useWorkbenchBootstrap.ts`. -- `App.tsx` no longer imports or owns `useEffect`; it wires hook state into panels and delegates lifecycle loading to focused hooks. -- Extended orchestration regression tests so bootstrap loading and result refresh effects stay out of `App.tsx`. -- No behavior, API contracts, migrations, provider fetching or AI behavior changed. - -## Sprint 42 App entrypoint cleanup (2026-06-17) - -- Removed the stale `FormEvent`/`useState` React imports from `frontend/src/App.tsx`. -- Removed the UTF-8 BOM from the frontend entrypoint so future text patches and static checks are stable. -- Added a regression test that keeps `App.tsx` free of the stale imports and BOM. -- No behavior, API contracts, migrations, provider fetching or AI behavior changed. - -## Sprint 41 Demo workflow hook decomposition (2026-06-17) - -- Moved offline demo workflow orchestration from `App.tsx` into `frontend/src/hooks/useDemoWorkflow.ts`. -- The hook keeps the existing cross-module selection behavior for project, candidate/reference datasets, map AOI, QA/QC, detection, segmentation and export refresh state. -- Extended frontend orchestration regression tests so `demoApi` stays out of `App.tsx`. -- No API contracts, migrations, product features, provider fetching or AI behavior were introduced. - -## Sprint 40 Project workspace hook decomposition (2026-06-17) - -- Moved project listing/creation, area creation and project-scoped area/dataset loading from `App.tsx` into `frontend/src/hooks/useProjectWorkspace.ts`. -- Moved default clip-area selection into `useDatasetWorkflow.ts` and default map-area selection into `useMapWorkspaceState.ts`, keeping selection state with the owning workflow. -- Extended frontend orchestration regression tests to keep project, provider, change-detection and map orchestration out of `App.tsx`. -- No API contracts, migrations, product features, provider fetching or AI behavior were introduced. - -## Sprint 39 Frontend orchestration decomposition (2026-06-17) - -- Moved provider capability loading from `App.tsx` into `frontend/src/hooks/useProviderCapabilities.ts`. -- Moved change detection state and API orchestration into `frontend/src/hooks/useChangeDetectionWorkflow.ts`. -- Moved derived MapLibre workbench state, feature collection selection and feature-inspector reset behavior into `frontend/src/hooks/useMapWorkspaceState.ts`. -- Added regression tests that keep provider/change/map orchestration out of `App.tsx`. -- No API contracts, migrations, product features, provider fetching or AI behavior were introduced. - -## Sprint 38 Export Center preview hardening (2026-06-17) - -- Prevented HTML project report artifacts from being offered through the JSON preview path in the frontend Export Center. -- Added a clear backend `EXPORT_CONTENT_UNSUPPORTED` response when `/api/v1/exports/{export_id}/content` is called for HTML report artifacts. -- Extracted export JSON preview rendering into `frontend/src/components/exports/ExportPreview.tsx`. -- Added regression coverage for HTML report content-preview rejection. -- No API routes, migrations, product features, provider fetching or AI behavior were introduced. - -## Sprint 37 Tower PostgreSQL collation maintenance (2026-06-17) - -- Created a live Tower database backup before collation maintenance: `backups/geointel-before-collation-refresh-20260617-065707.dump`. -- Ran `REINDEX DATABASE geointel;` and `ALTER DATABASE "geointel" REFRESH COLLATION VERSION;` against the all-in-one PostGIS runtime. -- Verified the reused database volume now reports matching collation versions: `stored=2.36 actual=2.36`. -- Re-ran live migration smoke, browser runtime smoke, GIS runtime smoke and demo/export/golden QA workflow smoke successfully against `http://192.0.2.10:1202`. -- No API contracts, migrations, product features, provider fetching or AI behavior were introduced. - -## Sprint 36 PostgreSQL collation maintenance visibility (2026-06-17) - -- Added database collation version reporting to `scripts/live_migration_smoke.sh`. -- The live smoke now prints `COLLATION_VERSION_MISMATCH` plus the exact `ALTER DATABASE ... REFRESH COLLATION VERSION` acknowledgement command when an old PostGIS volume is reused on a newer runtime. -- Documented the Unraid maintenance procedure and backup/index review guidance. -- Added regression coverage for the collation mismatch reporting path. -- No API contracts, migrations, product features, provider fetching or AI behavior were introduced. - -## Sprint 35 Docker runtime secret hygiene (2026-06-17) - -- Removed embedded PostGIS database name/user/password defaults from `deploy/unraid/Dockerfile.all-in-one` image metadata. -- Kept database credentials as runtime configuration through `.env`, the Unraid template, Compose or `docker run -e`. -- Added regression coverage so `GEOINTEL_POSTGRES_PASSWORD` is not baked into the all-in-one Dockerfile again. -- Updated Unraid runtime documentation to clarify that credentials are runtime config, not image metadata. -- No API contracts, migrations, product features, provider fetching or AI behavior were introduced. - -## Sprint 34 browser-facing golden QA demo hardening (2026-06-17) - -- Hardened `scripts/verify_demo_export_workflow.sh` so the browser-facing demo/export smoke compares persisted QA/QC metrics against `fixtures/golden/expected_qa_metrics.json`. -- The runtime smoke now verifies QA/QC status, F1 score, precision, recall, mean IoU, false positives, false negatives and match counts from persisted `quality_checks`/`metrics`. -- Corrected the offline demo AOI to cover the golden building fixtures and made existing demo workflows self-heal stale/unsupported QA checks by syncing the AOI and persisting a fresh golden QA result. -- Added regression tests to keep the golden QA baseline wired into the demo/export smoke. -- Updated script documentation for the stricter runtime QA/QC checks. -- No API contracts, migrations, product features, live provider fetching or AI behavior were introduced. - -## Sprint 33 QA/QC benchmark readiness hardening (2026-06-17) - -- Added `scripts/verify_golden_qa_benchmark.sh` as a shell wrapper for the deterministic QA/QC golden benchmark. -- Made `scripts/run_readiness_check.sh` execute the golden QA/QC benchmark and syntax-check the wrapper. -- Hardened fixture validation so `fixtures/golden` GeoJSON files and expected fixture paths are checked. -- Added regression tests to keep the golden benchmark in the readiness gate. -- Updated script/backend docs to document the benchmark wrapper and release gate behavior. -- No API contracts, migrations, product features, live provider fetching or AI behavior were introduced. - -## Sprint 32 Unraid all-in-one runtime (2026-06-17) - -- Added `docker-compose.unraid.yml` for a single `geointel` container on Unraid. -- Added `deploy/unraid/Dockerfile.all-in-one`, embedding PostgreSQL 16/PostGIS, FastAPI, nginx and the built React frontend in one image. -- Added `deploy/unraid/all-in-one-start.sh` to start embedded PostGIS, apply Alembic migrations, start the backend and serve nginx. -- Added `deploy/unraid/nginx-all-in-one.conf` with localhost backend proxying inside the same container. -- Added a PNG DockerMan icon and made the Unraid template name match the running `geointel` container. -- Added DockerMan labels to the all-in-one Compose service so Unraid can associate the running container with web UI and icon metadata. -- Added `deploy/unraid/run-dockerman-container.sh` so repo deploys automatically replace Compose-owned containers with a DockerMan-native `geointel` container while preserving/migrating persisted data. -- Switched Tower deploy image creation from `docker compose build` to plain `docker build` to avoid Compose metadata labels on the final DockerMan-managed container. -- Updated Tower deploy scripts to install `/boot/config/plugins/dockerMan/templates-user/my-geointel.xml` and `/boot/config/plugins/dockerMan/images/geointel-icon.png`. -- Updated Tower deploy scripts to stop the old multi-container stack without removing volumes and start the all-in-one stack. -- Updated the Unraid template so the Docker can be edited from Unraid with one web port, storage path, PostGIS data path and app icon. -- Hardened live migration and browser runtime smoke scripts with startup retries and an icon check. -- Verified Tower deployment at `http://192.0.2.10:1202` with one healthy `geointel` container, passing live migration smoke, API proxy smoke and icon smoke. -- No API contracts, migrations, product features, provider fetching or AI behavior were introduced. - -## Sprint 31 Unraid deployment template (2026-06-17) - -- Made Docker Compose ports, storage path, PostGIS credentials, CORS origins and upload limit configurable through `.env` defaults. -- Added `deploy/unraid/geointel.env.example` for Unraid/Tower setup. -- Added `deploy/unraid/geointel-unraid-template.xml` documenting editable Unraid settings for the multi-container Compose stack. -- Added GeoIntel SVG icon assets for Unraid/template use and frontend favicon serving. -- Added regression coverage for Compose env defaults, Unraid template settings, README instructions and icon availability. -- No API contracts, backend behavior, migrations, product features, provider fetching or AI behavior were introduced. - -## Sprint 30 workbench component decomposition (2026-06-17) - -- Moved persisted QA/QC result rendering into `QualityResultsPanel`. -- Moved map controls, MapLibre composition and feature inspector rendering into `MapWorkspace`. -- Added regression coverage to verify `App.tsx` wires these presentational components without taking QA/map markup back inline. -- No API contracts, backend behavior, migrations, product features, provider fetching, AI behavior or UI redesign were introduced. - -## Sprint 29 dataset component decomposition (2026-06-17) - -- Moved dataset upload/list UI into `DatasetPanel`. -- Moved dataset details and job list UI into `DatasetDetailPanel`. -- Split raster and vector controls into `RasterControls` and `VectorControls`. -- Added regression coverage to verify `App.tsx` wires the new presentational dataset components without taking dataset markup back inline. -- No API contracts, backend behavior, migrations, product features, provider fetching, AI behavior or UI redesign were introduced. - -## Sprint 28 dataset workflow hook hardening (2026-06-17) - -- Moved dataset selection, upload, detail loading, dataset jobs and raster/vector operation orchestration from `App.tsx` into `useDatasetWorkflow`. -- Kept project dataset listing in `App.tsx` so project/area loading remains the shared workbench boundary. -- Added regression coverage to verify `App.tsx` still wires dataset, raster and vector UI callbacks while operation API ownership stays inside the focused hook. -- No API contracts, backend behavior, migrations, product features, provider fetching, AI behavior or UI redesign were introduced. - -## Sprint 27 export and QA workflow hook hardening (2026-06-17) - -- Moved Export Center orchestration state and API calls from `App.tsx` into `useExportWorkflow`. -- Moved QA/QC comparison state and persisted quality-check loading from `App.tsx` into `useQualityWorkflow`. -- Added regression coverage to verify `App.tsx` wires the new hooks while export and QA API ownership stays inside focused hooks. -- No API contracts, backend behavior, migrations, product features, provider fetching, AI behavior or UI redesign were introduced. - -## Sprint 26 frontend workflow hook hardening (2026-06-17) - -- Moved Detection Lab orchestration state and API calls from `App.tsx` into `useDetectionWorkflow`. -- Moved Segmentation Lab orchestration state and API calls from `App.tsx` into `useSegmentationWorkflow`. -- Added shared frontend `formatError` helper. -- Added regression coverage to verify `App.tsx` wires the workflow hooks and panels without direct detection/segmentation API ownership. -- No API contracts, backend behavior, migrations, product features, provider fetching, AI behavior or UI redesign were introduced. - -## Sprint 25 YOLO compatibility smoke hardening (2026-06-17) - -- Added an explicit `--check-model-load` mode to `scripts/yolo_preflight.py`. -- Added the same YOLO preflight entrypoint under `backend/scripts/` so it can run inside the backend Docker container. -- The smoke loads only a configured local model file through the YOLO adapter, runs no inference and does not download weights. -- The CLI rejects `--check-model-load` together with `--assume-dependencies` to avoid false-positive AI readiness. -- Added tests for successful mocked model-load smoke, load failure reporting and CLI guard behavior. -- Added the YOLO preflight script to the main readiness gate via Python compile validation. -- No base dependencies, API contracts, migrations, product features, provider fetching or detection persistence behavior were changed. - -## Sprint 24 demo/export artifact cleanup tooling (2026-06-17) - -- Added `scripts/cleanup_demo_artifacts.py`, a dry-run-first maintenance script for old offline demo export artifacts. -- Added the same cleanup entrypoint under `backend/scripts/` so it can run inside the backend Docker container. -- The cleanup keeps the newest exports per matching demo project, deletes only explicit `exports` rows/files when `--apply` is set and refuses file deletion outside `STORAGE_ROOT`. -- Added tests for cleanup candidate selection, storage-root path safety and readiness gate coverage. -- Added the cleanup script to the main readiness gate via Python compile validation. -- No API contracts, migrations, product features, provider fetching, AI inference or source dataset cleanup behavior were changed. - -## Sprint 23 V1 report handoff summary (2026-06-17) - -- Added V1 readiness summary data to project metadata exports. -- Added a V1 Readiness Summary and Known Limitations section to lightweight HTML project reports. -- The summary covers project, AOI, dataset readiness, QA/QC and export history using persisted state. -- No new report designer, PDF generation, provider fetching, AI inference, migrations or API route changes were introduced. - -## Sprint 22 V1 workbench status strip (2026-06-17) - -- Added a compact frontend status strip for project, AOI, datasets, active map layer, QA/QC and exports. -- The strip is driven by existing App state and suggests the next operator action in the V1 loop. -- Hardened the MapLibre component so GeoJSON sources/layers wait for the map style to finish loading before updates run. -- Hardened the offline demo workflow so duplicate historical demo projects prefer complete fixture state before repairing incomplete state. -- Added regression coverage to ensure the strip remains wired without introducing new API calls. -- No backend behavior, migrations, API contracts, provider downloads, AI inference or new dependencies were introduced. - -## Sprint 21 V1 demo workflow smoke hardening (2026-06-17) - -- Hardened the browser-facing demo/export smoke to verify connected V1 state: project area GeoJSON, fixture datasets, vector FeatureCollection content, vector feature summary, persisted QA/QC metrics and export downloads. -- Loading the offline demo workflow in the frontend now opens the candidate vector fixture dataset directly, so the map workbench is populated after the demo action. -- Added regression tests for the strengthened demo smoke and frontend demo dataset loading contract. -- No migrations, provider downloads, AI inference, new dependencies or API route renames were introduced. - -## Sprint 20 selected area map overlay (2026-06-17) - -- Added persisted AOI GeoJSON to area API responses without changing the database schema. -- Added a dedicated MapLibre area overlay layer with visibility and opacity controls. -- Added area list actions to choose which AOI is shown on the map. -- Added regression tests for area GeoJSON serialization and frontend map overlay wiring. -- No migrations, provider downloads, AI inference, new dependencies or API route renames were introduced. - -## Sprint 19 V1 map workbench controls (2026-06-17) - -- Added MapLibre layer visibility and opacity controls for the active GeoJSON workbench layer. -- Added click-to-inspect feature properties for the active map layer. -- Updated the visible app identity from the stale Sprint 9 label to GeoIntel Kempen V1 Workbench. -- Added regression tests that lock the map control and feature inspection wiring. -- No API contracts, migrations, backend behavior, provider fetching, AI inference or new dependencies were introduced. - -## Sprint 18 vector change detection foundation (2026-06-16) - -- Added `POST /api/v1/analysis/change-detection` for synchronous comparison of two vector datasets in the same project. -- Added a `ChangeDetectionService` that prefers persisted `vector_features`, falls back to stored GeoJSON with an explicit warning, and returns added/removed/unchanged GeoJSON features. -- Added a frontend Change Detection panel and MapLibre change overlay styling for added, removed and unchanged geometries. -- Added nginx no-cache headers for frontend HTML/assets so LAN Docker rebuilds are visible without stale browser modules. -- Added backend tests for persisted vector feature comparison and canonical API envelope behavior. -- No migrations, live provider fetching, AI inference, new dependencies, LiDAR, Copilot, Training Studio or separate Reports module were introduced. - -## Release hardening audit pass (2026-06-15) - -- Replaced remaining backend `datetime.utcnow()` usage with timezone-aware UTC timestamps. -- Verified the affected backend tests with `DeprecationWarning` promoted to errors. -- Split the frontend production bundle into explicit app, React vendor and MapLibre vendor chunks. -- Raised the Vite chunk warning threshold to match the isolated MapLibre GIS dependency rather than masking app-code growth. -- Hardened the main readiness gate so backend deprecation warnings fail release readiness. -- Added API contract smoke validation to the main readiness gate. -- Hardened the pass-end placeholder scan to skip dependency, build-output and bytecode-cache folders. -- Added backend tests for the release/readiness script expectations. -- Updated `docs/TODO.md` with current implementation status while preserving older planning context. -- No API contracts, migrations, product features, AI dependencies or provider behavior were changed. - -## Docker runtime hardening (2026-06-15) - -- Fixed the backend Docker build by copying `README.md` and `app/` before `pip install .`. -- Removed mandatory Compose `.env` references so `docker compose up` works with checked-in local defaults. -- Published the Docker Compose frontend on host port `1202`. -- Added backend CORS defaults for `http://localhost:1202` and `http://127.0.0.1:1202`. -- Stopped publishing PostGIS on host port `5432`; backend uses Docker-internal `db:5432`. -- Added a PostGIS healthcheck and made the backend wait for a healthy database. -- Added a backend Docker start script that retries a real SQL connection before running migrations, avoiding first-start database race conditions. -- Made the backend container run `alembic upgrade head` before starting Uvicorn. -- Added backend/frontend `.dockerignore` files to keep dependency folders, build outputs and caches out of Docker build contexts. -- Added Docker runtime configuration regression tests. -- Fixed Alembic logging format so Docker migration logs no longer print literal `%(levelname)` formatter strings. -- Changed the frontend API default to same-origin requests and added a Vite proxy for `/api` and `/health`, with Docker routing to `http://backend:8000`. -- Added a browser runtime verification script that fails when the frontend `/api` proxy returns Vite HTML instead of the backend JSON envelope. -- Updated environment and local runbook documentation so Docker/LAN browser clients use same-origin API calls through the frontend proxy by default. -- Corrected example YOLO environment variables to the names the backend actually reads: `YOLO_ENABLED`, `YOLO_MODEL_PATH` and `YOLO_MAX_TILES`. -- Replaced the Docker frontend runtime with an nginx-served production build and explicit `/api` plus `/health` reverse proxy to the backend service, avoiding Vite HTML fallback for API requests. - -## M6 — Codex Autonomy Pack - -Added: - -- M6 autonomy boundaries. -- M6 quality gates. -- Codex self-review checklist. -- Failure recovery playbook. -- Gap registry. -- Next-day execution checklist. -- Final handoff template. -- Codex pass prompts PASS 00 through PASS 12. -- GitHub issue templates and PR template. -- GitHub Actions docs/contract smoke workflow. -- Codex preflight and pass-end scripts. - -Purpose: - -- Prepare the repository so Codex can build with strict guidance and bounded improvement freedom. - -## M7 - Implementation Control Layer - -Added: - -- M7 implementation control layer. -- Locked build sequence. -- Regression trap catalogue. -- Codex self-review checklist. -- Geospatial calculation rules. -- Frontend state rules. -- API response rules. -- Module completion matrix. -- Codex decision boundaries. -- Proposed improvements backlog. -- End-of-pass review prompts. -- Regression and contract drift audit prompts. -- Module contracts for project/area/dataset, detection boundary and QA/QC. -- M7 self-review scripts. - -## M8 - Tomorrow Execution Pack - -- Added Day 1 Codex execution pack. -- Added pass-by-pass Day 1 prompts. -- Added autonomy boundaries, failure recovery and quality gate matrix. -- Added operator checklist and smoke script scaffold. -- Added next-pass guidance for Day 2 GeoAI loop. - -## v0.9 — M9 Max Preparation - -- Added Codex day-one master prompt. -- Added autonomous build doctrine and pass scorecards. -- Added real-vs-demo data policy and detailed data contracts. -- Added geospatial edge cases, UI state spec and API validation examples. -- Added implementation review script, regression map and gap-to-task conversion rules. -- Added final pre-code checklist and long-form prompt variants. - -## Sprint 1 readiness hardening (2026-06-11) - -- Added cross-platform backend/runtime scripts with `python`/`python3` fallback in readiness tooling. -- Fixed backend packaging metadata so editable install works in current flat repo layout. -- Added dependency and smoke test script updates for Sprint 1 services. -- Added minimal Sprint 1 tests for health endpoint, GeoJSON metadata extraction, invalid payload rejection, and dataset content reads. -- Fixed frontend README doc reference typo for repository conventions. -- Updated Sprint 1 docs to include backend import smoke and concrete local setup commands. - -## Sprint 2 foundation (2026-06-11) - -- Added canonical vector/raster dataset handling and lifecycle status transitions (`uploaded`, `validating`, `ready`, `failed`). -- Added vector metadata extraction (feature count, geometry types, bounds, approximate area, CRS assumptions). -- Added raster metadata extraction service with dependency-aware fallback (`RASTER_PROCESSING_UNAVAILABLE`). -- Added deterministic storage metadata capture (`original_filename`, `stored_filename`, `content_type`, `size_bytes`, `checksum_sha256`) and upload folder layout. -- Added dataset inspection/vector summary/raster metadata API endpoints and frontend detail panel support. -- Added Sprint 2 tests for vector metadata, invalid GeoJSON handling, legacy geojson compatibility and raster dependency fallback. - -## Sprint 3 foundation (2026-06-11) - -- Added job model and database migration for queued/running/success/failed operations. -- Added job APIs for create/list/read/status under project scope. -- Added vector operation services and route wiring for inspect/bbox/stats/clip/buffer/intersect. -- Added raster operation scaffolding for inspect/metadata/preview, with dependency-aware clip/tile unavailability. -- Added frontend operation controls, job status display, and derived dataset link-through in dataset detail panel. -- Updated API contracts and execution log for Sprint 3 foundations. - -## Sprint 5 raster analytics hardening (2026-06-11) - -- Added raster band statistics operation: - - min, max, mean, std, nodata count, nodata ratio, valid pixel count, dtype, band index and optional histogram. - - chunked raster reads to reduce memory pressure and explicit dependency-aware unavailable mode when raster libs are missing. -- Added raster reproject operation foundation with CRS validation: - - supports target CRS selection via explicit parameter, - - persists derived output dataset with operation provenance, - - records operation parameters and error details when invalid. -- Hardened raster clip and tile manifest flow: - - explicit empty clip failure behavior, - - bounds/metadata refresh and improved tile manifest fields. -- Added raster operation job persistence tests: - - result_json and error_message persistence, - - dependency-aware statistics failure behavior, - - invalid CRS handling, - - output linkage for reprojected datasets. -- Extended dataset UI dataset detail job panel: - - raster metadata visibility (CRS, bounds, resolution), - - raster band statistics rendering, - - reproject form and job result visibility. - -## Sprint 6 local spectral indices (2026-06-12) - -- Added local spectral index operations: - - NDVI endpoint - - NDWI endpoint - - NDBI endpoint -- Added explicit spectral index input validation: - - positive integer checks - - source raster band-count bounds checks -- Implemented dependency-aware index execution for missing raster dependencies. -- Added local spectral raster output generation using float32 and `NaN` invalid handling. -- Stored index-derived dataset provenance metadata: - - `source_dataset_id` - - `operation` (`raster.ndvi`, `raster.ndwi`, `raster.ndbi`) - - `band_mapping` - - `formula` - - `output_dtype` - - `nodata_strategy` - - `value_range_note` - - `created_at` - - `output_dataset_id` - - `path` -- Extended dataset detail UI with spectral index controls and result dataset actions. -- Updated: - - `docs/API_CONTRACTS.md` - - `docs/RASTER_OPERATIONS_SPEC.md` - - `backend/README.md` - - `frontend/README.md` - - `docs/CODEX_EXECUTION_LOG.md` - -## Sprint 7A persistence and QA foundation (2026-06-12) - -- Added `vector_features` as first-class queryable vector state while preserving original uploaded files as source artifacts. -- Added `quality_checks` and `metrics` as persisted QA/QC domain records. -- Added Alembic migration `202606120700_sprint7a_persistence_foundation.py` for vector features, quality checks, metrics and required indexes. -- Persisted uploaded vector GeoJSON feature properties and geometries into PostGIS-backed feature rows. -- Updated QA candidate-vs-reference jobs to persist quality checks and metric rows and return `quality_check_id`. -- Hardened GRB/OSM provider contracts as honest `not_configured` capability stubs only. -- Added tests for Sprint 7A persistence, dataset role validation, provider contracts, migration integrity and QA route persistence. - -## Sprint 7B provider integration skeleton (2026-06-12) - -- Added central provider registry entries for `grb`, `osm`, `manual` and `fixture`. -- Added provider capability, layer, status and future import-contract endpoints using the existing API envelope style. -- Kept GRB and OSM as explicit `not_configured` providers with no live WFS, Overpass or download behavior. -- Added provider-to-dataset mapping rules for future imports through `DatasetService` and `VectorFeatureService`. -- Added lightweight frontend Provider Capabilities panel with status, authority, layers, query modes and limitations. -- Added live PostGIS migration smoke script for opt-in local database verification. -- Added Sprint 7B provider registry/API tests. - -## Sprint 8 Detection Lab foundation (2026-06-12) - -- Added `detections` as first-class persisted PostGIS records linked to project, dataset, job and analysis run. -- Hardened `analysis_runs` with dataset/job/model/result metadata for future detection and segmentation workflows. -- Added model registry capabilities for `yolo-placeholder` and `manual-fixture-detector`. -- Added Detection Lab service and API foundation with dependency-aware `DETECTION_MODEL_UNAVAILABLE` responses. -- Added explicit fixture detector mode for tests/demo fixtures only; no fake production inference was introduced. -- Added minimal frontend Detection Lab panel for model status, raster dataset selection, confidence threshold and run status. -- Added Sprint 8 tests for persistence, model capabilities, unavailable model behavior, invalid dataset validation, explicit fixture persistence and API envelope shape. - -## Sprint 8B configured YOLO foundation (2026-06-12) - -- Added optional `ai` backend dependency group for Ultralytics/Torch without making AI dependencies mandatory for normal startup. -- Added `yolo-configured` model registry capability with `not_configured`, `dependency_unavailable` and `configured` status behavior. -- Added import-safe YOLO adapter that loads only an existing local model path and does not auto-download weights. -- Added raster tile manifest validation, configured tile limits and pixel bbox to EPSG:4326 detection polygon conversion. -- Added mocked YOLO persistence tests that verify first-class detection records without requiring YOLO dependencies. -- Added Detection Lab tile manifest path input for configured YOLO runs. -- Updated AI/API/backend/frontend docs for Sprint 8B configuration and limitations. - -## Sprint 8C detection visualization and QA integration (2026-06-12) - -- Added detection result review endpoints for run lists, filtered detections, detection detail and GeoJSON FeatureCollection output. -- Added detection QA against persisted reference `vector_features` using existing `quality_checks` and `metrics`. -- Added frontend Detection Lab run selection, detection table, class/confidence filters and MapLibre detection GeoJSON overlay. -- Added frontend detection QA controls and metric summary display. -- Added tests for detection GeoJSON shape, filters, detail, QA persistence, no-match QA and Sprint 8B manifest edge cases. -- Segmentation, LiDAR, Copilot, Training Studio and Reports remain out of scope. - -## Sprint 9 Segmentation Lab foundation (2026-06-12) - -- Added `segmentations` as first-class persisted PostGIS MultiPolygon records linked to project, dataset, job and analysis run. -- Added deterministic segmentation mask path convention under `storage/masks/{project_id}/{analysis_run_id}/tile_{tile_index}/`. -- Added segmentation model registry capabilities: - - `segmentation-placeholder` - - `fixture-segmenter` - - `yolo-seg-configured` - - `sam-configured` -- Added Segmentation Lab service and API foundation for model listing, run creation, run/result listing, detail, GeoJSON output and reference QA. -- Added segmentation QA against persisted reference `vector_features` using existing `quality_checks` and `metrics`. -- Added minimal frontend Segmentation Lab UI with model status, raster selection, run/result table, map overlay and QA metric display. -- Real SAM, real YOLO-seg, model downloads, new AI dependencies, LiDAR, Copilot, Training Studio and Reports remain out of scope. - -## Sprint 10 release hardening and modularization (2026-06-13) - -- Extracted project, area, provider capabilities, Detection Lab and Segmentation Lab UI sections from `frontend/src/App.tsx` into focused components. -- Preserved existing API client usage, state ownership, MapLibre overlay behavior and workbench UX. -- Hardened readiness checks to include Alembic head verification and `scripts/live_migration_smoke.sh` syntax validation. -- No new product features, migrations, AI dependencies or live external provider fetching were introduced. - -## Sprint 11 live Docker/PostGIS runtime validation (2026-06-13) - -- Hardened `scripts/live_migration_smoke.sh` so fresh databases run Alembic migrations before checking `PostGIS_Version()`. -- Added live runtime schema-object checks for core migrated tables and geometry indexes. -- Added backend tests that lock the live migration smoke ordering and schema-check contract. -- Documented exact Docker/PostGIS validation commands, expected `DATABASE_URL` and local cleanup commands. -- Docker was unavailable in the current shell, so live container execution remains pending on a Docker-enabled machine. - -## Sprint 12 QA/QC golden dataset and benchmarking (2026-06-15) - -- Added deterministic golden building QA/QC fixtures and expected metric baseline. -- Added `scripts/run_golden_qa_benchmark.py` to run existing QA/QC logic against the golden fixtures and fail on metric drift. -- Added backend tests covering expected golden metrics and `QualityCheck`/`Metric` persistence verification. -- Documented benchmark purpose, command, expected outputs, tolerance and limitations. -- No product features, API contracts, migrations, live providers, AI models or new dependencies were introduced. - -## Sprint 13 real YOLO operational hardening (2026-06-15) - -- Added `YoloPreflightService` for local configured-YOLO readiness checks without loading models or running inference. -- Added `scripts/yolo_preflight.py` for checking enabled state, optional dependency availability, local model path, tile manifest validity, tile limit and referenced tile paths. -- Added backend tests for disabled, dependency-unavailable and ready preflight states plus CLI JSON output. -- Documented preflight usage in backend and AI pipeline docs. -- No model downloads, API contracts, migrations, new dependencies, segmentation behavior or provider fetching were introduced. - -## Sprint 14 Docker GIS runtime enablement (2026-06-16) - -- Added a backend `gis` optional dependency group for the approved raster/vector runtime stack. -- Updated the backend Docker image to install the `gis` extra plus GDAL/GEOS/PROJ system packages. -- Added `scripts/verify_gis_runtime.sh` to verify browser-facing PostGIS, Rasterio and GeoPandas capabilities through the frontend proxy. -- Added `scripts/gis_import_smoke.py` and made the backend Docker build fail if Rasterio, GeoPandas or pyogrio cannot be imported. -- Moved the Docker build-time GIS import smoke into the backend build context and kept the root script as a local wrapper. -- Included the GIS runtime script syntax check in the main readiness gate. -- Added backend and frontend Docker Compose healthchecks and made the frontend wait for a healthy backend. -- Added regression tests for Docker GIS dependency installation and capability verification script coverage. -- Documented Docker GIS runtime verification commands for local and LAN deployments. -- No API contracts, migrations, AI dependencies, provider fetching or product features were changed. - -## Sprint 15 explicit demo workflow seed (2026-06-16) - -- Added `POST /api/v1/demo/workflow` to seed or return an explicit offline demo workflow. -- The demo workflow creates a project, AOI, fixture reference building dataset, fixture candidate building dataset and persisted QA/QC metrics. -- Added `scripts/seed_demo_workflow.py` for CLI-based demo seeding. -- Added frontend "Load demo workflow" action in the Projects panel. -- Added tests for the demo endpoint envelope and fixture contract. -- No live GRB/OSM fetching, AI inference, migrations or new dependencies were introduced. - -## Sprint 16 QA/QC result visibility (2026-06-16) - -- Added `GET /api/v1/projects/{project_id}/quality-checks` to list persisted quality checks and metric rows. -- Added a frontend QA/QC Results panel for project-level persisted QA output. -- Demo workflow loading and QA actions now refresh visible QA/QC results. -- Added backend tests for quality check listing and canonical response envelopes. -- No migrations, new dependencies, live provider fetching or AI inference were introduced. - -## Sprint 17 export foundation (2026-06-16) - -- Hardened `POST /api/v1/exports/geojson` so exports persist `Export` rows instead of returning dataset ids as export ids. -- Added GeoJSON export support for vector datasets, detection runs and segmentation runs using existing persisted geometry services. -- Added project metadata JSON export, lightweight project report HTML export and export list/read/content/download endpoints. -- Added a frontend Export Center panel for creating exports, listing export records, previewing JSON artifact content and downloading artifacts. -- Added export history to project metadata/report artifacts. -- Added `scripts/verify_demo_export_workflow.sh` to smoke test demo seeding, QA/QC visibility, metadata/report/vector exports, export listing and artifact downloads through the browser-facing URL. -- Added backend tests for export persistence, artifact writing, raster rejection, HTML report creation, canonical export envelopes and raw file downloads. -- No migrations, new dependencies, live provider fetching, AI inference, LiDAR, Copilot, Training Studio or separate Reports module were introduced. - -## Sprint 51 QA/QC and export workspace polish (2026-06-17) - -- Polished the QA/QC workspace with persisted-check summary tiles, clearer empty state, quality-check cards and metric chips. -- Polished the Exports workspace with artifact action groups, latest-export card, export history cards and preview panel framing. -- Preserved existing API clients, callbacks and export/QA behavior. -- Added regression coverage for the QA/QC and Exports workspace structure. -- No API contracts, migrations, product capabilities, live provider fetching or AI/model dependency changes were introduced. - -## Sprint 52 selected context inspector tabs (2026-06-17) - -- Replaced the fixed dataset-only right inspector with tabbed Context, Dataset, QA/Exports and AI Runs inspection. -- Reused the existing dataset detail component for raster/vector operations so dataset behavior and callbacks remain unchanged. -- Added context cards for selected project, AOI, map feature, latest QA/QC result, latest export and selected detection/segmentation run state. -- Added regression coverage for inspector wiring and tab structure. -- No API contracts, migrations, product capabilities, live provider fetching or AI/model dependency changes were introduced. - -## Sprint 53 map/dataset selection ergonomics (2026-06-17) - -- Added active selected-state styling to dataset cards. -- Added dataset quick actions for opening the selected dataset in the Map workspace or Exports workspace. -- Added inspector navigation actions for Data, Map, QA/QC, Exports and AI Labs workspaces. -- Preserved existing dataset detail loading, map layer state, export actions and API client behavior. -- Added regression coverage for dataset quick actions and inspector navigation wiring. -- No API contracts, migrations, product capabilities, live provider fetching or AI/model dependency changes were introduced. - -## Sprint 54 populated-state UI polish (2026-06-17) - -- Ran the live demo/export workflow against Tower and audited populated Data and Exports states. -- Changed the Data workspace to keep Project and AOI side by side while giving the Dataset catalog a full-width row. -- Compacted the Exports history to show the latest 10 artifacts by default with an explicit show-all toggle. -- Kept a visible Export Preview panel even before preview content is selected. -- Shortened displayed export paths while preserving the full path in the element title. -- Added regression coverage for populated-state Data layout, export limiting and export preview empty state. -- No API contracts, migrations, product capabilities, live provider fetching or AI/model dependency changes were introduced. - -## Sprint 55 live visual shell polish (2026-06-17) - -- Audited the live workbench visually in Browser on `http://192.0.2.10:1202`. -- Compacted the top context bar and primary navigation so the workbench has more usable canvas space. -- Moved the inspector below the workspace on standard desktop widths instead of forcing a cramped three-column layout. -- Preserved the side inspector behavior for wider screens. -- Improved Map workspace control wrapping so the map/status controls do not clip at 1280px. -- Reset page scroll on workspace changes so workspaces open from their heading instead of inheriting stale scroll positions. -- Added regression coverage for the standard-desktop layout and workspace scroll reset. -- No API contracts, migrations, product capabilities, live provider fetching or AI/model dependency changes were introduced. - -## Sprint 56 export history controls (2026-06-17) - -- Added frontend-only export history search across export type, status, id and storage path. -- Added export type and status filters based on the currently loaded export records. -- Made the existing latest-10 export limiter operate on filtered results instead of the whole export list. -- Added a no-match empty state and reset view action for filtered export history. -- Slightly compacted export action buttons so filters are visible earlier on standard desktop viewports. -- Added regression coverage for filtering controls, filtered list limiting and the no-match state. -- No API contracts, migrations, product capabilities, live provider fetching or AI/model dependency changes were introduced. - -## Sprint 57 safer demo export cleanup (2026-06-17) - -- Hardened the existing dry-run-first demo export cleanup command with a `--max-delete` safety cap. -- Added repeated `--export-type` filters so operators can clean only selected artifact kinds. -- Cleanup apply runs now report a `blocked_reason` instead of deleting when selected candidates exceed the cap. -- Dry-run output now includes `candidate_exports` with export ids so duplicate storage paths remain auditable. -- Updated root and backend cleanup entrypoints, docs and regression coverage. -- No API contracts, migrations, product capabilities, live provider fetching or AI/model dependency changes were introduced. - -## Sprint 58 demo cleanup dry-run smoke (2026-06-18) - -- Added `scripts/verify_demo_cleanup_dry_run.sh` to verify the demo export cleanup path against a running backend without passing `--apply`. -- The smoke supports compose, all-in-one container and local modes, and asserts `dry_run=true`, `deleted_export_count=0`, empty deleted files and candidate dry-run fields. -- Added the smoke syntax check to the main readiness gate and regression coverage for the non-mutating script contract. -- Updated maintenance documentation in `scripts/README.md`, `docs/STORAGE_ARCHITECTURE.md` and `backend/README.md`. -- No API contracts, migrations, product capabilities, live provider fetching or AI/model dependency changes were introduced. - -## Sprint 59 workbench screenshot artifacts (2026-06-18) - -- Added `scripts/capture_workbench_screenshots.sh` for optional visual regression handoff screenshots. -- The capture script seeds the explicit offline demo workflow, opens each main workspace and writes viewport PNG screenshots plus a `manifest.json` under ignored local artifacts. -- Desktop screenshots are always captured; mobile screenshots are captured by default and can be disabled with `CAPTURE_MOBILE=0`. -- Added readiness syntax coverage and regression checks for the non-mutating screenshot capture contract. -- No API contracts, migrations, product capabilities, live provider fetching or AI/model dependency changes were introduced. - -## Sprint 60 API error-envelope contract hardening (2026-06-18) - -- Aligned backend error responses with the documented `ApiError` contract: top-level `error`, `message`, `details` and `request_id`. -- Preserved frontend compatibility with both the canonical top-level error payload and the older nested error-object shape. -- Added regression coverage for AppError, HTTPException and validation-error envelopes. -- Added static frontend parser coverage so API client error parsing does not drift silently. -- No migrations, product capabilities, live provider fetching or AI/model dependency changes were introduced. - -## Sprint 64 export/report handoff polish (2026-06-18) - -- Added a handoff readiness summary to the Export Center for selected dataset, detection run, segmentation run and latest artifact context. -- Grouped existing export actions into scan-friendly artifact cards for project report, metadata, vector GeoJSON, detection GeoJSON and segmentation GeoJSON. -- Added clearer export history provenance with formatted export-type badges, analysis-run ids and created timestamps when available. -- Added regression coverage for the Export Center handoff structure and responsive styling. -- No API contracts, migrations, product capabilities, live provider fetching or AI/model dependency changes were introduced. - -## Sprint 65 project report readability polish (2026-06-18) - -- Reworked the lightweight HTML project report template into a self-contained handoff layout with hero, readiness pill, scorecards and sectioned tables. -- Added print-friendly CSS and scroll-safe table wrappers while preserving the existing `project_report_html` export type and download behavior. -- Added source/CRS columns to the dataset inventory section and clearer "Dataset inventory", "QA/QC evidence" and "Artifact history" report headings. -- Added regression coverage for report layout markers, print CSS and HTML escaping. -- No API contracts, migrations, product capabilities, PDF/report-designer functionality, live provider fetching or AI/model dependency changes were introduced. - -## Sprint 67 map empty-state quick actions (2026-06-19) - -- Added ready vector/GeoJSON dataset quick actions to the Map workspace empty state. -- Reused the existing `openDatasetInMap` flow so selecting a quick action loads the persisted dataset layer without changing API contracts. -- Added responsive styling and regression coverage for the Map quick-action grid. -- Verified locally against the live demo state that the empty map state exposes two dataset actions and opens `demo_predicted_buildings.geojson` as a 2-feature map layer. -- No API contracts, migrations, product capabilities, live provider fetching or AI/model dependency changes were introduced. - -## Sprint 103 AI Lab run readiness (2026-06-24) - -- Added compact run-readiness panels to Detection Lab and Segmentation Lab. -- Detection readiness now shows raster dataset, model availability and the configured-YOLO tile manifest requirement before submitting a run. -- Segmentation readiness now shows raster dataset, model availability and tile manifest provenance state before submitting a run. -- Added regression coverage for the AI Lab readiness UI contract and styling. -- No API contracts, migrations, product capabilities, live provider fetching or AI/model dependency changes were introduced. - -## Sprint 104 AI Lab action guardrails (2026-06-24) - -- Added explicit action guardrails below Detection and Segmentation run-readiness panels. -- Detection now distinguishes configured model state from UI-runnable state and blocks the explicit test/demo-only fixture detector in the normal run form. -- Segmentation now distinguishes configured model state from UI-runnable state and blocks the explicit test/demo-only fixture segmenter in the normal run form. -- Added regression coverage for AI Lab action guardrails and compact guardrail styling. -- No API contracts, migrations, product capabilities, live provider fetching or AI/model dependency changes were introduced. - -## Operator YOLOv8s hard-negative benchmark (2026-07-08) - -- Trained a Tower-local YOLOv8s hard-negative building detector from the existing operator tile dataset. -- Published the trained runtime artifact as `geointel-building-yolov8s-hardneg160r4e50-pt` in the live model asset catalog without adding application download behavior. -- Reused persisted dense QA and hard-negative benchmark runs through the existing live API. -- Observed dense QA F1 scores up to `0.6380` and safest current threshold behavior around `0.25`. -- Kept the model inactive by default because the `kasterlee_bos` hard-negative sample still produced 10 detections at threshold `0.25`. -- No repository code, API contracts, migrations, product behavior, provider fetching or AI dependency strategy changed in this benchmark pass. - -## Sprint 122 Detection model asset activation guardrails (2026-07-08) - -- Hardened Detection Lab so local model assets are no longer auto-selected when the backend reports available model files. -- Required an explicit local model asset choice before configured YOLO can be submitted when local assets exist. -- Added local model asset details in the run surface: active runtime env status, SHA-256 preview, file size, path and `will_download_models`. -- Surfaced the current YOLOv8s hard-negative benchmark candidate and recommended starting threshold `0.25` as operator guidance. -- Added regression coverage for the no-auto-select behavior and UI guardrail copy. -- No backend API contracts, migrations, model downloads, provider fetching or model weight mutation behavior changed. - -## Sprint 123 Raster detection manifest handoff (2026-07-08) - -- Added a structured raster tile manifest handoff from the Data workspace into Detection Lab. -- Raster controls now surface manifest tile count, tile size, overlap and tile-set provenance before handing the manifest to AI workflows. -- The Detection Lab handoff now selects the configured YOLO run path, keeps local model assets explicit, applies the current recommended `0.25` starting threshold and refreshes YOLO preflight for the linked manifest. -- Detection Lab now shows linked tile manifest provenance plus preflight manifest validation, tile count and `will_run_inference` state. -- Added regression coverage for the handoff contract and preserved the existing no-auto-select model guardrail. -- No backend API contracts, migrations, model downloads, provider fetching or model weight mutation behavior changed. - -## Sprint 133 Detection threshold calibration UX (2026-07-08) - -- Added a Detection Lab calibration comparison panel that joins persisted detection runs with persisted QA/QC checks. -- The panel compares confidence threshold, model, detection count, precision, recall, F1, false positives and false negatives. -- Added operator guidance for best F1, best precision and lowest false-positive pressure, with a promotion guardrail to inspect evidence across AOIs before accepting a setting. -- Added regression coverage for the persisted calibration UI contract. -- No backend API contracts, migrations, model downloads, provider fetching or AI/model execution behavior changed. - -## Sprint 134 Guided detection calibration runner (2026-07-08) - -- Added an explicit in-app calibration runner to Detection Lab for operator-selected confidence threshold sweeps. -- The runner reuses existing detection and QA APIs once per threshold, producing persisted DetectionRun, Job, Detection, QualityCheck and Metric records. -- Added visible threshold progress with per-row status, detection count, precision, recall, F1, false positives and false negatives. -- Added validation guardrails for selected project, raster dataset, reference dataset, configured non-fixture model, tile manifest and explicit local model asset. -- Added regression coverage for the guided runner contract. -- No backend API contracts, migrations, model downloads, provider fetching, automatic promotion or model file mutation behavior changed. - -## Sprint 142 Calibration evidence response uniqueness (2026-07-08) - -- Hardened the calibration evidence exporter so response artifacts are keyed by threshold and quality-check id. -- Prevented multi-model portfolios from overwriting runs that share the same threshold. -- Added regression coverage proving same-threshold runs are preserved in the assembled portfolio. -- No API contracts, migrations, model downloads, provider fetching or AI inference behavior changed. -# Unreleased - -- Added `scripts/audit_operator_yolo_dataset_quality.py`, an operator-only YOLO tile dataset quality audit that produces JSON and Markdown reports for sample coverage, split coverage, repeated hard-negative pressure and label-size integrity before further training runs. -- Added pytest coverage and readiness syntax checking for the new operator YOLO dataset audit script. -- Recorded live Tower audit results showing `yolo-building-tile-expanded160` as the clean current baseline and r4/r8 hard-negative datasets as repeat-heavy evidence sets that need more unique background AOIs before further hard-negative training. -- Expanded the explicit operator background-candidate AOI registry from 3 to 9 unique hard-negative locations and added tests for diversity/spread before further YOLO training. -- Fixed the all-in-one Dockerfile so documented operator scripts are copied into `/app/scripts/`, then prepared and audited the new Tower `yolo-building-tile-uniquehardneg160` dataset as the next training candidate. -- Fixed the YOLO preflight CLI so it respects environment-provided runtime configuration instead of reporting `not_configured` unless CLI flags were supplied. -- Rebuilt the Tower all-in-one image with AI dependencies and verified live migration smoke, browser runtime and YOLO preflight readiness against an existing raster tile manifest. -- Fixed the all-in-one Dockerfile so the operator YOLO training wrapper is available and executable inside `/app/scripts`. +All notable public changes are recorded here. Internal deployment events, +runtime evidence and model-review artifacts are intentionally not part of the +public repository. + +## Unreleased + +- Prepared the repository for public release under Apache-2.0. +- Reworked the README around user workflows, capabilities and supported setup. +- Removed generated accuracy evidence, production snapshots and internal + execution records from the public source tree. +- Bound guest access to a reserved public-demo identity, protected that project + from operator uploads and mutations, and added guest compute limits. +- Required production provenance before HTTP-triggered model loading. +- Added decoded-raster resource budgets and downsampled preview reads. +- Reduced unauthenticated health responses to coarse status information. +- Pinned production container base images by digest. + +## 1.0.0 + +- Initial public GeoIntel workbench for Belgium and the Belgian North Sea. +- Map-first raster/vector workflows, governed acquisitions, GeoAI adapters, + QA/QC, provenance, exports and an Unraid-oriented container deployment. diff --git a/README.md b/README.md index 8f54ea7a..a4de9f90 100644 --- a/README.md +++ b/README.md @@ -1,14 +1,5 @@ # GeoIntel -GeoIntel ondersteunt een gesynchroniseerde tweeschermwerkruimte: de kaart blijft -maximaal zichtbaar op het hoofdscherm terwijl analyses, kwaliteitsbewijs en -resultaten live in een tweede venster staan. Zie -[`docs/DUAL_DISPLAY_WORKFLOW.md`](docs/DUAL_DISPLAY_WORKFLOW.md). - -De actieve `v1.0.0`-releasegrenzen en uitvoeringsvolgorde staan in -[`docs/RC_SCOPE_FREEZE_BELGIUM_NORTH_SEA.md`](docs/RC_SCOPE_FREEZE_BELGIUM_NORTH_SEA.md) -en [`docs/RC_ROADMAP_BELGIUM_NORTH_SEA.md`](docs/RC_ROADMAP_BELGIUM_NORTH_SEA.md). -

GeoIntel logo

@@ -47,8 +38,8 @@ België plus de juridisch benoemde Belgische maritieme zones. ## Product in beeld -De onderstaande screenshots zijn rechtstreeks vastgelegd op de actuele -Unraid-productieomgeving. De gastmodus toont een projectgebonden demowerkruimte +De onderstaande screenshots tonen de huidige applicatie met publieke +demodata. De gastmodus toont een projectgebonden demowerkruimte met dezelfde kaart-, bron-, model-, analyse-, QA- en exportflow als een operator. Alleen beheer, instellingen, uploads, bronconfiguratie, projectbeheer en evidence-review blijven afgeschermd. @@ -173,10 +164,10 @@ Productie-AI gebruikt de NVIDIA GPU van de server. De runtime faalt gesloten wanneer CUDA vereist maar niet beschikbaar is; ontbrekende modelconfiguratie wordt als `not_configured` getoond en nooit als geslaagde inferentie. -De actuele productieproef draait met een CUDA-build van PyTorch op een NVIDIA -GeForce RTX 4080 SUPER. Corpus-, kalibratie-, test- en pure-background-gates -blijven gescheiden: een experimentele label- of modelvariant wordt pas actief -nadat alle toepasselijke kwaliteitscontroles slagen. +Corpus-, kalibratie-, test- en pure-background-gates blijven gescheiden: een +experimentele label- of modelvariant wordt pas actief nadat alle toepasselijke +kwaliteitscontroles slagen. Exacte runtime- en hardwaregegevens horen bij de +lokale deployment, niet bij de publieke broncode. Controleer GPU-zichtbaarheid in de container met: @@ -197,18 +188,11 @@ productresultaten blijft de taakgeschikte officiële bron doorslaggevend; een AI-detectie is controleerbaar voorstelbewijs zolang een taakgebonden releasegate niet aantoonbaar anders beslist. -De onafhankelijke AI-visuele hercontrole van 30 augustus 2026 vond nog -blokkerende referentiegeometrie, dense/nested labels, tile-edge-onduidelijkheid -en onvoldoende onafhankelijke pure-background/hard-negative dekking. Deze -controle is uitdrukkelijk geen menselijke acceptatie. Nieuwe training en -modelpromotie blijven daarom geblokkeerd; er wordt geen 100%-accuratieclaim -gemaakt. - Modelactivatie vereist naast het oudere diagnostische promotierapport ook een geslaagd, governed Phase-4/5 release-gaterapport dat exact dezelfde candidate key, model-SHA-256 en benchmarkmanifest-SHA-256 bindt. Zie -[de actuele accuracy-status](docs/accuracy-program/status.json) en het -[visuele reviewbewijs](artifacts/evidence/accuracy/model-training/20260830-independent-ai-visual-review.json). +[Accuracy, modelgrenzen en bewijs](docs/ACCURACY.md). Er wordt geen +100%-accuratieclaim gemaakt; modeloutput blijft controleerbaar voorstelbewijs. ## Portfolio case study @@ -243,19 +227,12 @@ Een wijziging is pas afgerond wanneer de toepasselijke criteria uit [docs/DEFINITION_OF_DONE.md](docs/DEFINITION_OF_DONE.md) aantoonbaar zijn afgevinkt. -## Tower / Unraid deploy +## Unraid-deployment -De canonieke checkout op Tower staat in `/mnt/user/appdata/geointel`. Gebruik -de releasewrapper; de productiecontainer wordt niet met een alternatieve -Compose-checkout vervangen. - -```powershell -powershell -ExecutionPolicy Bypass -File scripts/deploy_tower.ps1 ` - -RemoteHost root@ ` - -RemotePath /mnt/user/appdata/geointel ` - -RemoteBranch main ` - -FrontendUrl http://:1202 -``` +De ondersteunde productieopstelling bundelt PostGIS, backend en frontend in één +Unraid-container. Kopieer de voorbeeldconfiguratie, vul de verplichte +authenticatie- en opslaginstellingen in en gebruik de releaseworkflow met +backup-, healthcheck- en rollbackcontrole. Zie [deploy/unraid/README.md](deploy/unraid/README.md) en [docs/RELEASE_RUNBOOK.md](docs/RELEASE_RUNBOOK.md) voor configuratie, @@ -265,6 +242,7 @@ healthchecks en rollback. - [Start hier](docs/00-start/START_HERE.md) - [Belgium/North Sea scope freeze](docs/RC_SCOPE_FREEZE_BELGIUM_NORTH_SEA.md) +- [Actieve release-roadmap](docs/RC_ROADMAP_BELGIUM_NORTH_SEA.md) - [API-contracten](docs/API_CONTRACTS.md) - [Database-implementatieplan](docs/DATABASE_IMPLEMENTATION_PLAN.md) - [Bekende beperkingen](docs/KNOWN_LIMITATIONS.md) diff --git a/artifacts/evidence/accuracy/P1/alembic-heads.txt b/artifacts/evidence/accuracy/P1/alembic-heads.txt deleted file mode 100644 index b0466ad6..00000000 --- a/artifacts/evidence/accuracy/P1/alembic-heads.txt +++ /dev/null @@ -1,5 +0,0 @@ -command=python -m alembic heads -exit_code=0 -captured_at=2026-08-01T18:37:24.0020021+02:00 - -202607260001 (head) diff --git a/artifacts/evidence/accuracy/P1/alembic-offline-upgrade.sql b/artifacts/evidence/accuracy/P1/alembic-offline-upgrade.sql deleted file mode 100644 index 3257c5af..00000000 --- a/artifacts/evidence/accuracy/P1/alembic-offline-upgrade.sql +++ /dev/null @@ -1,500 +0,0 @@ --- command=python -m alembic upgrade head --sql --- exit_code=0 --- captured_at=2026-08-01T18:37:24.0299035+02:00 - -BEGIN; - -INFO [alembic.runtime.migration] Context impl PostgresqlImpl. -INFO [alembic.runtime.migration] Generating static SQL -INFO [alembic.runtime.migration] Will assume transactional DDL. -CREATE TABLE alembic_version ( - version_num VARCHAR(32) NOT NULL, - CONSTRAINT alembic_version_pkc PRIMARY KEY (version_num) -); - -INFO [alembic.runtime.migration] Running upgrade -> 202601110001, Initial PostGIS schema for Sprint 1 foundation. --- Running upgrade -> 202601110001 - -CREATE EXTENSION IF NOT EXISTS postgis; - -CREATE EXTENSION IF NOT EXISTS postgis_topology; - -CREATE EXTENSION IF NOT EXISTS "uuid-ossp"; - -CREATE TABLE projects ( - id UUID NOT NULL, - name TEXT NOT NULL, - description TEXT, - region TEXT DEFAULT 'Kempen' NOT NULL, - status TEXT DEFAULT 'active' NOT NULL, - created_at TIMESTAMP WITH TIME ZONE DEFAULT NOW(), - updated_at TIMESTAMP WITH TIME ZONE DEFAULT NOW(), - PRIMARY KEY (id) -); - -CREATE TABLE areas ( - id UUID NOT NULL, - project_id UUID NOT NULL, - name TEXT NOT NULL, - geometry geometry(MULTIPOLYGON,4326) NOT NULL, - original_crs TEXT, - area_m2 FLOAT, - bbox geometry(POLYGON,4326), - created_at TIMESTAMP WITH TIME ZONE DEFAULT NOW(), - PRIMARY KEY (id), - FOREIGN KEY(project_id) REFERENCES projects (id) ON DELETE CASCADE -); - -CREATE INDEX idx_areas_geometry ON areas USING gist (geometry); - -CREATE INDEX idx_areas_bbox ON areas USING gist (bbox); - -CREATE TABLE datasets ( - id UUID NOT NULL, - project_id UUID NOT NULL, - area_id UUID, - name TEXT NOT NULL, - dataset_type TEXT NOT NULL, - source TEXT NOT NULL, - storage_path TEXT, - derived_from_dataset_id UUID, - crs TEXT, - bounds_json JSON, - resolution_json JSON, - bands_json JSON, - metadata_json JSON, - status TEXT DEFAULT 'created' NOT NULL, - created_at TIMESTAMP WITH TIME ZONE DEFAULT NOW(), - updated_at TIMESTAMP WITH TIME ZONE DEFAULT NOW(), - PRIMARY KEY (id), - FOREIGN KEY(project_id) REFERENCES projects (id) ON DELETE CASCADE, - FOREIGN KEY(area_id) REFERENCES areas (id) ON DELETE SET NULL, - FOREIGN KEY(derived_from_dataset_id) REFERENCES datasets (id) ON DELETE SET NULL -); - -CREATE TABLE dataset_versions ( - id UUID NOT NULL, - dataset_id UUID NOT NULL, - version INTEGER DEFAULT '1' NOT NULL, - storage_path TEXT, - created_at TIMESTAMP WITH TIME ZONE DEFAULT NOW(), - PRIMARY KEY (id), - FOREIGN KEY(dataset_id) REFERENCES datasets (id) ON DELETE CASCADE -); - -CREATE TABLE analysis_runs ( - id UUID NOT NULL, - project_id UUID NOT NULL, - area_id UUID, - analysis_type TEXT NOT NULL, - status TEXT NOT NULL, - parameters_json JSON NOT NULL, - started_at TIMESTAMP WITH TIME ZONE, - finished_at TIMESTAMP WITH TIME ZONE, - error_message TEXT, - PRIMARY KEY (id), - FOREIGN KEY(project_id) REFERENCES projects (id) ON DELETE CASCADE, - FOREIGN KEY(area_id) REFERENCES areas (id) ON DELETE SET NULL -); - -CREATE TABLE exports ( - id UUID NOT NULL, - project_id UUID NOT NULL, - analysis_run_id UUID, - export_type TEXT NOT NULL, - storage_path TEXT NOT NULL, - metadata_json JSON, - created_at TIMESTAMP WITH TIME ZONE DEFAULT NOW(), - PRIMARY KEY (id), - FOREIGN KEY(project_id) REFERENCES projects (id) ON DELETE CASCADE, - FOREIGN KEY(analysis_run_id) REFERENCES analysis_runs (id) ON DELETE SET NULL -); - -CREATE INDEX ix_areas_geometry ON areas USING gist (geometry); - -CREATE INDEX ix_areas_project_id ON areas (project_id); - -CREATE INDEX ix_datasets_project_id ON datasets (project_id); - -INSERT INTO alembic_version (version_num) VALUES ('202601110001') RETURNING alembic_version.version_num; - -INFO [alembic.runtime.migration] Running upgrade 202601110001 -> 202601120001, Add dataset storage metadata columns. --- Running upgrade 202601110001 -> 202601120001 - -ALTER TABLE datasets ADD COLUMN original_filename TEXT; - -ALTER TABLE datasets ADD COLUMN stored_filename TEXT; - -ALTER TABLE datasets ADD COLUMN content_type TEXT; - -ALTER TABLE datasets ADD COLUMN size_bytes INTEGER; - -ALTER TABLE datasets ADD COLUMN checksum_sha256 TEXT; - -ALTER TABLE datasets ALTER COLUMN status SET DEFAULT 'uploaded'; - -UPDATE alembic_version SET version_num='202601120001' WHERE alembic_version.version_num = '202601110001'; - -INFO [alembic.runtime.migration] Running upgrade 202601120001 -> 20260611212435, Add lightweight job table for sprint-3 async architecture foundation. --- Running upgrade 202601120001 -> 20260611212435 - -CREATE TABLE jobs ( - id UUID NOT NULL, - job_type TEXT NOT NULL, - status TEXT DEFAULT 'queued' NOT NULL, - project_id UUID NOT NULL, - dataset_id UUID, - input_dataset_id UUID, - output_dataset_id UUID, - parameters_json JSON NOT NULL, - result_json JSON, - error_message TEXT, - created_at TIMESTAMP WITH TIME ZONE DEFAULT NOW(), - started_at TIMESTAMP WITH TIME ZONE, - finished_at TIMESTAMP WITH TIME ZONE, - PRIMARY KEY (id), - FOREIGN KEY(project_id) REFERENCES projects (id) ON DELETE CASCADE, - FOREIGN KEY(dataset_id) REFERENCES datasets (id) ON DELETE SET NULL, - FOREIGN KEY(input_dataset_id) REFERENCES datasets (id) ON DELETE SET NULL, - FOREIGN KEY(output_dataset_id) REFERENCES datasets (id) ON DELETE SET NULL -); - -CREATE INDEX ix_jobs_project_id ON jobs (project_id); - -CREATE INDEX ix_jobs_status ON jobs (status); - -UPDATE alembic_version SET version_num='20260611212435' WHERE alembic_version.version_num = '202601120001'; - -INFO [alembic.runtime.migration] Running upgrade 20260611212435 -> 202606120001, Add dataset reference and provenance metadata columns. --- Running upgrade 20260611212435 -> 202606120001 - -ALTER TABLE datasets ADD COLUMN dataset_role TEXT DEFAULT 'source' NOT NULL; - -ALTER TABLE datasets ADD COLUMN source_name TEXT; - -ALTER TABLE datasets ADD COLUMN reference_layer_name TEXT; - -ALTER TABLE datasets ADD COLUMN source_metadata JSON; - -ALTER TABLE datasets ADD COLUMN provenance_metadata JSON; - -ALTER TABLE datasets ADD COLUMN imported_at TIMESTAMP WITH TIME ZONE DEFAULT NOW() NOT NULL; - -UPDATE alembic_version SET version_num='202606120001' WHERE alembic_version.version_num = '20260611212435'; - -INFO [alembic.runtime.migration] Running upgrade 202606120001 -> 202606120700, Add Sprint 7A vector feature and QA persistence foundation. --- Running upgrade 202606120001 -> 202606120700 - -CREATE TABLE vector_features ( - id UUID NOT NULL, - dataset_id UUID NOT NULL, - feature_class TEXT, - source_feature_id TEXT, - properties_json JSON, - geometry geometry(GEOMETRY,4326) NOT NULL, - created_at TIMESTAMP WITH TIME ZONE DEFAULT NOW(), - PRIMARY KEY (id), - FOREIGN KEY(dataset_id) REFERENCES datasets (id) ON DELETE CASCADE -); - -CREATE INDEX ix_vector_features_dataset_id ON vector_features (dataset_id); - -CREATE INDEX ix_vector_features_geometry ON vector_features USING gist (geometry); - -CREATE TABLE quality_checks ( - id UUID NOT NULL, - project_id UUID NOT NULL, - job_id UUID, - analysis_run_id UUID, - candidate_dataset_id UUID, - reference_dataset_id UUID NOT NULL, - check_type TEXT NOT NULL, - status TEXT NOT NULL, - score FLOAT, - parameters_json JSON, - findings_json JSON, - created_at TIMESTAMP WITH TIME ZONE DEFAULT NOW(), - completed_at TIMESTAMP WITH TIME ZONE, - PRIMARY KEY (id), - FOREIGN KEY(project_id) REFERENCES projects (id) ON DELETE CASCADE, - FOREIGN KEY(job_id) REFERENCES jobs (id) ON DELETE SET NULL, - FOREIGN KEY(analysis_run_id) REFERENCES analysis_runs (id) ON DELETE SET NULL, - FOREIGN KEY(candidate_dataset_id) REFERENCES datasets (id) ON DELETE SET NULL, - FOREIGN KEY(reference_dataset_id) REFERENCES datasets (id) ON DELETE CASCADE -); - -CREATE INDEX ix_quality_checks_project_id ON quality_checks (project_id); - -CREATE INDEX ix_quality_checks_reference_dataset_id ON quality_checks (reference_dataset_id); - -CREATE INDEX ix_quality_checks_candidate_dataset_id ON quality_checks (candidate_dataset_id); - -CREATE INDEX ix_quality_checks_analysis_run_id ON quality_checks (analysis_run_id); - -CREATE TABLE metrics ( - id UUID NOT NULL, - quality_check_id UUID, - analysis_run_id UUID, - metric_key TEXT NOT NULL, - metric_value FLOAT, - metric_unit TEXT, - label TEXT, - metadata_json JSON, - created_at TIMESTAMP WITH TIME ZONE DEFAULT NOW(), - PRIMARY KEY (id), - FOREIGN KEY(quality_check_id) REFERENCES quality_checks (id) ON DELETE CASCADE, - FOREIGN KEY(analysis_run_id) REFERENCES analysis_runs (id) ON DELETE SET NULL -); - -CREATE INDEX ix_metrics_quality_check_id ON metrics (quality_check_id); - -CREATE INDEX ix_metrics_analysis_run_id ON metrics (analysis_run_id); - -UPDATE alembic_version SET version_num='202606120700' WHERE alembic_version.version_num = '202606120001'; - -INFO [alembic.runtime.migration] Running upgrade 202606120700 -> 202606120800, Add Sprint 8 detection foundation. --- Running upgrade 202606120700 -> 202606120800 - -ALTER TABLE analysis_runs ADD COLUMN dataset_id UUID; - -ALTER TABLE analysis_runs ADD FOREIGN KEY(dataset_id) REFERENCES datasets (id) ON DELETE SET NULL; - -ALTER TABLE analysis_runs ADD COLUMN job_id UUID; - -ALTER TABLE analysis_runs ADD FOREIGN KEY(job_id) REFERENCES jobs (id) ON DELETE SET NULL; - -ALTER TABLE analysis_runs ADD COLUMN model_name VARCHAR(255); - -ALTER TABLE analysis_runs ADD COLUMN model_version VARCHAR(120); - -ALTER TABLE analysis_runs ADD COLUMN result_json JSON; - -ALTER TABLE analysis_runs ADD COLUMN created_at TIMESTAMP WITH TIME ZONE DEFAULT NOW() NOT NULL; - -CREATE TABLE detections ( - id UUID NOT NULL, - project_id UUID NOT NULL, - dataset_id UUID, - analysis_run_id UUID, - job_id UUID, - model_name VARCHAR(255) NOT NULL, - model_version VARCHAR(120), - class_name VARCHAR(120) NOT NULL, - confidence FLOAT NOT NULL, - geometry geometry(GEOMETRY,4326) NOT NULL, - bbox_json JSON, - source_tile_path VARCHAR(500), - properties_json JSON, - created_at TIMESTAMP WITH TIME ZONE DEFAULT NOW() NOT NULL, - PRIMARY KEY (id), - FOREIGN KEY(project_id) REFERENCES projects (id) ON DELETE CASCADE, - FOREIGN KEY(dataset_id) REFERENCES datasets (id) ON DELETE SET NULL, - FOREIGN KEY(analysis_run_id) REFERENCES analysis_runs (id) ON DELETE SET NULL, - FOREIGN KEY(job_id) REFERENCES jobs (id) ON DELETE SET NULL -); - -CREATE INDEX ix_detections_project_id ON detections (project_id); - -CREATE INDEX ix_detections_dataset_id ON detections (dataset_id); - -CREATE INDEX ix_detections_analysis_run_id ON detections (analysis_run_id); - -CREATE INDEX ix_detections_class_name ON detections (class_name); - -CREATE INDEX ix_detections_geometry ON detections USING gist (geometry); - -UPDATE alembic_version SET version_num='202606120800' WHERE alembic_version.version_num = '202606120700'; - -INFO [alembic.runtime.migration] Running upgrade 202606120800 -> 202606120900, Add Sprint 9 segmentation foundation. --- Running upgrade 202606120800 -> 202606120900 - -CREATE TABLE segmentations ( - id UUID NOT NULL, - project_id UUID NOT NULL, - dataset_id UUID, - job_id UUID, - analysis_run_id UUID, - model_name VARCHAR(255) NOT NULL, - model_version VARCHAR(120), - class_name VARCHAR(120) NOT NULL, - confidence FLOAT, - geometry geometry(MULTIPOLYGON,4326) NOT NULL, - bbox_json JSON, - area_m2 FLOAT, - mask_path TEXT, - source_tile_path VARCHAR(500), - tile_index INTEGER, - properties_json JSON, - provenance_json JSON, - created_at TIMESTAMP WITH TIME ZONE DEFAULT NOW() NOT NULL, - PRIMARY KEY (id), - FOREIGN KEY(project_id) REFERENCES projects (id) ON DELETE CASCADE, - FOREIGN KEY(dataset_id) REFERENCES datasets (id) ON DELETE SET NULL, - FOREIGN KEY(job_id) REFERENCES jobs (id) ON DELETE SET NULL, - FOREIGN KEY(analysis_run_id) REFERENCES analysis_runs (id) ON DELETE SET NULL -); - -CREATE INDEX ix_segmentations_project_id ON segmentations (project_id); - -CREATE INDEX ix_segmentations_dataset_id ON segmentations (dataset_id); - -CREATE INDEX ix_segmentations_analysis_run_id ON segmentations (analysis_run_id); - -CREATE INDEX ix_segmentations_job_id ON segmentations (job_id); - -CREATE INDEX ix_segmentations_class_name ON segmentations (class_name); - -CREATE INDEX ix_segmentations_geometry ON segmentations USING gist (geometry); - -UPDATE alembic_version SET version_num='202606120900' WHERE alembic_version.version_num = '202606120800'; - -INFO [alembic.runtime.migration] Running upgrade 202606120900 -> 202607140001, Add temporal dataset metadata and durable dataset-version provenance. --- Running upgrade 202606120900 -> 202607140001 - -ALTER TABLE datasets ADD COLUMN temporal_series_key VARCHAR(255); - -ALTER TABLE datasets ADD COLUMN observed_at TIMESTAMP WITH TIME ZONE; - -ALTER TABLE datasets ADD COLUMN valid_from TIMESTAMP WITH TIME ZONE; - -ALTER TABLE datasets ADD COLUMN valid_to TIMESTAMP WITH TIME ZONE; - -ALTER TABLE datasets ADD COLUMN temporal_granularity VARCHAR(32); - -ALTER TABLE datasets ADD COLUMN source_version VARCHAR(120); - -ALTER TABLE dataset_versions ADD COLUMN source_version VARCHAR(120); - -ALTER TABLE dataset_versions ADD COLUMN observed_at TIMESTAMP WITH TIME ZONE; - -ALTER TABLE dataset_versions ADD COLUMN valid_from TIMESTAMP WITH TIME ZONE; - -ALTER TABLE dataset_versions ADD COLUMN valid_to TIMESTAMP WITH TIME ZONE; - -ALTER TABLE dataset_versions ADD COLUMN checksum_sha256 VARCHAR(64); - -ALTER TABLE dataset_versions ADD COLUMN source_metadata JSON; - -ALTER TABLE dataset_versions ADD COLUMN provenance_metadata JSON; - -CREATE INDEX ix_datasets_project_temporal_series_observed ON datasets (project_id, temporal_series_key, observed_at); - -CREATE UNIQUE INDEX ix_dataset_versions_dataset_version ON dataset_versions (dataset_id, version); - -CREATE INDEX ix_vector_features_dataset_source_feature ON vector_features (dataset_id, source_feature_id); - -ALTER TABLE datasets ADD CONSTRAINT ck_datasets_temporal_valid_range CHECK (valid_to IS NULL OR valid_from IS NULL OR valid_to >= valid_from); - -ALTER TABLE dataset_versions ADD CONSTRAINT ck_dataset_versions_temporal_valid_range CHECK (valid_to IS NULL OR valid_from IS NULL OR valid_to >= valid_from); - -UPDATE alembic_version SET version_num='202607140001' WHERE alembic_version.version_num = '202606120900'; - -INFO [alembic.runtime.migration] Running upgrade 202607140001 -> 202607150001, Add durable operator review decisions for detection QA evidence. --- Running upgrade 202607140001 -> 202607150001 - -CREATE TABLE detection_reviews ( - id UUID NOT NULL, - project_id UUID NOT NULL, - quality_check_id UUID NOT NULL, - analysis_run_id UUID, - evidence_role VARCHAR(32) NOT NULL, - evidence_feature_id VARCHAR(255) NOT NULL, - detection_id UUID, - reference_feature_id UUID, - decision VARCHAR(64) DEFAULT 'unreviewed' NOT NULL, - notes TEXT, - reviewed_by VARCHAR(120) DEFAULT 'operator' NOT NULL, - created_at TIMESTAMP WITH TIME ZONE DEFAULT now() NOT NULL, - updated_at TIMESTAMP WITH TIME ZONE DEFAULT now() NOT NULL, - PRIMARY KEY (id), - CONSTRAINT ck_detection_reviews_evidence_role CHECK (evidence_role IN ('false_positive', 'false_negative')), - CONSTRAINT ck_detection_reviews_decision CHECK (decision IN ('confirmed_model_false_positive', 'confirmed_model_false_negative', 'reference_gap_or_change', 'qa_alignment_mismatch', 'imagery_obscured_or_uncertain', 'uncertain', 'unreviewed')), - FOREIGN KEY(analysis_run_id) REFERENCES analysis_runs (id) ON DELETE SET NULL, - FOREIGN KEY(detection_id) REFERENCES detections (id) ON DELETE SET NULL, - FOREIGN KEY(project_id) REFERENCES projects (id) ON DELETE CASCADE, - FOREIGN KEY(quality_check_id) REFERENCES quality_checks (id) ON DELETE CASCADE, - FOREIGN KEY(reference_feature_id) REFERENCES vector_features (id) ON DELETE SET NULL, - CONSTRAINT uq_detection_reviews_evidence UNIQUE (quality_check_id, evidence_role, evidence_feature_id) -); - -CREATE INDEX ix_detection_reviews_project_id ON detection_reviews (project_id); - -CREATE INDEX ix_detection_reviews_quality_check_id ON detection_reviews (quality_check_id); - -CREATE INDEX ix_detection_reviews_analysis_run_id ON detection_reviews (analysis_run_id); - -CREATE INDEX ix_detection_reviews_decision ON detection_reviews (decision); - -UPDATE alembic_version SET version_num='202607150001' WHERE alembic_version.version_num = '202607140001'; - -INFO [alembic.runtime.migration] Running upgrade 202607150001 -> 202607160001, Index partitioned vector features by dataset and municipality. --- Running upgrade 202607150001 -> 202607160001 - -CREATE INDEX ix_vector_features_dataset_municipality ON vector_features (dataset_id, (properties_json ->> 'municipality')); - -UPDATE alembic_version SET version_num='202607160001' WHERE alembic_version.version_num = '202607150001'; - -INFO [alembic.runtime.migration] Running upgrade 202607160001 -> 202607260001, Add resumable AOI parent and partition operations. --- Running upgrade 202607160001 -> 202607260001 - -CREATE TABLE aoi_operations ( - id UUID NOT NULL, - project_id UUID NOT NULL, - area_id UUID, - parent_job_id UUID, - operation_type VARCHAR(128) NOT NULL, - status VARCHAR(32) NOT NULL, - geometry geometry(MULTIPOLYGON,4326) NOT NULL, - request_json JSON NOT NULL, - plan_json JSON NOT NULL, - result_json JSON, - error_message TEXT, - created_at TIMESTAMP WITH TIME ZONE DEFAULT now(), - started_at TIMESTAMP WITH TIME ZONE, - finished_at TIMESTAMP WITH TIME ZONE, - updated_at TIMESTAMP WITH TIME ZONE DEFAULT now(), - PRIMARY KEY (id), - CONSTRAINT ck_aoi_operations_status CHECK (status IN ('queued', 'running', 'partial', 'success', 'failed', 'cancelled')), - FOREIGN KEY(project_id) REFERENCES projects (id) ON DELETE CASCADE, - FOREIGN KEY(area_id) REFERENCES areas (id) ON DELETE SET NULL, - FOREIGN KEY(parent_job_id) REFERENCES jobs (id) ON DELETE SET NULL -); - -CREATE INDEX ix_aoi_operations_project_status ON aoi_operations (project_id, status); - -CREATE INDEX ix_aoi_operations_geometry ON aoi_operations USING gist (geometry); - -CREATE TABLE aoi_operation_partitions ( - id UUID NOT NULL, - operation_id UUID NOT NULL, - child_job_id UUID, - partition_key VARCHAR(255) NOT NULL, - provider_key VARCHAR(120) NOT NULL, - product_key VARCHAR(120) NOT NULL, - ordinal INTEGER NOT NULL, - status VARCHAR(32) NOT NULL, - geometry geometry(MULTIPOLYGON,4326) NOT NULL, - attempt_count INTEGER DEFAULT '0' NOT NULL, - max_attempts INTEGER DEFAULT '3' NOT NULL, - checkpoint_json JSON, - result_json JSON, - error_message TEXT, - created_at TIMESTAMP WITH TIME ZONE DEFAULT now(), - started_at TIMESTAMP WITH TIME ZONE, - finished_at TIMESTAMP WITH TIME ZONE, - updated_at TIMESTAMP WITH TIME ZONE DEFAULT now(), - PRIMARY KEY (id), - CONSTRAINT ck_aoi_operation_partitions_status CHECK (status IN ('queued', 'running', 'success', 'failed', 'skipped')), - CONSTRAINT uq_aoi_operation_partition_key UNIQUE (operation_id, partition_key), - FOREIGN KEY(operation_id) REFERENCES aoi_operations (id) ON DELETE CASCADE, - FOREIGN KEY(child_job_id) REFERENCES jobs (id) ON DELETE SET NULL -); - -CREATE INDEX ix_aoi_operation_partitions_operation_status ON aoi_operation_partitions (operation_id, status); - -CREATE INDEX ix_aoi_operation_partitions_geometry ON aoi_operation_partitions USING gist (geometry); - -UPDATE alembic_version SET version_num='202607260001' WHERE alembic_version.version_num = '202607160001'; - -COMMIT; - diff --git a/artifacts/evidence/accuracy/P1/backend-ci-entrypoint.txt b/artifacts/evidence/accuracy/P1/backend-ci-entrypoint.txt deleted file mode 100644 index 015f7700..00000000 --- a/artifacts/evidence/accuracy/P1/backend-ci-entrypoint.txt +++ /dev/null @@ -1,28 +0,0 @@ -workdir=backend -command=python -m pytest -W error::DeprecationWarning -exit_code=2 -captured_at=2026-08-01T18:33:34.1591431+02:00 - -============================= test session starts ============================= -platform win32 -- Python 3.13.2, pytest-8.4.0, pluggy-1.6.0 -rootdir: C:\Projects\geointel\backend -configfile: pyproject.toml -plugins: asyncio-1.0.0, cov-6.3.0, anyio-4.12.1 -asyncio: mode=Mode.STRICT, asyncio_default_fixture_loop_scope=None, asyncio_default_test_loop_scope=function -collected 1194 items / 1 error - -=================================== ERRORS ==================================== -__________ ERROR collecting tests/test_operator_polygon_label_qa.py ___________ -ImportError while importing test module 'C:\Projects\geointel\backend\tests\test_operator_polygon_label_qa.py'. -Hint: make sure your test modules/packages have valid Python names. -Traceback: -C:\Program Files\Python313\Lib\importlib\__init__.py:88: in import_module - return _bootstrap._gcd_import(name[level:], package, level) - ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ -tests\test_operator_polygon_label_qa.py:1: in - from scripts.render_operator_polygon_label_qa import geometry_rings -E ModuleNotFoundError: No module named 'scripts.render_operator_polygon_label_qa' -=========================== short test summary info =========================== -ERROR tests/test_operator_polygon_label_qa.py -!!!!!!!!!!!!!!!!!!! Interrupted: 1 error during collection !!!!!!!!!!!!!!!!!!!! -============================== 1 error in 5.69s =============================== diff --git a/artifacts/evidence/accuracy/P1/backend-full-suite.junit.xml b/artifacts/evidence/accuracy/P1/backend-full-suite.junit.xml deleted file mode 100644 index 47321013..00000000 --- a/artifacts/evidence/accuracy/P1/backend-full-suite.junit.xml +++ /dev/null @@ -1,233 +0,0 @@ -def test_frontend_prefers_materialized_national_workspace_and_resolves_drawn_bbox() -> None: - root = Path(__file__).parents[2] - focus = (root / "frontend" / "src" / "config" / "primaryFocus.ts").read_text(encoding="utf-8") - workspace_hook = (root / "frontend" / "src" / "hooks" / "useProjectWorkspace.ts").read_text(encoding="utf-8") - coverage_hook = (root / "frontend" / "src" / "hooks" / "useCoverageResolver.ts").read_text(encoding="utf-8") - map_workspace = (root / "frontend" / "src" / "components" / "map" / "MapWorkspace.tsx").read_text(encoding="utf-8") - - assert "Belgium and North Sea Workbench" in focus - assert "nationalProject" in workspace_hook - assert "return nationalProject.id" in workspace_hook - assert "NATIONAL_WORKSPACE_REGION" in workspace_hook - assert "externalApi.resolveCoverage" in coverage_hook - assert "coverage.outside_supported_scope" in map_workspace - assert "coverageStatusLabel" in map_workspace -> assert "coverageSelectionAvailable" in map_workspace -E assert 'coverageSelectionAvailable' in "import { useCallback, useEffect, useMemo, useRef, useState, type KeyboardEvent } from 'react'\nimport { BoxSelect, Ch...ijken.</p>\n )}\n </div>\n </div>\n </details>\n </div>\n </section>\n )\n}\n" - -backend\tests\test_rc4_national_coverage.py:432: AssertionErrordef test_runtime_configuration_is_validated_before_container_replacement() -> None: - run_script = (ROOT / "deploy" / "unraid" / "run-dockerman-container.sh").read_text(encoding="utf-8") - - validation_index = run_script.index("validate_runtime_config") -> replacement_index = run_script.index("docker compose down") - ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ -E ValueError: substring not found - -backend\tests\test_rc5_release_deployment.py:65: ValueErrordef test_rc9_loading_and_accessibility_states_are_explicit() -> None: - app = (ROOT / "frontend" / "src" / "App.tsx").read_text(encoding="utf-8") - map_workspace = ( - ROOT / "frontend" / "src" / "components" / "map" / "MapWorkspace.tsx" - ).read_text(encoding="utf-8") - geo_map = (ROOT / "frontend" / "src" / "components" / "GeoMap.tsx").read_text( - encoding="utf-8" - ) - - assert "workspaceDataLoading" in app - assert 'role="status" aria-live="polite"' in app - assert "Databronnen worden gecontroleerd" in map_workspace -> assert "Beschikbaarheid controleren" in map_workspace -E assert 'Beschikbaarheid controleren' in "import { useCallback, useEffect, useMemo, useRef, useState, type KeyboardEvent } from 'react'\nimport { BoxSelect, Ch...ijken.</p>\n )}\n </div>\n </div>\n </details>\n </div>\n </section>\n )\n}\n" - -backend\tests\test_rc9_ux_release_contract.py:33: AssertionErrordef test_all_in_one_deploy_embeds_immutable_build_identity() -> None: - dockerfile = (ROOT / "deploy" / "unraid" / "Dockerfile.all-in-one").read_text(encoding="utf-8") - release_script = (ROOT / "deploy" / "unraid" / "deploy-release.sh").read_text(encoding="utf-8") - deploy_powershell = (ROOT / "scripts" / "deploy_tower.ps1").read_text(encoding="utf-8") - deploy_shell = (ROOT / "scripts" / "deploy_tower.sh").read_text(encoding="utf-8") - - assert "ARG GEOINTEL_BUILD_SHA=unknown" in dockerfile - assert 'GEOINTEL_BUILD_SHA="${GEOINTEL_BUILD_SHA}"' in dockerfile - assert 'GEOINTEL_BUILD_TIME="${GEOINTEL_BUILD_TIME}"' in dockerfile - assert 'org.opencontainers.image.revision="${GEOINTEL_BUILD_SHA}"' in dockerfile -> assert 'GEOINTEL_BUILD_SHA="$(git rev-parse HEAD)"' in release_script -E assert 'GEOINTEL_BUILD_SHA="$(git rev-parse HEAD)"' in '#!/usr/bin/env bash\nset -euo pipefail\n\nROOT="$(cd "$(dirname "${BASH_SOURCE[0]}")/../.." && pwd)"\ncd "$ROOT"\n\nG...ge.revision"}} created={{index .Config.Labels "org.opencontainers.image.created"}}\' \\\n "$GEOINTEL_RELEASE_IMAGE"\n' - -backend\tests\test_rc_runtime_observability.py:47: AssertionErrordef test_frontend_exposes_map_bbox_selection_contracts() -> None: - api_client = (ROOT / "frontend" / "src" / "services" / "api" / "datasets.ts").read_text(encoding="utf-8") - map_workspace = (ROOT / "frontend" / "src" / "components" / "map" / "MapWorkspace.tsx").read_text(encoding="utf-8") - geomap = (ROOT / "frontend" / "src" / "components" / "GeoMap.tsx").read_text(encoding="utf-8") - app = (ROOT / "frontend" / "src" / "App.tsx").read_text(encoding="utf-8") - extract_hook = (ROOT / "frontend" / "src" / "hooks" / "useMapSelectionExtract.ts").read_text(encoding="utf-8") - theme_hook = (ROOT / "frontend" / "src" / "hooks" / "useMapThemeSelectionInsights.ts").read_text(encoding="utf-8") - - assert "selectVectorFeatures" in api_client - assert "Area selection" in map_workspace - assert "Teken rechthoek" in map_workspace - assert "Objecten in gebied ophalen" in map_workspace - assert "Gebiedsdownload bewaren" in map_workspace - assert "bboxSelectionMode" in geomap - assert "selection-bbox" in geomap - assert "selection-result" in geomap - assert "useMapSelectionExtract" in app - assert "area_id: areaId" in extract_hook - assert "area_id: areaId" in theme_hook -> assert "analyzeSelection(selectedAreaBbox, selectedMapArea?.id)" in map_workspace -E assert 'analyzeSelection(selectedAreaBbox, selectedMapArea?.id)' in "import { useCallback, useEffect, useMemo, useRef, useState, type KeyboardEvent } from 'react'\nimport { BoxSelect, Ch...ijken.</p>\n )}\n </div>\n </div>\n </details>\n </div>\n </section>\n )\n}\n" - -backend\tests\test_sprint106_map_bbox_extract.py:356: AssertionErrordef test_frontend_declares_national_scope_as_primary_operating_focus() -> None: - focus = (ROOT / "frontend" / "src" / "config" / "primaryFocus.ts").read_text( - encoding="utf-8" - ) - project_hook = (ROOT / "frontend" / "src" / "hooks" / "useProjectWorkspace.ts").read_text( - encoding="utf-8" - ) - map_source = (ROOT / "frontend" / "src" / "components" / "GeoMap.tsx").read_text( - encoding="utf-8" - ) - navigation = ( - ROOT - / "frontend" - / "src" - / "components" - / "shell" - / "WorkbenchNavigation.tsx" - ).read_text(encoding="utf-8") - - assert "NATIONAL_WORKSPACE_PROJECT_NAME = 'Belgium and North Sea Workbench'" in focus - assert "NATIONAL_WORKSPACE_REGION = 'Belgie en Belgische Noordzee'" in focus - assert "NATIONAL_MAP_CENTER" in focus - assert "return nationalProject.id" in project_hook - assert "hasMappedAnalysisContext(data)" in project_hook - assert "dataset.dataset_type === 'raster'" in project_hook - assert "dataset.dataset_type === 'vector' || dataset.dataset_type === 'geojson'" in project_hook - assert "PRIMARY_FOCUS_AREA_NAME" not in project_hook - assert "PRIMARY_FOCUS_AREA_GEOJSON" not in project_hook - assert "center: NATIONAL_MAP_CENTER" in map_source - assert "zoom: NATIONAL_MAP_ZOOM" in map_source - assert "GeoIntel" in navigation -> assert "Atlas Workbench" in navigation -E AssertionError: assert 'Atlas Workbench' in 'import {\n Activity,\n Bot,\n Database,\n Download,\n Map,\n ScanSearch,\n Settings,\n ShieldCheck,\n type L... )\n })}\n </div>\n ))}\n </nav>\n <ItWorxSignature />\n </aside>\n )\n}\n' - -backend\tests\test_sprint177_mol_primary_focus.py:38: AssertionErrordef test_product_docs_record_national_scope_and_mol_regression_focus() -> None: - readme = (ROOT / "README.md").read_text(encoding="utf-8") - vision = (ROOT / "docs" / "PRODUCT_VISION.md").read_text(encoding="utf-8") - -> assert "Belgium and the Belgian North Sea" in readme -E assert 'Belgium and the Belgian North Sea' in '# GeoIntel\n\n<p align="center">\n <img src="frontend/public/geointel-icon.png" width="92" alt="GeoIntel logo">\n</p...\n\nActieve mijlpaal: **v1.0.0 — Belgium and Belgian North Sea**.\n\nGeoIntel is een project van Jens / ITWorx.tech.\n' - -backend\tests\test_sprint177_mol_primary_focus.py:62: AssertionErrordef test_map_first_explorer_is_the_default_product_flow() -> None: - app = read("frontend/src/App.tsx") - workspace = read("frontend/src/components/map/MapWorkspace.tsx") - - assert "useState<WorkspaceKey>('map')" in app - assert "Gebied analyseren" in workspace -> assert "<h3>Focus op de kaart <small>optioneel</small></h3>" in workspace -E assert '<h3>Focus op de kaart <small>optioneel</small></h3>' in "import { useCallback, useEffect, useMemo, useRef, useState, type KeyboardEvent } from 'react'\nimport { BoxSelect, Ch...ijken.</p>\n )}\n </div>\n </div>\n </details>\n </div>\n </section>\n )\n}\n" - -backend\tests\test_sprint186_map_first_geographic_explorer.py:19: AssertionErrordef test_map_rectangle_drag_is_wired_to_automatic_analysis() -> None: - workspace = read("frontend/src/components/map/MapWorkspace.tsx") - geomap = read("frontend/src/components/GeoMap.tsx") - styles = read("frontend/src/styles/app.css") - - assert "onMapBboxPreview={handleMapBboxPreview}" in workspace - assert "onMapBboxSelect={handleMapBboxSelect}" in workspace - assert "void analyzeSelection(bbox, areaIdForSelection(bbox))" in workspace - assert "const areaIdForSelection" in workspace - assert "bbox && selectedMapArea ? selectedMapArea.id : undefined" in workspace -> assert "void analyzeSelection(selectedAreaBbox, selectedMapArea?.id)" in workspace -E assert 'void analyzeSelection(selectedAreaBbox, selectedMapArea?.id)' in "import { useCallback, useEffect, useMemo, useRef, useState, type KeyboardEvent } from 'react'\nimport { BoxSelect, Ch...ijken.</p>\n )}\n </div>\n </div>\n </details>\n </div>\n </section>\n )\n}\n" - -backend\tests\test_sprint186_map_first_geographic_explorer.py:44: AssertionErrordef test_evolution_theme_catalog_distinguishes_history_from_current_only_data() -> None: - workspace = read("frontend/src/components/map/MapWorkspace.tsx") - - assert "analysisMode === 'current'" in workspace -> assert "Boolean(dataset || onDemandProduct)" in workspace -E assert 'Boolean(dataset || onDemandProduct)' in "import { useCallback, useEffect, useMemo, useRef, useState, type KeyboardEvent } from 'react'\nimport { BoxSelect, Ch...ijken.</p>\n )}\n </div>\n </div>\n </details>\n </div>\n </section>\n )\n}\n" - -backend\tests\test_sprint200_temporal_explorer_handoff.py:25: AssertionErrordef test_regional_map_uses_logical_partition_groups_and_exact_analysis() -> None: - app = (ROOT / "frontend/src/App.tsx").read_text(encoding="utf-8") - workspace = (ROOT / "frontend/src/components/map/MapWorkspace.tsx").read_text(encoding="utf-8") - hook = (ROOT / "frontend/src/hooks/useMapThemeSelectionInsights.ts").read_text(encoding="utf-8") - api = (ROOT / "frontend/src/services/api/datasets.ts").read_text(encoding="utf-8") - - assert "regionalScopeSelected" in workspace - assert "rasterPartitionsForDataset" in workspace - assert "imageOverlays={activeImageOverlays}" in workspace -> assert "de juiste gemeentelijke rasters worden automatisch gecombineerd" in workspace -E assert 'de juiste gemeentelijke rasters worden automatisch gecombineerd' in "import { useCallback, useEffect, useMemo, useRef, useState, type KeyboardEvent } from 'react'\nimport { BoxSelect, Ch...ijken.</p>\n )}\n </div>\n </div>\n </details>\n </div>\n </section>\n )\n}\n" - -backend\tests\test_sprint219_regional_raster_explorer.py:30: AssertionErrordef test_frontend_uses_partitioned_bathymetry_selection_for_regional_scope() -> None: - app = (ROOT / "frontend" / "src" / "App.tsx").read_text(encoding="utf-8") - index = (ROOT / "frontend" / "index.html").read_text(encoding="utf-8") - focus = ( - ROOT / "frontend" / "src" / "config" / "primaryFocus.ts" - ).read_text(encoding="utf-8") - map_workspace = ( - ROOT / "frontend" / "src" / "components" / "map" / "MapWorkspace.tsx" - ).read_text(encoding="utf-8") - theme_hook = ( - ROOT / "frontend" / "src" / "hooks" / "useMapThemeSelectionInsights.ts" - ).read_text(encoding="utf-8") - dataset_api = ( - ROOT / "frontend" / "src" / "services" / "api" / "datasets.ts" - ).read_text(encoding="utf-8") - - assert "isPartitionedBathymetry" in map_workspace - assert "regionalPartitionedThemeActive" in map_workspace -> assert "datasetAvailabilityLabel(dataset, partitions)" in map_workspace -E assert 'datasetAvailabilityLabel(dataset, partitions)' in "import { useCallback, useEffect, useMemo, useRef, useState, type KeyboardEvent } from 'react'\nimport { BoxSelect, Ch...ijken.</p>\n )}\n </div>\n </div>\n </details>\n </div>\n </section>\n )\n}\n" - -backend\tests\test_sprint236_bathymetry_expansion.py:478: AssertionErrordef test_flanders_workspace_exposes_governed_thematic_products_on_demand() -> None: - workspace = read("frontend/src/components/map/MapWorkspace.tsx") - product_hook = read("frontend/src/hooks/useOfficialMapProducts.ts") - selection_hook = read("frontend/src/hooks/useMapThemeSelectionInsights.ts") - api = read("frontend/src/services/api/datasets.ts") - - assert "activeScopeProject?.name === FLANDERS_WORKSPACE_PROJECT_NAME" in workspace - assert "new Map<DataThemeId, OnDemandMapProduct>" in workspace -> assert "'Automatisch'" in workspace -E assert "'Automatisch'" in "import { useCallback, useEffect, useMemo, useRef, useState, type KeyboardEvent } from 'react'\nimport { BoxSelect, Ch...ijken.</p>\n )}\n </div>\n </div>\n </details>\n </div>\n </section>\n )\n}\n" - -backend\tests\test_sprint237_flanders_thematic_on_demand.py:19: AssertionErrordef test_selection_reads_and_bounded_acquires_all_relevant_themes() -> None: - workspace = read("frontend/src/components/map/MapWorkspace.tsx") - app = read("frontend/src/App.tsx") - selection_hook = read("frontend/src/hooks/useMapThemeSelectionInsights.ts") - -> assert "for (const theme of [activeTheme])" in workspace -E assert 'for (const theme of [activeTheme])' in "import { useCallback, useEffect, useMemo, useRef, useState, type KeyboardEvent } from 'react'\nimport { BoxSelect, Ch...ijken.</p>\n )}\n </div>\n </div>\n </details>\n </div>\n </section>\n )\n}\n" - -backend\tests\test_sprint237_flanders_thematic_on_demand.py:37: AssertionErrordef test_regional_on_demand_sources_require_a_bounded_drawn_selection() -> None: - workspace = read("frontend/src/components/map/MapWorkspace.tsx") - - assert "regionalOnDemandThemeActive" in workspace -> assert "regionalRasterThemeActive || regionalOnDemandThemeActive" in workspace -E assert 'regionalRasterThemeActive || regionalOnDemandThemeActive' in "import { useCallback, useEffect, useMemo, useRef, useState, type KeyboardEvent } from 'react'\nimport { BoxSelect, Ch...ijken.</p>\n )}\n </div>\n </div>\n </details>\n </div>\n </section>\n )\n}\n" - -backend\tests\test_sprint237_flanders_thematic_on_demand.py:56: AssertionErrordef test_grb_frontend_and_contracts_use_only_the_governed_backend_path() -> None: - selection_hook = (ROOT / "frontend/src/hooks/useMapThemeSelectionInsights.ts").read_text(encoding="utf-8") - catalog_hook = (ROOT / "frontend/src/hooks/useOfficialMapProducts.ts").read_text(encoding="utf-8") - workspace = (ROOT / "frontend/src/components/map/MapWorkspace.tsx").read_text(encoding="utf-8") - contracts = (ROOT / "docs/API_CONTRACTS.md").read_text(encoding="utf-8") - - assert "datasetsApi.acquireGrb" in selection_hook - assert "datasetsApi.listGrbProducts" in catalog_hook - assert "officialMapProducts.grb" in workspace - assert "result[product.key] = null" in workspace - assert ": onDemandThemeActive\n ? null\n : mapFeatureCollection" in workspace - assert "onSetContextLayerLabel" in workspace -> assert "'Automatisch'" in workspace -E assert "'Automatisch'" in "import { useCallback, useEffect, useMemo, useRef, useState, type KeyboardEvent } from 'react'\nimport { BoxSelect, Ch...ijken.</p>\n )}\n </div>\n </div>\n </details>\n </div>\n </section>\n )\n}\n" - -backend\tests\test_sprint239_bounded_grb_acquisition.py:394: AssertionErrordef test_app_entrypoint_has_clean_encoding_and_react_imports() -> None: - app_path = ROOT / "frontend" / "src" / "App.tsx" - app_bytes = app_path.read_bytes() - app = app_path.read_text(encoding="utf-8") - - assert not app_bytes.startswith(b"\xef\xbb\xbf") - assert "import { useEffect, useMemo, useRef, useState } from 'react'" in app - assert "FormEvent" not in app -> assert app.count("useEffect(") == 1 -E assert 3 == 1 -E + where 3 = <built-in method count of str object at 0x000001FED98D8C30>('useEffect(') -E + where <built-in method count of str object at 0x000001FED98D8C30> = "import { useEffect, useMemo, useRef, useState } from 'react'\nimport { CircleAlert, LogOut, ShieldCheck, UserRound } ...ator' : 'open')}\n loggingOut={loggingOut}\n onLogout={handleLogout}\n />\n )\n}\n\nexport default App\n".count - -backend\tests\test_sprint39_frontend_orchestration_hooks.py:40: AssertionError \ No newline at end of file diff --git a/artifacts/evidence/accuracy/P1/backend-full-suite.txt b/artifacts/evidence/accuracy/P1/backend-full-suite.txt deleted file mode 100644 index a85b2336..00000000 --- a/artifacts/evidence/accuracy/P1/backend-full-suite.txt +++ /dev/null @@ -1,325 +0,0 @@ -command=python -m pytest backend/tests -q -p no:cacheprovider -W error::DeprecationWarning --junitxml=artifacts/evidence/accuracy/P1/backend-full-suite.junit.xml -exit_code=1 -captured_at=2026-08-01T18:32:02.4460806+02:00 - 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[100%] -================================== FAILURES =================================== -_ test_frontend_prefers_materialized_national_workspace_and_resolves_drawn_bbox _ - - def test_frontend_prefers_materialized_national_workspace_and_resolves_drawn_bbox() -> None: - root = Path(__file__).parents[2] - focus = (root / "frontend" / "src" / "config" / "primaryFocus.ts").read_text(encoding="utf-8") - workspace_hook = (root / "frontend" / "src" / "hooks" / "useProjectWorkspace.ts").read_text(encoding="utf-8") - coverage_hook = (root / "frontend" / "src" / "hooks" / "useCoverageResolver.ts").read_text(encoding="utf-8") - map_workspace = (root / "frontend" / "src" / "components" / "map" / "MapWorkspace.tsx").read_text(encoding="utf-8") - - assert "Belgium and North Sea Workbench" in focus - assert "nationalProject" in workspace_hook - assert "return nationalProject.id" in workspace_hook - assert "NATIONAL_WORKSPACE_REGION" in workspace_hook - assert "externalApi.resolveCoverage" in coverage_hook - assert "coverage.outside_supported_scope" in map_workspace - assert "coverageStatusLabel" in map_workspace -> assert "coverageSelectionAvailable" in map_workspace -E assert 'coverageSelectionAvailable' in "import { useCallback, useEffect, useMemo, useRef, useState, type KeyboardEvent } from 'react'\nimport { BoxSelect, Ch...ijken.

\n )}\n \n \n \n \n \n )\n}\n" - -backend\tests\test_rc4_national_coverage.py:432: AssertionError -____ test_runtime_configuration_is_validated_before_container_replacement _____ - - def test_runtime_configuration_is_validated_before_container_replacement() -> None: - run_script = (ROOT / "deploy" / "unraid" / "run-dockerman-container.sh").read_text(encoding="utf-8") - - validation_index = run_script.index("validate_runtime_config") -> replacement_index = run_script.index("docker compose down") - ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ -E ValueError: substring not found - -backend\tests\test_rc5_release_deployment.py:65: ValueError -___________ test_rc9_loading_and_accessibility_states_are_explicit ____________ - - def test_rc9_loading_and_accessibility_states_are_explicit() -> None: - app = (ROOT / "frontend" / "src" / "App.tsx").read_text(encoding="utf-8") - map_workspace = ( - ROOT / "frontend" / "src" / "components" / "map" / "MapWorkspace.tsx" - ).read_text(encoding="utf-8") - geo_map = (ROOT / "frontend" / "src" / "components" / "GeoMap.tsx").read_text( - encoding="utf-8" - ) - - assert "workspaceDataLoading" in app - assert 'role="status" aria-live="polite"' in app - assert "Databronnen worden gecontroleerd" in map_workspace -> assert "Beschikbaarheid controleren" in map_workspace -E assert 'Beschikbaarheid controleren' in "import { useCallback, useEffect, useMemo, useRef, useState, type KeyboardEvent } from 'react'\nimport { BoxSelect, Ch...ijken.

\n )}\n \n \n \n \n \n )\n}\n" - -backend\tests\test_rc9_ux_release_contract.py:33: AssertionError -___________ test_all_in_one_deploy_embeds_immutable_build_identity ____________ - - def test_all_in_one_deploy_embeds_immutable_build_identity() -> None: - dockerfile = (ROOT / "deploy" / "unraid" / "Dockerfile.all-in-one").read_text(encoding="utf-8") - release_script = (ROOT / "deploy" / "unraid" / "deploy-release.sh").read_text(encoding="utf-8") - deploy_powershell = (ROOT / "scripts" / "deploy_tower.ps1").read_text(encoding="utf-8") - deploy_shell = (ROOT / "scripts" / "deploy_tower.sh").read_text(encoding="utf-8") - - assert "ARG GEOINTEL_BUILD_SHA=unknown" in dockerfile - assert 'GEOINTEL_BUILD_SHA="${GEOINTEL_BUILD_SHA}"' in dockerfile - assert 'GEOINTEL_BUILD_TIME="${GEOINTEL_BUILD_TIME}"' in dockerfile - assert 'org.opencontainers.image.revision="${GEOINTEL_BUILD_SHA}"' in dockerfile -> assert 'GEOINTEL_BUILD_SHA="$(git rev-parse HEAD)"' in release_script -E assert 'GEOINTEL_BUILD_SHA="$(git rev-parse HEAD)"' in '#!/usr/bin/env bash\nset -euo pipefail\n\nROOT="$(cd "$(dirname "${BASH_SOURCE[0]}")/../.." && pwd)"\ncd "$ROOT"\n\nG...ge.revision"}} created={{index .Config.Labels "org.opencontainers.image.created"}}\' \\\n "$GEOINTEL_RELEASE_IMAGE"\n' - -backend\tests\test_rc_runtime_observability.py:47: AssertionError -_____________ test_frontend_exposes_map_bbox_selection_contracts ______________ - - def test_frontend_exposes_map_bbox_selection_contracts() -> None: - api_client = (ROOT / "frontend" / "src" / "services" / "api" / "datasets.ts").read_text(encoding="utf-8") - map_workspace = (ROOT / "frontend" / "src" / "components" / "map" / "MapWorkspace.tsx").read_text(encoding="utf-8") - geomap = (ROOT / "frontend" / "src" / "components" / "GeoMap.tsx").read_text(encoding="utf-8") - app = (ROOT / "frontend" / "src" / "App.tsx").read_text(encoding="utf-8") - extract_hook = (ROOT / "frontend" / "src" / "hooks" / "useMapSelectionExtract.ts").read_text(encoding="utf-8") - theme_hook = (ROOT / "frontend" / "src" / "hooks" / "useMapThemeSelectionInsights.ts").read_text(encoding="utf-8") - - assert "selectVectorFeatures" in api_client - assert "Area selection" in map_workspace - assert "Teken rechthoek" in map_workspace - assert "Objecten in gebied ophalen" in map_workspace - assert "Gebiedsdownload bewaren" in map_workspace - assert "bboxSelectionMode" in geomap - assert "selection-bbox" in geomap - assert "selection-result" in geomap - assert "useMapSelectionExtract" in app - assert "area_id: areaId" in extract_hook - assert "area_id: areaId" in theme_hook -> assert "analyzeSelection(selectedAreaBbox, selectedMapArea?.id)" in map_workspace -E assert 'analyzeSelection(selectedAreaBbox, selectedMapArea?.id)' in "import { useCallback, useEffect, useMemo, useRef, useState, type KeyboardEvent } from 'react'\nimport { BoxSelect, Ch...ijken.

\n )}\n \n \n \n \n \n )\n}\n" - -backend\tests\test_sprint106_map_bbox_extract.py:356: AssertionError -______ test_frontend_declares_national_scope_as_primary_operating_focus _______ - - def test_frontend_declares_national_scope_as_primary_operating_focus() -> None: - focus = (ROOT / "frontend" / "src" / "config" / "primaryFocus.ts").read_text( - encoding="utf-8" - ) - project_hook = (ROOT / "frontend" / "src" / "hooks" / "useProjectWorkspace.ts").read_text( - encoding="utf-8" - ) - map_source = (ROOT / "frontend" / "src" / "components" / "GeoMap.tsx").read_text( - encoding="utf-8" - ) - navigation = ( - ROOT - / "frontend" - / "src" - / "components" - / "shell" - / "WorkbenchNavigation.tsx" - ).read_text(encoding="utf-8") - - assert "NATIONAL_WORKSPACE_PROJECT_NAME = 'Belgium and North Sea Workbench'" in focus - assert "NATIONAL_WORKSPACE_REGION = 'Belgie en Belgische Noordzee'" in focus - assert "NATIONAL_MAP_CENTER" in focus - assert "return nationalProject.id" in project_hook - assert "hasMappedAnalysisContext(data)" in project_hook - assert "dataset.dataset_type === 'raster'" in project_hook - assert "dataset.dataset_type === 'vector' || dataset.dataset_type === 'geojson'" in project_hook - assert "PRIMARY_FOCUS_AREA_NAME" not in project_hook - assert "PRIMARY_FOCUS_AREA_GEOJSON" not in project_hook - assert "center: NATIONAL_MAP_CENTER" in map_source - assert "zoom: NATIONAL_MAP_ZOOM" in map_source - assert "GeoIntel" in navigation -> assert "Atlas Workbench" in navigation -E AssertionError: assert 'Atlas Workbench' in 'import {\n Activity,\n Bot,\n Database,\n Download,\n Map,\n ScanSearch,\n Settings,\n ShieldCheck,\n type L... )\n })}\n \n ))}\n \n \n \n )\n}\n' - -backend\tests\test_sprint177_mol_primary_focus.py:38: AssertionError -______ test_product_docs_record_national_scope_and_mol_regression_focus _______ - - def test_product_docs_record_national_scope_and_mol_regression_focus() -> None: - readme = (ROOT / "README.md").read_text(encoding="utf-8") - vision = (ROOT / "docs" / "PRODUCT_VISION.md").read_text(encoding="utf-8") - -> assert "Belgium and the Belgian North Sea" in readme -E assert 'Belgium and the Belgian North Sea' in '# GeoIntel\n\n

\n GeoIntel logo\n None: - app = read("frontend/src/App.tsx") - workspace = read("frontend/src/components/map/MapWorkspace.tsx") - - assert "useState('map')" in app - assert "Gebied analyseren" in workspace -> assert "

Focus op de kaart optioneel

" in workspace -E assert '

Focus op de kaart optioneel

' in "import { useCallback, useEffect, useMemo, useRef, useState, type KeyboardEvent } from 'react'\nimport { BoxSelect, Ch...ijken.

\n )}\n \n \n \n \n \n )\n}\n" - -backend\tests\test_sprint186_map_first_geographic_explorer.py:19: AssertionError -___________ test_map_rectangle_drag_is_wired_to_automatic_analysis ____________ - - def test_map_rectangle_drag_is_wired_to_automatic_analysis() -> None: - workspace = read("frontend/src/components/map/MapWorkspace.tsx") - geomap = read("frontend/src/components/GeoMap.tsx") - styles = read("frontend/src/styles/app.css") - - assert "onMapBboxPreview={handleMapBboxPreview}" in workspace - assert "onMapBboxSelect={handleMapBboxSelect}" in workspace - assert "void analyzeSelection(bbox, areaIdForSelection(bbox))" in workspace - assert "const areaIdForSelection" in workspace - assert "bbox && selectedMapArea ? selectedMapArea.id : undefined" in workspace -> assert "void analyzeSelection(selectedAreaBbox, selectedMapArea?.id)" in workspace -E assert 'void analyzeSelection(selectedAreaBbox, selectedMapArea?.id)' in "import { useCallback, useEffect, useMemo, useRef, useState, type KeyboardEvent } from 'react'\nimport { BoxSelect, Ch...ijken.

\n )}\n \n \n \n \n \n )\n}\n" - -backend\tests\test_sprint186_map_first_geographic_explorer.py:44: AssertionError -__ test_evolution_theme_catalog_distinguishes_history_from_current_only_data __ - - def test_evolution_theme_catalog_distinguishes_history_from_current_only_data() -> None: - workspace = read("frontend/src/components/map/MapWorkspace.tsx") - - assert "analysisMode === 'current'" in workspace -> assert "Boolean(dataset || onDemandProduct)" in workspace -E assert 'Boolean(dataset || onDemandProduct)' in "import { useCallback, useEffect, useMemo, useRef, useState, type KeyboardEvent } from 'react'\nimport { BoxSelect, Ch...ijken.

\n )}\n \n \n \n \n \n )\n}\n" - -backend\tests\test_sprint200_temporal_explorer_handoff.py:25: AssertionError -_____ test_regional_map_uses_logical_partition_groups_and_exact_analysis ______ - - def test_regional_map_uses_logical_partition_groups_and_exact_analysis() -> None: - app = (ROOT / "frontend/src/App.tsx").read_text(encoding="utf-8") - workspace = (ROOT / "frontend/src/components/map/MapWorkspace.tsx").read_text(encoding="utf-8") - hook = (ROOT / "frontend/src/hooks/useMapThemeSelectionInsights.ts").read_text(encoding="utf-8") - api = (ROOT / "frontend/src/services/api/datasets.ts").read_text(encoding="utf-8") - - assert "regionalScopeSelected" in workspace - assert "rasterPartitionsForDataset" in workspace - assert "imageOverlays={activeImageOverlays}" in workspace -> assert "de juiste gemeentelijke rasters worden automatisch gecombineerd" in workspace -E assert 'de juiste gemeentelijke rasters worden automatisch gecombineerd' in "import { useCallback, useEffect, useMemo, useRef, useState, type KeyboardEvent } from 'react'\nimport { BoxSelect, Ch...ijken.

\n )}\n \n \n \n \n \n )\n}\n" - -backend\tests\test_sprint219_regional_raster_explorer.py:30: AssertionError -___ test_frontend_uses_partitioned_bathymetry_selection_for_regional_scope ____ - - def test_frontend_uses_partitioned_bathymetry_selection_for_regional_scope() -> None: - app = (ROOT / "frontend" / "src" / "App.tsx").read_text(encoding="utf-8") - index = (ROOT / "frontend" / "index.html").read_text(encoding="utf-8") - focus = ( - ROOT / "frontend" / "src" / "config" / "primaryFocus.ts" - ).read_text(encoding="utf-8") - map_workspace = ( - ROOT / "frontend" / "src" / "components" / "map" / "MapWorkspace.tsx" - ).read_text(encoding="utf-8") - theme_hook = ( - ROOT / "frontend" / "src" / "hooks" / "useMapThemeSelectionInsights.ts" - ).read_text(encoding="utf-8") - dataset_api = ( - ROOT / "frontend" / "src" / "services" / "api" / "datasets.ts" - ).read_text(encoding="utf-8") - - assert "isPartitionedBathymetry" in map_workspace - assert "regionalPartitionedThemeActive" in map_workspace -> assert "datasetAvailabilityLabel(dataset, partitions)" in map_workspace -E assert 'datasetAvailabilityLabel(dataset, partitions)' in "import { useCallback, useEffect, useMemo, useRef, useState, type KeyboardEvent } from 'react'\nimport { BoxSelect, Ch...ijken.

\n )}\n \n \n \n \n \n )\n}\n" - -backend\tests\test_sprint236_bathymetry_expansion.py:478: AssertionError -____ test_flanders_workspace_exposes_governed_thematic_products_on_demand _____ - - def test_flanders_workspace_exposes_governed_thematic_products_on_demand() -> None: - workspace = read("frontend/src/components/map/MapWorkspace.tsx") - product_hook = read("frontend/src/hooks/useOfficialMapProducts.ts") - selection_hook = read("frontend/src/hooks/useMapThemeSelectionInsights.ts") - api = read("frontend/src/services/api/datasets.ts") - - assert "activeScopeProject?.name === FLANDERS_WORKSPACE_PROJECT_NAME" in workspace - assert "new Map" in workspace -> assert "'Automatisch'" in workspace -E assert "'Automatisch'" in "import { useCallback, useEffect, useMemo, useRef, useState, type KeyboardEvent } from 'react'\nimport { BoxSelect, Ch...ijken.

\n )}\n \n \n \n \n \n )\n}\n" - -backend\tests\test_sprint237_flanders_thematic_on_demand.py:19: AssertionError -________ test_selection_reads_and_bounded_acquires_all_relevant_themes ________ - - def test_selection_reads_and_bounded_acquires_all_relevant_themes() -> None: - workspace = read("frontend/src/components/map/MapWorkspace.tsx") - app = read("frontend/src/App.tsx") - selection_hook = read("frontend/src/hooks/useMapThemeSelectionInsights.ts") - -> assert "for (const theme of [activeTheme])" in workspace -E assert 'for (const theme of [activeTheme])' in "import { useCallback, useEffect, useMemo, useRef, useState, type KeyboardEvent } from 'react'\nimport { BoxSelect, Ch...ijken.

\n )}\n \n \n \n \n \n )\n}\n" - -backend\tests\test_sprint237_flanders_thematic_on_demand.py:37: AssertionError -______ test_regional_on_demand_sources_require_a_bounded_drawn_selection ______ - - def test_regional_on_demand_sources_require_a_bounded_drawn_selection() -> None: - workspace = read("frontend/src/components/map/MapWorkspace.tsx") - - assert "regionalOnDemandThemeActive" in workspace -> assert "regionalRasterThemeActive || regionalOnDemandThemeActive" in workspace -E assert 'regionalRasterThemeActive || regionalOnDemandThemeActive' in "import { useCallback, useEffect, useMemo, useRef, useState, type KeyboardEvent } from 'react'\nimport { BoxSelect, Ch...ijken.

\n )}\n \n \n \n \n \n )\n}\n" - -backend\tests\test_sprint237_flanders_thematic_on_demand.py:56: AssertionError -_____ test_grb_frontend_and_contracts_use_only_the_governed_backend_path ______ - - def test_grb_frontend_and_contracts_use_only_the_governed_backend_path() -> None: - selection_hook = (ROOT / "frontend/src/hooks/useMapThemeSelectionInsights.ts").read_text(encoding="utf-8") - catalog_hook = (ROOT / "frontend/src/hooks/useOfficialMapProducts.ts").read_text(encoding="utf-8") - workspace = (ROOT / "frontend/src/components/map/MapWorkspace.tsx").read_text(encoding="utf-8") - contracts = (ROOT / "docs/API_CONTRACTS.md").read_text(encoding="utf-8") - - assert "datasetsApi.acquireGrb" in selection_hook - assert "datasetsApi.listGrbProducts" in catalog_hook - assert "officialMapProducts.grb" in workspace - assert "result[product.key] = null" in workspace - assert ": onDemandThemeActive\n ? null\n : mapFeatureCollection" in workspace - assert "onSetContextLayerLabel" in workspace -> assert "'Automatisch'" in workspace -E assert "'Automatisch'" in "import { useCallback, useEffect, useMemo, useRef, useState, type KeyboardEvent } from 'react'\nimport { BoxSelect, Ch...ijken.

\n )}\n \n \n \n \n \n )\n}\n" - -backend\tests\test_sprint239_bounded_grb_acquisition.py:394: AssertionError -__________ test_app_entrypoint_has_clean_encoding_and_react_imports ___________ - - def test_app_entrypoint_has_clean_encoding_and_react_imports() -> None: - app_path = ROOT / "frontend" / "src" / "App.tsx" - app_bytes = app_path.read_bytes() - app = app_path.read_text(encoding="utf-8") - - assert not app_bytes.startswith(b"\xef\xbb\xbf") - assert "import { useEffect, useMemo, useRef, useState } from 'react'" in app - assert "FormEvent" not in app -> assert app.count("useEffect(") == 1 -E assert 3 == 1 -E + where 3 = ('useEffect(') -E + where = "import { useEffect, useMemo, useRef, useState } from 'react'\nimport { CircleAlert, LogOut, ShieldCheck, UserRound } ...ator' : 'open')}\n loggingOut={loggingOut}\n onLogout={handleLogout}\n />\n )\n}\n\nexport default App\n".count - -backend\tests\test_sprint39_frontend_orchestration_hooks.py:40: AssertionError -- generated xml file: C:\Projects\geointel\artifacts\evidence\accuracy\P1\backend-full-suite.junit.xml - -=========================== short test summary info =========================== -FAILED backend\tests\test_rc4_national_coverage.py::test_frontend_prefers_materialized_national_workspace_and_resolves_drawn_bbox -FAILED backend\tests\test_rc5_release_deployment.py::test_runtime_configuration_is_validated_before_container_replacement -FAILED backend\tests\test_rc9_ux_release_contract.py::test_rc9_loading_and_accessibility_states_are_explicit -FAILED backend\tests\test_rc_runtime_observability.py::test_all_in_one_deploy_embeds_immutable_build_identity -FAILED backend\tests\test_sprint106_map_bbox_extract.py::test_frontend_exposes_map_bbox_selection_contracts -FAILED backend\tests\test_sprint177_mol_primary_focus.py::test_frontend_declares_national_scope_as_primary_operating_focus -FAILED backend\tests\test_sprint177_mol_primary_focus.py::test_product_docs_record_national_scope_and_mol_regression_focus -FAILED backend\tests\test_sprint186_map_first_geographic_explorer.py::test_map_first_explorer_is_the_default_product_flow -FAILED backend\tests\test_sprint186_map_first_geographic_explorer.py::test_map_rectangle_drag_is_wired_to_automatic_analysis -FAILED backend\tests\test_sprint200_temporal_explorer_handoff.py::test_evolution_theme_catalog_distinguishes_history_from_current_only_data -FAILED backend\tests\test_sprint219_regional_raster_explorer.py::test_regional_map_uses_logical_partition_groups_and_exact_analysis -FAILED backend\tests\test_sprint236_bathymetry_expansion.py::test_frontend_uses_partitioned_bathymetry_selection_for_regional_scope -FAILED backend\tests\test_sprint237_flanders_thematic_on_demand.py::test_flanders_workspace_exposes_governed_thematic_products_on_demand -FAILED backend\tests\test_sprint237_flanders_thematic_on_demand.py::test_selection_reads_and_bounded_acquires_all_relevant_themes -FAILED backend\tests\test_sprint237_flanders_thematic_on_demand.py::test_regional_on_demand_sources_require_a_bounded_drawn_selection -FAILED backend\tests\test_sprint239_bounded_grb_acquisition.py::test_grb_frontend_and_contracts_use_only_the_governed_backend_path -FAILED backend\tests\test_sprint39_frontend_orchestration_hooks.py::test_app_entrypoint_has_clean_encoding_and_react_imports -17 failed, 1180 passed in 70.63s (0:01:10) diff --git a/artifacts/evidence/accuracy/P1/commands-and-results.md b/artifacts/evidence/accuracy/P1/commands-and-results.md deleted file mode 100644 index 02adc0a8..00000000 --- a/artifacts/evidence/accuracy/P1/commands-and-results.md +++ /dev/null @@ -1,266 +0,0 @@ -# Phase 1 command and result ledger - -Captured: 2026-08-01 -Audited repository baseline: `0c019bb22f816db1e4b7a68379bcad08924d9a21` -Branch: `codex/geointel-accuracy-program` - -This ledger records the commands and claim boundaries behind the retained -evidence. JSON, JUnit, SQL and full text logs in this directory are the source -of truth when this summary and a raw artifact differ. - -## Repository and static inventory - -```powershell -python scripts/run_accuracy_phase1_baseline.py --output-dir artifacts/evidence/accuracy/P1 -``` - -Result: completed. The baseline found 2,495 tracked files, including a tracked -`geointel/` mirror with 1,153 files; 68 paired files differ from root. No model -checkpoint is tracked in the local checkout. The mirror is excluded by the root -`.dockerignore`; the residual risk is source/import/maintenance ambiguity, not -official all-in-one build-context inclusion. - -Evidence: - -- `phase1-baseline-summary.json` -- `repository-inventory.json` -- `local-artifact-inventory.json` -- `static-risk-signals.json` - -## Deterministic contract reproductions - -```powershell -python scripts/reproduce_accuracy_phase1_findings.py -``` - -Result: 7 of 7 expected violations reproduced. They cover cross-theme coverage -contamination, metres-as-degrees buffering, Lambert-as-4326 persistence, -caller-spoofed source authority, mutable-name model scope, mutable-name legal -scope and silently ignored Area PATCH geometry. - -Evidence: `forensic-reproductions.json`. - -## Tower runtime, database and storage references - -The collector was streamed into the running `geointel` container and executed -with read-only SQL and a 30-second statement timeout: - -```text -docker exec -i geointel env PYTHONPATH=/app/backend python - -``` - -Result: - -- Python 3.11.2, PyTorch 2.11.0+cu128, CUDA 12.8, Ultralytics 8.4.99; -- NVIDIA GeForce RTX 4080 SUPER visible on `cuda:0`; -- Alembic head `202607260001`; -- 5,816 direct database storage references checked, 0 missing; -- four Geel detections contain Lambert-domain coordinates while the geometry - column reports SRID 4326; -- no database or storage row was modified. - -A broader recursive `audit_data_operations.py` storage scan was stopped by its -244-second execution timeout and produced no retained result. It is not counted -as a pass. The bounded, direct-reference collector above completed and is the -only storage-completeness claim made here. - -Evidence: - -- `tower-runtime-database-snapshot.json` -- `tower-runtime-database-snapshot-detailed.json` - -## Real GPU inference smoke - -The read-only collector used the production `YoloDetectionAdapter`, the active -model and one existing Geel tile: - -```text -python - --model-path /app/models/geointel-building-yolov8s-smallbld-minpx3-img640-ft30.pt \ - --tile-path /app/storage/tiles/cb80638d-dbef-48ac-b19c-cec7c3efc96e/ae0ff76d-70c0-404f-b777-54d14517179a/b191c968-7d56-4e0d-afbb-8b5baaa62470/tile_0000.tif \ - --manifest-path /app/storage/tiles/cb80638d-dbef-48ac-b19c-cec7c3efc96e/ae0ff76d-70c0-404f-b777-54d14517179a/b191c968-7d56-4e0d-afbb-8b5baaa62470/manifest.json \ - --confidence 0.5 --image-size 640 --max-detections 1000 --device cuda:0 --seed 20260801 -``` - -Result: passed; 17 raw building detections; 0.883694486 s synchronized -inference; model SHA-256 -`a9088b8491dfae36694b53e9e9406cb4e3511d334a5712fa34f75078a47759c1`. - -Claim boundary: this proves one runtime execution. It does not prove that any -box is correct, that confidence is calibrated, or that the model generalizes. - -Evidence: `tower-gpu-inference-smoke.json`. - -## ML/data-lineage inventory - -The bounded collector read V56/V58/V62/V66 plus model, checkpoint, report and -manifest metadata from the mounted Tower volume: - -```text -docker exec -i geointel python - --app-root /app -``` - -Result: - -- 26 model assets, 229 training checkpoints, 424 training JSON reports and - 36 operator manifests inventoried; -- V56 has 180 AOIs and 0 completed human reviews; -- three pure-empty background-test AOIs: Flanders 2, Wallonia 1, Brussels 0; -- zero exact cross-split raster-hash duplicates; -- bounded 64-bit dHash screen: 180 rasters, minimum Hamming distance 17, - zero cross-split pairs at or below 4; -- minimum cross-split AOI bbox distance 95.720336 m and 24 pairs below 2 km; -- V58/V62 evidence is calibration-only; at threshold 0.15 aggregate F1 is - 0.512905 while Flanders recall and F1 are 0; -- no protected-test, background-test promotion or national-release evidence. - -Claim boundary: exact/dHash and bbox-distance screens do not establish -municipality, flight-strip, instance, semantic or imagery-edition independence. - -Evidence: `tower-ml-data-lineage-snapshot.json` and -`tower-key-artifact-hashes.json` (V62 best/last checkpoints and V56 tile audit). - -## Backend tests - -### Full root-context suite - -```powershell -$env:PYTHONPATH='C:\Projects\geointel\backend;C:\Projects\geointel' -python -m pytest backend/tests -q -p no:cacheprovider \ - -W error::DeprecationWarning \ - --junitxml=artifacts/evidence/accuracy/P1/backend-full-suite.junit.xml -``` - -Result: exit 1; 1,180 passed and 17 failed in 70.63 seconds. The 17 failures are -stale source/contract assertions, including expectations that conflict with the -new explicit user-selected model flow. They remain release-blocking until -replaced with reviewed behavior tests. - -Evidence: - -- `backend-full-suite.txt` -- `backend-full-suite.junit.xml` - -### Actual backend CI working directory - -```powershell -cd backend -python -m pytest -W error::DeprecationWarning -``` - -Result: exit 2 during collection; 1,194 items collected plus one import error: - -```text -ModuleNotFoundError: No module named 'scripts.render_operator_polygon_label_qa' -``` - -Evidence: `backend-ci-entrypoint.txt`. - -### Phase 1 tooling - -```powershell -python -m pytest tests/test_accuracy_phase1_baseline.py -q -p no:cacheprovider -``` - -Result: 4 passed. - -Evidence: `phase1-tooling-tests.txt`. - -## Lint - -```powershell -python -m ruff check scripts/collect_accuracy_phase1_inference_smoke.py \ - scripts/collect_accuracy_phase1_ml_lineage.py \ - scripts/collect_accuracy_phase1_runtime.py \ - scripts/reproduce_accuracy_phase1_findings.py \ - scripts/run_accuracy_phase1_baseline.py tests/test_accuracy_phase1_baseline.py -``` - -Result: all new Phase 1 code passed. - -```powershell -python -m ruff check backend scripts tests -``` - -Result: exit 1; 112 findings: E402 13, E701 2, E702 69, F401 23, F403 1, -F811 2 and F841 2. - -Evidence: - -- `repository-ruff-baseline.txt` -- `repository-ruff-baseline.json` - -## Frontend - -```powershell -cd frontend -npm run test:unit -npm run typecheck -npm run build -``` - -Results: - -- Vitest: 16 files, 51 tests passed; -- TypeScript typecheck: passed; -- production build: passed, 1,896 modules transformed. - -The attempted generic `npm test -- --run` failed because no `test` script -exists; the configured command is `test:unit`. The test strategy also calls -for lint, but `npm run lint` fails with `Missing script: "lint"`. - -Evidence: - -- `frontend-vitest.txt` (failed non-existent generic command, retained) -- `frontend-vitest-unit.txt` (correct configured command, passed) -- `frontend-typecheck.txt` -- `frontend-build.txt` -- `frontend-lint.txt` - -## API, migrations and golden QA - -```powershell -python scripts/audit_api_contracts.py -``` - -Result: 147 implemented routes match documentation; 10 explicitly tracked -non-envelope endpoints. - -Evidence: `openapi-contract-audit.txt`. - -```powershell -cd backend -python -m alembic heads -python -m alembic upgrade head --sql -``` - -Result: one head, `202607260001`; complete offline upgrade rendered 496 SQL/log -lines. This is not a local live-PostGIS migration test. - -Evidence: - -- `alembic-heads.txt` -- `alembic-offline-upgrade.sql` - -```powershell -python scripts/run_golden_qa_benchmark.py --json -``` - -Result: two runs have semantically identical metric results but different file -hashes because run identities use UUID4. - -Evidence: - -- `golden-qa-run-1.json` -- `golden-qa-run-2.json` -- `golden-qa-reproducibility.json` - -## Explicitly not executed as a success gate - -- no protected test or background-test portfolio was opened; -- no training, calibration fitting, checkpoint promotion or active-model change; -- no label was accepted on behalf of a human reviewer; -- no production database migration or data repair; -- no dataset, checkpoint, cache, output or user-owned untracked file deleted, - rewritten or moved; -- no segmentation, SAM or solar asset was inferred to be production-ready from - file presence. diff --git a/artifacts/evidence/accuracy/P1/evidence-manifest-20260830-verification.json b/artifacts/evidence/accuracy/P1/evidence-manifest-20260830-verification.json deleted file mode 100644 index 0bcbc860..00000000 --- a/artifacts/evidence/accuracy/P1/evidence-manifest-20260830-verification.json +++ /dev/null @@ -1,284 +0,0 @@ -{ - "audited_repository_head": "0e3c1b20e931941c346da08f6fa8847e674bdadb", - "claim_boundary": "This manifest proves retained-file identity and completeness. 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"size_bytes": 3009 - } - ], - "schema_version": 1 -} diff --git a/artifacts/evidence/accuracy/P1/forensic-reproductions.json b/artifacts/evidence/accuracy/P1/forensic-reproductions.json deleted file mode 100644 index 865c88c0..00000000 --- a/artifacts/evidence/accuracy/P1/forensic-reproductions.json +++ /dev/null @@ -1,116 +0,0 @@ -{ - "findings": [ - { - "expected": "A small buildings partition remains partial; a roads bbox cannot complete buildings coverage.", - "id": "P1-COV-001", - "observed": { - "fully_covered": true, - "matched_dataset_ids": [ - "00000000-0000-4000-8000-000000000001" - ] - }, - "reproduced": true, - "severity": "critical", - "source": "backend/app/services/coverage_registry_service.py:481-505" - }, - { - "expected": "A 100 metre buffer is projected to a metric CRS and spans roughly hundreds of metres.", - "id": "P1-CRS-001", - "observed": { - "bounds_epsg4326": [ - -95.0, - -49.0, - 105.0, - 151.0 - ], - "longitude_span_degrees": 200.0 - }, - "reproduced": true, - "severity": "critical", - "source": "backend/app/services/vector_operations_service.py:179-203" - }, - { - "expected": "Non-WGS84 input is transformed to EPSG:4326 or rejected before persistence.", - "id": "P1-CRS-002", - "observed": { - "stored_coordinates": [ - 150000.0, - 210000.0 - ], - "stored_srid": 4326 - }, - "reproduced": true, - "severity": "critical", - "source": "backend/app/services/vector_feature_service.py:271-299" - }, - { - "expected": "Only server-attested source identities can produce authoritative operational coverage.", - "id": "P1-AUTH-001", - "observed": { - "caller_controlled_source_name": "grb", - "coverage_status": "operational", - "reported_authority": "authoritative" - }, - "reproduced": true, - "severity": "critical", - "source": "backend/app/api/routes/datasets.py:142-163; backend/app/services/coverage_registry_service.py:463-559" - }, - { - "expected": "Validation scope is bound to immutable geometry/source/checksum evidence.", - "id": "P1-AI-001", - "observed": { - "accepted": true, - "area_name": "Mol validation bypass", - "geometry_bounds": [ - -75.0, - 35.0, - -74.9, - 35.1 - ] - }, - "reproduced": true, - "severity": "critical", - "source": "backend/app/services/detection_service.py:223-232" - }, - { - "expected": "Renaming an Area cannot change its legal coverage-zone identity.", - "id": "P1-COV-002", - "observed": { - "canonical": { - "outside": false, - "zones": [ - "flanders" - ] - }, - "renamed_same_geometry": { - "outside": true, - "zones": [] - } - }, - "reproduced": true, - "severity": "high", - "source": "backend/app/services/coverage_registry_service.py:56-65,425-447" - }, - { - "expected": "PATCH /areas/{area_id} either validates and applies geometry or rejects the field.", - "id": "P1-API-001", - "observed": { - "geometry_silently_ignored": true, - "parsed_payload": { - "crs": null, - "name": "Renamed" - } - }, - "reproduced": true, - "severity": "high", - "source": "backend/app/schemas/area.py:15-17; backend/app/services/area_service.py:154-171" - } - ], - "purpose": "Read-only deterministic reproductions of Phase-1 contract violations.", - "schema_version": 1, - "summary": { - "all_reproduced": true, - "reproduced": 7, - "total": 7 - } -} diff --git a/artifacts/evidence/accuracy/P1/frontend-build.txt b/artifacts/evidence/accuracy/P1/frontend-build.txt deleted file mode 100644 index 93f27f37..00000000 --- a/artifacts/evidence/accuracy/P1/frontend-build.txt +++ /dev/null @@ -1,31 +0,0 @@ -command=npm run build -exit_code=0 -captured_at=2026-08-01T18:34:50.3212385+02:00 - - -> geointel-frontend@1.0.0 build -> tsc -b && vite build - -vite v7.3.6 building client environment for production... -transforming... -✓ 1896 modules transformed. -rendering chunks... -computing gzip size... -dist/index.html  0.98 kB │ gzip: 0.49 kB -dist/assets/manrope-latin-500-normal-BYYD-dBL.woff2  14.04 kB -dist/assets/manrope-latin-600-normal-4f0koTD-.woff2  14.17 kB -dist/assets/manrope-latin-700-normal-BZp_XxE4.woff2  14.21 kB -dist/assets/public-sans-latin-600-normal-Fru-LXNs.woff2  14.59 kB -dist/assets/public-sans-latin-400-normal-8Rpg0ruU.woff2  14.63 kB -dist/assets/public-sans-latin-500-normal-NlrCPXnF.woff2  14.66 kB -dist/assets/manrope-latin-500-normal-DMZssgOp.woff  18.24 kB -dist/assets/manrope-latin-600-normal-BqgrALkZ.woff  18.38 kB -dist/assets/manrope-latin-700-normal-DGRFkw-m.woff  18.41 kB -dist/assets/public-sans-latin-400-normal-SBbinRkI.woff  18.49 kB -dist/assets/public-sans-latin-500-normal-vCxiVFAq.woff  18.52 kB -dist/assets/public-sans-latin-600-normal-BR59oU-I.woff  18.56 kB -dist/assets/index-BNS8Tp4f.css 426.59 kB │ gzip: 69.40 kB -dist/assets/vendor-CrqJdhs-.js 140.80 kB │ gzip: 45.27 kB -dist/assets/index-DR8RUeAl.js 457.16 kB │ gzip: 119.71 kB -dist/assets/maplibre-DEBTaTl_.js 802.71 kB │ gzip: 217.71 kB -✓ built in 9.80s diff --git a/artifacts/evidence/accuracy/P1/frontend-lint.txt b/artifacts/evidence/accuracy/P1/frontend-lint.txt deleted file mode 100644 index 523ad0cc..00000000 --- a/artifacts/evidence/accuracy/P1/frontend-lint.txt +++ /dev/null @@ -1,12 +0,0 @@ -command=npm run lint -exit_code=1 -captured_at=2026-08-01T18:36:26.6162306+02:00 - -npm error Missing script: "lint" -npm error -npm error Did you mean this? -npm error npm link # Symlink a package folder -npm error -npm error To see a list of scripts, run: -npm error npm run -npm error A complete log of this run can be found in: C:\Users\Jens\AppData\Local\npm-cache\_logs\2026-08-01T16_36_25_353Z-debug-0.log diff --git a/artifacts/evidence/accuracy/P1/frontend-typecheck.txt b/artifacts/evidence/accuracy/P1/frontend-typecheck.txt deleted file mode 100644 index fa691209..00000000 --- a/artifacts/evidence/accuracy/P1/frontend-typecheck.txt +++ /dev/null @@ -1,8 +0,0 @@ -command=npm run typecheck -exit_code=0 -captured_at=2026-08-01T18:34:27.3623155+02:00 - - -> geointel-frontend@1.0.0 typecheck -> tsc -p tsconfig.json --noEmit - diff --git a/artifacts/evidence/accuracy/P1/frontend-vitest-unit.txt b/artifacts/evidence/accuracy/P1/frontend-vitest-unit.txt deleted file mode 100644 index 81768fe4..00000000 --- a/artifacts/evidence/accuracy/P1/frontend-vitest-unit.txt +++ /dev/null @@ -1,35 +0,0 @@ -command=npm run test:unit -exit_code=0 -captured_at=2026-08-01T18:35:24.4298867+02:00 - - -> geointel-frontend@1.0.0 test:unit -> vitest run - - - RUN  v3.2.6 C:/Projects/geointel/frontend - - ✓ src/lib/datasetCapabilities.test.ts (2 tests) 5ms - ✓ src/lib/performanceBudget.test.ts (3 tests) 41ms - ✓ src/components/map/mapWorkspaceUtils.test.ts (14 tests) 36ms - ✓ src/hooks/useMapThemeSelectionInsights.test.ts (2 tests) 43ms - ✓ src/hooks/useCoverageResolver.test.tsx (4 tests) 47ms - ✓ src/hooks/useTemporalComparison.test.tsx (3 tests) 36ms - ✓ src/components/WorkbenchStatusStrip.test.tsx (2 tests) 151ms - ✓ src/hooks/useWorkbenchBootstrap.test.tsx (3 tests) 60ms - ✓ src/components/map/LiveAnalysisJourney.test.tsx (3 tests) 59ms - ✓ src/components/overview/ProjectAtlasIllustration.test.tsx (2 tests) 267ms - ✓ src/components/models/ModelSelector.test.tsx (2 tests) 342ms - ✓ src/components/detection/AiPipelineIllustration.test.tsx (1 test) 296ms - ✓ src/components/auth/LandingProjectStory.test.tsx (2 tests) 332ms - ✓ src/components/map/MunicipalitySearch.test.tsx (2 tests) 483ms - ✓ MunicipalitySearch > searches the official municipality catalog and activates a result  468ms - ✓ src/components/auth/LandingPage.test.tsx (4 tests) 825ms - ✓ LandingPage > presents the professionalised landing page and submits the operator login  471ms - ✓ src/lib/bathymetryRaster.test.ts (2 tests) 3ms - - Test Files  16 passed (16) - Tests  51 passed (51) - Start at  18:35:16 - Duration  7.37s (transform 2.45s, setup 0ms, collect 14.66s, tests 3.03s, environment 45.46s, prepare 8.07s) - diff --git a/artifacts/evidence/accuracy/P1/frontend-vitest.txt b/artifacts/evidence/accuracy/P1/frontend-vitest.txt deleted file mode 100644 index 8c753fea..00000000 --- a/artifacts/evidence/accuracy/P1/frontend-vitest.txt +++ /dev/null @@ -1,9 +0,0 @@ -command=npm test -- --run -exit_code=1 -captured_at=2026-08-01T18:34:11.9904224+02:00 - -npm error Missing script: "test" -npm error -npm error To see a list of scripts, run: -npm error npm run -npm error A complete log of this run can be found in: C:\Users\Jens\AppData\Local\npm-cache\_logs\2026-08-01T16_34_11_785Z-debug-0.log diff --git a/artifacts/evidence/accuracy/P1/golden-qa-reproducibility.json b/artifacts/evidence/accuracy/P1/golden-qa-reproducibility.json deleted file mode 100644 index 212e9f25..00000000 --- a/artifacts/evidence/accuracy/P1/golden-qa-reproducibility.json +++ /dev/null @@ -1,11 +0,0 @@ -{ - "schema_version": 1, - "command": "python scripts/run_golden_qa_benchmark.py --json", - "run_1_exit_code": 0, - "run_2_exit_code": 0, - "run_1_sha256": "ec96862b024987b59e56579920361582e718126b07885732335ac1b4d51b61bc", - "run_2_sha256": "4f900711a706dd56dd16b368e261761051f6d52a38bfd421e7d1c5f66ee51e49", - "byte_identical": false, - "semantic_results_equal": true, - "interpretation": "Metric values are stable, but UUID4-backed run identity makes retained JSON byte-nondeterministic." -} diff --git a/artifacts/evidence/accuracy/P1/golden-qa-run-1.json b/artifacts/evidence/accuracy/P1/golden-qa-run-1.json deleted file mode 100644 index 40780ba9..00000000 --- a/artifacts/evidence/accuracy/P1/golden-qa-run-1.json +++ /dev/null @@ -1,177 +0,0 @@ -{ - "benchmark_id": "golden-buildings-partial-match-v1", - "fixtures": { - "candidate": "fixtures/golden/predicted_buildings.geojson", - "reference": "fixtures/golden/reference_buildings.geojson" - }, - "metrics": { - "f1": 0.5, - "false_negative_count": 1, - 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"output" - ], - "total_size_bytes": 84874287 -} diff --git a/artifacts/evidence/accuracy/P1/openapi-contract-audit.txt b/artifacts/evidence/accuracy/P1/openapi-contract-audit.txt deleted file mode 100644 index 6b8f8479..00000000 --- a/artifacts/evidence/accuracy/P1/openapi-contract-audit.txt +++ /dev/null @@ -1,5 +0,0 @@ -command=python scripts/audit_api_contracts.py -exit_code=0 -captured_at=2026-08-01T18:37:24.4984309+02:00 - -API contract audit OK: 147 implemented routes match docs; 10 explicit non-envelope endpoints tracked. diff --git a/artifacts/evidence/accuracy/P1/phase1-baseline-summary.json b/artifacts/evidence/accuracy/P1/phase1-baseline-summary.json deleted file mode 100644 index 7a78581b..00000000 --- a/artifacts/evidence/accuracy/P1/phase1-baseline-summary.json +++ /dev/null @@ -1,36 +0,0 @@ -{ - "baseline_scope": [ - "tracked repository state", - "static code/test/migration inventory", - "tracked mirror comparison", - "local artifact inventory", - "mock/fixture/placeholder/fallback triage signals" - ], - "finding_count": 2, - "findings": [ - { - "evidence": { - "paired_different_file_count": 68, - "tracked_mirror_file_count": 1153 - }, - "id": "P1-REPO-001", - "severity": "high", - "title": "Tracked nested repository mirror creates ambiguous source state" - }, - { - "id": "P1-ML-LOCAL-001", - "interpretation": "Production model truth must be verified on the mounted Tower volume.", - "severity": "info", - "title": "No local checkpoint is available in the repository checkout" - } - ], - "generated_at": "2026-08-01T15:53:53.482303+00:00", - "schema_version": 1, - "separate_required_evidence": [ - "Tower database/storage audit", - "Tower CUDA/model preflight and representative inference", - "corpus leakage/duplicate/label/time review", - "independent human visual review" - ], - "status": "findings_present" -} diff --git a/artifacts/evidence/accuracy/P1/phase1-tooling-tests.txt b/artifacts/evidence/accuracy/P1/phase1-tooling-tests.txt deleted file mode 100644 index c125d88f..00000000 --- a/artifacts/evidence/accuracy/P1/phase1-tooling-tests.txt +++ /dev/null @@ -1,6 +0,0 @@ -command=python -m pytest tests/test_accuracy_phase1_baseline.py -q -p no:cacheprovider -exit_code=0 -captured_at=2026-08-01T18:33:32.0526074+02:00 - 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"row": 222 - }, - "filename": "C:\\Projects\\geointel\\scripts\\create_portfolio_case_study.py", - "fix": null, - "location": { - "column": 26, - "row": 222 - }, - "message": "Multiple statements on one line (semicolon)", - "noqa_row": 222, - "url": "https://docs.astral.sh/ruff/rules/multiple-statements-on-one-line-semicolon" - }, - { - "cell": null, - "code": "E702", - "end_location": { - "column": 53, - "row": 222 - }, - "filename": "C:\\Projects\\geointel\\scripts\\create_portfolio_case_study.py", - "fix": null, - "location": { - "column": 52, - "row": 222 - }, - "message": "Multiple statements on one line (semicolon)", - "noqa_row": 222, - "url": "https://docs.astral.sh/ruff/rules/multiple-statements-on-one-line-semicolon" - }, - { - "cell": null, - "code": "E702", - "end_location": { - "column": 41, - "row": 223 - }, - "filename": "C:\\Projects\\geointel\\scripts\\create_portfolio_case_study.py", - "fix": null, - "location": { - "column": 40, - "row": 223 - }, - "message": "Multiple statements on one line (semicolon)", - "noqa_row": 223, - "url": "https://docs.astral.sh/ruff/rules/multiple-statements-on-one-line-semicolon" - }, - { - "cell": null, - "code": "E702", - "end_location": { - "column": 61, - "row": 223 - }, - "filename": "C:\\Projects\\geointel\\scripts\\create_portfolio_case_study.py", - "fix": null, - "location": { - "column": 60, - "row": 223 - }, - "message": "Multiple statements on one line (semicolon)", - "noqa_row": 223, - "url": "https://docs.astral.sh/ruff/rules/multiple-statements-on-one-line-semicolon" - }, - { - "cell": null, - "code": "F401", - "end_location": { - "column": 18, - "row": 46 - }, - "filename": "C:\\Projects\\geointel\\scripts\\provision_regional_grb_context.py", - "fix": { - "applicability": "safe", - "edits": [ - { - "content": "from provision_regional_grb_buildings import (\n DEFAULT_API_URL,\n DEFAULT_MAX_FEATURES_PER_MEMBER,\n DEFAULT_MAX_TOTAL_FEATURES,\n DEFAULT_OUTPUT_ROOT,\n DEFAULT_PAGE_LIMIT,\n DEFAULT_SCOPE_KEY,\n GEOJSON_CRS,\n GRB_ATTRIBUTION,\n bounds_overlap,\n build_member_geometries,\n build_source_session,\n ensure_backend_path,\n list_paginated_items,\n next_page_url,\n observed_at,\n reusable_manifest,\n safe_slug,\n sha256_file,\n utc_now,\n write_json_atomic,\n)", - "end_location": { - "column": 2, - "row": 52 - }, - "location": { - "column": 1, - "row": 30 - } - } - ], - "message": "Remove unused import: `provision_regional_grb_buildings.response_data`" - }, - "location": { - "column": 5, - "row": 46 - }, - "message": "`provision_regional_grb_buildings.response_data` imported but unused", - "noqa_row": 46, - "url": "https://docs.astral.sh/ruff/rules/unused-import" - }, - { - "cell": null, - "code": "F401", - "end_location": { - "column": 35, - "row": 26 - }, - "filename": "C:\\Projects\\geointel\\scripts\\provision_waterinfo_station_history.py", - "fix": { - "applicability": "safe", - "edits": [ - { - "content": "from shapely.geometry import shape", - "end_location": { - "column": 51, - "row": 26 - }, - "location": { - "column": 1, - "row": 26 - } - } - ], - "message": "Remove unused import" - }, - "location": { - "column": 30, - "row": 26 - }, - "message": "`shapely.geometry.Point` imported but unused", - "noqa_row": 26, - "url": "https://docs.astral.sh/ruff/rules/unused-import" - }, - { - "cell": null, - "code": "F401", - "end_location": { - "column": 44, - "row": 26 - }, - "filename": "C:\\Projects\\geointel\\scripts\\provision_waterinfo_station_history.py", - "fix": { - "applicability": "safe", - "edits": [ - { - "content": "from shapely.geometry import shape", - "end_location": { - "column": 51, - "row": 26 - }, - "location": { - "column": 1, - "row": 26 - } - } - ], - "message": "Remove unused import" - }, - "location": { - "column": 37, - "row": 26 - }, - "message": "`shapely.geometry.mapping` imported but unused", - "noqa_row": 26, - "url": "https://docs.astral.sh/ruff/rules/unused-import" - }, - { - "cell": null, - "code": "F401", - "end_location": { - "column": 23, - "row": 14 - }, - "filename": "C:\\Projects\\geointel\\scripts\\refine_yolo_labels_with_sam.py", - "fix": { - "applicability": "safe", - "edits": [ - { - "content": "", - "end_location": { - "column": 1, - "row": 15 - }, - "location": { - "column": 1, - "row": 14 - } - } - ], - "message": "Remove unused import: `typing.Any`" - }, - "location": { - "column": 20, - "row": 14 - }, - "message": "`typing.Any` imported but unused", - "noqa_row": 14, - "url": "https://docs.astral.sh/ruff/rules/unused-import" - }, - { - "cell": null, - "code": "F401", - "end_location": { - "column": 28, - "row": 15 - }, - "filename": "C:\\Projects\\geointel\\scripts\\run_golden_qa_benchmark.py", - "fix": { - "applicability": "safe", - "edits": [ - { - "content": "from app.models import Dataset, Metric, QualityCheck", - "end_location": { - "column": 59, - "row": 15 - }, - "location": { - "column": 1, - "row": 15 - } - } - ], - "message": "Remove unused import: `app.models.Area`" - }, - "location": { - "column": 24, - "row": 15 - }, - "message": "`app.models.Area` imported but unused", - "noqa_row": 15, - "url": "https://docs.astral.sh/ruff/rules/unused-import" - }, - { - "cell": null, - "code": "E402", - "end_location": { - "column": 40, - "row": 11 - }, - "filename": "C:\\Projects\\geointel\\scripts\\seed_demo_workflow.py", - "fix": null, - "location": { - "column": 1, - "row": 11 - }, - "message": "Module level import not at top of file", - "noqa_row": 11, - "url": "https://docs.astral.sh/ruff/rules/module-import-not-at-top-of-file" - }, - { - "cell": null, - "code": "E402", - "end_location": { - "column": 67, - "row": 12 - }, - "filename": "C:\\Projects\\geointel\\scripts\\seed_demo_workflow.py", - "fix": null, - "location": { - "column": 1, - "row": 12 - }, - "message": "Module level import not at top of file", - "noqa_row": 12, - "url": "https://docs.astral.sh/ruff/rules/module-import-not-at-top-of-file" - }, - { - "cell": null, - "code": "E701", - "end_location": { - "column": 12, - "row": 4 - }, - "filename": "C:\\Projects\\geointel\\scripts\\smoke_contracts.py", - "fix": null, - "location": { - "column": 11, - "row": 4 - }, - "message": "Multiple statements on one line (colon)", - "noqa_row": 4, - "url": "https://docs.astral.sh/ruff/rules/multiple-statements-on-one-line-colon" - }, - { - "cell": null, - "code": "E701", - "end_location": { - "column": 12, - "row": 5 - }, - "filename": "C:\\Projects\\geointel\\scripts\\smoke_docs.py", - "fix": null, - "location": { - "column": 11, - "row": 5 - }, - "message": "Multiple statements on one line (colon)", - "noqa_row": 5, - "url": "https://docs.astral.sh/ruff/rules/multiple-statements-on-one-line-colon" - }, - { - "cell": null, - "code": "F401", - "end_location": { - "column": 49, - "row": 136 - }, - "filename": "C:\\Projects\\geointel\\scripts\\train_building_proposal_filter.py", - "fix": { - "applicability": "safe", - "edits": [ - { - "content": "from torchvision import datasets", - "end_location": { - "column": 49, - "row": 136 - }, - "location": { - "column": 5, - "row": 136 - } - } - ], - "message": "Remove unused import: `torchvision.transforms`" - }, - "location": { - "column": 39, - "row": 136 - }, - "message": "`torchvision.transforms` imported but unused", - "noqa_row": 136, - "url": "https://docs.astral.sh/ruff/rules/unused-import" - } -] diff --git a/artifacts/evidence/accuracy/P1/repository-ruff-baseline.txt b/artifacts/evidence/accuracy/P1/repository-ruff-baseline.txt deleted file mode 100644 index b1466301..00000000 --- a/artifacts/evidence/accuracy/P1/repository-ruff-baseline.txt +++ /dev/null @@ -1,1088 +0,0 @@ -command=python -m ruff check backend scripts tests -exit_code=1 -captured_at=2026-08-01T18:34:08.5284079+02:00 - -backend\app\models.py:1:1: F403 `from app.models import *` used; unable to detect undefined names - | -1 | from app.models import * - | ^^^^^^^^^^^^^^^^^^^^^^^^ F403 - | - -backend\app\schemas\__init__.py:101:5: F401 `.bathymetry.BathymetryRasterMetric` imported but unused; consider removing, adding to `__all__`, or using a redundant alias - | - 99 | BathymetryProfileAcquireRequest, -100 | BathymetryProfileAcquisitionResult, -101 | BathymetryRasterMetric, - | ^^^^^^^^^^^^^^^^^^^^^^ F401 -102 | BathymetryRasterSelectionRequest, -103 | BathymetryRasterSelectionResponse, - | - = help: Add unused import `BathymetryRasterMetric` to __all__ - -backend\app\schemas\__init__.py:102:5: F401 `.bathymetry.BathymetryRasterSelectionRequest` imported but unused; consider removing, adding to `__all__`, or using a redundant alias - | -100 | BathymetryProfileAcquisitionResult, -101 | BathymetryRasterMetric, -102 | BathymetryRasterSelectionRequest, - | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ F401 -103 | BathymetryRasterSelectionResponse, -104 | BathymetryRasterSelectionSummary, - | - = help: Add unused import `BathymetryRasterSelectionRequest` to __all__ - -backend\app\schemas\__init__.py:103:5: F401 `.bathymetry.BathymetryRasterSelectionResponse` imported but unused; consider removing, adding to `__all__`, or using a redundant alias - | -101 | BathymetryRasterMetric, -102 | BathymetryRasterSelectionRequest, -103 | BathymetryRasterSelectionResponse, - | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ F401 -104 | BathymetryRasterSelectionSummary, -105 | BathymetrySourceProbeRead, - | - = help: Add unused import `BathymetryRasterSelectionResponse` to __all__ - -backend\app\schemas\__init__.py:104:5: F401 `.bathymetry.BathymetryRasterSelectionSummary` imported but unused; consider removing, adding to `__all__`, or using a redundant alias - | -102 | BathymetryRasterSelectionRequest, -103 | BathymetryRasterSelectionResponse, -104 | BathymetryRasterSelectionSummary, - | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ F401 -105 | BathymetrySourceProbeRead, -106 | BathymetrySourceRead, - | - = help: Add unused import `BathymetryRasterSelectionSummary` to __all__ - -backend\app\services\aoi_operation_executor.py:56:26: E702 Multiple statements on one line (semicolon) - | -54 | partition = db.get(AoiOperationPartition, partition.id) -55 | partition.child_job_id = child.id -56 | db.add(partition); db.commit() - | ^ E702 -57 | JobService.mark_running(db, child.id) -58 | try: - | - -backend\app\services\aoi_operation_service.py:210:37: E702 Multiple statements on one line (semicolon) - | -208 | return None -209 | now = datetime.now(timezone.utc) -210 | partition.status = "running"; partition.started_at = now; partition.attempt_count += 1; partition.error_message = None - | ^ E702 -211 | operation.status = "running"; operation.started_at = operation.started_at or now -212 | db.add(partition); db.add(operation); db.commit(); db.refresh(partition) - | - -backend\app\services\aoi_operation_service.py:210:65: E702 Multiple statements on one line (semicolon) - | -208 | return None -209 | now = datetime.now(timezone.utc) -210 | partition.status = "running"; partition.started_at = now; partition.attempt_count += 1; partition.error_message = None - | ^ E702 -211 | operation.status = "running"; operation.started_at = operation.started_at or now -212 | db.add(partition); db.add(operation); db.commit(); db.refresh(partition) - | - -backend\app\services\aoi_operation_service.py:210:95: E702 Multiple statements on one line (semicolon) - | -208 | return None -209 | now = datetime.now(timezone.utc) -210 | partition.status = "running"; partition.started_at = now; partition.attempt_count += 1; partition.error_message = None - | ^ E702 -211 | operation.status = "running"; operation.started_at = operation.started_at or now -212 | db.add(partition); db.add(operation); db.commit(); db.refresh(partition) - | - -backend\app\services\aoi_operation_service.py:211:37: E702 Multiple statements on one line (semicolon) - | -209 | now = datetime.now(timezone.utc) -210 | partition.status = "running"; partition.started_at = now; partition.attempt_count += 1; partition.error_message = None -211 | operation.status = "running"; operation.started_at = operation.started_at or now - | ^ E702 -212 | db.add(partition); db.add(operation); db.commit(); db.refresh(partition) -213 | return partition - | - -backend\app\services\aoi_operation_service.py:212:26: E702 Multiple statements on one line (semicolon) - | -210 | partition.status = "running"; partition.started_at = now; partition.attempt_count += 1; partition.error_message = None -211 | operation.status = "running"; operation.started_at = operation.started_at or now -212 | db.add(partition); db.add(operation); db.commit(); db.refresh(partition) - | ^ E702 -213 | return partition - | - -backend\app\services\aoi_operation_service.py:212:45: E702 Multiple statements on one line (semicolon) - | -210 | partition.status = "running"; partition.started_at = now; partition.attempt_count += 1; partition.error_message = None -211 | operation.status = "running"; operation.started_at = operation.started_at or now -212 | db.add(partition); db.add(operation); db.commit(); db.refresh(partition) - | ^ E702 -213 | return partition - | - -backend\app\services\aoi_operation_service.py:212:58: E702 Multiple statements on one line (semicolon) - | -210 | partition.status = "running"; partition.started_at = now; partition.attempt_count += 1; partition.error_message = None -211 | operation.status = "running"; operation.started_at = operation.started_at or now -212 | db.add(partition); db.add(operation); db.commit(); db.refresh(partition) - | ^ E702 -213 | return partition - | - -backend\app\services\aoi_operation_service.py:220:47: E702 Multiple statements on one line (semicolon) - | -218 | if partition.status != "running": -219 | raise AppError(code="AOI_PARTITION_NOT_RUNNING", message="Only a running partition can be checkpointed", status_code=409) -220 | partition.checkpoint_json = checkpoint; db.add(partition); db.commit(); db.refresh(partition) - | ^ E702 -221 | return partition - | - -backend\app\services\aoi_operation_service.py:220:66: E702 Multiple statements on one line (semicolon) - | -218 | if partition.status != "running": -219 | raise AppError(code="AOI_PARTITION_NOT_RUNNING", message="Only a running partition can be checkpointed", status_code=409) -220 | partition.checkpoint_json = checkpoint; db.add(partition); db.commit(); db.refresh(partition) - | ^ E702 -221 | return partition - | - -backend\app\services\aoi_operation_service.py:220:79: E702 Multiple statements on one line (semicolon) - | -218 | if partition.status != "running": -219 | raise AppError(code="AOI_PARTITION_NOT_RUNNING", message="Only a running partition can be checkpointed", status_code=409) -220 | partition.checkpoint_json = checkpoint; db.add(partition); db.commit(); db.refresh(partition) - | ^ E702 -221 | return partition - | - -backend\app\services\aoi_operation_service.py:230:63: E702 Multiple statements on one line (semicolon) - | -228 | … if partition.status != "running": -229 | … raise AppError(code="AOI_PARTITION_NOT_RUNNING", message="Only a running partition can complete", status_code=409) -230 | … partition.status = "skipped" if skipped else "success"; partition.result_json = result; partition.finished_at = datetime.now(ti… - | ^ E702 -231 | … db.add(partition); db.commit(); AoiOperationService._refresh_parent(db, operation_id) -232 | … return AoiOperationService.read(db, project_id, operation_id) - | - -backend\app\services\aoi_operation_service.py:230:95: E702 Multiple statements on one line (semicolon) - | -228 | … if partition.status != "running": -229 | … raise AppError(code="AOI_PARTITION_NOT_RUNNING", message="Only a running partition can complete", status_code=409) -230 | … partition.status = "skipped" if skipped else "success"; partition.result_json = result; partition.finished_at = datetime.now(ti… - | ^ E702 -231 | … db.add(partition); db.commit(); AoiOperationService._refresh_parent(db, operation_id) -232 | … return AoiOperationService.read(db, project_id, operation_id) - | - -backend\app\services\aoi_operation_service.py:231:26: E702 Multiple statements on one line (semicolon) - | -229 | … raise AppError(code="AOI_PARTITION_NOT_RUNNING", message="Only a running partition can complete", status_code=409) -230 | … partition.status = "skipped" if skipped else "success"; partition.result_json = result; partition.finished_at = datetime.now(ti… -231 | … db.add(partition); db.commit(); AoiOperationService._refresh_parent(db, operation_id) - | ^ E702 -232 | … return AoiOperationService.read(db, project_id, operation_id) - | - -backend\app\services\aoi_operation_service.py:231:39: E702 Multiple statements on one line (semicolon) - | -229 | … raise AppError(code="AOI_PARTITION_NOT_RUNNING", message="Only a running partition can complete", status_code=409) -230 | … partition.status = "skipped" if skipped else "success"; partition.result_json = result; partition.finished_at = datetime.now(ti… -231 | … db.add(partition); db.commit(); AoiOperationService._refresh_parent(db, operation_id) - | ^ E702 -232 | … return AoiOperationService.read(db, project_id, operation_id) - | - -backend\app\services\aoi_operation_service.py:237:42: E702 Multiple statements on one line (semicolon) - | -235 | def fail(db, project_id: UUID, operation_id: UUID, partition_id: UUID, message: str, retryable: bool, details: dict): -236 | partition = AoiOperationService._partition_row(db, project_id, operation_id, partition_id) -237 | partition.error_message = message; partition.result_json = {"details": details} - | ^ E702 -238 | partition.status = "queued" if retryable and partition.attempt_count < partition.max_attempts else "failed" -239 | partition.finished_at = None if partition.status == "queued" else datetime.now(timezone.utc) - | - -backend\app\services\aoi_operation_service.py:240:26: E702 Multiple statements on one line (semicolon) - | -238 | partition.status = "queued" if retryable and partition.attempt_count < partition.max_attempts else "failed" -239 | partition.finished_at = None if partition.status == "queued" else datetime.now(timezone.utc) -240 | db.add(partition); db.commit(); AoiOperationService._refresh_parent(db, operation_id) - | ^ E702 -241 | return AoiOperationService.read(db, project_id, operation_id) - | - -backend\app\services\aoi_operation_service.py:240:39: E702 Multiple statements on one line (semicolon) - | -238 | partition.status = "queued" if retryable and partition.attempt_count < partition.max_attempts else "failed" -239 | partition.finished_at = None if partition.status == "queued" else datetime.now(timezone.utc) -240 | db.add(partition); db.commit(); AoiOperationService._refresh_parent(db, operation_id) - | ^ E702 -241 | return AoiOperationService.read(db, project_id, operation_id) - | - -backend\app\services\aoi_operation_service.py:245:55: E702 Multiple statements on one line (semicolon) - | -243 | @staticmethod -244 | def _partition_row(db, project_id, operation_id, partition_id): -245 | operation = db.get(AoiOperation, operation_id); partition = db.get(AoiOperationPartition, partition_id) - | ^ E702 -246 | if operation is None or operation.project_id != project_id or partition is None or partition.operation_id != operation_id: -247 | raise AppError(code="AOI_PARTITION_NOT_FOUND", message="AOI partition not found", status_code=404) - | - -backend\app\services\aoi_operation_service.py:272:41: E702 Multiple statements on one line (semicolon) - | -270 | … now = datetime.now(timezone.utc) -271 | … if statuses and all(status in {"success", "skipped"} for status in statuses): -272 | … operation.status = "success"; operation.finished_at = now; operation.error_message = None - | ^ E702 -273 | … elif "failed" in statuses and not any(status in {"queued", "running"} for status in statuses): -274 | … operation.status = "partial" if any(status in {"success", "skipped"} for status in statuses) else "failed"; operation.finis… - | - -backend\app\services\aoi_operation_service.py:272:70: E702 Multiple statements on one line (semicolon) - | -270 | … now = datetime.now(timezone.utc) -271 | … if statuses and all(status in {"success", "skipped"} for status in statuses): -272 | … operation.status = "success"; operation.finished_at = now; operation.error_message = None - | ^ E702 -273 | … elif "failed" in statuses and not any(status in {"queued", "running"} for status in statuses): -274 | … operation.status = "partial" if any(status in {"success", "skipped"} for status in statuses) else "failed"; operation.finis… - | - -backend\app\services\aoi_operation_service.py:274:119: E702 Multiple statements on one line (semicolon) - | -272 | … operation.status = "success"; operation.finished_at = now; operation.error_message = None -273 | … elif "failed" in statuses and not any(status in {"queued", "running"} for status in statuses): -274 | … operation.status = "partial" if any(status in {"success", "skipped"} for status in statuses) else "failed"; operation.finis… - | ^ E702 -275 | … operation.error_message = "One or more bounded source partitions failed; inspect partition evidence." -276 | … db.add(operation); db.commit() - | - -backend\app\services\aoi_operation_service.py:276:26: E702 Multiple statements on one line (semicolon) - | -274 | … operation.status = "partial" if any(status in {"success", "skipped"} for status in statuses) else "failed"; operation.finis… -275 | … operation.error_message = "One or more bounded source partitions failed; inspect partition evidence." -276 | … db.add(operation); db.commit() - | ^ E702 - | - -backend\app\services\demo_workflow_service.py:253:9: F841 Local variable `rasterio` is assigned to but never used - | -251 | def _create_demo_raster_bytes() -> bytes: -252 | numpy = importlib.import_module("numpy") -253 | rasterio = importlib.import_module("rasterio") - | ^^^^^^^^ F841 -254 | rasterio_io = importlib.import_module("rasterio.io") -255 | rasterio_transform = importlib.import_module("rasterio.transform") - | - = help: Remove assignment to unused variable `rasterio` - -backend\app\services\detection_review_service.py:4:20: F401 [*] `typing.Any` imported but unused - | -3 | from collections import Counter -4 | from typing import Any - | ^^^ F401 -5 | from uuid import UUID - | - = help: Remove unused import: `typing.Any` - -backend\app\services\qa_service.py:14:30: F401 [*] `shapely.geometry.shape` imported but unused - | -12 | from shapely.ops import unary_union -13 | from shapely.validation import make_valid -14 | from shapely.geometry import shape - | ^^^^^ F401 -15 | from app.core.errors import AppError -16 | from app.models import Area, Dataset - | - = help: Remove unused import: `shapely.geometry.shape` - -backend\app\services\thematic_raster_acquisition_service.py:409:20: F401 `rasterio` imported but unused; consider using `importlib.util.find_spec` to test for availability - | -407 | return coverages[0] -408 | try: -409 | import rasterio - | ^^^^^^^^ F401 -410 | from rasterio.io import MemoryFile -411 | from rasterio.merge import merge - | - = help: Remove unused import: `rasterio` - -backend\scripts\cleanup_demo_artifacts.py:17:1: E402 Module level import not at top of file - | -15 | sys.path.insert(0, str(SCRIPTS_ROOT)) -16 | -17 | from app.core.config import get_settings - | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E402 -18 | from app.db.session import SessionLocal -19 | from app.models import Export, Project - | - -backend\scripts\cleanup_demo_artifacts.py:18:1: E402 Module level import not at top of file - | -17 | from app.core.config import get_settings -18 | from app.db.session import SessionLocal - | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E402 -19 | from app.models import Export, Project -20 | from release_backup_guard import require_confirmation, verify_current_backup - | - -backend\scripts\cleanup_demo_artifacts.py:19:1: E402 Module level import not at top of file - | -17 | from app.core.config import get_settings -18 | from app.db.session import SessionLocal -19 | from app.models import Export, Project - | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E402 -20 | from release_backup_guard import require_confirmation, verify_current_backup - | - -backend\scripts\cleanup_demo_artifacts.py:20:1: E402 Module level import not at top of file - | -18 | from app.db.session import SessionLocal -19 | from app.models import Export, Project -20 | from release_backup_guard import require_confirmation, verify_current_backup - | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E402 - | - -backend\tests\test_auth.py:189:5: F841 Local variable `client` is assigned to but never used - | -188 | def test_guest_session_tokens_fail_closed_without_a_project_scope(monkeypatch) -> None: -189 | client = auth_client(monkeypatch, guest_access=True) - | ^^^^^^ F841 -190 | settings = get_settings() - | - = help: Remove assignment to unused variable `client` - -backend\tests\test_qa_service.py:5:19: F401 [*] `types.SimpleNamespace` imported but unused - | -3 | import json -4 | from pathlib import Path -5 | from types import SimpleNamespace - | ^^^^^^^^^^^^^^^ F401 -6 | from uuid import uuid4 - | - = help: Remove unused import: `types.SimpleNamespace` - -backend\tests\test_qa_service.py:8:24: F401 [*] `app.models.Area` imported but unused - | -6 | from uuid import uuid4 -7 | -8 | from app.models import Area, Dataset - | ^^^^ F401 -9 | from app.services.qa_service import QaService - | - = help: Remove unused import: `app.models.Area` - -backend\tests\test_raster_operations_service.py:3:19: F401 [*] `types.ModuleType` imported but unused - | -1 | from __future__ import annotations -2 | -3 | from types import ModuleType, SimpleNamespace - | ^^^^^^^^^^ F401 -4 | from uuid import uuid4 -5 | from pathlib import Path - | - = help: Remove unused import: `types.ModuleType` - -backend\tests\test_sprint108_map_selection_derived_dataset.py:10:33: F401 [*] `app.models.VectorFeature` imported but unused - | - 9 | from app.main import app -10 | from app.models import Dataset, VectorFeature - | ^^^^^^^^^^^^^ F401 -11 | from app.schemas.dataset import DatasetCreateResponse -12 | from app.services.storage_service import StorageService - | - = help: Remove unused import: `app.models.VectorFeature` - -backend\tests\test_sprint205_agricultural_parcel_history.py:4:8: F401 [*] `json` imported but unused - | -3 | import importlib.util -4 | import json - | ^^^^ F401 -5 | import sys -6 | import zipfile - | - = help: Remove unused import: `json` - -backend\tests\test_sprint205_agricultural_parcel_history.py:79:9: F811 Redefinition of unused `json` from line 4 - | -77 | self.data = data -78 | -79 | def json(self): - | ^^^^ F811 -80 | return {"data": self.data} - | - = help: Remove definition: `json` - -backend\tests\test_sprint213_thematic_rasters.py:10:8: F401 [*] `rasterio` imported but unused - | - 8 | import numpy as np - 9 | import pytest -10 | import rasterio - | ^^^^^^^^ F401 -11 | from fastapi.testclient import TestClient -12 | from pyproj import Transformer - | - = help: Remove unused import: `rasterio` - -backend\tests\test_sprint233_operational_completion.py:5:19: F401 [*] `types.SimpleNamespace` imported but unused - | -3 | import json -4 | from pathlib import Path -5 | from types import SimpleNamespace - | ^^^^^^^^^^^^^^^ F401 -6 | from uuid import uuid4 - | - = help: Remove unused import: `types.SimpleNamespace` - -backend\tests\test_sprint236_bathymetry_expansion.py:4:8: F401 [*] `json` imported but unused - | -3 | from datetime import UTC, datetime -4 | import json - | ^^^^ F401 -5 | from pathlib import Path -6 | import ssl - | - = help: Remove unused import: `json` - -backend\tests\test_sprint236_bathymetry_expansion.py:59:9: F811 Redefinition of unused `json` from line 4 - | -57 | return None -58 | -59 | def json(self): - | ^^^^ F811 -60 | return self.payload - | - = help: Remove definition: `json` - -backend\tests\test_sprint241_spw_bathymetry_raster.py:4:8: F401 [*] `io` imported but unused - | -3 | import importlib.util -4 | import io - | ^^ F401 -5 | from pathlib import Path -6 | import sys - | - = help: Remove unused import: `io` - -backend\tests\test_vector_operations_service.py:4:19: F401 [*] `types.SimpleNamespace` imported but unused - | -3 | from pathlib import Path -4 | from types import SimpleNamespace - | ^^^^^^^^^^^^^^^ F401 -5 | from uuid import UUID, uuid4 - | - = help: Remove unused import: `types.SimpleNamespace` - -scripts\archive_technical_projects.py:20:1: E402 Module level import not at top of file - | -18 | sys.path.insert(0, str(BACKEND_ROOT)) -19 | -20 | from app.db.session import SessionLocal - | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E402 -21 | from app.models import Project - | - -scripts\archive_technical_projects.py:21:1: E402 Module level import not at top of file - | -20 | from app.db.session import SessionLocal -21 | from app.models import Project - | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E402 - | - -scripts\audit_data_operations.py:23:1: E402 Module level import not at top of file - | -21 | sys.path.insert(0, str(BACKEND_ROOT)) -22 | -23 | from app.core.config import get_settings - | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E402 -24 | from app.db.session import SessionLocal -25 | from sqlalchemy import func - | - -scripts\audit_data_operations.py:24:1: E402 Module level import not at top of file - | -23 | from app.core.config import get_settings -24 | from app.db.session import SessionLocal - | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E402 -25 | from sqlalchemy import func - | - -scripts\audit_data_operations.py:25:1: E402 Module level import not at top of file - | -23 | from app.core.config import get_settings -24 | from app.db.session import SessionLocal -25 | from sqlalchemy import func - | ^^^^^^^^^^^^^^^^^^^^^^^^^^^ E402 -26 | -27 | from app.models import AnalysisRun, Dataset, DatasetVersion, Detection, Export, Job, Project, Segmentation - | - -scripts\audit_data_operations.py:27:1: E402 Module level import not at top of file - | -25 | from sqlalchemy import func -26 | -27 | from app.models import AnalysisRun, Dataset, DatasetVersion, Detection, Export, Job, Project, Segmentation - | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E402 - | - -scripts\build_building_proposal_classifier_dataset.py:20:1: E402 Module level import not at top of file - | -18 | sys.path.insert(0, str(SCRIPT_DIR)) -19 | -20 | from evaluate_belgium_building_candidate import iou, read_references - | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E402 - | - -scripts\create_portfolio_case_study.py:127:26: E702 Multiple statements on one line (semicolon) - | -126 | def draw_challenge(c: canvas.Canvas) -> None: -127 | c.setFillColor(white); c.rect(0, 0, W, H, fill=1, stroke=0) - | ^ E702 -128 | title(c, "01 / Productvraag", "Niet alleen zien, maar kunnen verdedigen") -129 | y = paragraph(c, "Geoportalen tonen vaak lagen en losse metingen. GeoIntel maakt van bron, gebied, analyse en bewijs één operatio… - | - -scripts\create_portfolio_case_study.py:137:29: E702 Multiple statements on one line (semicolon) - | -135 | for index, (num, head, body) in enumerate(cards): -136 | cy = y - 42 - index * 78 -137 | c.setFillColor(PALE); c.roundRect(42, cy - 54, 330, 64, 10, fill=1, stroke=0) - | ^ E702 -138 | c.setFillColor(TEAL); c.setFont(FONT_BOLD, 8); c.drawString(56, cy - 6, num) -139 | c.setFillColor(INK); c.setFont(FONT_BOLD, 11); c.drawString(86, cy - 7, head) - | - -scripts\create_portfolio_case_study.py:138:29: E702 Multiple statements on one line (semicolon) - | -136 | cy = y - 42 - index * 78 -137 | c.setFillColor(PALE); c.roundRect(42, cy - 54, 330, 64, 10, fill=1, stroke=0) -138 | c.setFillColor(TEAL); c.setFont(FONT_BOLD, 8); c.drawString(56, cy - 6, num) - | ^ E702 -139 | c.setFillColor(INK); c.setFont(FONT_BOLD, 11); c.drawString(86, cy - 7, head) -140 | paragraph(c, body, 86, cy - 18, 266, 8.2, MUTED, 12) - | - -scripts\create_portfolio_case_study.py:138:54: E702 Multiple statements on one line (semicolon) - | -136 | cy = y - 42 - index * 78 -137 | c.setFillColor(PALE); c.roundRect(42, cy - 54, 330, 64, 10, fill=1, stroke=0) -138 | c.setFillColor(TEAL); c.setFont(FONT_BOLD, 8); c.drawString(56, cy - 6, num) - | ^ E702 -139 | c.setFillColor(INK); c.setFont(FONT_BOLD, 11); c.drawString(86, cy - 7, head) -140 | paragraph(c, body, 86, cy - 18, 266, 8.2, MUTED, 12) - | - -scripts\create_portfolio_case_study.py:139:28: E702 Multiple statements on one line (semicolon) - | -137 | c.setFillColor(PALE); c.roundRect(42, cy - 54, 330, 64, 10, fill=1, stroke=0) -138 | c.setFillColor(TEAL); c.setFont(FONT_BOLD, 8); c.drawString(56, cy - 6, num) -139 | c.setFillColor(INK); c.setFont(FONT_BOLD, 11); c.drawString(86, cy - 7, head) - | ^ E702 -140 | paragraph(c, body, 86, cy - 18, 266, 8.2, MUTED, 12) -141 | image_cover(c, ASSETS / "geointel-landing-hero.png", 410, 53, 385, 415) - | - -scripts\create_portfolio_case_study.py:139:54: E702 Multiple statements on one line (semicolon) - | -137 | c.setFillColor(PALE); c.roundRect(42, cy - 54, 330, 64, 10, fill=1, stroke=0) -138 | c.setFillColor(TEAL); c.setFont(FONT_BOLD, 8); c.drawString(56, cy - 6, num) -139 | c.setFillColor(INK); c.setFont(FONT_BOLD, 11); c.drawString(86, cy - 7, head) - | ^ E702 -140 | paragraph(c, body, 86, cy - 18, 266, 8.2, MUTED, 12) -141 | image_cover(c, ASSETS / "geointel-landing-hero.png", 410, 53, 385, 415) - | - -scripts\create_portfolio_case_study.py:146:40: E702 Multiple statements on one line (semicolon) - | -145 | def draw_experience(c: canvas.Canvas) -> None: -146 | c.setFillColor(HexColor("#f5faf8")); c.rect(0, 0, W, H, fill=1, stroke=0) - | ^ E702 -147 | title(c, "02 / Experience design", "De kaart blijft het werkblad", "Rustige hiërarchie, zichtbare herkomst en bewijs op het momen… -148 | image_cover(c, ASSETS / "geointel-workbench-map.png", 42, 73, 485, 360) - | - -scripts\create_portfolio_case_study.py:157:24: E702 Multiple statements on one line (semicolon) - | -156 | def draw_ai(c: canvas.Canvas) -> None: -157 | c.setFillColor(INK); c.rect(0, 0, W, H, fill=1, stroke=0) - | ^ E702 -158 | c.setFillColor(MINT); c.setFont(FONT_BOLD, 8); c.drawString(42, H - 44, "03 / PYTORCH + NVIDIA") -159 | c.setFillColor(white); c.setFont(FONT_BOLD, 25); c.drawString(42, H - 78, "Van bronpixel naar gecontroleerde detectie") - | - -scripts\create_portfolio_case_study.py:158:25: E702 Multiple statements on one line (semicolon) - | -156 | def draw_ai(c: canvas.Canvas) -> None: -157 | c.setFillColor(INK); c.rect(0, 0, W, H, fill=1, stroke=0) -158 | c.setFillColor(MINT); c.setFont(FONT_BOLD, 8); c.drawString(42, H - 44, "03 / PYTORCH + NVIDIA") - | ^ E702 -159 | c.setFillColor(white); c.setFont(FONT_BOLD, 25); c.drawString(42, H - 78, "Van bronpixel naar gecontroleerde detectie") -160 | c.setFillColor(HexColor("#b8d4cd")); c.setFont(FONT, 9); c.drawString(42, H - 99, "Elke schakel bewaart de context die nodig is o… - | - -scripts\create_portfolio_case_study.py:158:50: E702 Multiple statements on one line (semicolon) - | -156 | def draw_ai(c: canvas.Canvas) -> None: -157 | c.setFillColor(INK); c.rect(0, 0, W, H, fill=1, stroke=0) -158 | c.setFillColor(MINT); c.setFont(FONT_BOLD, 8); c.drawString(42, H - 44, "03 / PYTORCH + NVIDIA") - | ^ E702 -159 | c.setFillColor(white); c.setFont(FONT_BOLD, 25); c.drawString(42, H - 78, "Van bronpixel naar gecontroleerde detectie") -160 | c.setFillColor(HexColor("#b8d4cd")); c.setFont(FONT, 9); c.drawString(42, H - 99, "Elke schakel bewaart de context die nodig is o… - | - -scripts\create_portfolio_case_study.py:159:26: E702 Multiple statements on one line (semicolon) - | -157 | c.setFillColor(INK); c.rect(0, 0, W, H, fill=1, stroke=0) -158 | c.setFillColor(MINT); c.setFont(FONT_BOLD, 8); c.drawString(42, H - 44, "03 / PYTORCH + NVIDIA") -159 | c.setFillColor(white); c.setFont(FONT_BOLD, 25); c.drawString(42, H - 78, "Van bronpixel naar gecontroleerde detectie") - | ^ E702 -160 | c.setFillColor(HexColor("#b8d4cd")); c.setFont(FONT, 9); c.drawString(42, H - 99, "Elke schakel bewaart de context die nodig is o… -161 | stages = [ - | - -scripts\create_portfolio_case_study.py:159:52: E702 Multiple statements on one line (semicolon) - | -157 | c.setFillColor(INK); c.rect(0, 0, W, H, fill=1, stroke=0) -158 | c.setFillColor(MINT); c.setFont(FONT_BOLD, 8); c.drawString(42, H - 44, "03 / PYTORCH + NVIDIA") -159 | c.setFillColor(white); c.setFont(FONT_BOLD, 25); c.drawString(42, H - 78, "Van bronpixel naar gecontroleerde detectie") - | ^ E702 -160 | c.setFillColor(HexColor("#b8d4cd")); c.setFont(FONT, 9); c.drawString(42, H - 99, "Elke schakel bewaart de context die nodig is o… -161 | stages = [ - | - -scripts\create_portfolio_case_study.py:160:40: E702 Multiple statements on one line (semicolon) - | -158 | c.setFillColor(MINT); c.setFont(FONT_BOLD, 8); c.drawString(42, H - 44, "03 / PYTORCH + NVIDIA") -159 | c.setFillColor(white); c.setFont(FONT_BOLD, 25); c.drawString(42, H - 78, "Van bronpixel naar gecontroleerde detectie") -160 | c.setFillColor(HexColor("#b8d4cd")); c.setFont(FONT, 9); c.drawString(42, H - 99, "Elke schakel bewaart de context die nodig is o… - | ^ E702 -161 | stages = [ -162 | ("01", "Orthofoto", "CRS + dekking"), - | - -scripts\create_portfolio_case_study.py:160:60: E702 Multiple statements on one line (semicolon) - | -158 | c.setFillColor(MINT); c.setFont(FONT_BOLD, 8); c.drawString(42, H - 44, "03 / PYTORCH + NVIDIA") -159 | c.setFillColor(white); c.setFont(FONT_BOLD, 25); c.drawString(42, H - 78, "Van bronpixel naar gecontroleerde detectie") -160 | c.setFillColor(HexColor("#b8d4cd")); c.setFont(FONT, 9); c.drawString(42, H - 99, "Elke schakel bewaart de context die nodig is o… - | ^ E702 -161 | stages = [ -162 | ("01", "Orthofoto", "CRS + dekking"), - | - -scripts\create_portfolio_case_study.py:169:42: E702 Multiple statements on one line (semicolon) - | -167 | ] -168 | x0, gap, bw = 42, 13, 139 -169 | c.setStrokeColor(HexColor("#4bb99f")); c.setLineWidth(2); c.line(95, 285, 746, 285) - | ^ E702 -170 | for i, (num, head, body) in enumerate(stages): -171 | x = x0 + i * (bw + gap) - | - -scripts\create_portfolio_case_study.py:169:61: E702 Multiple statements on one line (semicolon) - | -167 | ] -168 | x0, gap, bw = 42, 13, 139 -169 | c.setStrokeColor(HexColor("#4bb99f")); c.setLineWidth(2); c.line(95, 285, 746, 285) - | ^ E702 -170 | for i, (num, head, body) in enumerate(stages): -171 | x = x0 + i * (bw + gap) - | - -scripts\create_portfolio_case_study.py:172:44: E702 Multiple statements on one line (semicolon) - | -170 | for i, (num, head, body) in enumerate(stages): -171 | x = x0 + i * (bw + gap) -172 | c.setFillColor(HexColor("#12443d")); c.roundRect(x, 205, bw, 160, 12, fill=1, stroke=0) - | ^ E702 -173 | c.setFillColor(MINT); c.setFont(FONT_BOLD, 8); c.drawString(x + 14, 340, num) -174 | c.setFillColor(white); c.setFont(FONT_BOLD, 10); c.drawString(x + 14, 295, head) - | - -scripts\create_portfolio_case_study.py:173:29: E702 Multiple statements on one line (semicolon) - | -171 | x = x0 + i * (bw + gap) -172 | c.setFillColor(HexColor("#12443d")); c.roundRect(x, 205, bw, 160, 12, fill=1, stroke=0) -173 | c.setFillColor(MINT); c.setFont(FONT_BOLD, 8); c.drawString(x + 14, 340, num) - | ^ E702 -174 | c.setFillColor(white); c.setFont(FONT_BOLD, 10); c.drawString(x + 14, 295, head) -175 | c.setFillColor(HexColor("#9fc9bf")); c.setFont(FONT, 7.4); c.drawString(x + 14, 275, body) - | - -scripts\create_portfolio_case_study.py:173:54: E702 Multiple statements on one line (semicolon) - | -171 | x = x0 + i * (bw + gap) -172 | c.setFillColor(HexColor("#12443d")); c.roundRect(x, 205, bw, 160, 12, fill=1, stroke=0) -173 | c.setFillColor(MINT); c.setFont(FONT_BOLD, 8); c.drawString(x + 14, 340, num) - | ^ E702 -174 | c.setFillColor(white); c.setFont(FONT_BOLD, 10); c.drawString(x + 14, 295, head) -175 | c.setFillColor(HexColor("#9fc9bf")); c.setFont(FONT, 7.4); c.drawString(x + 14, 275, body) - | - -scripts\create_portfolio_case_study.py:174:30: E702 Multiple statements on one line (semicolon) - | -172 | c.setFillColor(HexColor("#12443d")); c.roundRect(x, 205, bw, 160, 12, fill=1, stroke=0) -173 | c.setFillColor(MINT); c.setFont(FONT_BOLD, 8); c.drawString(x + 14, 340, num) -174 | c.setFillColor(white); c.setFont(FONT_BOLD, 10); c.drawString(x + 14, 295, head) - | ^ E702 -175 | c.setFillColor(HexColor("#9fc9bf")); c.setFont(FONT, 7.4); c.drawString(x + 14, 275, body) -176 | c.setFillColor(MINT if i < 3 else AMBER); c.circle(x + bw / 2, 230, 6, fill=1, stroke=0) - | - -scripts\create_portfolio_case_study.py:174:56: E702 Multiple statements on one line (semicolon) - | -172 | c.setFillColor(HexColor("#12443d")); c.roundRect(x, 205, bw, 160, 12, fill=1, stroke=0) -173 | c.setFillColor(MINT); c.setFont(FONT_BOLD, 8); c.drawString(x + 14, 340, num) -174 | c.setFillColor(white); c.setFont(FONT_BOLD, 10); c.drawString(x + 14, 295, head) - | ^ E702 -175 | c.setFillColor(HexColor("#9fc9bf")); c.setFont(FONT, 7.4); c.drawString(x + 14, 275, body) -176 | c.setFillColor(MINT if i < 3 else AMBER); c.circle(x + bw / 2, 230, 6, fill=1, stroke=0) - | - -scripts\create_portfolio_case_study.py:175:44: E702 Multiple statements on one line (semicolon) - | -173 | c.setFillColor(MINT); c.setFont(FONT_BOLD, 8); c.drawString(x + 14, 340, num) -174 | c.setFillColor(white); c.setFont(FONT_BOLD, 10); c.drawString(x + 14, 295, head) -175 | c.setFillColor(HexColor("#9fc9bf")); c.setFont(FONT, 7.4); c.drawString(x + 14, 275, body) - | ^ E702 -176 | c.setFillColor(MINT if i < 3 else AMBER); c.circle(x + bw / 2, 230, 6, fill=1, stroke=0) -177 | paragraph(c, "Fail-closed runtime: wanneer CUDA vereist maar niet beschikbaar is, of wanneer een lokaal model ontbreekt, toont Ge… - | - -scripts\create_portfolio_case_study.py:175:66: E702 Multiple statements on one line (semicolon) - | -173 | c.setFillColor(MINT); c.setFont(FONT_BOLD, 8); c.drawString(x + 14, 340, num) -174 | c.setFillColor(white); c.setFont(FONT_BOLD, 10); c.drawString(x + 14, 295, head) -175 | c.setFillColor(HexColor("#9fc9bf")); c.setFont(FONT, 7.4); c.drawString(x + 14, 275, body) - | ^ E702 -176 | c.setFillColor(MINT if i < 3 else AMBER); c.circle(x + bw / 2, 230, 6, fill=1, stroke=0) -177 | paragraph(c, "Fail-closed runtime: wanneer CUDA vereist maar niet beschikbaar is, of wanneer een lokaal model ontbreekt, toont Ge… - | - -scripts\create_portfolio_case_study.py:176:49: E702 Multiple statements on one line (semicolon) - | -174 | c.setFillColor(white); c.setFont(FONT_BOLD, 10); c.drawString(x + 14, 295, head) -175 | c.setFillColor(HexColor("#9fc9bf")); c.setFont(FONT, 7.4); c.drawString(x + 14, 275, body) -176 | c.setFillColor(MINT if i < 3 else AMBER); c.circle(x + bw / 2, 230, 6, fill=1, stroke=0) - | ^ E702 -177 | paragraph(c, "Fail-closed runtime: wanneer CUDA vereist maar niet beschikbaar is, of wanneer een lokaal model ontbreekt, toont Ge… -178 | footer(c, 4) - | - -scripts\create_portfolio_case_study.py:182:26: E702 Multiple statements on one line (semicolon) - | -181 | def draw_architecture(c: canvas.Canvas) -> None: -182 | c.setFillColor(white); c.rect(0, 0, W, H, fill=1, stroke=0) - | ^ E702 -183 | title(c, "04 / Architectuur", "Eén keten, expliciete verantwoordelijkheden") -184 | nodes = [ - | - -scripts\create_portfolio_case_study.py:193:79: E702 Multiple statements on one line (semicolon) - | -191 | ] -192 | for x, y, w, h, head, body in nodes: -193 | c.setFillColor(PALE if "PyTorch" not in head else HexColor("#0d5047")); c.roundRect(x, y, w, h, 10, fill=1, stroke=0) - | ^ E702 -194 | c.setFillColor(white if "PyTorch" in head else INK); c.setFont(FONT_BOLD, 9); c.drawString(x + 12, y + 39, head) -195 | c.setFillColor(HexColor("#b9d8d0") if "PyTorch" in head else MUTED); c.setFont(FONT, 7.2); c.drawString(x + 12, y + 21, body) - | - -scripts\create_portfolio_case_study.py:194:60: E702 Multiple statements on one line (semicolon) - | -192 | for x, y, w, h, head, body in nodes: -193 | c.setFillColor(PALE if "PyTorch" not in head else HexColor("#0d5047")); c.roundRect(x, y, w, h, 10, fill=1, stroke=0) -194 | c.setFillColor(white if "PyTorch" in head else INK); c.setFont(FONT_BOLD, 9); c.drawString(x + 12, y + 39, head) - | ^ E702 -195 | c.setFillColor(HexColor("#b9d8d0") if "PyTorch" in head else MUTED); c.setFont(FONT, 7.2); c.drawString(x + 12, y + 21, body) -196 | c.setStrokeColor(TEAL); c.setLineWidth(1.5) - | - -scripts\create_portfolio_case_study.py:194:85: E702 Multiple statements on one line (semicolon) - | -192 | for x, y, w, h, head, body in nodes: -193 | c.setFillColor(PALE if "PyTorch" not in head else HexColor("#0d5047")); c.roundRect(x, y, w, h, 10, fill=1, stroke=0) -194 | c.setFillColor(white if "PyTorch" in head else INK); c.setFont(FONT_BOLD, 9); c.drawString(x + 12, y + 39, head) - | ^ E702 -195 | c.setFillColor(HexColor("#b9d8d0") if "PyTorch" in head else MUTED); c.setFont(FONT, 7.2); c.drawString(x + 12, y + 21, body) -196 | c.setStrokeColor(TEAL); c.setLineWidth(1.5) - | - -scripts\create_portfolio_case_study.py:195:76: E702 Multiple statements on one line (semicolon) - | -193 | c.setFillColor(PALE if "PyTorch" not in head else HexColor("#0d5047")); c.roundRect(x, y, w, h, 10, fill=1, stroke=0) -194 | c.setFillColor(white if "PyTorch" in head else INK); c.setFont(FONT_BOLD, 9); c.drawString(x + 12, y + 39, head) -195 | c.setFillColor(HexColor("#b9d8d0") if "PyTorch" in head else MUTED); c.setFont(FONT, 7.2); c.drawString(x + 12, y + 21, body) - | ^ E702 -196 | c.setStrokeColor(TEAL); c.setLineWidth(1.5) -197 | arrows = [((185,303),(220,303)),((350,303),(385,388)),((350,303),(385,218)),((535,388),(645,336)),((535,218),(570,303)),((645,270… - | - -scripts\create_portfolio_case_study.py:195:98: E702 Multiple statements on one line (semicolon) - | -193 | c.setFillColor(PALE if "PyTorch" not in head else HexColor("#0d5047")); c.roundRect(x, y, w, h, 10, fill=1, stroke=0) -194 | c.setFillColor(white if "PyTorch" in head else INK); c.setFont(FONT_BOLD, 9); c.drawString(x + 12, y + 39, head) -195 | c.setFillColor(HexColor("#b9d8d0") if "PyTorch" in head else MUTED); c.setFont(FONT, 7.2); c.drawString(x + 12, y + 21, body) - | ^ E702 -196 | c.setStrokeColor(TEAL); c.setLineWidth(1.5) -197 | arrows = [((185,303),(220,303)),((350,303),(385,388)),((350,303),(385,218)),((535,388),(645,336)),((535,218),(570,303)),((645,270… - | - -scripts\create_portfolio_case_study.py:196:27: E702 Multiple statements on one line (semicolon) - | -194 | c.setFillColor(white if "PyTorch" in head else INK); c.setFont(FONT_BOLD, 9); c.drawString(x + 12, y + 39, head) -195 | c.setFillColor(HexColor("#b9d8d0") if "PyTorch" in head else MUTED); c.setFont(FONT, 7.2); c.drawString(x + 12, y + 21, body) -196 | c.setStrokeColor(TEAL); c.setLineWidth(1.5) - | ^ E702 -197 | arrows = [((185,303),(220,303)),((350,303),(385,388)),((350,303),(385,218)),((535,388),(645,336)),((535,218),(570,303)),((645,270… -198 | for (x1,y1),(x2,y2) in arrows: - | - -scripts\create_portfolio_case_study.py:199:28: E702 Multiple statements on one line (semicolon) - | -197 | arrows = [((185,303),(220,303)),((350,303),(385,388)),((350,303),(385,218)),((535,388),(645,336)),((535,218),(570,303)),((645,270… -198 | for (x1,y1),(x2,y2) in arrows: -199 | c.line(x1,y1,x2,y2); c.circle(x2,y2,2.5,fill=1,stroke=0) - | ^ E702 -200 | paragraph(c, "PostGIS bewaart querybare geometrie en lifecycle-records. Grote raster-, mask- en modelbestanden blijven versioned … -201 | footer(c, 5) - | - -scripts\create_portfolio_case_study.py:206:40: E702 Multiple statements on one line (semicolon) - | -204 | def draw_outcomes(c: canvas.Canvas) -> None: -205 | image_cover(c, PUBLIC / "geointel-dark-case-study-cover.png", 0, 0, W, H) -206 | c.setFillColor(HexColor("#041d19")); c.rect(0, 0, W, H, fill=1, stroke=0) - | ^ E702 -207 | c.setFillColor(MINT); c.setFont(FONT_BOLD, 8); c.drawString(42, H - 44, "05 / RESULTAAT") -208 | c.setFillColor(white); c.setFont(FONT_BOLD, 27); c.drawString(42, H - 82, "Een professionele GeoAI-workbench") - | - -scripts\create_portfolio_case_study.py:207:25: E702 Multiple statements on one line (semicolon) - | -205 | image_cover(c, PUBLIC / "geointel-dark-case-study-cover.png", 0, 0, W, H) -206 | c.setFillColor(HexColor("#041d19")); c.rect(0, 0, W, H, fill=1, stroke=0) -207 | c.setFillColor(MINT); c.setFont(FONT_BOLD, 8); c.drawString(42, H - 44, "05 / RESULTAAT") - | ^ E702 -208 | c.setFillColor(white); c.setFont(FONT_BOLD, 27); c.drawString(42, H - 82, "Een professionele GeoAI-workbench") -209 | c.setFillColor(HexColor("#c0dad4")); c.setFont(FONT, 10); c.drawString(42, H - 104, "Nationaal/maritiem van scope, lokaal control… - | - -scripts\create_portfolio_case_study.py:207:50: E702 Multiple statements on one line (semicolon) - | -205 | image_cover(c, PUBLIC / "geointel-dark-case-study-cover.png", 0, 0, W, H) -206 | c.setFillColor(HexColor("#041d19")); c.rect(0, 0, W, H, fill=1, stroke=0) -207 | c.setFillColor(MINT); c.setFont(FONT_BOLD, 8); c.drawString(42, H - 44, "05 / RESULTAAT") - | ^ E702 -208 | c.setFillColor(white); c.setFont(FONT_BOLD, 27); c.drawString(42, H - 82, "Een professionele GeoAI-workbench") -209 | c.setFillColor(HexColor("#c0dad4")); c.setFont(FONT, 10); c.drawString(42, H - 104, "Nationaal/maritiem van scope, lokaal control… - | - -scripts\create_portfolio_case_study.py:208:26: E702 Multiple statements on one line (semicolon) - | -206 | c.setFillColor(HexColor("#041d19")); c.rect(0, 0, W, H, fill=1, stroke=0) -207 | c.setFillColor(MINT); c.setFont(FONT_BOLD, 8); c.drawString(42, H - 44, "05 / RESULTAAT") -208 | c.setFillColor(white); c.setFont(FONT_BOLD, 27); c.drawString(42, H - 82, "Een professionele GeoAI-workbench") - | ^ E702 -209 | c.setFillColor(HexColor("#c0dad4")); c.setFont(FONT, 10); c.drawString(42, H - 104, "Nationaal/maritiem van scope, lokaal control… -210 | outcomes = [ - | - -scripts\create_portfolio_case_study.py:208:52: E702 Multiple statements on one line (semicolon) - | -206 | c.setFillColor(HexColor("#041d19")); c.rect(0, 0, W, H, fill=1, stroke=0) -207 | c.setFillColor(MINT); c.setFont(FONT_BOLD, 8); c.drawString(42, H - 44, "05 / RESULTAAT") -208 | c.setFillColor(white); c.setFont(FONT_BOLD, 27); c.drawString(42, H - 82, "Een professionele GeoAI-workbench") - | ^ E702 -209 | c.setFillColor(HexColor("#c0dad4")); c.setFont(FONT, 10); c.drawString(42, H - 104, "Nationaal/maritiem van scope, lokaal control… -210 | outcomes = [ - | - -scripts\create_portfolio_case_study.py:209:40: E702 Multiple statements on one line (semicolon) - | -207 | c.setFillColor(MINT); c.setFont(FONT_BOLD, 8); c.drawString(42, H - 44, "05 / RESULTAAT") -208 | c.setFillColor(white); c.setFont(FONT_BOLD, 27); c.drawString(42, H - 82, "Een professionele GeoAI-workbench") -209 | c.setFillColor(HexColor("#c0dad4")); c.setFont(FONT, 10); c.drawString(42, H - 104, "Nationaal/maritiem van scope, lokaal control… - | ^ E702 -210 | outcomes = [ -211 | ("Map-first", "De gebruiker blijft in dezelfde ruimtelijke context."), - | - -scripts\create_portfolio_case_study.py:209:61: E702 Multiple statements on one line (semicolon) - | -207 | c.setFillColor(MINT); c.setFont(FONT_BOLD, 8); c.drawString(42, H - 44, "05 / RESULTAAT") -208 | c.setFillColor(white); c.setFont(FONT_BOLD, 27); c.drawString(42, H - 82, "Een professionele GeoAI-workbench") -209 | c.setFillColor(HexColor("#c0dad4")); c.setFont(FONT, 10); c.drawString(42, H - 104, "Nationaal/maritiem van scope, lokaal control… - | ^ E702 -210 | outcomes = [ -211 | ("Map-first", "De gebruiker blijft in dezelfde ruimtelijke context."), - | - -scripts\create_portfolio_case_study.py:219:44: E702 Multiple statements on one line (semicolon) - | -217 | x = 42 + (i % 2) * 375 -218 | y = 330 - (i // 2) * 105 -219 | c.setFillColor(HexColor("#123f38")); c.roundRect(x, y, 350, 78, 11, fill=1, stroke=0) - | ^ E702 -220 | c.setFillColor(MINT); c.setFont(FONT_BOLD, 11); c.drawString(x + 16, y + 48, head) -221 | paragraph(c, body, x + 16, y + 38, 316, 8, HexColor("#b8d2cc"), 12) - | - -scripts\create_portfolio_case_study.py:220:29: E702 Multiple statements on one line (semicolon) - | -218 | y = 330 - (i // 2) * 105 -219 | c.setFillColor(HexColor("#123f38")); c.roundRect(x, y, 350, 78, 11, fill=1, stroke=0) -220 | c.setFillColor(MINT); c.setFont(FONT_BOLD, 11); c.drawString(x + 16, y + 48, head) - | ^ E702 -221 | paragraph(c, body, x + 16, y + 38, 316, 8, HexColor("#b8d2cc"), 12) -222 | c.setFillColor(white); c.setFont(FONT_BOLD, 11); c.drawString(42, 58, "GeoIntel · Jens / ITWorx.tech") - | - -scripts\create_portfolio_case_study.py:220:55: E702 Multiple statements on one line (semicolon) - | -218 | y = 330 - (i // 2) * 105 -219 | c.setFillColor(HexColor("#123f38")); c.roundRect(x, y, 350, 78, 11, fill=1, stroke=0) -220 | c.setFillColor(MINT); c.setFont(FONT_BOLD, 11); c.drawString(x + 16, y + 48, head) - | ^ E702 -221 | paragraph(c, body, x + 16, y + 38, 316, 8, HexColor("#b8d2cc"), 12) -222 | c.setFillColor(white); c.setFont(FONT_BOLD, 11); c.drawString(42, 58, "GeoIntel · Jens / ITWorx.tech") - | - -scripts\create_portfolio_case_study.py:222:26: E702 Multiple statements on one line (semicolon) - | -220 | c.setFillColor(MINT); c.setFont(FONT_BOLD, 11); c.drawString(x + 16, y + 48, head) -221 | paragraph(c, body, x + 16, y + 38, 316, 8, HexColor("#b8d2cc"), 12) -222 | c.setFillColor(white); c.setFont(FONT_BOLD, 11); c.drawString(42, 58, "GeoIntel · Jens / ITWorx.tech") - | ^ E702 -223 | c.setFillColor(HexColor("#8fb9af")); c.setFont(FONT, 8); c.drawString(42, 42, "Belgium and the Belgian North Sea · v1.0.0") - | - -scripts\create_portfolio_case_study.py:222:52: E702 Multiple statements on one line (semicolon) - | -220 | c.setFillColor(MINT); c.setFont(FONT_BOLD, 11); c.drawString(x + 16, y + 48, head) -221 | paragraph(c, body, x + 16, y + 38, 316, 8, HexColor("#b8d2cc"), 12) -222 | c.setFillColor(white); c.setFont(FONT_BOLD, 11); c.drawString(42, 58, "GeoIntel · Jens / ITWorx.tech") - | ^ E702 -223 | c.setFillColor(HexColor("#8fb9af")); c.setFont(FONT, 8); c.drawString(42, 42, "Belgium and the Belgian North Sea · v1.0.0") - | - -scripts\create_portfolio_case_study.py:223:40: E702 Multiple statements on one line (semicolon) - | -221 | paragraph(c, body, x + 16, y + 38, 316, 8, HexColor("#b8d2cc"), 12) -222 | c.setFillColor(white); c.setFont(FONT_BOLD, 11); c.drawString(42, 58, "GeoIntel · Jens / ITWorx.tech") -223 | c.setFillColor(HexColor("#8fb9af")); c.setFont(FONT, 8); c.drawString(42, 42, "Belgium and the Belgian North Sea · v1.0.0") - | ^ E702 - | - -scripts\create_portfolio_case_study.py:223:60: E702 Multiple statements on one line (semicolon) - | -221 | paragraph(c, body, x + 16, y + 38, 316, 8, HexColor("#b8d2cc"), 12) -222 | c.setFillColor(white); c.setFont(FONT_BOLD, 11); c.drawString(42, 58, "GeoIntel · Jens / ITWorx.tech") -223 | c.setFillColor(HexColor("#8fb9af")); c.setFont(FONT, 8); c.drawString(42, 42, "Belgium and the Belgian North Sea · v1.0.0") - | ^ E702 - | - -scripts\provision_regional_grb_context.py:46:5: F401 [*] `provision_regional_grb_buildings.response_data` imported but unused - | -44 | next_page_url, -45 | observed_at, -46 | response_data, - | ^^^^^^^^^^^^^ F401 -47 | reusable_manifest, -48 | safe_slug, - | - = help: Remove unused import: `provision_regional_grb_buildings.response_data` - -scripts\provision_waterinfo_station_history.py:26:30: F401 [*] `shapely.geometry.Point` imported but unused - | -24 | import requests -25 | from requests.adapters import HTTPAdapter -26 | from shapely.geometry import Point, mapping, shape - | ^^^^^ F401 -27 | from urllib3.util.retry import Retry - | - = help: Remove unused import - -scripts\provision_waterinfo_station_history.py:26:37: F401 [*] `shapely.geometry.mapping` imported but unused - | -24 | import requests -25 | from requests.adapters import HTTPAdapter -26 | from shapely.geometry import Point, mapping, shape - | ^^^^^^^ F401 -27 | from urllib3.util.retry import Retry - | - = help: Remove unused import - -scripts\refine_yolo_labels_with_sam.py:14:20: F401 [*] `typing.Any` imported but unused - | -12 | import shutil -13 | from pathlib import Path -14 | from typing import Any - | ^^^ F401 - | - = help: Remove unused import: `typing.Any` - -scripts\run_golden_qa_benchmark.py:15:24: F401 [*] `app.models.Area` imported but unused - | -13 | sys.path.insert(0, str(BACKEND_ROOT)) -14 | -15 | from app.models import Area, Dataset, Metric, QualityCheck # noqa: E402 - | ^^^^ F401 -16 | from app.services.qa_service import QaService # noqa: E402 -17 | from app.services.quality_service import QualityService # noqa: E402 - | - = help: Remove unused import: `app.models.Area` - -scripts\seed_demo_workflow.py:11:1: E402 Module level import not at top of file - | - 9 | sys.path.insert(0, str(ROOT / "backend")) -10 | -11 | from app.db.session import SessionLocal - | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E402 -12 | from app.services.demo_workflow_service import DemoWorkflowService - | - -scripts\seed_demo_workflow.py:12:1: E402 Module level import not at top of file - | -11 | from app.db.session import SessionLocal -12 | from app.services.demo_workflow_service import DemoWorkflowService - | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E402 - | - -scripts\smoke_contracts.py:4:11: E701 Multiple statements on one line (colon) - | -2 | ROOT = Path(__file__).resolve().parents[1] -3 | missing=[d for d in ["contracts/api","contracts/database","contracts/events"] if not (ROOT/d).exists()] -4 | if missing: raise SystemExit("Missing contract directories: "+", ".join(missing)) - | ^ E701 -5 | print("Contracts smoke OK") - | - -scripts\smoke_docs.py:5:11: E701 Multiple statements on one line (colon) - | -3 | required_docs = ["docs/M5_OPERATIONAL_READINESS.md","docs/BUILD_GOVERNANCE.md","docs/CI_CD_SPECIFICATION.md","docs/HEALTHCHECK_CONTRACT… -4 | missing=[p for p in required_docs if not (ROOT/p).exists()] -5 | if missing: raise SystemExit("Missing docs:\n"+"\n".join(missing)) - | ^ E701 -6 | print("Documentation smoke OK") - | - -scripts\train_building_proposal_filter.py:136:39: F401 [*] `torchvision.transforms` imported but unused - | -134 | from torch import nn -135 | from torch.utils.data import DataLoader -136 | from torchvision import datasets, transforms - | ^^^^^^^^^^ F401 -137 | from torchvision.models import ResNet18_Weights, resnet18 -138 | from ultralytics import YOLO - | - = help: Remove unused import: `torchvision.transforms` - -Found 112 errors. -[*] 18 fixable with the `--fix` option (2 hidden fixes can be enabled with the `--unsafe-fixes` option). diff --git a/artifacts/evidence/accuracy/P1/static-risk-signals.json b/artifacts/evidence/accuracy/P1/static-risk-signals.json deleted file mode 100644 index afe84396..00000000 --- a/artifacts/evidence/accuracy/P1/static-risk-signals.json +++ /dev/null @@ -1,663 +0,0 @@ -{ - "counts": { - "fallback": 27, - "fixture": 94, - "heuristic": 1, - "mock": 31, - "not_configured": 24, - "placeholder": 39, - "todo": 2 - }, - "examples": { - "fallback": [ - { - "line": 1046, - "path": "backend/app/services/export_service.py", - "text": "def _filename(name: str | None, fallback: str, suffix: str) -> str:" - }, - { - "line": 1047, - "path": "backend/app/services/export_service.py", - "text": "raw_name = name or fallback" - }, - { - "line": 1050, - "path": "backend/app/services/export_service.py", - "text": "cleaned = fallback" - }, - { - "line": 29, - "path": "backend/app/services/mdk_bathymetry_acquisition_service.py", - "text": "No depth values are ever synthesized, no insecure TLS fallback exists and the" - }, - { - "line": 173, - "path": "backend/app/services/mdk_bathymetry_probe_service.py", - "text": "message=\"MDK WCS TLS certificate validation failed; insecure fallback is prohibited.\"," - }, - { - "line": 186, - "path": "backend/app/services/mdk_bathymetry_probe_service.py", - "text": "\"MDK WCS TLS certificate validation failed; insecure fallback is prohibited.\"" - }, - { - "line": 440, - "path": "backend/app/services/raster_operations_service.py", - "text": "# best effort fallback; keep computed dimensions." - }, - { - "line": 19, - "path": "backend/app/services/raster_service.py", - "text": "except Exception as exc: # pragma: no cover - exercised via API-level fallback tests" - }, - { - "line": 26, - "path": "backend/app/services/storage_service.py", - "text": "fallback = \"upload\"" - }, - { - "line": 28, - "path": "backend/app/services/storage_service.py", - "text": "return fallback" - }, - { - "line": 37, - "path": "backend/app/services/storage_service.py", - "text": "return cleaned or fallback" - }, - { - "line": 76, - "path": "frontend/src/hooks/useGeoAssistant.ts", - "text": "const fallback = result.default_model && result.items.some((model) => model.name === result.default_model)" - }, - { - "line": 79, - "path": "frontend/src/hooks/useGeoAssistant.ts", - "text": "setDefaultModel(fallback)" - }, - { - "line": 9, - "path": "frontend/src/lib/authError.ts", - "text": "export function formatAuthError(error: unknown, fallback: string): string {" - }, - { - "line": 10, - "path": "frontend/src/lib/authError.ts", - "text": "if (!(error instanceof Error)) return fallback" - }, - { - "line": 21, - "path": "frontend/src/lib/authError.ts", - "text": "return fallback" - }, - { - "line": 24, - "path": "frontend/src/lib/authError.ts", - "text": "return error.message || fallback" - }, - { - "line": 1, - "path": "frontend/src/lib/formatError.ts", - "text": "export function formatError(error: unknown, fallback: string): string {" - }, - { - "line": 6, - "path": "frontend/src/lib/formatError.ts", - "text": "return fallback" - }, - { - "line": 501, - "path": "scripts/provision_belgium_north_sea_scope.py", - "text": "def _max_admin_modification(payloads: dict[str, dict[str, Any]], fallback: str) -> str:" - }, - { - "line": 507, - "path": "scripts/provision_belgium_north_sea_scope.py", - "text": "value = max(values) if values else fallback" - }, - { - "line": 111, - "path": "scripts/refine_yolo_labels_with_sam.py", - "text": "parser.add_argument(\"--fallback-policy\", choices=(\"retain\", \"drop\"), default=\"retain\")" - }, - { - "line": 42, - "path": "scripts/run_accuracy_phase1_baseline.py", - "text": "\"fallback\": re.compile(r\"\\b(?:fallback|fall back)\\b\", re.IGNORECASE)," - }, - { - "line": 347, - "path": "scripts/run_accuracy_phase1_baseline.py", - "text": "\"mock/fixture/placeholder/fallback triage signals\"," - }, - { - "line": 52, - "path": "scripts/run_golden_qa_benchmark.py", - "text": "# Backwards-compatible fallback for older checkouts and local smoke scripts." - } - ], - "fixture": [ - { - "line": 3, - "path": "backend/app/providers/__init__.py", - "text": "from app.providers import base, fixture, grb, manual, osm, registry" - }, - { - "line": 5, - "path": "backend/app/providers/__init__.py", - "text": "__all__ = [\"base\", \"fixture\", \"grb\", \"manual\", \"osm\", \"registry\"]" - }, - { - "line": 9, - "path": "backend/app/providers/fixture.py", - "text": "provider_name=\"fixture\"," - }, - { - "line": 10, - "path": "backend/app/providers/fixture.py", - "text": "display_name=\"Fixture data\"," - }, - { - "line": 11, - "path": "backend/app/providers/fixture.py", - "text": "authority_level=\"fixture\"," - }, - { - "line": 14, - "path": "backend/app/providers/fixture.py", - "text": "supported_query_modes=[\"fixture\"]," - }, - { - "line": 15, - "path": "backend/app/providers/fixture.py", - "text": "fetch_signature=\"tests/fixtures and demo fixture upload flow\"," - }, - { - "line": 16, - "path": "backend/app/providers/fixture.py", - "text": "limitation_message=\"Fixture provider represents local test/demo fixtures only.\"," - }, - { - "line": 7, - "path": "backend/app/providers/registry.py", - "text": "from app.providers.fixture import FixtureProvider" - }, - { - "line": 37, - "path": "backend/app/providers/registry.py", - "text": "\"fixture\": FixtureProvider()," - }, - { - "line": 112, - "path": "backend/app/providers/registry.py", - "text": "provider_name=\"fixture\"," - }, - { - "line": 114, - "path": "backend/app/providers/registry.py", - "text": "message=\"Fixture provider data must use checked-in demo/test fixture flows.\"," - }, - { - "line": 122, - "path": "backend/app/services/demo_workflow_service.py", - "text": ".filter(Dataset.source_name == \"fixture\")" - }, - { - "line": 129, - "path": "backend/app/services/demo_workflow_service.py", - "text": ".filter(Dataset.source_name == \"fixture\")" - }, - { - "line": 148, - "path": "backend/app/services/demo_workflow_service.py", - "text": ".filter(Dataset.source_name == \"fixture\")" - }, - { - "line": 213, - "path": "backend/app/services/demo_workflow_service.py", - "text": "source=\"fixture\"," - }, - { - "line": 218, - "path": "backend/app/services/demo_workflow_service.py", - "text": "\"fixture\": True," - }, - { - "line": 298, - "path": "backend/app/services/demo_workflow_service.py", - "text": "source=\"fixture\"," - }, - { - "line": 300, - "path": "backend/app/services/demo_workflow_service.py", - "text": "source_name=\"fixture\"," - }, - { - "line": 303, - "path": "backend/app/services/demo_workflow_service.py", - "text": "\"fixture\": True," - }, - { - "line": 423, - "path": "backend/app/services/demo_workflow_service.py", - "text": ".filter(Dataset.source_name == \"fixture\")" - }, - { - "line": 430, - "path": "backend/app/services/demo_workflow_service.py", - "text": ".filter(Dataset.source_name == \"fixture\")" - }, - { - "line": 472, - "path": "backend/app/services/demo_workflow_service.py", - "text": "description=\"Offline fixture workflow: reference buildings, predicted buildings and persisted QA metrics.\"," - }, - { - "line": 497, - "path": "backend/app/services/demo_workflow_service.py", - "text": "source_name=\"fixture\"," - }, - { - "line": 509, - "path": "backend/app/services/demo_workflow_service.py", - "text": "source_name=\"fixture\"," - } - ], - "heuristic": [ - { - "line": 39, - "path": "scripts/run_accuracy_phase1_baseline.py", - "text": "\"heuristic\": re.compile(r\"\\bheuristic(?:s)?\\b\", re.IGNORECASE)," - } - ], - "mock": [ - { - "line": 7, - "path": "frontend/src/components/auth/LandingPage.test.tsx", - "text": "vi.mock('../../services/api/auth', () => ({" - }, - { - "line": 34, - "path": "frontend/src/components/auth/LandingPage.test.tsx", - "text": "vi.mocked(login).mockReset()" - }, - { - "line": 35, - "path": "frontend/src/components/auth/LandingPage.test.tsx", - "text": "vi.mocked(loginAsGuest).mockReset()" - }, - { - "line": 42, - "path": "frontend/src/components/auth/LandingPage.test.tsx", - "text": "vi.mocked(login).mockResolvedValue(operatorSession)" - }, - { - "line": 57, - "path": "frontend/src/components/auth/LandingPage.test.tsx", - "text": "vi.mocked(loginAsGuest).mockResolvedValue(guestSession)" - }, - { - "line": 75, - "path": "frontend/src/components/auth/LandingPage.test.tsx", - "text": "vi.mocked(login).mockRejectedValue(new Error('Gebruikersnaam of wachtwoord is onjuist.'))" - }, - { - "line": 8, - "path": "frontend/src/components/map/MunicipalitySearch.test.tsx", - "text": "vi.mock('../../services/api/areas', () => ({" - }, - { - "line": 14, - "path": "frontend/src/components/map/MunicipalitySearch.test.tsx", - "text": "vi.mocked(areasApi.searchMunicipalities).mockResolvedValue({" - }, - { - "line": 5, - "path": "frontend/src/hooks/useCoverageResolver.test.tsx", - "text": "const mocks = vi.hoisted(() => ({" - }, - { - "line": 9, - "path": "frontend/src/hooks/useCoverageResolver.test.tsx", - "text": "vi.mock('../services/api', () => ({" - }, - { - "line": 11, - "path": "frontend/src/hooks/useCoverageResolver.test.tsx", - "text": "resolveCoverage: mocks.resolveCoverage," - }, - { - "line": 35, - "path": "frontend/src/hooks/useCoverageResolver.test.tsx", - "text": "mocks.resolveCoverage.mockResolvedValue(coverageResult)" - }, - { - "line": 51, - "path": "frontend/src/hooks/useCoverageResolver.test.tsx", - "text": "expect(mocks.resolveCoverage).not.toHaveBeenCalled()" - }, - { - "line": 58, - "path": "frontend/src/hooks/useCoverageResolver.test.tsx", - "text": "expect(mocks.resolveCoverage).not.toHaveBeenCalled()" - }, - { - "line": 64, - "path": "frontend/src/hooks/useCoverageResolver.test.tsx", - "text": "expect(mocks.resolveCoverage).toHaveBeenCalledWith({" - }, - { - "line": 89, - "path": "frontend/src/hooks/useCoverageResolver.test.tsx", - "text": "mocks.resolveCoverage.mockRejectedValueOnce(new Error('provider unavailable'))" - }, - { - "line": 102, - "path": "frontend/src/hooks/useCoverageResolver.test.tsx", - "text": "mocks.resolveCoverage.mockImplementationOnce(" - }, - { - "line": 5, - "path": "frontend/src/hooks/useTemporalComparison.test.tsx", - "text": "const mocks = vi.hoisted(() => ({" - }, - { - "line": 9, - "path": "frontend/src/hooks/useTemporalComparison.test.tsx", - "text": "vi.mock('../services/api/temporal', () => ({" - }, - { - "line": 11, - "path": "frontend/src/hooks/useTemporalComparison.test.tsx", - "text": "compare: mocks.compare," - }, - { - "line": 34, - "path": "frontend/src/hooks/useTemporalComparison.test.tsx", - "text": "expect(mocks.compare).not.toHaveBeenCalled()" - }, - { - "line": 43, - "path": "frontend/src/hooks/useTemporalComparison.test.tsx", - "text": "expect(mocks.compare).not.toHaveBeenCalled()" - }, - { - "line": 53, - "path": "frontend/src/hooks/useTemporalComparison.test.tsx", - "text": "mocks.compare.mockResolvedValueOnce(comparison)" - }, - { - "line": 64, - "path": "frontend/src/hooks/useTemporalComparison.test.tsx", - "text": "expect(mocks.compare).toHaveBeenCalledWith('project-1', {" - }, - { - "line": 37, - "path": "scripts/run_accuracy_phase1_baseline.py", - "text": "\"mock\": re.compile(r\"\\bmock(?:ed|ing|s)?\\b\", re.IGNORECASE)," - } - ], - "not_configured": [ - { - "line": 166, - "path": "backend/app/api/routes/external.py", - "text": "status=response.get(\"status\", \"not_configured\")," - }, - { - "line": 149, - "path": "backend/app/api/routes/health.py", - "text": "yolo_status = configured_yolo.status if configured_yolo else \"not_configured\"" - }, - { - "line": 79, - "path": "backend/app/providers/base.py", - "text": "status=\"configured\" if self.is_configured else \"not_configured\"," - }, - { - "line": 94, - "path": "backend/app/providers/base.py", - "text": "\"status\": \"not_configured\"," - }, - { - "line": 96, - "path": "backend/app/providers/registry.py", - "text": "status=\"not_configured\"," - }, - { - "line": 9, - "path": "backend/app/schemas/coverage.py", - "text": "CoverageStatus = Literal[\"operational\", \"partial\", \"not_configured\", \"unsupported\"]" - }, - { - "line": 53, - "path": "backend/app/services/coverage_registry_service.py", - "text": "STATUS_ORDER = (\"unsupported\", \"not_configured\", \"partial\", \"operational\")" - }, - { - "line": 340, - "path": "backend/app/services/coverage_registry_service.py", - "text": "integration_status=\"not_configured\"," - }, - { - "line": 572, - "path": "backend/app/services/coverage_registry_service.py", - "text": "\"not_configured\"" - }, - { - "line": 266, - "path": "backend/app/services/geo_assistant_service.py", - "text": "status=\"not_configured\"," - }, - { - "line": 42, - "path": "backend/app/services/model_registry_service.py", - "text": "status=\"not_configured\"," - }, - { - "line": 98, - "path": "backend/app/services/model_registry_service.py", - "text": "status=\"not_configured\"," - }, - { - "line": 127, - "path": "backend/app/services/model_registry_service.py", - "text": "status = \"not_configured\"" - }, - { - "line": 169, - "path": "backend/app/services/model_registry_service.py", - "text": "status = \"not_configured\"" - }, - { - "line": 211, - "path": "backend/app/services/model_registry_service.py", - "text": "status = \"not_configured\"" - }, - { - "line": 36, - "path": "backend/app/services/yolo_preflight_service.py", - "text": "\"status\": \"not_configured\"," - }, - { - "line": 40, - "path": "frontend/src/components/detection/DetectionModelManagement.tsx", - "text": "if (value === 'not_configured') return 'niet geconfigureerd'" - }, - { - "line": 295, - "path": "frontend/src/components/map/MapWorkspace.tsx", - "text": "not_configured: 'Niet gekoppeld'," - }, - { - "line": 1050, - "path": "frontend/src/components/map/MapWorkspace.tsx", - "text": "{ operational: 0, partial: 0, not_configured: 0, unsupported: 0 }," - }, - { - "line": 1051, - "path": "frontend/src/components/map/MapWorkspace.tsx", - "text": ") ?? { operational: 0, partial: 0, not_configured: 0, unsupported: 0 }," - }, - { - "line": 3365, - "path": "frontend/src/components/map/MapWorkspace.tsx", - "text": "{coverageCounts.not_configured} niet gekoppeld" - }, - { - "line": 6, - "path": "frontend/src/components/models/modelOptions.ts", - "text": "const configured = model.configured && model.status !== 'not_configured'" - }, - { - "line": 1072, - "path": "frontend/src/types.ts", - "text": "export type CoverageStatus = 'operational' | 'partial' | 'not_configured' | 'unsupported'" - }, - { - "line": 40, - "path": "scripts/run_accuracy_phase1_baseline.py", - "text": "\"not_configured\": re.compile(r\"\\bnot_configured\\b\", re.IGNORECASE)," - } - ], - "placeholder": [ - { - "line": 36, - "path": "backend/app/services/model_registry_service.py", - "text": "model_id=\"yolo-placeholder\"," - }, - { - "line": 37, - "path": "backend/app/services/model_registry_service.py", - "text": "display_name=\"YOLO detector placeholder\"," - }, - { - "line": 92, - "path": "backend/app/services/model_registry_service.py", - "text": "model_id=\"segmentation-placeholder\"," - }, - { - "line": 93, - "path": "backend/app/services/model_registry_service.py", - "text": "display_name=\"Segmentation placeholder\"," - }, - { - "line": 94, - "path": "backend/app/services/model_registry_service.py", - "text": "framework=\"placeholder\"," - }, - { - "line": 99, - "path": "backend/app/services/model_registry_service.py", - "text": "limitation_message=\"Segmentation inference is not configured for this placeholder; no model is downloaded or executed.\"," - }, - { - "line": 187, - "path": "frontend/src/components/assistant/GeoAssistantPanel.tsx", - "text": "placeholder=\"Bijvoorbeeld: hoeveel bos verdween er sinds 2013?\"" - }, - { - "line": 246, - "path": "frontend/src/components/datasets/DatasetPanel.tsx", - "text": "placeholder=\"bijvoorbeeld eigen luchtbeeld\"" - }, - { - "line": 306, - "path": "frontend/src/components/datasets/DatasetPanel.tsx", - "text": "placeholder=\"Naam, bron, gemeente of type\"" - }, - { - "line": 276, - "path": "frontend/src/components/datasets/RasterControls.tsx", - "text": "placeholder=\"EPSG:31370\"" - }, - { - "line": 345, - "path": "frontend/src/components/datasets/RasterControls.tsx", - "text": "placeholder=\"optioneel\"" - }, - { - "line": 44, - "path": "frontend/src/components/detection/DetectionLab.tsx", - "text": "if (modelName === 'yolo-placeholder') return 'Niet-geconfigureerd gebouwmodel'" - }, - { - "line": 516, - "path": "frontend/src/components/detection/DetectionLab.tsx", - "text": "placeholder=\"Pad naar de aangemaakte beeldtegels\"" - }, - { - "line": 583, - "path": "frontend/src/components/detection/DetectionLab.tsx", - "text": "placeholder=\"0.50 0.25 0.15\"" - }, - { - "line": 715, - "path": "frontend/src/components/detection/DetectionLab.tsx", - "text": "placeholder=\"bijvoorbeeld gebouw\"" - }, - { - "line": 28, - "path": "frontend/src/components/detection/DetectionModelManagement.tsx", - "text": "if (model.model_id === 'yolo-placeholder') return 'Gebouwmodel nog niet geconfigureerd'" - }, - { - "line": 402, - "path": "frontend/src/components/exports/ExportCenter.tsx", - "text": "placeholder=\"Type, id of pad\"" - }, - { - "line": 2312, - "path": "frontend/src/components/map/MapWorkspace.tsx", - "text": "placeholder=\"Zoek thema’s\"" - }, - { - "line": 82, - "path": "frontend/src/components/map/MunicipalitySearch.tsx", - "text": "placeholder=\"Gemeentenaam of NIS-code\"" - }, - { - "line": 98, - "path": "frontend/src/components/project/AreaPanel.tsx", - "text": "placeholder=\"Naam van het gebied\"" - }, - { - "line": 106, - "path": "frontend/src/components/project/AreaPanel.tsx", - "text": "placeholder=\"EPSG:4326\"" - }, - { - "line": 142, - "path": "frontend/src/components/project/AreaPanel.tsx", - "text": "placeholder=\"Bijvoorbeeld Brussel, Namen of Noordzee\"" - }, - { - "line": 119, - "path": "frontend/src/components/project/ProjectPanel.tsx", - "text": "placeholder=\"Naam van de werkruimte\"" - }, - { - "line": 127, - "path": "frontend/src/components/project/ProjectPanel.tsx", - "text": "placeholder=\"Korte beschrijving\"" - }, - { - "line": 135, - "path": "frontend/src/components/project/ProjectPanel.tsx", - "text": "placeholder=\"Regio\"" - } - ], - "todo": [ - { - "line": 23, - "path": "scripts/codex_pass_end_check.sh", - "text": "\"TODO: implement later\\|placeholder only\\|fake completed\" \\" - }, - { - "line": 6, - "path": "scripts/contract_drift_grep.sh", - "text": "if grep -R \"TODO: decide\\|TBD\\|placeholder only\\|fake real\" -n docs contracts backend frontend prompts 2>/dev/null; then" - } - ] - }, - "interpretation": "Triage signals only; production impact requires a traced contract/runtime path." -} diff --git a/artifacts/evidence/accuracy/P1/tower-gpu-inference-smoke.json b/artifacts/evidence/accuracy/P1/tower-gpu-inference-smoke.json deleted file mode 100644 index 396035ce..00000000 --- a/artifacts/evidence/accuracy/P1/tower-gpu-inference-smoke.json +++ /dev/null @@ -1,215 +0,0 @@ -{ - "captured_at": "2026-08-01T18:13:54.6553+02:00", - "claim_boundary": "One production-adapter inference completed on one existing tile. No accuracy, calibration, geographic-generalization, or release claim follows from this smoke.", - "configuration": { - "confidence": 0.5, - "deterministic_algorithms": true, - "device": "cuda:0", - "image_size": 640, - "max_detections": 1000, - "seed": 20260801 - }, - "input": { - "manifest_path": "/app/storage/tiles/cb80638d-dbef-48ac-b19c-cec7c3efc96e/ae0ff76d-70c0-404f-b777-54d14517179a/b191c968-7d56-4e0d-afbb-8b5baaa62470/manifest.json", - "manifest_sha256": "6ab8a96bf2a1405e224932afb90255311a09bbeaed4e9a2fdcdf8b1bc2230abd", - "raster": { - "available": true, - "bounds": [ - 193277.53584918313, - 205708.27443503588, - 193777.53584918313, - 206208.27443503588 - ], - "count": 3, - "crs": "EPSG:31370", - "dtypes": [ - "uint8", - "uint8", - "uint8" - ], - "height": 512, - "nodata": null, - "transform": [ - 0.9765625, - 0.0, - 193277.53584918313, - 0.0, - -0.9765625, - 206208.27443503588, - 0.0, - 0.0, - 1.0 - ], - "width": 512 - }, - "tile_path": "/app/storage/tiles/cb80638d-dbef-48ac-b19c-cec7c3efc96e/ae0ff76d-70c0-404f-b777-54d14517179a/b191c968-7d56-4e0d-afbb-8b5baaa62470/tile_0000.tif", - "tile_sha256": "134a9e86850c92c577c73bc6ee57a9df7d4c1c513ae6450263e800b6dd47b6ee", - "tile_size_bytes": 669227 - }, - "model": { - "path": "/app/models/geointel-building-yolov8s-smallbld-minpx3-img640-ft30.pt", - "sha256": "a9088b8491dfae36694b53e9e9406cb4e3511d334a5712fa34f75078a47759c1", - "size_bytes": 22516074 - }, - "output": { - "class_counts": { - "building": 17 - }, - "confidence": { - "maximum": 0.8144345879554749, - "mean": 0.5594814244438621, - "minimum": 0.5008771419525146 - }, - "count": 17, - "sample": [ - { - "bbox": [ - 125.5418930053711, - 157.9995880126953, - 187.2771453857422, - 232.72903442382812 - ], - "class_name": "building", - "confidence": 0.8144345879554749, - "properties": { - "class_id": 0 - } - }, - { - "bbox": [ - 38.20725631713867, - 487.8446350097656, - 56.458614349365234, - 510.8298034667969 - ], - "class_name": "building", - "confidence": 0.6531882286071777, - "properties": { - "class_id": 0 - } - }, - { - "bbox": [ - 177.36990356445312, - 229.9929656982422, - 248.5861053466797, - 267.96173095703125 - ], - "class_name": "building", - "confidence": 0.6213690638542175, - "properties": { - "class_id": 0 - } - }, - { - "bbox": [ - 367.4935607910156, - 474.3263244628906, - 407.673828125, - 498.2358093261719 - ], - "class_name": "building", - "confidence": 0.6148342490196228, - "properties": { - "class_id": 0 - } - }, - { - "bbox": [ - 435.2783203125, - 131.2145233154297, - 453.61016845703125, - 166.76919555664062 - ], - "class_name": "building", - "confidence": 0.5637134313583374, - "properties": { - "class_id": 0 - } - }, - { - "bbox": [ - 407.32525634765625, - 317.380126953125, - 416.885009765625, - 326.8919982910156 - ], - "class_name": "building", - "confidence": 0.547556459903717, - "properties": { - "class_id": 0 - } - }, - { - "bbox": [ - 395.66558837890625, - 356.8952331542969, - 413.51416015625, - 377.1672668457031 - ], - "class_name": "building", - "confidence": 0.5378748774528503, - "properties": { - "class_id": 0 - } - }, - { - "bbox": [ - 394.0309143066406, - 143.1604461669922, - 408.4023132324219, - 167.8805389404297 - ], - "class_name": "building", - "confidence": 0.5360639095306396, - "properties": { - "class_id": 0 - } - }, - { - "bbox": [ - 125.3250503540039, - 56.1500358581543, - 157.87998962402344, - 68.70291900634766 - ], - "class_name": "building", - "confidence": 0.5342658162117004, - "properties": { - "class_id": 0 - } - }, - { - "bbox": [ - 213.7998504638672, - 77.86518859863281, - 230.8061065673828, - 90.1888198852539 - ], - "class_name": "building", - "confidence": 0.5319290161132812, - "properties": { - "class_id": 0 - } - } - ] - }, - "read_only": true, - "runtime": { - "cuda_available": true, - "cuda_device_index": 0, - "cuda_device_name": "NVIDIA GeForce RTX 4080 SUPER", - "cuda_peak_memory_bytes": 82307072, - "cuda_runtime": "12.8", - "python": "3.11.2 (main, May 12 2026, 05:17:27) [GCC 12.2.0]", - "torch": "2.11.0+cu128", - "ultralytics": "8.4.99" - }, - "schema_version": 1, - "status": "passed", - "timing_seconds": { - 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The fixture database name begins with geointel_phase2_ and is not a production database." - }, - { - "path": "artifacts/evidence/accuracy/P2/source-contract-inventory.json", - "sha256": "c7445ab984407d3a835532182767cf87e5e26fd79b3ecba123aef54ee3cdc733", - "meaning": "Static registry and contract inventory: 40 server-owned source definitions and the active versioned vector, raster, label and model contracts." - } - ], - "verification": [ - { - "command": "python scripts\\verify_phase2_postgres_guards.py --database-url --output artifacts\\evidence\\accuracy\\P2\\postgres-migration-guards.json", - "result": "passed", - "coverage": [ - "upgrade to 202608010001 and downgrade to base", - "source/snapshot pairing and source/snapshot immutability", - "passed contract reports and exact Dataset/DatasetVersion checksum-to-snapshot binding", - "accepted artifact, provenance and temporal-evidence immutability", - "lineage-cycle rejection and insert-only lineage edges", - "version quarantine, shared-snapshot fan-out and transitive A-to-B-to-C lineage quarantine" - ] - }, - { - "command": "python scripts\\run_accuracy_phase2_foundation_audit.py --output artifacts\\evidence\\accuracy\\P2\\source-contract-inventory.json", - "result": "passed", - "coverage": [ - "40 source definitions", - "source classifications and task policy", - "GRB primary building-validation policy", - "separate Buildings Register, DHMV, Sentinel-2 and OSM roles", - "versioned contract fingerprints" - ] - }, - { - "command": "python -m pytest tests/test_accuracy_phase2_foundation_audit.py tests/test_accuracy_phase2_source_registry.py tests/test_data_contract_validation.py tests/test_dataset_consumption_gate.py tests/test_governed_dataset_ingest.py tests/test_phase2_derived_dataset_governance.py tests/test_runtime_model_provenance_service.py tests/test_training_dataset_eligibility.py tests/test_training_release_manifest.py tests/test_rc4_national_coverage.py tests/test_run_state_consistency.py tests/test_sprint196_map_orthophoto_analysis.py tests/test_sprint205_dhmv_terrain.py tests/test_sprint233_operational_completion.py tests/test_sprint12_golden_qa_benchmark.py tests/test_vector_operations_service.py tests/test_geojson_dataset_service.py tests/test_model_asset_catalog.py tests/test_segmentation_configured_models.py tests/test_sprint8_detection_foundation.py tests/test_sprint8b_yolo_foundation.py tests/test_qa_service.py -q -p no:cacheprovider", - "result": "221 passed", - "coverage": [ - "contract validation", - "source registry, governed ingest and immutable snapshot replay", - "consumption gates and quarantine", - "canonical EPSG:4326 vector storage, checksum tamper rejection and derived governance", - "database-bound runtime model provenance before adapter loading", - "training release and protected-data eligibility" - ] - }, - { - "command": "python -m pytest tests -q -p no:cacheprovider", - "result": "34 passed", - "coverage": [ - "proposal-classifier crop provenance and trainer release binding" - ] - }, - { - "command": "npm run typecheck && npm run test:unit && npm run build", - "result": "passed; 51 frontend unit tests", - "coverage": [ - "TypeScript", - "frontend unit tests", - "Vite production build" - ] - } - ], - "non_green_global_gates": [ - { - "command": "python -m pytest -q -p no:cacheprovider", - "result": "1282 passed, 17 failed", - "reason": "The former backend-CI collection error is fixed. Sixteen remaining failures are historical source-text assertions for user-modified UI/deployment/README behavior; one additional Windows run could not spawn the WSL-backed bash.exe for the shell-wrapper syntax test, although that test passes in isolation. They remain visible and block a claim that the complete repository suite is green." - }, - { - "command": "python -m ruff check backend scripts tests --output-format concise", - "result": "95 existing findings", - "reason": "The P2-changed Python paths were linted clean separately; repository-wide Ruff remediation is an outstanding P2-01 gate." - }, - { - "command": "npm run lint", - "result": "failed: script is absent", - "reason": "Frontend lint configuration remains an outstanding P2-01 gate." - } - ], - "remaining_limits": [ - "No production database migration or deployment was performed in this phase; the live migration evidence is disposable only.", - "Legacy Tower datasets and model runs remain incomplete until a new governed ingest/release supplies original evidence.", - "Physical quarantine storage and protected-test credential isolation are not yet proven.", - "End-to-end UI provenance rendering is a required target contract, not yet retained as full browser/API evidence.", - "Human label review, independent AOIs, pure-background/difficult negatives, temporal/dense-label remediation, corpus rebuild, CUDA candidate training, protected testing and promotion remain blocked." - ], - "phase_decision": { - "phase2_status": "in_progress", - "phase3_status": "not_ready", - "training_allowed_now": false, - "promotion_allowed": false - } -} diff --git a/artifacts/evidence/accuracy/P2/postgres-migration-guards.json b/artifacts/evidence/accuracy/P2/postgres-migration-guards.json deleted file mode 100644 index 3ec3ac4c..00000000 --- a/artifacts/evidence/accuracy/P2/postgres-migration-guards.json +++ /dev/null @@ -1,46 +0,0 @@ -{ - "completed_at": "2026-08-01T21:40:13.288545+00:00", - "database_name": "geointel_phase2_guard_test", - "downgrade_output_tail": [ - "DROP TABLE areas", - "INFO [sqlalchemy.engine.Engine] [no key 0.00014s] {}", - "INFO [sqlalchemy.engine.Engine] ", - "DROP TABLE projects", - "INFO [sqlalchemy.engine.Engine] [no key 0.00014s] {}", - "INFO [sqlalchemy.engine.Engine] DELETE FROM alembic_version WHERE alembic_version.version_num = '202601110001'", - "INFO [sqlalchemy.engine.Engine] [generated in 0.00018s] {}", - "INFO [sqlalchemy.engine.Engine] COMMIT" - ], - "guards": { - "accepted_artifact_and_temporal_evidence_immutable": "passed", - "accepted_contract_evidence_immutable": "passed", - "accepted_dataset_version_contract_evidence_immutable": "passed", - "lineage_cycle": "passed", - "lineage_edge_immutable": "passed", - "passed_contract_report_required": "passed", - "passed_dataset_checksum_required_and_snapshot_bound": "passed", - "passed_dataset_version_checksum_required_and_snapshot_bound": "passed", - "snapshot_evidence_immutable": "passed", - "snapshot_quarantine_fanout": "passed", - "snapshot_registry_immutable": "passed", - "snapshot_registry_pairing": "passed", - "source_registry_immutable": "passed", - "transitive_lineage_quarantine": "passed", - "version_quarantine_propagation": "passed" - }, - "migration_revision": "202608010001", - "phase": "P2", - "result": "passed", - "schema_version": 1, - "started_at": "2026-08-01T21:40:07.178237+00:00", - "upgrade_output_tail": [ - " CREATE TRIGGER trg_dataset_quarantines_state_guard", - " AFTER INSERT OR UPDATE OF status, dataset_id, dataset_version_id, source_snapshot_id ON dataset_quarantines", - " FOR EACH ROW EXECUTE FUNCTION geointel_phase2_quarantine_state_guard();", - " ", - "INFO [sqlalchemy.engine.Engine] [generated in 0.00053s] {}", - "INFO [sqlalchemy.engine.Engine] UPDATE alembic_version SET version_num='202608010001' WHERE alembic_version.version_num = '202607260001'", - "INFO [sqlalchemy.engine.Engine] [generated in 0.00021s] {}", - "INFO [sqlalchemy.engine.Engine] COMMIT" - ] -} diff --git a/artifacts/evidence/accuracy/P2/source-contract-inventory.json b/artifacts/evidence/accuracy/P2/source-contract-inventory.json deleted file mode 100644 index 6df650f7..00000000 --- a/artifacts/evidence/accuracy/P2/source-contract-inventory.json +++ /dev/null @@ -1,757 +0,0 @@ -{ - "claim_boundary": "Static policy/contract inventory only. It does not attest that a database migration ran, that legacy rows are complete, or that a model/corpus is release-ready.", - "collected_at": "2026-08-01T21:40:49.817334+00:00", - "data_contracts": [ - { - "accepted_source_crs": [], - "canonical_storage_crs": null, - "fingerprint_sha256": "908ce483237cc83b35844c3dd21c6f774d10b4241f78f71f8d86a016dd1e9332", - "key": "geointel.label.yolo", - "kind": "label", - "required_metadata_fields": [ - "image_checksum_sha256", - "class_ontology_version", - "tile_manifest_sha256" - ], - "requires_source_registry": true, - "requires_source_snapshot": true, - "requires_upstream_assets": true, - "version": "1.0.0" - }, - { - "accepted_source_crs": [], - "canonical_storage_crs": null, - "fingerprint_sha256": "8eff1113520cca04fad8a919bfadc85d6f1e30e5fd41fcc1ed70e7eb5bd41c07", - "key": "geointel.label.yolo", - "kind": "label", - "required_metadata_fields": [ - "image_checksum_sha256", - "class_ontology_version", - "source_corpus_manifest_sha256", - "label_mode" - ], - "requires_source_registry": true, - "requires_source_snapshot": true, - "requires_upstream_assets": true, - "version": "1.1.0" - }, - { - "accepted_source_crs": [], - "canonical_storage_crs": null, - "fingerprint_sha256": "fa2531c3b34c9ad7e473cb10071a32743a6349cd9dde9345ac2d44e38159b457", - "key": "geointel.model.pytorch", - "kind": "model", - "required_metadata_fields": [ - "training_manifest_sha256", - "runtime_manifest_sha256" - ], - "requires_source_registry": true, - "requires_source_snapshot": true, - "requires_upstream_assets": true, - "version": "1.0.0" - }, - { - "accepted_source_crs": [ - "EPSG:31370", - "EPSG:3812", - "EPSG:4326" - ], - "canonical_storage_crs": null, - "fingerprint_sha256": "51e19aa7b26c555319f26623dbfc837786ce47260025c7af9b878e40ad65478e", - "key": "geointel.raster.geotiff", - "kind": "raster", - "required_metadata_fields": [ - "license" - ], - "requires_source_registry": true, - "requires_source_snapshot": true, - "requires_upstream_assets": false, - "version": "1.0.0" - }, - { - "accepted_source_crs": [ - "EPSG:31370", - "EPSG:3812", - "EPSG:4326" - ], - "canonical_storage_crs": "EPSG:4326", - "fingerprint_sha256": "d6594faa7bea62ae61a41d7e1e254a9c3b7f7693430e90dcc3995b16ff3704fd", - "key": "geointel.vector.geojson", - "kind": "vector", - "required_metadata_fields": [ - "license" - ], - "requires_source_registry": true, - "requires_source_snapshot": true, - "requires_upstream_assets": false, - "version": "1.0.0" - } - ], - "migration_revision": "202608010001", - "phase": "P2", - "program": "GeoIntel Accuracy Improvement Program", - "repository": { - "branch": "codex/geointel-accuracy-program", - "dirty": true, - "head": "cebeb5f3b4f836274c0504c2cc5fc2a019a8ea8b" - }, - "schema_version": 1, - "scope": "Belgium and the Belgian North Sea", - "source_registry": { - "classification_counts": { - "authoritative": 25, - "contextual": 5, - "corroborative": 2, - "derived": 3, - "experimental": 5 - }, - "definition_count": 40, - "definitions": [ - { - "authority_name": "Agentschap Landbouw en Zeevisserij", - "authority_scope": { - "theme": "agricultural_parcels", - "zone": "Flanders" - }, - "classification": "authoritative", - "default_crs": "EPSG:31370", - "default_units": "metres", - "freshness_status": "unknown", - "ground_truth_allowed": false, - "ingest_status": "registered", - "provider_adapter_key": null, - "source_key": "agentschap_landbouw_zeevisserij_agricultural_parcels", - "training_allowed": false - }, - { - "authority_name": "Departement Omgeving", - "authority_scope": { - "theme": "land_use", - "zone": "Flanders" - }, - "classification": "authoritative", - "default_crs": "EPSG:31370", - "default_units": "metres", - "freshness_status": "unknown", - "ground_truth_allowed": false, - "ingest_status": "registered", - "provider_adapter_key": null, - "source_key": "department_omgeving_land_use", - "training_allowed": false - }, - { - "authority_name": "Departement Omgeving", - "authority_scope": { - "theme": "thematic_raster", - "zone": "Flanders" - }, - "classification": "authoritative", - "default_crs": "EPSG:31370", - "default_units": "source_specific", - "freshness_status": "unknown", - "ground_truth_allowed": false, - "ingest_status": "registered", - "provider_adapter_key": null, - "source_key": "department_omgeving_thematic_raster", - "training_allowed": false - }, - { - "authority_name": "GeoIntel derived operation", - "authority_scope": { - "scope": "derived_from_registered_input" - }, - "classification": "derived", - "default_crs": "unknown", - "default_units": "unknown", - "freshness_status": "unknown", - "ground_truth_allowed": false, - "ingest_status": "registered", - "provider_adapter_key": null, - "source_key": "derived", - "training_allowed": false - }, - { - "authority_name": "Digitaal Vlaanderen", - "authority_scope": { - "role": "umbrella_catalogue_and_adapter_authority", - "zone": "Flanders" - }, - "classification": "authoritative", - "default_crs": "product_specific", - "default_units": "product_specific", - "freshness_status": "unknown", - "ground_truth_allowed": false, - "ingest_status": "configured", - "provider_adapter_key": "digitaal_vlaanderen", - "source_key": "digitaal_vlaanderen", - "training_allowed": false - }, - { - "authority_name": "Digitaal Vlaanderen", - "authority_scope": { - "theme": "buildings_addresses", - "zone": "Flanders" - }, - "classification": "authoritative", - "default_crs": "EPSG:31370", - "default_units": "metres", - "freshness_status": "unknown", - "ground_truth_allowed": false, - "ingest_status": "registered", - "provider_adapter_key": "buildings_addresses_register", - "source_key": "digitaal_vlaanderen_buildings_addresses_register", - "training_allowed": false - }, - { - "authority_name": "Digitaal Vlaanderen", - "authority_scope": { - "role": "terrain_height_corroboration", - "zone": "Flanders" - }, - "classification": "authoritative", - "default_crs": "EPSG:31370", - "default_units": "m TAW", - "freshness_status": "unknown", - "ground_truth_allowed": false, - "ingest_status": "configured", - "provider_adapter_key": "dhmv", - "source_key": "digitaal_vlaanderen_dhmv", - "training_allowed": true - }, - { - "authority_name": "Digitaal Vlaanderen", - "authority_scope": { - "role": "imagery", - "zone": "Flanders" - }, - "classification": "contextual", - "default_crs": "EPSG:31370", - "default_units": "pixel", - "freshness_status": "unknown", - "ground_truth_allowed": false, - "ingest_status": "configured", - "provider_adapter_key": null, - "source_key": "digitaal_vlaanderen_orthophoto", - "training_allowed": true - }, - { - "authority_name": "Databank Ondergrond Vlaanderen", - "authority_scope": { - "theme": "soil", - "zone": "Flanders" - }, - "classification": "authoritative", - "default_crs": "EPSG:31370", - "default_units": "metres", - "freshness_status": "unknown", - "ground_truth_allowed": false, - "ingest_status": "registered", - "provider_adapter_key": null, - "source_key": "dov_soil_map", - "training_allowed": false - }, - { - "authority_name": "Unverified", - "authority_scope": { - "scope": "unverified" - }, - "classification": "experimental", - "default_crs": "unknown", - "default_units": "unknown", - "freshness_status": "unknown", - "ground_truth_allowed": false, - "ingest_status": "registered", - "provider_adapter_key": null, - "source_key": "experimental", - "training_allowed": false - }, - { - "authority_name": "GeoIntel test fixture", - "authority_scope": { - "scope": "test_only" - }, - "classification": "experimental", - "default_crs": "fixture_specific", - "default_units": "fixture_specific", - "freshness_status": "unknown", - "ground_truth_allowed": false, - "ingest_status": "configured", - "provider_adapter_key": null, - "source_key": "fixture", - "training_allowed": false - }, - { - "authority_name": "Digitaal Vlaanderen", - "authority_scope": { - "themes": [ - "buildings", - "roads", - "water", - "parcels" - ], - "zone": "Flanders" - }, - "classification": "authoritative", - "default_crs": "EPSG:31370", - "default_units": "metres", - "freshness_status": "unknown", - "ground_truth_allowed": true, - "ingest_status": "configured", - "provider_adapter_key": "grb", - "source_key": "grb", - "training_allowed": true - }, - { - "authority_name": "Historical archive provider", - "authority_scope": { - "scope": "Belgium", - "theme": "historical_land_use" - }, - "classification": "corroborative", - "default_crs": "source_specific", - "default_units": "source_specific", - "freshness_status": "unknown", - "ground_truth_allowed": false, - "ingest_status": "registered", - "provider_adapter_key": null, - "source_key": "historical_landuse", - "training_allowed": false - }, - { - "authority_name": "INBO", - "authority_scope": { - "theme": "nature", - "zone": "Flanders" - }, - "classification": "authoritative", - "default_crs": "EPSG:31370", - "default_units": "metres", - "freshness_status": "unknown", - "ground_truth_allowed": false, - "ingest_status": "registered", - "provider_adapter_key": null, - "source_key": "inbo_bwk_natura2000", - "training_allowed": false - }, - { - "authority_name": "Legacy import \u2014 unverified", - "authority_scope": { - "scope": "legacy", - "trust": "unverified" - }, - "classification": "experimental", - "default_crs": "unknown", - "default_units": "unknown", - "freshness_status": "unknown", - "ground_truth_allowed": false, - "ingest_status": "legacy_unverified", - "provider_adapter_key": null, - "source_key": "legacy_unknown", - "training_allowed": false - }, - { - "authority_name": "Operator supplied", - "authority_scope": { - "scope": "operator_supplied", - "trust": "unverified" - }, - "classification": "experimental", - "default_crs": "unknown", - "default_units": "unknown", - "freshness_status": "unknown", - "ground_truth_allowed": false, - "ingest_status": "configured", - "provider_adapter_key": null, - "source_key": "manual", - "training_allowed": false - }, - { - "authority_name": "GeoIntel derived operation", - "authority_scope": { - "scope": "derived_from_registered_input" - }, - "classification": "derived", - "default_crs": "EPSG:4326", - "default_units": "source_dependent", - "freshness_status": "unknown", - "ground_truth_allowed": false, - "ingest_status": "registered", - "provider_adapter_key": null, - "source_key": "map_selection", - "training_allowed": false - }, - { - "authority_name": "Maritieme Dienstverlening en Kust", - "authority_scope": { - "theme": "bathymetry", - "zone": "Belgian North Sea" - }, - "classification": "authoritative", - "default_crs": "EPSG:3812", - "default_units": "metres", - "freshness_status": "unknown", - "ground_truth_allowed": false, - "ingest_status": "registered", - "provider_adapter_key": null, - "source_key": "mdk_bathymetry", - "training_allowed": false - }, - { - "authority_name": "Maritieme Dienstverlening en Kust", - "authority_scope": { - "role": "coverage_probe_and_governed_acquisition", - "theme": "bathymetry", - "zone": "Belgian North Sea" - }, - "classification": "authoritative", - "default_crs": "EPSG:3812", - "default_units": "metres", - "freshness_status": "unknown", - "ground_truth_allowed": false, - "ingest_status": "not_configured", - "provider_adapter_key": "mdk_bcp_bathymetry", - "source_key": "mdk_bcp_bathymetry", - "training_allowed": false - }, - { - "authority_name": "GeoIntel model pipeline", - "authority_scope": { - "scope": "internal_model_artifact" - }, - "classification": "experimental", - "default_crs": "unknown", - "default_units": "unknown", - "freshness_status": "unknown", - "ground_truth_allowed": false, - "ingest_status": "registered", - "provider_adapter_key": null, - "source_key": "model", - "training_allowed": false - }, - { - "authority_name": "Nationaal Geografisch Instituut", - "authority_scope": { - "scope": "Belgium" - }, - "classification": "authoritative", - "default_crs": "EPSG:31370", - "default_units": "metres", - "freshness_status": "unknown", - "ground_truth_allowed": false, - "ingest_status": "registered", - "provider_adapter_key": null, - "source_key": "ngi_adminvector", - "training_allowed": false - }, - { - "authority_name": "OpenStreetMap contributors", - "authority_scope": { - "role": "contextual", - "scope": "community-maintained" - }, - "classification": "contextual", - "default_crs": "EPSG:4326", - "default_units": "mixed", - "freshness_status": "unknown", - "ground_truth_allowed": false, - "ingest_status": "not_configured", - "provider_adapter_key": "osm", - "source_key": "osm", - "training_allowed": false - }, - { - "authority_name": "RBINS", - "authority_scope": { - "zone": "Belgian North Sea" - }, - "classification": "authoritative", - "default_crs": "EPSG:4326", - "default_units": "degrees", - "freshness_status": "unknown", - "ground_truth_allowed": false, - "ingest_status": "registered", - "provider_adapter_key": null, - "source_key": "rbins_marine_reporting_units", - "training_allowed": false - }, - { - "authority_name": "RBINS", - "authority_scope": { - "edition": "2026-2034", - "zone": "Belgian North Sea" - }, - "classification": "authoritative", - "default_crs": "EPSG:4326", - "default_units": "degrees", - "freshness_status": "unknown", - "ground_truth_allowed": false, - "ingest_status": "registered", - "provider_adapter_key": null, - "source_key": "rbins_msp_2026", - "training_allowed": false - }, - { - "authority_name": "Copernicus Programme", - "authority_scope": { - "role": "multispectral_context", - "scope": "Belgium and Belgian North Sea" - }, - "classification": "contextual", - "default_crs": "product_specific", - "default_units": "reflectance", - "freshness_status": "unknown", - "ground_truth_allowed": false, - "ingest_status": "not_configured", - "provider_adapter_key": "sentinel_2", - "source_key": "sentinel_2", - "training_allowed": true - }, - { - "authority_name": "Service public de Wallonie", - "authority_scope": { - "theme": "bathymetry", - "zone": "Wallonia" - }, - "classification": "authoritative", - "default_crs": "EPSG:3812", - "default_units": "mDNG", - "freshness_status": "unknown", - "ground_truth_allowed": false, - "ingest_status": "registered", - "provider_adapter_key": null, - "source_key": "spw_bathymetry", - "training_allowed": false - }, - { - "authority_name": "Service public de Wallonie", - "authority_scope": { - "theme": "flood_hazard", - "zone": "Wallonia" - }, - "classification": "authoritative", - "default_crs": "EPSG:3812", - "default_units": "metres", - "freshness_status": "unknown", - "ground_truth_allowed": false, - "ingest_status": "registered", - "provider_adapter_key": null, - "source_key": "spw_flood_hazard", - "training_allowed": false - }, - { - "authority_name": "Service public de Wallonie", - "authority_scope": { - "role": "umbrella_catalogue_and_adapter_authority", - "zone": "Wallonia" - }, - "classification": "authoritative", - "default_crs": "product_specific", - "default_units": "product_specific", - "freshness_status": "unknown", - "ground_truth_allowed": false, - "ingest_status": "configured", - "provider_adapter_key": "spw_geoportail", - "source_key": "spw_geoportail", - "training_allowed": false - }, - { - "authority_name": "Service public de Wallonie", - "authority_scope": { - "role": "imagery", - "zone": "Wallonia" - }, - "classification": "contextual", - "default_crs": "EPSG:31370", - "default_units": "pixel", - "freshness_status": "unknown", - "ground_truth_allowed": false, - "ingest_status": "configured", - "provider_adapter_key": null, - "source_key": "spw_orthophoto", - "training_allowed": true - }, - { - "authority_name": "Service public de Wallonie", - "authority_scope": { - "theme": "topography_buildings", - "zone": "Wallonia" - }, - "classification": "authoritative", - "default_crs": "EPSG:31370", - "default_units": "metres", - "freshness_status": "unknown", - "ground_truth_allowed": true, - "ingest_status": "registered", - "provider_adapter_key": null, - "source_key": "spw_picc", - "training_allowed": true - }, - { - "authority_name": "Service public de Wallonie", - "authority_scope": { - "theme": "terrain", - "zone": "Wallonia" - }, - "classification": "corroborative", - 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"path": "storage/tiles/277180a4-cd74-42ed-a231-0d194b3fca9f/0f96a4f7-6b24-4969-9564-abbde30b5a51/9199f079-42fc-48cc-86ff-d1072f801932/tile_0001.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "6cf9933a9b0c3d8c9923", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\277180a4-cd74-42ed-a231-0d194b3fca9f\\0f96a4f7-6b24-4969-9564-abbde30b5a51\\9199f079-42fc-48cc-86ff-d1072f801932\\tile_0002.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/277180a4-cd74-42ed-a231-0d194b3fca9f/0f96a4f7-6b24-4969-9564-abbde30b5a51/9199f079-42fc-48cc-86ff-d1072f801932/tile_0002.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "c51dff8856043721992e", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\277180a4-cd74-42ed-a231-0d194b3fca9f\\0f96a4f7-6b24-4969-9564-abbde30b5a51\\9199f079-42fc-48cc-86ff-d1072f801932\\tile_0003.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/277180a4-cd74-42ed-a231-0d194b3fca9f/0f96a4f7-6b24-4969-9564-abbde30b5a51/9199f079-42fc-48cc-86ff-d1072f801932/tile_0003.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "a1e7317f6a0c2dfb7235", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\277180a4-cd74-42ed-a231-0d194b3fca9f\\0f96a4f7-6b24-4969-9564-abbde30b5a51\\9199f079-42fc-48cc-86ff-d1072f801932\\tile_0004.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/277180a4-cd74-42ed-a231-0d194b3fca9f/0f96a4f7-6b24-4969-9564-abbde30b5a51/9199f079-42fc-48cc-86ff-d1072f801932/tile_0004.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "5069a8562d88d6913bfd", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\277180a4-cd74-42ed-a231-0d194b3fca9f\\0f96a4f7-6b24-4969-9564-abbde30b5a51\\9199f079-42fc-48cc-86ff-d1072f801932\\tile_0005.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/277180a4-cd74-42ed-a231-0d194b3fca9f/0f96a4f7-6b24-4969-9564-abbde30b5a51/9199f079-42fc-48cc-86ff-d1072f801932/tile_0005.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "2200c4a8006caa7fd98a", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\277180a4-cd74-42ed-a231-0d194b3fca9f\\0f96a4f7-6b24-4969-9564-abbde30b5a51\\9199f079-42fc-48cc-86ff-d1072f801932\\tile_0006.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/277180a4-cd74-42ed-a231-0d194b3fca9f/0f96a4f7-6b24-4969-9564-abbde30b5a51/9199f079-42fc-48cc-86ff-d1072f801932/tile_0006.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "f4fb0308ffbd8d6fd880", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\277180a4-cd74-42ed-a231-0d194b3fca9f\\0f96a4f7-6b24-4969-9564-abbde30b5a51\\9199f079-42fc-48cc-86ff-d1072f801932\\tile_0007.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/277180a4-cd74-42ed-a231-0d194b3fca9f/0f96a4f7-6b24-4969-9564-abbde30b5a51/9199f079-42fc-48cc-86ff-d1072f801932/tile_0007.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "b18eaa92bfb6f82949cc", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\277180a4-cd74-42ed-a231-0d194b3fca9f\\0f96a4f7-6b24-4969-9564-abbde30b5a51\\9199f079-42fc-48cc-86ff-d1072f801932\\tile_0008.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/277180a4-cd74-42ed-a231-0d194b3fca9f/0f96a4f7-6b24-4969-9564-abbde30b5a51/9199f079-42fc-48cc-86ff-d1072f801932/tile_0008.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "f87e566976251b0ddd3d", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\277180a4-cd74-42ed-a231-0d194b3fca9f\\0f96a4f7-6b24-4969-9564-abbde30b5a51\\9199f079-42fc-48cc-86ff-d1072f801932\\tile_0009.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/277180a4-cd74-42ed-a231-0d194b3fca9f/0f96a4f7-6b24-4969-9564-abbde30b5a51/9199f079-42fc-48cc-86ff-d1072f801932/tile_0009.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "379ac5f7a3a7d258b56f", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\277180a4-cd74-42ed-a231-0d194b3fca9f\\0f96a4f7-6b24-4969-9564-abbde30b5a51\\9199f079-42fc-48cc-86ff-d1072f801932\\tile_0010.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/277180a4-cd74-42ed-a231-0d194b3fca9f/0f96a4f7-6b24-4969-9564-abbde30b5a51/9199f079-42fc-48cc-86ff-d1072f801932/tile_0010.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "2ec9764c5631b5c7a1b4", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\277180a4-cd74-42ed-a231-0d194b3fca9f\\0f96a4f7-6b24-4969-9564-abbde30b5a51\\9199f079-42fc-48cc-86ff-d1072f801932\\tile_0011.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/277180a4-cd74-42ed-a231-0d194b3fca9f/0f96a4f7-6b24-4969-9564-abbde30b5a51/9199f079-42fc-48cc-86ff-d1072f801932/tile_0011.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "ac9cbb366a7c16a79b44", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\277180a4-cd74-42ed-a231-0d194b3fca9f\\0f96a4f7-6b24-4969-9564-abbde30b5a51\\9199f079-42fc-48cc-86ff-d1072f801932\\tile_0012.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/277180a4-cd74-42ed-a231-0d194b3fca9f/0f96a4f7-6b24-4969-9564-abbde30b5a51/9199f079-42fc-48cc-86ff-d1072f801932/tile_0012.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "5adaba8e404c16d70d1b", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\277180a4-cd74-42ed-a231-0d194b3fca9f\\0f96a4f7-6b24-4969-9564-abbde30b5a51\\9199f079-42fc-48cc-86ff-d1072f801932\\tile_0013.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/277180a4-cd74-42ed-a231-0d194b3fca9f/0f96a4f7-6b24-4969-9564-abbde30b5a51/9199f079-42fc-48cc-86ff-d1072f801932/tile_0013.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "e61c40ce9d3d2b9d369d", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\277180a4-cd74-42ed-a231-0d194b3fca9f\\0f96a4f7-6b24-4969-9564-abbde30b5a51\\9199f079-42fc-48cc-86ff-d1072f801932\\tile_0014.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/277180a4-cd74-42ed-a231-0d194b3fca9f/0f96a4f7-6b24-4969-9564-abbde30b5a51/9199f079-42fc-48cc-86ff-d1072f801932/tile_0014.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "a814da6efe81f095c9e3", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\277180a4-cd74-42ed-a231-0d194b3fca9f\\0f96a4f7-6b24-4969-9564-abbde30b5a51\\9199f079-42fc-48cc-86ff-d1072f801932\\tile_0015.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/277180a4-cd74-42ed-a231-0d194b3fca9f/0f96a4f7-6b24-4969-9564-abbde30b5a51/9199f079-42fc-48cc-86ff-d1072f801932/tile_0015.tif", - "severity": "critical" - }, - { - "action": "quarantine", - "code": "manifest.zero_bbox", - "field": "bounds", - "item_id": "1500315e2bdebe9d3462", - "message": "Manifest declares a zero-area bounding box", - "path": "storage/tiles/7175ae58-2b09-4fab-83e1-5d95e2969d35/07738ebe-2c5e-4d6c-960d-1c03f216a3a0/7529e658-b42a-47cb-a23c-d9d350b5d8c4/manifest.json", - "severity": "major" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "82177cf3088b3fae2281", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\7175ae58-2b09-4fab-83e1-5d95e2969d35\\07738ebe-2c5e-4d6c-960d-1c03f216a3a0\\7529e658-b42a-47cb-a23c-d9d350b5d8c4\\tile_0000.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/7175ae58-2b09-4fab-83e1-5d95e2969d35/07738ebe-2c5e-4d6c-960d-1c03f216a3a0/7529e658-b42a-47cb-a23c-d9d350b5d8c4/tile_0000.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "6c9f6f1cd68adead5055", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\7175ae58-2b09-4fab-83e1-5d95e2969d35\\07738ebe-2c5e-4d6c-960d-1c03f216a3a0\\7529e658-b42a-47cb-a23c-d9d350b5d8c4\\tile_0001.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/7175ae58-2b09-4fab-83e1-5d95e2969d35/07738ebe-2c5e-4d6c-960d-1c03f216a3a0/7529e658-b42a-47cb-a23c-d9d350b5d8c4/tile_0001.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "c8280727cb07e1423a97", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\7175ae58-2b09-4fab-83e1-5d95e2969d35\\07738ebe-2c5e-4d6c-960d-1c03f216a3a0\\7529e658-b42a-47cb-a23c-d9d350b5d8c4\\tile_0002.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/7175ae58-2b09-4fab-83e1-5d95e2969d35/07738ebe-2c5e-4d6c-960d-1c03f216a3a0/7529e658-b42a-47cb-a23c-d9d350b5d8c4/tile_0002.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "2e89e578c950d03db653", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\7175ae58-2b09-4fab-83e1-5d95e2969d35\\07738ebe-2c5e-4d6c-960d-1c03f216a3a0\\7529e658-b42a-47cb-a23c-d9d350b5d8c4\\tile_0003.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/7175ae58-2b09-4fab-83e1-5d95e2969d35/07738ebe-2c5e-4d6c-960d-1c03f216a3a0/7529e658-b42a-47cb-a23c-d9d350b5d8c4/tile_0003.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "0e60a5f162f918773b06", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\7175ae58-2b09-4fab-83e1-5d95e2969d35\\07738ebe-2c5e-4d6c-960d-1c03f216a3a0\\7529e658-b42a-47cb-a23c-d9d350b5d8c4\\tile_0004.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/7175ae58-2b09-4fab-83e1-5d95e2969d35/07738ebe-2c5e-4d6c-960d-1c03f216a3a0/7529e658-b42a-47cb-a23c-d9d350b5d8c4/tile_0004.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "4b1ff1eeb59cf97d722c", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\7175ae58-2b09-4fab-83e1-5d95e2969d35\\07738ebe-2c5e-4d6c-960d-1c03f216a3a0\\7529e658-b42a-47cb-a23c-d9d350b5d8c4\\tile_0005.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/7175ae58-2b09-4fab-83e1-5d95e2969d35/07738ebe-2c5e-4d6c-960d-1c03f216a3a0/7529e658-b42a-47cb-a23c-d9d350b5d8c4/tile_0005.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "71fff7a0187642c79b89", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\7175ae58-2b09-4fab-83e1-5d95e2969d35\\07738ebe-2c5e-4d6c-960d-1c03f216a3a0\\7529e658-b42a-47cb-a23c-d9d350b5d8c4\\tile_0006.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/7175ae58-2b09-4fab-83e1-5d95e2969d35/07738ebe-2c5e-4d6c-960d-1c03f216a3a0/7529e658-b42a-47cb-a23c-d9d350b5d8c4/tile_0006.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "90c5c1cbd336f0758242", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\7175ae58-2b09-4fab-83e1-5d95e2969d35\\07738ebe-2c5e-4d6c-960d-1c03f216a3a0\\7529e658-b42a-47cb-a23c-d9d350b5d8c4\\tile_0007.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/7175ae58-2b09-4fab-83e1-5d95e2969d35/07738ebe-2c5e-4d6c-960d-1c03f216a3a0/7529e658-b42a-47cb-a23c-d9d350b5d8c4/tile_0007.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "d3b1d530bd052ac1b53e", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\7175ae58-2b09-4fab-83e1-5d95e2969d35\\07738ebe-2c5e-4d6c-960d-1c03f216a3a0\\7529e658-b42a-47cb-a23c-d9d350b5d8c4\\tile_0008.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/7175ae58-2b09-4fab-83e1-5d95e2969d35/07738ebe-2c5e-4d6c-960d-1c03f216a3a0/7529e658-b42a-47cb-a23c-d9d350b5d8c4/tile_0008.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "8cb6365e148d4e5b9b33", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\7175ae58-2b09-4fab-83e1-5d95e2969d35\\07738ebe-2c5e-4d6c-960d-1c03f216a3a0\\7529e658-b42a-47cb-a23c-d9d350b5d8c4\\tile_0009.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/7175ae58-2b09-4fab-83e1-5d95e2969d35/07738ebe-2c5e-4d6c-960d-1c03f216a3a0/7529e658-b42a-47cb-a23c-d9d350b5d8c4/tile_0009.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "3c46ab42aef67799f868", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\7175ae58-2b09-4fab-83e1-5d95e2969d35\\07738ebe-2c5e-4d6c-960d-1c03f216a3a0\\7529e658-b42a-47cb-a23c-d9d350b5d8c4\\tile_0010.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/7175ae58-2b09-4fab-83e1-5d95e2969d35/07738ebe-2c5e-4d6c-960d-1c03f216a3a0/7529e658-b42a-47cb-a23c-d9d350b5d8c4/tile_0010.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "51dae1e198b0e2be9a25", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\7175ae58-2b09-4fab-83e1-5d95e2969d35\\07738ebe-2c5e-4d6c-960d-1c03f216a3a0\\7529e658-b42a-47cb-a23c-d9d350b5d8c4\\tile_0011.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/7175ae58-2b09-4fab-83e1-5d95e2969d35/07738ebe-2c5e-4d6c-960d-1c03f216a3a0/7529e658-b42a-47cb-a23c-d9d350b5d8c4/tile_0011.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "6587704f64f657c9b261", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\7175ae58-2b09-4fab-83e1-5d95e2969d35\\07738ebe-2c5e-4d6c-960d-1c03f216a3a0\\7529e658-b42a-47cb-a23c-d9d350b5d8c4\\tile_0012.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/7175ae58-2b09-4fab-83e1-5d95e2969d35/07738ebe-2c5e-4d6c-960d-1c03f216a3a0/7529e658-b42a-47cb-a23c-d9d350b5d8c4/tile_0012.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "b7965c4fe187fb9a6e72", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\7175ae58-2b09-4fab-83e1-5d95e2969d35\\07738ebe-2c5e-4d6c-960d-1c03f216a3a0\\7529e658-b42a-47cb-a23c-d9d350b5d8c4\\tile_0013.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/7175ae58-2b09-4fab-83e1-5d95e2969d35/07738ebe-2c5e-4d6c-960d-1c03f216a3a0/7529e658-b42a-47cb-a23c-d9d350b5d8c4/tile_0013.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "b54051b8cb4ca92387b2", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\7175ae58-2b09-4fab-83e1-5d95e2969d35\\07738ebe-2c5e-4d6c-960d-1c03f216a3a0\\7529e658-b42a-47cb-a23c-d9d350b5d8c4\\tile_0014.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/7175ae58-2b09-4fab-83e1-5d95e2969d35/07738ebe-2c5e-4d6c-960d-1c03f216a3a0/7529e658-b42a-47cb-a23c-d9d350b5d8c4/tile_0014.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "85abe6c3be8c5f60f542", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\7175ae58-2b09-4fab-83e1-5d95e2969d35\\07738ebe-2c5e-4d6c-960d-1c03f216a3a0\\7529e658-b42a-47cb-a23c-d9d350b5d8c4\\tile_0015.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/7175ae58-2b09-4fab-83e1-5d95e2969d35/07738ebe-2c5e-4d6c-960d-1c03f216a3a0/7529e658-b42a-47cb-a23c-d9d350b5d8c4/tile_0015.tif", - "severity": "critical" - }, - { - "action": "quarantine", - "code": "manifest.zero_bbox", - "field": "bounds", - "item_id": "b6b16941c235d9cb21df", - "message": "Manifest declares a zero-area bounding box", - "path": "storage/tiles/a7a94d0b-9b27-49bd-9e44-97b0b75677ad/e2a3f62a-76f0-4611-81a3-d2ca948cda75/6e53d525-f603-4eb3-8bf7-05da59832013/manifest.json", - "severity": "major" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "20e3d2bb3ee9bb98f8b2", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\a7a94d0b-9b27-49bd-9e44-97b0b75677ad\\e2a3f62a-76f0-4611-81a3-d2ca948cda75\\6e53d525-f603-4eb3-8bf7-05da59832013\\tile_0000.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/a7a94d0b-9b27-49bd-9e44-97b0b75677ad/e2a3f62a-76f0-4611-81a3-d2ca948cda75/6e53d525-f603-4eb3-8bf7-05da59832013/tile_0000.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "4e4919deb1ec3b7df24d", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\a7a94d0b-9b27-49bd-9e44-97b0b75677ad\\e2a3f62a-76f0-4611-81a3-d2ca948cda75\\6e53d525-f603-4eb3-8bf7-05da59832013\\tile_0001.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/a7a94d0b-9b27-49bd-9e44-97b0b75677ad/e2a3f62a-76f0-4611-81a3-d2ca948cda75/6e53d525-f603-4eb3-8bf7-05da59832013/tile_0001.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "0f87eb34f3f0359638a2", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\a7a94d0b-9b27-49bd-9e44-97b0b75677ad\\e2a3f62a-76f0-4611-81a3-d2ca948cda75\\6e53d525-f603-4eb3-8bf7-05da59832013\\tile_0002.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/a7a94d0b-9b27-49bd-9e44-97b0b75677ad/e2a3f62a-76f0-4611-81a3-d2ca948cda75/6e53d525-f603-4eb3-8bf7-05da59832013/tile_0002.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "e5f08ed47ebbc2dc539d", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\a7a94d0b-9b27-49bd-9e44-97b0b75677ad\\e2a3f62a-76f0-4611-81a3-d2ca948cda75\\6e53d525-f603-4eb3-8bf7-05da59832013\\tile_0003.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/a7a94d0b-9b27-49bd-9e44-97b0b75677ad/e2a3f62a-76f0-4611-81a3-d2ca948cda75/6e53d525-f603-4eb3-8bf7-05da59832013/tile_0003.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "776ded90bfd4c9e66373", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\a7a94d0b-9b27-49bd-9e44-97b0b75677ad\\e2a3f62a-76f0-4611-81a3-d2ca948cda75\\6e53d525-f603-4eb3-8bf7-05da59832013\\tile_0004.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/a7a94d0b-9b27-49bd-9e44-97b0b75677ad/e2a3f62a-76f0-4611-81a3-d2ca948cda75/6e53d525-f603-4eb3-8bf7-05da59832013/tile_0004.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "2a37d92cc1f4c7760875", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\a7a94d0b-9b27-49bd-9e44-97b0b75677ad\\e2a3f62a-76f0-4611-81a3-d2ca948cda75\\6e53d525-f603-4eb3-8bf7-05da59832013\\tile_0005.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/a7a94d0b-9b27-49bd-9e44-97b0b75677ad/e2a3f62a-76f0-4611-81a3-d2ca948cda75/6e53d525-f603-4eb3-8bf7-05da59832013/tile_0005.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "d3d5a58eb923e4e58858", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\a7a94d0b-9b27-49bd-9e44-97b0b75677ad\\e2a3f62a-76f0-4611-81a3-d2ca948cda75\\6e53d525-f603-4eb3-8bf7-05da59832013\\tile_0006.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/a7a94d0b-9b27-49bd-9e44-97b0b75677ad/e2a3f62a-76f0-4611-81a3-d2ca948cda75/6e53d525-f603-4eb3-8bf7-05da59832013/tile_0006.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "91c929ee528e638a6a76", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\a7a94d0b-9b27-49bd-9e44-97b0b75677ad\\e2a3f62a-76f0-4611-81a3-d2ca948cda75\\6e53d525-f603-4eb3-8bf7-05da59832013\\tile_0007.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/a7a94d0b-9b27-49bd-9e44-97b0b75677ad/e2a3f62a-76f0-4611-81a3-d2ca948cda75/6e53d525-f603-4eb3-8bf7-05da59832013/tile_0007.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "e480cf83cf5db4b2e52d", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\a7a94d0b-9b27-49bd-9e44-97b0b75677ad\\e2a3f62a-76f0-4611-81a3-d2ca948cda75\\6e53d525-f603-4eb3-8bf7-05da59832013\\tile_0008.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/a7a94d0b-9b27-49bd-9e44-97b0b75677ad/e2a3f62a-76f0-4611-81a3-d2ca948cda75/6e53d525-f603-4eb3-8bf7-05da59832013/tile_0008.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "c0ad18065477ffaad4ac", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\a7a94d0b-9b27-49bd-9e44-97b0b75677ad\\e2a3f62a-76f0-4611-81a3-d2ca948cda75\\6e53d525-f603-4eb3-8bf7-05da59832013\\tile_0009.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/a7a94d0b-9b27-49bd-9e44-97b0b75677ad/e2a3f62a-76f0-4611-81a3-d2ca948cda75/6e53d525-f603-4eb3-8bf7-05da59832013/tile_0009.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "ba9cbe3cdf31c09754b6", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\a7a94d0b-9b27-49bd-9e44-97b0b75677ad\\e2a3f62a-76f0-4611-81a3-d2ca948cda75\\6e53d525-f603-4eb3-8bf7-05da59832013\\tile_0010.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/a7a94d0b-9b27-49bd-9e44-97b0b75677ad/e2a3f62a-76f0-4611-81a3-d2ca948cda75/6e53d525-f603-4eb3-8bf7-05da59832013/tile_0010.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "74791aaeb46bd8705f5c", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\a7a94d0b-9b27-49bd-9e44-97b0b75677ad\\e2a3f62a-76f0-4611-81a3-d2ca948cda75\\6e53d525-f603-4eb3-8bf7-05da59832013\\tile_0011.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/a7a94d0b-9b27-49bd-9e44-97b0b75677ad/e2a3f62a-76f0-4611-81a3-d2ca948cda75/6e53d525-f603-4eb3-8bf7-05da59832013/tile_0011.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "e6494b03753f6de23316", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\a7a94d0b-9b27-49bd-9e44-97b0b75677ad\\e2a3f62a-76f0-4611-81a3-d2ca948cda75\\6e53d525-f603-4eb3-8bf7-05da59832013\\tile_0012.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/a7a94d0b-9b27-49bd-9e44-97b0b75677ad/e2a3f62a-76f0-4611-81a3-d2ca948cda75/6e53d525-f603-4eb3-8bf7-05da59832013/tile_0012.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "c2301617d835cbe7a9da", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\a7a94d0b-9b27-49bd-9e44-97b0b75677ad\\e2a3f62a-76f0-4611-81a3-d2ca948cda75\\6e53d525-f603-4eb3-8bf7-05da59832013\\tile_0013.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/a7a94d0b-9b27-49bd-9e44-97b0b75677ad/e2a3f62a-76f0-4611-81a3-d2ca948cda75/6e53d525-f603-4eb3-8bf7-05da59832013/tile_0013.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "712708cfd7b54f652c1f", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\a7a94d0b-9b27-49bd-9e44-97b0b75677ad\\e2a3f62a-76f0-4611-81a3-d2ca948cda75\\6e53d525-f603-4eb3-8bf7-05da59832013\\tile_0014.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/a7a94d0b-9b27-49bd-9e44-97b0b75677ad/e2a3f62a-76f0-4611-81a3-d2ca948cda75/6e53d525-f603-4eb3-8bf7-05da59832013/tile_0014.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "bfbadaaae125e34b5828", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\a7a94d0b-9b27-49bd-9e44-97b0b75677ad\\e2a3f62a-76f0-4611-81a3-d2ca948cda75\\6e53d525-f603-4eb3-8bf7-05da59832013\\tile_0015.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/a7a94d0b-9b27-49bd-9e44-97b0b75677ad/e2a3f62a-76f0-4611-81a3-d2ca948cda75/6e53d525-f603-4eb3-8bf7-05da59832013/tile_0015.tif", - "severity": "critical" - }, - { - "action": "quarantine", - "code": "manifest.zero_bbox", - "field": "bounds", - "item_id": "04f3407f941cd1dc895e", - "message": "Manifest declares a zero-area bounding box", - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/manifest.json", - "severity": "major" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "4def26f935acc400079e", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0000.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/tile_0000.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "9e093656fa6b9d623331", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0001.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/tile_0001.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "463efcbe145941dc1ded", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0002.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/tile_0002.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "6b1012bfdedb2641eb37", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0003.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/tile_0003.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "71979d432b49d84e9e75", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0004.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/tile_0004.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "649fd55f6d877aa78bb2", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0005.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/tile_0005.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "52e170d64fb1a011de45", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0006.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/tile_0006.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "46628f46cd8911a36f86", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0007.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/tile_0007.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "889b2e92c1aa378722aa", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0008.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/tile_0008.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "67a46403c7fb388bb484", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0009.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/tile_0009.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "25123fae6d918a76ac7a", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0010.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/tile_0010.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "7407fad7de42e36fe791", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0011.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/tile_0011.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "eaa22fd47e90efa7dbdd", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0012.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/tile_0012.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "46aaf33ee50eaa14edfd", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0013.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/tile_0013.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "6d3766eca60a28941699", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0014.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/tile_0014.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "a870f7c9d918ccf7d5a6", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0015.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/tile_0015.tif", - "severity": "critical" - }, - { - "action": "quarantine", - "code": "manifest.zero_bbox", - "field": "bounds", - "item_id": "42f97df8f1716a98cc5a", - "message": "Manifest declares a zero-area bounding box", - "path": "storage/tiles/db240e97-188d-48fd-98f3-7abd9131ffeb/2df0e426-f569-459f-a4ad-d3f42539bc23/f31826fa-10e3-4154-95c2-d89d21813379/manifest.json", - "severity": "major" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "33b3c33cb179ac85ada1", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\db240e97-188d-48fd-98f3-7abd9131ffeb\\2df0e426-f569-459f-a4ad-d3f42539bc23\\f31826fa-10e3-4154-95c2-d89d21813379\\tile_0000.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/db240e97-188d-48fd-98f3-7abd9131ffeb/2df0e426-f569-459f-a4ad-d3f42539bc23/f31826fa-10e3-4154-95c2-d89d21813379/tile_0000.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "346a71885fe0853cfc30", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\db240e97-188d-48fd-98f3-7abd9131ffeb\\2df0e426-f569-459f-a4ad-d3f42539bc23\\f31826fa-10e3-4154-95c2-d89d21813379\\tile_0001.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/db240e97-188d-48fd-98f3-7abd9131ffeb/2df0e426-f569-459f-a4ad-d3f42539bc23/f31826fa-10e3-4154-95c2-d89d21813379/tile_0001.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "6fab06961d3c3d439c73", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\db240e97-188d-48fd-98f3-7abd9131ffeb\\2df0e426-f569-459f-a4ad-d3f42539bc23\\f31826fa-10e3-4154-95c2-d89d21813379\\tile_0002.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/db240e97-188d-48fd-98f3-7abd9131ffeb/2df0e426-f569-459f-a4ad-d3f42539bc23/f31826fa-10e3-4154-95c2-d89d21813379/tile_0002.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "bc61a64bf00351eaa325", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\db240e97-188d-48fd-98f3-7abd9131ffeb\\2df0e426-f569-459f-a4ad-d3f42539bc23\\f31826fa-10e3-4154-95c2-d89d21813379\\tile_0003.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/db240e97-188d-48fd-98f3-7abd9131ffeb/2df0e426-f569-459f-a4ad-d3f42539bc23/f31826fa-10e3-4154-95c2-d89d21813379/tile_0003.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "af6d1e573b5b4b191b87", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\db240e97-188d-48fd-98f3-7abd9131ffeb\\2df0e426-f569-459f-a4ad-d3f42539bc23\\f31826fa-10e3-4154-95c2-d89d21813379\\tile_0004.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/db240e97-188d-48fd-98f3-7abd9131ffeb/2df0e426-f569-459f-a4ad-d3f42539bc23/f31826fa-10e3-4154-95c2-d89d21813379/tile_0004.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "ef9696bc380f7e9dc039", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\db240e97-188d-48fd-98f3-7abd9131ffeb\\2df0e426-f569-459f-a4ad-d3f42539bc23\\f31826fa-10e3-4154-95c2-d89d21813379\\tile_0005.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/db240e97-188d-48fd-98f3-7abd9131ffeb/2df0e426-f569-459f-a4ad-d3f42539bc23/f31826fa-10e3-4154-95c2-d89d21813379/tile_0005.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "e440975ad15713709d14", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\db240e97-188d-48fd-98f3-7abd9131ffeb\\2df0e426-f569-459f-a4ad-d3f42539bc23\\f31826fa-10e3-4154-95c2-d89d21813379\\tile_0006.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/db240e97-188d-48fd-98f3-7abd9131ffeb/2df0e426-f569-459f-a4ad-d3f42539bc23/f31826fa-10e3-4154-95c2-d89d21813379/tile_0006.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "3f1f44d08c10be760fa3", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\db240e97-188d-48fd-98f3-7abd9131ffeb\\2df0e426-f569-459f-a4ad-d3f42539bc23\\f31826fa-10e3-4154-95c2-d89d21813379\\tile_0007.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/db240e97-188d-48fd-98f3-7abd9131ffeb/2df0e426-f569-459f-a4ad-d3f42539bc23/f31826fa-10e3-4154-95c2-d89d21813379/tile_0007.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "bc0e44ce91c97c3723c9", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\db240e97-188d-48fd-98f3-7abd9131ffeb\\2df0e426-f569-459f-a4ad-d3f42539bc23\\f31826fa-10e3-4154-95c2-d89d21813379\\tile_0008.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/db240e97-188d-48fd-98f3-7abd9131ffeb/2df0e426-f569-459f-a4ad-d3f42539bc23/f31826fa-10e3-4154-95c2-d89d21813379/tile_0008.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "9d163f657df866f7a22b", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\db240e97-188d-48fd-98f3-7abd9131ffeb\\2df0e426-f569-459f-a4ad-d3f42539bc23\\f31826fa-10e3-4154-95c2-d89d21813379\\tile_0009.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/db240e97-188d-48fd-98f3-7abd9131ffeb/2df0e426-f569-459f-a4ad-d3f42539bc23/f31826fa-10e3-4154-95c2-d89d21813379/tile_0009.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "c3ecd380ee4499edfd90", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\db240e97-188d-48fd-98f3-7abd9131ffeb\\2df0e426-f569-459f-a4ad-d3f42539bc23\\f31826fa-10e3-4154-95c2-d89d21813379\\tile_0010.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/db240e97-188d-48fd-98f3-7abd9131ffeb/2df0e426-f569-459f-a4ad-d3f42539bc23/f31826fa-10e3-4154-95c2-d89d21813379/tile_0010.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "d46845df780977985a5e", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\db240e97-188d-48fd-98f3-7abd9131ffeb\\2df0e426-f569-459f-a4ad-d3f42539bc23\\f31826fa-10e3-4154-95c2-d89d21813379\\tile_0011.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/db240e97-188d-48fd-98f3-7abd9131ffeb/2df0e426-f569-459f-a4ad-d3f42539bc23/f31826fa-10e3-4154-95c2-d89d21813379/tile_0011.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "38b78e73d14a80e5034a", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\db240e97-188d-48fd-98f3-7abd9131ffeb\\2df0e426-f569-459f-a4ad-d3f42539bc23\\f31826fa-10e3-4154-95c2-d89d21813379\\tile_0012.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/db240e97-188d-48fd-98f3-7abd9131ffeb/2df0e426-f569-459f-a4ad-d3f42539bc23/f31826fa-10e3-4154-95c2-d89d21813379/tile_0012.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "d3c5bdffafb98153e8d9", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\db240e97-188d-48fd-98f3-7abd9131ffeb\\2df0e426-f569-459f-a4ad-d3f42539bc23\\f31826fa-10e3-4154-95c2-d89d21813379\\tile_0013.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/db240e97-188d-48fd-98f3-7abd9131ffeb/2df0e426-f569-459f-a4ad-d3f42539bc23/f31826fa-10e3-4154-95c2-d89d21813379/tile_0013.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "7e850fe24708dda753f0", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\db240e97-188d-48fd-98f3-7abd9131ffeb\\2df0e426-f569-459f-a4ad-d3f42539bc23\\f31826fa-10e3-4154-95c2-d89d21813379\\tile_0014.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/db240e97-188d-48fd-98f3-7abd9131ffeb/2df0e426-f569-459f-a4ad-d3f42539bc23/f31826fa-10e3-4154-95c2-d89d21813379/tile_0014.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "303f7135858218c797ce", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\db240e97-188d-48fd-98f3-7abd9131ffeb\\2df0e426-f569-459f-a4ad-d3f42539bc23\\f31826fa-10e3-4154-95c2-d89d21813379\\tile_0015.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/db240e97-188d-48fd-98f3-7abd9131ffeb/2df0e426-f569-459f-a4ad-d3f42539bc23/f31826fa-10e3-4154-95c2-d89d21813379/tile_0015.tif", - "severity": "critical" - }, - { - "action": "quarantine", - "code": "manifest.zero_bbox", - "field": "bounds", - "item_id": "3838bd5bae003af13690", - "message": "Manifest declares a zero-area bounding box", - "path": "storage/tiles/df217a4e-7f2e-4989-880e-30fb9a7ec645/f6848732-1f78-41ba-967c-11a577112b17/5e0d5f61-e7fb-4d4a-ae96-84b9060554d6/manifest.json", - "severity": "major" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "295dc32a2407bf282a8c", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\df217a4e-7f2e-4989-880e-30fb9a7ec645\\f6848732-1f78-41ba-967c-11a577112b17\\5e0d5f61-e7fb-4d4a-ae96-84b9060554d6\\tile_0000.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/df217a4e-7f2e-4989-880e-30fb9a7ec645/f6848732-1f78-41ba-967c-11a577112b17/5e0d5f61-e7fb-4d4a-ae96-84b9060554d6/tile_0000.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "abd539c47bb02eed552f", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\df217a4e-7f2e-4989-880e-30fb9a7ec645\\f6848732-1f78-41ba-967c-11a577112b17\\5e0d5f61-e7fb-4d4a-ae96-84b9060554d6\\tile_0001.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/df217a4e-7f2e-4989-880e-30fb9a7ec645/f6848732-1f78-41ba-967c-11a577112b17/5e0d5f61-e7fb-4d4a-ae96-84b9060554d6/tile_0001.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "6f3267beda326834d472", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\df217a4e-7f2e-4989-880e-30fb9a7ec645\\f6848732-1f78-41ba-967c-11a577112b17\\5e0d5f61-e7fb-4d4a-ae96-84b9060554d6\\tile_0002.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/df217a4e-7f2e-4989-880e-30fb9a7ec645/f6848732-1f78-41ba-967c-11a577112b17/5e0d5f61-e7fb-4d4a-ae96-84b9060554d6/tile_0002.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "81ca8f6bfc34b1cdcb10", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\df217a4e-7f2e-4989-880e-30fb9a7ec645\\f6848732-1f78-41ba-967c-11a577112b17\\5e0d5f61-e7fb-4d4a-ae96-84b9060554d6\\tile_0003.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/df217a4e-7f2e-4989-880e-30fb9a7ec645/f6848732-1f78-41ba-967c-11a577112b17/5e0d5f61-e7fb-4d4a-ae96-84b9060554d6/tile_0003.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "7192190199b044390815", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\df217a4e-7f2e-4989-880e-30fb9a7ec645\\f6848732-1f78-41ba-967c-11a577112b17\\5e0d5f61-e7fb-4d4a-ae96-84b9060554d6\\tile_0004.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/df217a4e-7f2e-4989-880e-30fb9a7ec645/f6848732-1f78-41ba-967c-11a577112b17/5e0d5f61-e7fb-4d4a-ae96-84b9060554d6/tile_0004.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "b9d3054f0d9a803d09b5", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\df217a4e-7f2e-4989-880e-30fb9a7ec645\\f6848732-1f78-41ba-967c-11a577112b17\\5e0d5f61-e7fb-4d4a-ae96-84b9060554d6\\tile_0005.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/df217a4e-7f2e-4989-880e-30fb9a7ec645/f6848732-1f78-41ba-967c-11a577112b17/5e0d5f61-e7fb-4d4a-ae96-84b9060554d6/tile_0005.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "30a426290bc779af9d6a", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\df217a4e-7f2e-4989-880e-30fb9a7ec645\\f6848732-1f78-41ba-967c-11a577112b17\\5e0d5f61-e7fb-4d4a-ae96-84b9060554d6\\tile_0006.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/df217a4e-7f2e-4989-880e-30fb9a7ec645/f6848732-1f78-41ba-967c-11a577112b17/5e0d5f61-e7fb-4d4a-ae96-84b9060554d6/tile_0006.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "09bc3cdd65af8613dd32", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\df217a4e-7f2e-4989-880e-30fb9a7ec645\\f6848732-1f78-41ba-967c-11a577112b17\\5e0d5f61-e7fb-4d4a-ae96-84b9060554d6\\tile_0007.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/df217a4e-7f2e-4989-880e-30fb9a7ec645/f6848732-1f78-41ba-967c-11a577112b17/5e0d5f61-e7fb-4d4a-ae96-84b9060554d6/tile_0007.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "db688c755ad92613e5b2", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\df217a4e-7f2e-4989-880e-30fb9a7ec645\\f6848732-1f78-41ba-967c-11a577112b17\\5e0d5f61-e7fb-4d4a-ae96-84b9060554d6\\tile_0008.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/df217a4e-7f2e-4989-880e-30fb9a7ec645/f6848732-1f78-41ba-967c-11a577112b17/5e0d5f61-e7fb-4d4a-ae96-84b9060554d6/tile_0008.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "70cfc9a48bb0b6fbe125", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\df217a4e-7f2e-4989-880e-30fb9a7ec645\\f6848732-1f78-41ba-967c-11a577112b17\\5e0d5f61-e7fb-4d4a-ae96-84b9060554d6\\tile_0009.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/df217a4e-7f2e-4989-880e-30fb9a7ec645/f6848732-1f78-41ba-967c-11a577112b17/5e0d5f61-e7fb-4d4a-ae96-84b9060554d6/tile_0009.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "b8160ad197d56e6fefd2", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\df217a4e-7f2e-4989-880e-30fb9a7ec645\\f6848732-1f78-41ba-967c-11a577112b17\\5e0d5f61-e7fb-4d4a-ae96-84b9060554d6\\tile_0010.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/df217a4e-7f2e-4989-880e-30fb9a7ec645/f6848732-1f78-41ba-967c-11a577112b17/5e0d5f61-e7fb-4d4a-ae96-84b9060554d6/tile_0010.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "7815b5ffcca8b258f42e", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\df217a4e-7f2e-4989-880e-30fb9a7ec645\\f6848732-1f78-41ba-967c-11a577112b17\\5e0d5f61-e7fb-4d4a-ae96-84b9060554d6\\tile_0011.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/df217a4e-7f2e-4989-880e-30fb9a7ec645/f6848732-1f78-41ba-967c-11a577112b17/5e0d5f61-e7fb-4d4a-ae96-84b9060554d6/tile_0011.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "cbce46d3556b5408ccf0", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\df217a4e-7f2e-4989-880e-30fb9a7ec645\\f6848732-1f78-41ba-967c-11a577112b17\\5e0d5f61-e7fb-4d4a-ae96-84b9060554d6\\tile_0012.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/df217a4e-7f2e-4989-880e-30fb9a7ec645/f6848732-1f78-41ba-967c-11a577112b17/5e0d5f61-e7fb-4d4a-ae96-84b9060554d6/tile_0012.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "43a18bee9bf250564490", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\df217a4e-7f2e-4989-880e-30fb9a7ec645\\f6848732-1f78-41ba-967c-11a577112b17\\5e0d5f61-e7fb-4d4a-ae96-84b9060554d6\\tile_0013.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/df217a4e-7f2e-4989-880e-30fb9a7ec645/f6848732-1f78-41ba-967c-11a577112b17/5e0d5f61-e7fb-4d4a-ae96-84b9060554d6/tile_0013.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "dff9cee5f0f875a45247", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\df217a4e-7f2e-4989-880e-30fb9a7ec645\\f6848732-1f78-41ba-967c-11a577112b17\\5e0d5f61-e7fb-4d4a-ae96-84b9060554d6\\tile_0014.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/df217a4e-7f2e-4989-880e-30fb9a7ec645/f6848732-1f78-41ba-967c-11a577112b17/5e0d5f61-e7fb-4d4a-ae96-84b9060554d6/tile_0014.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "fbe412d93aefe8bbe414", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\df217a4e-7f2e-4989-880e-30fb9a7ec645\\f6848732-1f78-41ba-967c-11a577112b17\\5e0d5f61-e7fb-4d4a-ae96-84b9060554d6\\tile_0015.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/df217a4e-7f2e-4989-880e-30fb9a7ec645/f6848732-1f78-41ba-967c-11a577112b17/5e0d5f61-e7fb-4d4a-ae96-84b9060554d6/tile_0015.tif", - "severity": "critical" - }, - { - "action": "requires review", - "code": "freshness.missing", - "item_id": "867763fe8f71b713acdd", - "message": "Source-labelled item has no declared observation timestamp", - "path": "storage/uploads/30e69368-3047-4131-9a49-137351db5848/raster/f770f213-a474-4a0a-bed0-aca6d9238ed1/f770f213-a474-4a0a-bed0-aca6d9238ed1_dhmvii_terrain_5m_abefd0caf44e.tif", - "severity": "minor" - }, - { - "action": "requires review", - "code": "freshness.missing", - "item_id": "ce14b6ac0563dfad06b7", - "message": "Source-labelled item has no declared observation timestamp", - "path": "storage/uploads/6abbf506-a386-4451-8cd9-d595bc995d51/raster/76b6fcf4-29d4-4906-8687-a46bfe16be63/76b6fcf4-29d4-4906-8687-a46bfe16be63_dhmvii_terrain_5m_25afc05778f0.tif", - "severity": "minor" - }, - { - "action": "requires review", - "code": "freshness.missing", - "item_id": "2237c5ae9f8fce22c984", - "message": "Source-labelled item has no declared observation timestamp", - "path": "storage/uploads/bf96b94e-01aa-4912-9286-75a318cfc2ab/raster/12441c43-80db-43d6-bebf-8e4ff2207338/12441c43-80db-43d6-bebf-8e4ff2207338_dhmvii_terrain_5m_fc9d87c14310.tif", - "severity": "minor" - }, - { - "action": "requires review", - "code": "freshness.missing", - "item_id": "97e48e54218e7f126d40", - "message": "Source-labelled item has no declared observation timestamp", - "path": "storage/uploads/f7e7ba0c-e490-46c8-8467-28c9176ede55/raster/771bf37d-424a-4e56-98a5-35657f52674c/771bf37d-424a-4e56-98a5-35657f52674c_dhmvii_terrain_5m_9cde89f97e71.tif", - "severity": "minor" - }, - { - "action": "requires review", - "code": "freshness.missing", - "item_id": "4e742df38492234458e9", - "message": "Source-labelled item has no declared observation timestamp", - "path": "storage/uploads/fead1267-e2f8-4e25-af69-9333665e87e7/raster/4c2100cd-b167-4494-bfd4-78a378d3423c/4c2100cd-b167-4494-bfd4-78a378d3423c_dhmvii_terrain_5m_a193c984774e.tif", - "severity": "minor" - } - ], - "counts": { - "freshness.missing": 29, - "lineage.missing": 577, - "manifest.zero_bbox": 6, - "raster.unreadable": 96, - "scope.unreachable": 3 - }, - "scan_id": "p3-eb67185e61107cc7", - "schema_version": 1 -} diff --git a/artifacts/evidence/accuracy/P3/dataset-summary.json b/artifacts/evidence/accuracy/P3/dataset-summary.json deleted file mode 100644 index f8170f63..00000000 --- a/artifacts/evidence/accuracy/P3/dataset-summary.json +++ /dev/null @@ -1,1093 +0,0 @@ -{ - "anomaly_category_counts": { - "freshness.missing": 29, - "lineage.missing": 577, - "manifest.zero_bbox": 6, - 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"path": "storage/tiles/277180a4-cd74-42ed-a231-0d194b3fca9f/0f96a4f7-6b24-4969-9564-abbde30b5a51/9199f079-42fc-48cc-86ff-d1072f801932/tile_0008.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "f87e566976251b0ddd3d", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\277180a4-cd74-42ed-a231-0d194b3fca9f\\0f96a4f7-6b24-4969-9564-abbde30b5a51\\9199f079-42fc-48cc-86ff-d1072f801932\\tile_0009.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/277180a4-cd74-42ed-a231-0d194b3fca9f/0f96a4f7-6b24-4969-9564-abbde30b5a51/9199f079-42fc-48cc-86ff-d1072f801932/tile_0009.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "379ac5f7a3a7d258b56f", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\277180a4-cd74-42ed-a231-0d194b3fca9f\\0f96a4f7-6b24-4969-9564-abbde30b5a51\\9199f079-42fc-48cc-86ff-d1072f801932\\tile_0010.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/277180a4-cd74-42ed-a231-0d194b3fca9f/0f96a4f7-6b24-4969-9564-abbde30b5a51/9199f079-42fc-48cc-86ff-d1072f801932/tile_0010.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "2ec9764c5631b5c7a1b4", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\277180a4-cd74-42ed-a231-0d194b3fca9f\\0f96a4f7-6b24-4969-9564-abbde30b5a51\\9199f079-42fc-48cc-86ff-d1072f801932\\tile_0011.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/277180a4-cd74-42ed-a231-0d194b3fca9f/0f96a4f7-6b24-4969-9564-abbde30b5a51/9199f079-42fc-48cc-86ff-d1072f801932/tile_0011.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "ac9cbb366a7c16a79b44", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\277180a4-cd74-42ed-a231-0d194b3fca9f\\0f96a4f7-6b24-4969-9564-abbde30b5a51\\9199f079-42fc-48cc-86ff-d1072f801932\\tile_0012.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/277180a4-cd74-42ed-a231-0d194b3fca9f/0f96a4f7-6b24-4969-9564-abbde30b5a51/9199f079-42fc-48cc-86ff-d1072f801932/tile_0012.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "5adaba8e404c16d70d1b", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\277180a4-cd74-42ed-a231-0d194b3fca9f\\0f96a4f7-6b24-4969-9564-abbde30b5a51\\9199f079-42fc-48cc-86ff-d1072f801932\\tile_0013.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/277180a4-cd74-42ed-a231-0d194b3fca9f/0f96a4f7-6b24-4969-9564-abbde30b5a51/9199f079-42fc-48cc-86ff-d1072f801932/tile_0013.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "e61c40ce9d3d2b9d369d", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\277180a4-cd74-42ed-a231-0d194b3fca9f\\0f96a4f7-6b24-4969-9564-abbde30b5a51\\9199f079-42fc-48cc-86ff-d1072f801932\\tile_0014.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/277180a4-cd74-42ed-a231-0d194b3fca9f/0f96a4f7-6b24-4969-9564-abbde30b5a51/9199f079-42fc-48cc-86ff-d1072f801932/tile_0014.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "a814da6efe81f095c9e3", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\277180a4-cd74-42ed-a231-0d194b3fca9f\\0f96a4f7-6b24-4969-9564-abbde30b5a51\\9199f079-42fc-48cc-86ff-d1072f801932\\tile_0015.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/277180a4-cd74-42ed-a231-0d194b3fca9f/0f96a4f7-6b24-4969-9564-abbde30b5a51/9199f079-42fc-48cc-86ff-d1072f801932/tile_0015.tif", - "severity": "critical" - }, - { - "action": "quarantine", - "code": "manifest.zero_bbox", - "field": "bounds", - "item_id": "1500315e2bdebe9d3462", - "message": "Manifest declares a zero-area bounding box", - "path": "storage/tiles/7175ae58-2b09-4fab-83e1-5d95e2969d35/07738ebe-2c5e-4d6c-960d-1c03f216a3a0/7529e658-b42a-47cb-a23c-d9d350b5d8c4/manifest.json", - "severity": "major" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "82177cf3088b3fae2281", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\7175ae58-2b09-4fab-83e1-5d95e2969d35\\07738ebe-2c5e-4d6c-960d-1c03f216a3a0\\7529e658-b42a-47cb-a23c-d9d350b5d8c4\\tile_0000.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/7175ae58-2b09-4fab-83e1-5d95e2969d35/07738ebe-2c5e-4d6c-960d-1c03f216a3a0/7529e658-b42a-47cb-a23c-d9d350b5d8c4/tile_0000.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "6c9f6f1cd68adead5055", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\7175ae58-2b09-4fab-83e1-5d95e2969d35\\07738ebe-2c5e-4d6c-960d-1c03f216a3a0\\7529e658-b42a-47cb-a23c-d9d350b5d8c4\\tile_0001.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/7175ae58-2b09-4fab-83e1-5d95e2969d35/07738ebe-2c5e-4d6c-960d-1c03f216a3a0/7529e658-b42a-47cb-a23c-d9d350b5d8c4/tile_0001.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "c8280727cb07e1423a97", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\7175ae58-2b09-4fab-83e1-5d95e2969d35\\07738ebe-2c5e-4d6c-960d-1c03f216a3a0\\7529e658-b42a-47cb-a23c-d9d350b5d8c4\\tile_0002.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/7175ae58-2b09-4fab-83e1-5d95e2969d35/07738ebe-2c5e-4d6c-960d-1c03f216a3a0/7529e658-b42a-47cb-a23c-d9d350b5d8c4/tile_0002.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "2e89e578c950d03db653", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\7175ae58-2b09-4fab-83e1-5d95e2969d35\\07738ebe-2c5e-4d6c-960d-1c03f216a3a0\\7529e658-b42a-47cb-a23c-d9d350b5d8c4\\tile_0003.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/7175ae58-2b09-4fab-83e1-5d95e2969d35/07738ebe-2c5e-4d6c-960d-1c03f216a3a0/7529e658-b42a-47cb-a23c-d9d350b5d8c4/tile_0003.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "0e60a5f162f918773b06", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\7175ae58-2b09-4fab-83e1-5d95e2969d35\\07738ebe-2c5e-4d6c-960d-1c03f216a3a0\\7529e658-b42a-47cb-a23c-d9d350b5d8c4\\tile_0004.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/7175ae58-2b09-4fab-83e1-5d95e2969d35/07738ebe-2c5e-4d6c-960d-1c03f216a3a0/7529e658-b42a-47cb-a23c-d9d350b5d8c4/tile_0004.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "4b1ff1eeb59cf97d722c", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\7175ae58-2b09-4fab-83e1-5d95e2969d35\\07738ebe-2c5e-4d6c-960d-1c03f216a3a0\\7529e658-b42a-47cb-a23c-d9d350b5d8c4\\tile_0005.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/7175ae58-2b09-4fab-83e1-5d95e2969d35/07738ebe-2c5e-4d6c-960d-1c03f216a3a0/7529e658-b42a-47cb-a23c-d9d350b5d8c4/tile_0005.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "71fff7a0187642c79b89", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\7175ae58-2b09-4fab-83e1-5d95e2969d35\\07738ebe-2c5e-4d6c-960d-1c03f216a3a0\\7529e658-b42a-47cb-a23c-d9d350b5d8c4\\tile_0006.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/7175ae58-2b09-4fab-83e1-5d95e2969d35/07738ebe-2c5e-4d6c-960d-1c03f216a3a0/7529e658-b42a-47cb-a23c-d9d350b5d8c4/tile_0006.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "90c5c1cbd336f0758242", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\7175ae58-2b09-4fab-83e1-5d95e2969d35\\07738ebe-2c5e-4d6c-960d-1c03f216a3a0\\7529e658-b42a-47cb-a23c-d9d350b5d8c4\\tile_0007.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/7175ae58-2b09-4fab-83e1-5d95e2969d35/07738ebe-2c5e-4d6c-960d-1c03f216a3a0/7529e658-b42a-47cb-a23c-d9d350b5d8c4/tile_0007.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "d3b1d530bd052ac1b53e", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\7175ae58-2b09-4fab-83e1-5d95e2969d35\\07738ebe-2c5e-4d6c-960d-1c03f216a3a0\\7529e658-b42a-47cb-a23c-d9d350b5d8c4\\tile_0008.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/7175ae58-2b09-4fab-83e1-5d95e2969d35/07738ebe-2c5e-4d6c-960d-1c03f216a3a0/7529e658-b42a-47cb-a23c-d9d350b5d8c4/tile_0008.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "8cb6365e148d4e5b9b33", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\7175ae58-2b09-4fab-83e1-5d95e2969d35\\07738ebe-2c5e-4d6c-960d-1c03f216a3a0\\7529e658-b42a-47cb-a23c-d9d350b5d8c4\\tile_0009.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/7175ae58-2b09-4fab-83e1-5d95e2969d35/07738ebe-2c5e-4d6c-960d-1c03f216a3a0/7529e658-b42a-47cb-a23c-d9d350b5d8c4/tile_0009.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "3c46ab42aef67799f868", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\7175ae58-2b09-4fab-83e1-5d95e2969d35\\07738ebe-2c5e-4d6c-960d-1c03f216a3a0\\7529e658-b42a-47cb-a23c-d9d350b5d8c4\\tile_0010.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/7175ae58-2b09-4fab-83e1-5d95e2969d35/07738ebe-2c5e-4d6c-960d-1c03f216a3a0/7529e658-b42a-47cb-a23c-d9d350b5d8c4/tile_0010.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "51dae1e198b0e2be9a25", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\7175ae58-2b09-4fab-83e1-5d95e2969d35\\07738ebe-2c5e-4d6c-960d-1c03f216a3a0\\7529e658-b42a-47cb-a23c-d9d350b5d8c4\\tile_0011.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/7175ae58-2b09-4fab-83e1-5d95e2969d35/07738ebe-2c5e-4d6c-960d-1c03f216a3a0/7529e658-b42a-47cb-a23c-d9d350b5d8c4/tile_0011.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "6587704f64f657c9b261", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\7175ae58-2b09-4fab-83e1-5d95e2969d35\\07738ebe-2c5e-4d6c-960d-1c03f216a3a0\\7529e658-b42a-47cb-a23c-d9d350b5d8c4\\tile_0012.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/7175ae58-2b09-4fab-83e1-5d95e2969d35/07738ebe-2c5e-4d6c-960d-1c03f216a3a0/7529e658-b42a-47cb-a23c-d9d350b5d8c4/tile_0012.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "b7965c4fe187fb9a6e72", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\7175ae58-2b09-4fab-83e1-5d95e2969d35\\07738ebe-2c5e-4d6c-960d-1c03f216a3a0\\7529e658-b42a-47cb-a23c-d9d350b5d8c4\\tile_0013.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/7175ae58-2b09-4fab-83e1-5d95e2969d35/07738ebe-2c5e-4d6c-960d-1c03f216a3a0/7529e658-b42a-47cb-a23c-d9d350b5d8c4/tile_0013.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "b54051b8cb4ca92387b2", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\7175ae58-2b09-4fab-83e1-5d95e2969d35\\07738ebe-2c5e-4d6c-960d-1c03f216a3a0\\7529e658-b42a-47cb-a23c-d9d350b5d8c4\\tile_0014.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/7175ae58-2b09-4fab-83e1-5d95e2969d35/07738ebe-2c5e-4d6c-960d-1c03f216a3a0/7529e658-b42a-47cb-a23c-d9d350b5d8c4/tile_0014.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "85abe6c3be8c5f60f542", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\7175ae58-2b09-4fab-83e1-5d95e2969d35\\07738ebe-2c5e-4d6c-960d-1c03f216a3a0\\7529e658-b42a-47cb-a23c-d9d350b5d8c4\\tile_0015.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/7175ae58-2b09-4fab-83e1-5d95e2969d35/07738ebe-2c5e-4d6c-960d-1c03f216a3a0/7529e658-b42a-47cb-a23c-d9d350b5d8c4/tile_0015.tif", - "severity": "critical" - }, - { - "action": "quarantine", - "code": "manifest.zero_bbox", - "field": "bounds", - "item_id": "b6b16941c235d9cb21df", - "message": "Manifest declares a zero-area bounding box", - "path": "storage/tiles/a7a94d0b-9b27-49bd-9e44-97b0b75677ad/e2a3f62a-76f0-4611-81a3-d2ca948cda75/6e53d525-f603-4eb3-8bf7-05da59832013/manifest.json", - "severity": "major" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "20e3d2bb3ee9bb98f8b2", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\a7a94d0b-9b27-49bd-9e44-97b0b75677ad\\e2a3f62a-76f0-4611-81a3-d2ca948cda75\\6e53d525-f603-4eb3-8bf7-05da59832013\\tile_0000.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/a7a94d0b-9b27-49bd-9e44-97b0b75677ad/e2a3f62a-76f0-4611-81a3-d2ca948cda75/6e53d525-f603-4eb3-8bf7-05da59832013/tile_0000.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "4e4919deb1ec3b7df24d", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\a7a94d0b-9b27-49bd-9e44-97b0b75677ad\\e2a3f62a-76f0-4611-81a3-d2ca948cda75\\6e53d525-f603-4eb3-8bf7-05da59832013\\tile_0001.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/a7a94d0b-9b27-49bd-9e44-97b0b75677ad/e2a3f62a-76f0-4611-81a3-d2ca948cda75/6e53d525-f603-4eb3-8bf7-05da59832013/tile_0001.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "0f87eb34f3f0359638a2", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\a7a94d0b-9b27-49bd-9e44-97b0b75677ad\\e2a3f62a-76f0-4611-81a3-d2ca948cda75\\6e53d525-f603-4eb3-8bf7-05da59832013\\tile_0002.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/a7a94d0b-9b27-49bd-9e44-97b0b75677ad/e2a3f62a-76f0-4611-81a3-d2ca948cda75/6e53d525-f603-4eb3-8bf7-05da59832013/tile_0002.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "e5f08ed47ebbc2dc539d", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\a7a94d0b-9b27-49bd-9e44-97b0b75677ad\\e2a3f62a-76f0-4611-81a3-d2ca948cda75\\6e53d525-f603-4eb3-8bf7-05da59832013\\tile_0003.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/a7a94d0b-9b27-49bd-9e44-97b0b75677ad/e2a3f62a-76f0-4611-81a3-d2ca948cda75/6e53d525-f603-4eb3-8bf7-05da59832013/tile_0003.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "776ded90bfd4c9e66373", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\a7a94d0b-9b27-49bd-9e44-97b0b75677ad\\e2a3f62a-76f0-4611-81a3-d2ca948cda75\\6e53d525-f603-4eb3-8bf7-05da59832013\\tile_0004.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/a7a94d0b-9b27-49bd-9e44-97b0b75677ad/e2a3f62a-76f0-4611-81a3-d2ca948cda75/6e53d525-f603-4eb3-8bf7-05da59832013/tile_0004.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "2a37d92cc1f4c7760875", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\a7a94d0b-9b27-49bd-9e44-97b0b75677ad\\e2a3f62a-76f0-4611-81a3-d2ca948cda75\\6e53d525-f603-4eb3-8bf7-05da59832013\\tile_0005.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/a7a94d0b-9b27-49bd-9e44-97b0b75677ad/e2a3f62a-76f0-4611-81a3-d2ca948cda75/6e53d525-f603-4eb3-8bf7-05da59832013/tile_0005.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "d3d5a58eb923e4e58858", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\a7a94d0b-9b27-49bd-9e44-97b0b75677ad\\e2a3f62a-76f0-4611-81a3-d2ca948cda75\\6e53d525-f603-4eb3-8bf7-05da59832013\\tile_0006.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/a7a94d0b-9b27-49bd-9e44-97b0b75677ad/e2a3f62a-76f0-4611-81a3-d2ca948cda75/6e53d525-f603-4eb3-8bf7-05da59832013/tile_0006.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "91c929ee528e638a6a76", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\a7a94d0b-9b27-49bd-9e44-97b0b75677ad\\e2a3f62a-76f0-4611-81a3-d2ca948cda75\\6e53d525-f603-4eb3-8bf7-05da59832013\\tile_0007.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/a7a94d0b-9b27-49bd-9e44-97b0b75677ad/e2a3f62a-76f0-4611-81a3-d2ca948cda75/6e53d525-f603-4eb3-8bf7-05da59832013/tile_0007.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "e480cf83cf5db4b2e52d", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\a7a94d0b-9b27-49bd-9e44-97b0b75677ad\\e2a3f62a-76f0-4611-81a3-d2ca948cda75\\6e53d525-f603-4eb3-8bf7-05da59832013\\tile_0008.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/a7a94d0b-9b27-49bd-9e44-97b0b75677ad/e2a3f62a-76f0-4611-81a3-d2ca948cda75/6e53d525-f603-4eb3-8bf7-05da59832013/tile_0008.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "c0ad18065477ffaad4ac", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\a7a94d0b-9b27-49bd-9e44-97b0b75677ad\\e2a3f62a-76f0-4611-81a3-d2ca948cda75\\6e53d525-f603-4eb3-8bf7-05da59832013\\tile_0009.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/a7a94d0b-9b27-49bd-9e44-97b0b75677ad/e2a3f62a-76f0-4611-81a3-d2ca948cda75/6e53d525-f603-4eb3-8bf7-05da59832013/tile_0009.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "ba9cbe3cdf31c09754b6", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\a7a94d0b-9b27-49bd-9e44-97b0b75677ad\\e2a3f62a-76f0-4611-81a3-d2ca948cda75\\6e53d525-f603-4eb3-8bf7-05da59832013\\tile_0010.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/a7a94d0b-9b27-49bd-9e44-97b0b75677ad/e2a3f62a-76f0-4611-81a3-d2ca948cda75/6e53d525-f603-4eb3-8bf7-05da59832013/tile_0010.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "74791aaeb46bd8705f5c", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\a7a94d0b-9b27-49bd-9e44-97b0b75677ad\\e2a3f62a-76f0-4611-81a3-d2ca948cda75\\6e53d525-f603-4eb3-8bf7-05da59832013\\tile_0011.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/a7a94d0b-9b27-49bd-9e44-97b0b75677ad/e2a3f62a-76f0-4611-81a3-d2ca948cda75/6e53d525-f603-4eb3-8bf7-05da59832013/tile_0011.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "e6494b03753f6de23316", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\a7a94d0b-9b27-49bd-9e44-97b0b75677ad\\e2a3f62a-76f0-4611-81a3-d2ca948cda75\\6e53d525-f603-4eb3-8bf7-05da59832013\\tile_0012.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/a7a94d0b-9b27-49bd-9e44-97b0b75677ad/e2a3f62a-76f0-4611-81a3-d2ca948cda75/6e53d525-f603-4eb3-8bf7-05da59832013/tile_0012.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "c2301617d835cbe7a9da", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\a7a94d0b-9b27-49bd-9e44-97b0b75677ad\\e2a3f62a-76f0-4611-81a3-d2ca948cda75\\6e53d525-f603-4eb3-8bf7-05da59832013\\tile_0013.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/a7a94d0b-9b27-49bd-9e44-97b0b75677ad/e2a3f62a-76f0-4611-81a3-d2ca948cda75/6e53d525-f603-4eb3-8bf7-05da59832013/tile_0013.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "712708cfd7b54f652c1f", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\a7a94d0b-9b27-49bd-9e44-97b0b75677ad\\e2a3f62a-76f0-4611-81a3-d2ca948cda75\\6e53d525-f603-4eb3-8bf7-05da59832013\\tile_0014.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/a7a94d0b-9b27-49bd-9e44-97b0b75677ad/e2a3f62a-76f0-4611-81a3-d2ca948cda75/6e53d525-f603-4eb3-8bf7-05da59832013/tile_0014.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "bfbadaaae125e34b5828", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\a7a94d0b-9b27-49bd-9e44-97b0b75677ad\\e2a3f62a-76f0-4611-81a3-d2ca948cda75\\6e53d525-f603-4eb3-8bf7-05da59832013\\tile_0015.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/a7a94d0b-9b27-49bd-9e44-97b0b75677ad/e2a3f62a-76f0-4611-81a3-d2ca948cda75/6e53d525-f603-4eb3-8bf7-05da59832013/tile_0015.tif", - "severity": "critical" - }, - { - "action": "quarantine", - "code": "manifest.zero_bbox", - "field": "bounds", - "item_id": "04f3407f941cd1dc895e", - "message": "Manifest declares a zero-area bounding box", - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/manifest.json", - "severity": "major" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "4def26f935acc400079e", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0000.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/tile_0000.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "9e093656fa6b9d623331", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0001.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/tile_0001.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "463efcbe145941dc1ded", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0002.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/tile_0002.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "6b1012bfdedb2641eb37", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0003.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/tile_0003.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "71979d432b49d84e9e75", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0004.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/tile_0004.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "649fd55f6d877aa78bb2", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0005.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/tile_0005.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "52e170d64fb1a011de45", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0006.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/tile_0006.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "46628f46cd8911a36f86", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0007.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/tile_0007.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "889b2e92c1aa378722aa", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0008.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/tile_0008.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "67a46403c7fb388bb484", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0009.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/tile_0009.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "25123fae6d918a76ac7a", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0010.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/tile_0010.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "7407fad7de42e36fe791", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0011.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/tile_0011.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "eaa22fd47e90efa7dbdd", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0012.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/tile_0012.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "46aaf33ee50eaa14edfd", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0013.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/tile_0013.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "6d3766eca60a28941699", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0014.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/tile_0014.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "a870f7c9d918ccf7d5a6", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0015.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/tile_0015.tif", - "severity": "critical" - }, - { - "action": "quarantine", - "code": "manifest.zero_bbox", - "field": "bounds", - "item_id": "42f97df8f1716a98cc5a", - "message": "Manifest declares a zero-area bounding box", - "path": "storage/tiles/db240e97-188d-48fd-98f3-7abd9131ffeb/2df0e426-f569-459f-a4ad-d3f42539bc23/f31826fa-10e3-4154-95c2-d89d21813379/manifest.json", - "severity": "major" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "33b3c33cb179ac85ada1", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\db240e97-188d-48fd-98f3-7abd9131ffeb\\2df0e426-f569-459f-a4ad-d3f42539bc23\\f31826fa-10e3-4154-95c2-d89d21813379\\tile_0000.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/db240e97-188d-48fd-98f3-7abd9131ffeb/2df0e426-f569-459f-a4ad-d3f42539bc23/f31826fa-10e3-4154-95c2-d89d21813379/tile_0000.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "346a71885fe0853cfc30", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\db240e97-188d-48fd-98f3-7abd9131ffeb\\2df0e426-f569-459f-a4ad-d3f42539bc23\\f31826fa-10e3-4154-95c2-d89d21813379\\tile_0001.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/db240e97-188d-48fd-98f3-7abd9131ffeb/2df0e426-f569-459f-a4ad-d3f42539bc23/f31826fa-10e3-4154-95c2-d89d21813379/tile_0001.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "6fab06961d3c3d439c73", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\db240e97-188d-48fd-98f3-7abd9131ffeb\\2df0e426-f569-459f-a4ad-d3f42539bc23\\f31826fa-10e3-4154-95c2-d89d21813379\\tile_0002.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/db240e97-188d-48fd-98f3-7abd9131ffeb/2df0e426-f569-459f-a4ad-d3f42539bc23/f31826fa-10e3-4154-95c2-d89d21813379/tile_0002.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "bc61a64bf00351eaa325", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\db240e97-188d-48fd-98f3-7abd9131ffeb\\2df0e426-f569-459f-a4ad-d3f42539bc23\\f31826fa-10e3-4154-95c2-d89d21813379\\tile_0003.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/db240e97-188d-48fd-98f3-7abd9131ffeb/2df0e426-f569-459f-a4ad-d3f42539bc23/f31826fa-10e3-4154-95c2-d89d21813379/tile_0003.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "af6d1e573b5b4b191b87", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\db240e97-188d-48fd-98f3-7abd9131ffeb\\2df0e426-f569-459f-a4ad-d3f42539bc23\\f31826fa-10e3-4154-95c2-d89d21813379\\tile_0004.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/db240e97-188d-48fd-98f3-7abd9131ffeb/2df0e426-f569-459f-a4ad-d3f42539bc23/f31826fa-10e3-4154-95c2-d89d21813379/tile_0004.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "ef9696bc380f7e9dc039", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\db240e97-188d-48fd-98f3-7abd9131ffeb\\2df0e426-f569-459f-a4ad-d3f42539bc23\\f31826fa-10e3-4154-95c2-d89d21813379\\tile_0005.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/db240e97-188d-48fd-98f3-7abd9131ffeb/2df0e426-f569-459f-a4ad-d3f42539bc23/f31826fa-10e3-4154-95c2-d89d21813379/tile_0005.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "e440975ad15713709d14", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\db240e97-188d-48fd-98f3-7abd9131ffeb\\2df0e426-f569-459f-a4ad-d3f42539bc23\\f31826fa-10e3-4154-95c2-d89d21813379\\tile_0006.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/db240e97-188d-48fd-98f3-7abd9131ffeb/2df0e426-f569-459f-a4ad-d3f42539bc23/f31826fa-10e3-4154-95c2-d89d21813379/tile_0006.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "3f1f44d08c10be760fa3", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\db240e97-188d-48fd-98f3-7abd9131ffeb\\2df0e426-f569-459f-a4ad-d3f42539bc23\\f31826fa-10e3-4154-95c2-d89d21813379\\tile_0007.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/db240e97-188d-48fd-98f3-7abd9131ffeb/2df0e426-f569-459f-a4ad-d3f42539bc23/f31826fa-10e3-4154-95c2-d89d21813379/tile_0007.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "bc0e44ce91c97c3723c9", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\db240e97-188d-48fd-98f3-7abd9131ffeb\\2df0e426-f569-459f-a4ad-d3f42539bc23\\f31826fa-10e3-4154-95c2-d89d21813379\\tile_0008.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/db240e97-188d-48fd-98f3-7abd9131ffeb/2df0e426-f569-459f-a4ad-d3f42539bc23/f31826fa-10e3-4154-95c2-d89d21813379/tile_0008.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "9d163f657df866f7a22b", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\db240e97-188d-48fd-98f3-7abd9131ffeb\\2df0e426-f569-459f-a4ad-d3f42539bc23\\f31826fa-10e3-4154-95c2-d89d21813379\\tile_0009.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/db240e97-188d-48fd-98f3-7abd9131ffeb/2df0e426-f569-459f-a4ad-d3f42539bc23/f31826fa-10e3-4154-95c2-d89d21813379/tile_0009.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "c3ecd380ee4499edfd90", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\db240e97-188d-48fd-98f3-7abd9131ffeb\\2df0e426-f569-459f-a4ad-d3f42539bc23\\f31826fa-10e3-4154-95c2-d89d21813379\\tile_0010.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/db240e97-188d-48fd-98f3-7abd9131ffeb/2df0e426-f569-459f-a4ad-d3f42539bc23/f31826fa-10e3-4154-95c2-d89d21813379/tile_0010.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "d46845df780977985a5e", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\db240e97-188d-48fd-98f3-7abd9131ffeb\\2df0e426-f569-459f-a4ad-d3f42539bc23\\f31826fa-10e3-4154-95c2-d89d21813379\\tile_0011.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/db240e97-188d-48fd-98f3-7abd9131ffeb/2df0e426-f569-459f-a4ad-d3f42539bc23/f31826fa-10e3-4154-95c2-d89d21813379/tile_0011.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "38b78e73d14a80e5034a", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\db240e97-188d-48fd-98f3-7abd9131ffeb\\2df0e426-f569-459f-a4ad-d3f42539bc23\\f31826fa-10e3-4154-95c2-d89d21813379\\tile_0012.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/db240e97-188d-48fd-98f3-7abd9131ffeb/2df0e426-f569-459f-a4ad-d3f42539bc23/f31826fa-10e3-4154-95c2-d89d21813379/tile_0012.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "d3c5bdffafb98153e8d9", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\db240e97-188d-48fd-98f3-7abd9131ffeb\\2df0e426-f569-459f-a4ad-d3f42539bc23\\f31826fa-10e3-4154-95c2-d89d21813379\\tile_0013.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/db240e97-188d-48fd-98f3-7abd9131ffeb/2df0e426-f569-459f-a4ad-d3f42539bc23/f31826fa-10e3-4154-95c2-d89d21813379/tile_0013.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "7e850fe24708dda753f0", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\db240e97-188d-48fd-98f3-7abd9131ffeb\\2df0e426-f569-459f-a4ad-d3f42539bc23\\f31826fa-10e3-4154-95c2-d89d21813379\\tile_0014.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/db240e97-188d-48fd-98f3-7abd9131ffeb/2df0e426-f569-459f-a4ad-d3f42539bc23/f31826fa-10e3-4154-95c2-d89d21813379/tile_0014.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "303f7135858218c797ce", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\db240e97-188d-48fd-98f3-7abd9131ffeb\\2df0e426-f569-459f-a4ad-d3f42539bc23\\f31826fa-10e3-4154-95c2-d89d21813379\\tile_0015.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/db240e97-188d-48fd-98f3-7abd9131ffeb/2df0e426-f569-459f-a4ad-d3f42539bc23/f31826fa-10e3-4154-95c2-d89d21813379/tile_0015.tif", - "severity": "critical" - }, - { - "action": "quarantine", - "code": "manifest.zero_bbox", - "field": "bounds", - "item_id": "3838bd5bae003af13690", - "message": "Manifest declares a zero-area bounding box", - "path": "storage/tiles/df217a4e-7f2e-4989-880e-30fb9a7ec645/f6848732-1f78-41ba-967c-11a577112b17/5e0d5f61-e7fb-4d4a-ae96-84b9060554d6/manifest.json", - "severity": "major" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "295dc32a2407bf282a8c", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\df217a4e-7f2e-4989-880e-30fb9a7ec645\\f6848732-1f78-41ba-967c-11a577112b17\\5e0d5f61-e7fb-4d4a-ae96-84b9060554d6\\tile_0000.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/df217a4e-7f2e-4989-880e-30fb9a7ec645/f6848732-1f78-41ba-967c-11a577112b17/5e0d5f61-e7fb-4d4a-ae96-84b9060554d6/tile_0000.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "abd539c47bb02eed552f", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\df217a4e-7f2e-4989-880e-30fb9a7ec645\\f6848732-1f78-41ba-967c-11a577112b17\\5e0d5f61-e7fb-4d4a-ae96-84b9060554d6\\tile_0001.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/df217a4e-7f2e-4989-880e-30fb9a7ec645/f6848732-1f78-41ba-967c-11a577112b17/5e0d5f61-e7fb-4d4a-ae96-84b9060554d6/tile_0001.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "6f3267beda326834d472", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\df217a4e-7f2e-4989-880e-30fb9a7ec645\\f6848732-1f78-41ba-967c-11a577112b17\\5e0d5f61-e7fb-4d4a-ae96-84b9060554d6\\tile_0002.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/df217a4e-7f2e-4989-880e-30fb9a7ec645/f6848732-1f78-41ba-967c-11a577112b17/5e0d5f61-e7fb-4d4a-ae96-84b9060554d6/tile_0002.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "81ca8f6bfc34b1cdcb10", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\df217a4e-7f2e-4989-880e-30fb9a7ec645\\f6848732-1f78-41ba-967c-11a577112b17\\5e0d5f61-e7fb-4d4a-ae96-84b9060554d6\\tile_0003.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/df217a4e-7f2e-4989-880e-30fb9a7ec645/f6848732-1f78-41ba-967c-11a577112b17/5e0d5f61-e7fb-4d4a-ae96-84b9060554d6/tile_0003.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "7192190199b044390815", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\df217a4e-7f2e-4989-880e-30fb9a7ec645\\f6848732-1f78-41ba-967c-11a577112b17\\5e0d5f61-e7fb-4d4a-ae96-84b9060554d6\\tile_0004.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/df217a4e-7f2e-4989-880e-30fb9a7ec645/f6848732-1f78-41ba-967c-11a577112b17/5e0d5f61-e7fb-4d4a-ae96-84b9060554d6/tile_0004.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "b9d3054f0d9a803d09b5", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\df217a4e-7f2e-4989-880e-30fb9a7ec645\\f6848732-1f78-41ba-967c-11a577112b17\\5e0d5f61-e7fb-4d4a-ae96-84b9060554d6\\tile_0005.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/df217a4e-7f2e-4989-880e-30fb9a7ec645/f6848732-1f78-41ba-967c-11a577112b17/5e0d5f61-e7fb-4d4a-ae96-84b9060554d6/tile_0005.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "30a426290bc779af9d6a", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\df217a4e-7f2e-4989-880e-30fb9a7ec645\\f6848732-1f78-41ba-967c-11a577112b17\\5e0d5f61-e7fb-4d4a-ae96-84b9060554d6\\tile_0006.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/df217a4e-7f2e-4989-880e-30fb9a7ec645/f6848732-1f78-41ba-967c-11a577112b17/5e0d5f61-e7fb-4d4a-ae96-84b9060554d6/tile_0006.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "09bc3cdd65af8613dd32", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\df217a4e-7f2e-4989-880e-30fb9a7ec645\\f6848732-1f78-41ba-967c-11a577112b17\\5e0d5f61-e7fb-4d4a-ae96-84b9060554d6\\tile_0007.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/df217a4e-7f2e-4989-880e-30fb9a7ec645/f6848732-1f78-41ba-967c-11a577112b17/5e0d5f61-e7fb-4d4a-ae96-84b9060554d6/tile_0007.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "db688c755ad92613e5b2", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\df217a4e-7f2e-4989-880e-30fb9a7ec645\\f6848732-1f78-41ba-967c-11a577112b17\\5e0d5f61-e7fb-4d4a-ae96-84b9060554d6\\tile_0008.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/df217a4e-7f2e-4989-880e-30fb9a7ec645/f6848732-1f78-41ba-967c-11a577112b17/5e0d5f61-e7fb-4d4a-ae96-84b9060554d6/tile_0008.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "70cfc9a48bb0b6fbe125", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\df217a4e-7f2e-4989-880e-30fb9a7ec645\\f6848732-1f78-41ba-967c-11a577112b17\\5e0d5f61-e7fb-4d4a-ae96-84b9060554d6\\tile_0009.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/df217a4e-7f2e-4989-880e-30fb9a7ec645/f6848732-1f78-41ba-967c-11a577112b17/5e0d5f61-e7fb-4d4a-ae96-84b9060554d6/tile_0009.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "b8160ad197d56e6fefd2", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\df217a4e-7f2e-4989-880e-30fb9a7ec645\\f6848732-1f78-41ba-967c-11a577112b17\\5e0d5f61-e7fb-4d4a-ae96-84b9060554d6\\tile_0010.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/df217a4e-7f2e-4989-880e-30fb9a7ec645/f6848732-1f78-41ba-967c-11a577112b17/5e0d5f61-e7fb-4d4a-ae96-84b9060554d6/tile_0010.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "7815b5ffcca8b258f42e", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\df217a4e-7f2e-4989-880e-30fb9a7ec645\\f6848732-1f78-41ba-967c-11a577112b17\\5e0d5f61-e7fb-4d4a-ae96-84b9060554d6\\tile_0011.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/df217a4e-7f2e-4989-880e-30fb9a7ec645/f6848732-1f78-41ba-967c-11a577112b17/5e0d5f61-e7fb-4d4a-ae96-84b9060554d6/tile_0011.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "cbce46d3556b5408ccf0", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\df217a4e-7f2e-4989-880e-30fb9a7ec645\\f6848732-1f78-41ba-967c-11a577112b17\\5e0d5f61-e7fb-4d4a-ae96-84b9060554d6\\tile_0012.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/df217a4e-7f2e-4989-880e-30fb9a7ec645/f6848732-1f78-41ba-967c-11a577112b17/5e0d5f61-e7fb-4d4a-ae96-84b9060554d6/tile_0012.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "43a18bee9bf250564490", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\df217a4e-7f2e-4989-880e-30fb9a7ec645\\f6848732-1f78-41ba-967c-11a577112b17\\5e0d5f61-e7fb-4d4a-ae96-84b9060554d6\\tile_0013.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/df217a4e-7f2e-4989-880e-30fb9a7ec645/f6848732-1f78-41ba-967c-11a577112b17/5e0d5f61-e7fb-4d4a-ae96-84b9060554d6/tile_0013.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "dff9cee5f0f875a45247", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\df217a4e-7f2e-4989-880e-30fb9a7ec645\\f6848732-1f78-41ba-967c-11a577112b17\\5e0d5f61-e7fb-4d4a-ae96-84b9060554d6\\tile_0014.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/df217a4e-7f2e-4989-880e-30fb9a7ec645/f6848732-1f78-41ba-967c-11a577112b17/5e0d5f61-e7fb-4d4a-ae96-84b9060554d6/tile_0014.tif", - "severity": "critical" - }, - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "item_id": "fbe412d93aefe8bbe414", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\df217a4e-7f2e-4989-880e-30fb9a7ec645\\f6848732-1f78-41ba-967c-11a577112b17\\5e0d5f61-e7fb-4d4a-ae96-84b9060554d6\\tile_0015.tif' not recognized as being in a supported file format.", - "path": "storage/tiles/df217a4e-7f2e-4989-880e-30fb9a7ec645/f6848732-1f78-41ba-967c-11a577112b17/5e0d5f61-e7fb-4d4a-ae96-84b9060554d6/tile_0015.tif", - "severity": "critical" - }, - { - "action": "requires review", - "code": "freshness.missing", - "item_id": "867763fe8f71b713acdd", - "message": "Source-labelled item has no declared observation timestamp", - "path": "storage/uploads/30e69368-3047-4131-9a49-137351db5848/raster/f770f213-a474-4a0a-bed0-aca6d9238ed1/f770f213-a474-4a0a-bed0-aca6d9238ed1_dhmvii_terrain_5m_abefd0caf44e.tif", - "severity": "minor" - }, - { - "action": "requires review", - "code": "freshness.missing", - "item_id": "ce14b6ac0563dfad06b7", - "message": "Source-labelled item has no declared observation timestamp", - "path": "storage/uploads/6abbf506-a386-4451-8cd9-d595bc995d51/raster/76b6fcf4-29d4-4906-8687-a46bfe16be63/76b6fcf4-29d4-4906-8687-a46bfe16be63_dhmvii_terrain_5m_25afc05778f0.tif", - "severity": "minor" - }, - { - "action": "requires review", - "code": "freshness.missing", - "item_id": "2237c5ae9f8fce22c984", - "message": "Source-labelled item has no declared observation timestamp", - "path": "storage/uploads/bf96b94e-01aa-4912-9286-75a318cfc2ab/raster/12441c43-80db-43d6-bebf-8e4ff2207338/12441c43-80db-43d6-bebf-8e4ff2207338_dhmvii_terrain_5m_fc9d87c14310.tif", - "severity": "minor" - }, - { - "action": "requires review", - "code": "freshness.missing", - "item_id": "97e48e54218e7f126d40", - "message": "Source-labelled item has no declared observation timestamp", - "path": "storage/uploads/f7e7ba0c-e490-46c8-8467-28c9176ede55/raster/771bf37d-424a-4e56-98a5-35657f52674c/771bf37d-424a-4e56-98a5-35657f52674c_dhmvii_terrain_5m_9cde89f97e71.tif", - "severity": "minor" - }, - { - "action": "requires review", - "code": "freshness.missing", - "item_id": "4e742df38492234458e9", - "message": "Source-labelled item has no declared observation timestamp", - "path": "storage/uploads/fead1267-e2f8-4e25-af69-9333665e87e7/raster/4c2100cd-b167-4494-bfd4-78a378d3423c/4c2100cd-b167-4494-bfd4-78a378d3423c_dhmvii_terrain_5m_a193c984774e.tif", - "severity": "minor" - } - ], - "anomaly_category_counts": { - "freshness.missing": 29, - "lineage.missing": 577, - "manifest.zero_bbox": 6, - "raster.unreadable": 96, - "scope.unreachable": 3 - }, - "anomaly_count": 711, - "completed_at": "2026-08-30T00:47:12.278274+00:00", - "dataset_summary": { - "geointel.artifact.generic": { - "anomaly_count": 491, - "item_count": 620, - "paths": [ - "artifacts/codex-review/v31/contact_sheet_001.png", - "artifacts/codex-review/v31/qa.json", - "artifacts/codex-review/v33-flanders/candidate_error_contact_sheet.png", - "artifacts/codex-review/v33-flanders/genk.png", - "artifacts/codex-review/v33-flanders/lokeren.png", - "artifacts/codex-review/v33-flanders/ostend.png", - "artifacts/detection-calibration-smoke/20260801T130251Z/evidence/calibration_evidence_requests.tsv", - "artifacts/detection-calibration-smoke/20260801T130251Z/evidence/calibration_evidence_review.html", - "artifacts/detection-calibration-smoke/20260801T130251Z/evidence/calibration_evidence_summary.json", - "artifacts/detection-calibration-smoke/20260801T130251Z/evidence/threshold_0p15_qc-low_evidence_response.json", - "artifacts/detection-calibration-smoke/20260801T130251Z/evidence/threshold_0p35_qc-high_evidence_response.json", - "artifacts/detection-calibration-smoke/20260801T130251Z/mock-bin/curl", - 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"units": null - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\277180a4-cd74-42ed-a231-0d194b3fca9f\\0f96a4f7-6b24-4969-9564-abbde30b5a51\\9199f079-42fc-48cc-86ff-d1072f801932\\tile_0009.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "contract": { - "key": "geointel.raster.geotiff", - "version": "1.0.0" - }, - "crs": null, - "duplicate_group": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "empty_content": false, - "freshness": { - "reason": "no_declared_source_timestamp", - "status": "unknown" - }, - "geometry_validation": null, - "item_id": "f87e566976251b0ddd3d", - "lineage": null, - "modified_at": "2026-08-01T15:45:08.533397+00:00", - "near_duplicate_fingerprint": null, - "path": "storage/tiles/277180a4-cd74-42ed-a231-0d194b3fca9f/0f96a4f7-6b24-4969-9564-abbde30b5a51/9199f079-42fc-48cc-86ff-d1072f801932/tile_0009.tif", - "read_status": "unreadable", - "recommended_action": "unavailable or unreadable", - "resolution": null, - "schema_conformity": "invalid", - "sha256": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "size_bytes": 4, - "source": "unknown", - "spatial_coverage": null, - "status": "examined", - "temporal_coverage": null, - "units": null - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\277180a4-cd74-42ed-a231-0d194b3fca9f\\0f96a4f7-6b24-4969-9564-abbde30b5a51\\9199f079-42fc-48cc-86ff-d1072f801932\\tile_0010.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "contract": { - "key": "geointel.raster.geotiff", - "version": "1.0.0" - }, - "crs": null, - "duplicate_group": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "empty_content": false, - "freshness": { - "reason": "no_declared_source_timestamp", - 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"severity": "critical" - } - ], - "contract": { - "key": "geointel.raster.geotiff", - "version": "1.0.0" - }, - "crs": null, - "duplicate_group": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "empty_content": false, - "freshness": { - "reason": "no_declared_source_timestamp", - "status": "unknown" - }, - "geometry_validation": null, - "item_id": "2ec9764c5631b5c7a1b4", - "lineage": null, - "modified_at": "2026-08-01T15:45:08.534397+00:00", - "near_duplicate_fingerprint": null, - "path": "storage/tiles/277180a4-cd74-42ed-a231-0d194b3fca9f/0f96a4f7-6b24-4969-9564-abbde30b5a51/9199f079-42fc-48cc-86ff-d1072f801932/tile_0011.tif", - "read_status": "unreadable", - "recommended_action": "unavailable or unreadable", - "resolution": null, - "schema_conformity": "invalid", - "sha256": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "size_bytes": 4, - "source": "unknown", - "spatial_coverage": null, - "status": "examined", - "temporal_coverage": null, - "units": null - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\277180a4-cd74-42ed-a231-0d194b3fca9f\\0f96a4f7-6b24-4969-9564-abbde30b5a51\\9199f079-42fc-48cc-86ff-d1072f801932\\tile_0012.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "contract": { - "key": "geointel.raster.geotiff", - "version": "1.0.0" - }, - "crs": null, - "duplicate_group": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "empty_content": false, - "freshness": { - "reason": "no_declared_source_timestamp", - "status": "unknown" - }, - "geometry_validation": null, - "item_id": "ac9cbb366a7c16a79b44", - "lineage": null, - "modified_at": "2026-08-01T15:45:08.535398+00:00", - "near_duplicate_fingerprint": null, - "path": "storage/tiles/277180a4-cd74-42ed-a231-0d194b3fca9f/0f96a4f7-6b24-4969-9564-abbde30b5a51/9199f079-42fc-48cc-86ff-d1072f801932/tile_0012.tif", - "read_status": "unreadable", - "recommended_action": "unavailable or unreadable", - "resolution": null, - "schema_conformity": "invalid", - "sha256": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "size_bytes": 4, - "source": "unknown", - "spatial_coverage": null, - "status": "examined", - "temporal_coverage": null, - "units": null - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\277180a4-cd74-42ed-a231-0d194b3fca9f\\0f96a4f7-6b24-4969-9564-abbde30b5a51\\9199f079-42fc-48cc-86ff-d1072f801932\\tile_0013.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "contract": { - "key": "geointel.raster.geotiff", - "version": "1.0.0" - }, - "crs": null, - "duplicate_group": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "empty_content": false, - "freshness": { - "reason": "no_declared_source_timestamp", - "status": "unknown" - }, - "geometry_validation": null, - "item_id": "5adaba8e404c16d70d1b", - "lineage": null, - "modified_at": "2026-08-01T15:45:08.536394+00:00", - "near_duplicate_fingerprint": null, - "path": "storage/tiles/277180a4-cd74-42ed-a231-0d194b3fca9f/0f96a4f7-6b24-4969-9564-abbde30b5a51/9199f079-42fc-48cc-86ff-d1072f801932/tile_0013.tif", - "read_status": "unreadable", - "recommended_action": "unavailable or unreadable", - "resolution": null, - "schema_conformity": "invalid", - "sha256": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "size_bytes": 4, - "source": "unknown", - "spatial_coverage": null, - "status": "examined", - "temporal_coverage": null, - "units": null - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\277180a4-cd74-42ed-a231-0d194b3fca9f\\0f96a4f7-6b24-4969-9564-abbde30b5a51\\9199f079-42fc-48cc-86ff-d1072f801932\\tile_0014.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "contract": { - "key": "geointel.raster.geotiff", - "version": "1.0.0" - }, - "crs": null, - "duplicate_group": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "empty_content": false, - "freshness": { - "reason": "no_declared_source_timestamp", - "status": "unknown" - }, - "geometry_validation": null, - "item_id": "e61c40ce9d3d2b9d369d", - "lineage": null, - "modified_at": "2026-08-01T15:45:08.536394+00:00", - "near_duplicate_fingerprint": null, - "path": "storage/tiles/277180a4-cd74-42ed-a231-0d194b3fca9f/0f96a4f7-6b24-4969-9564-abbde30b5a51/9199f079-42fc-48cc-86ff-d1072f801932/tile_0014.tif", - "read_status": "unreadable", - "recommended_action": "unavailable or unreadable", - "resolution": null, - "schema_conformity": "invalid", - "sha256": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "size_bytes": 4, - "source": "unknown", - "spatial_coverage": null, - "status": "examined", - "temporal_coverage": null, - "units": null - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\277180a4-cd74-42ed-a231-0d194b3fca9f\\0f96a4f7-6b24-4969-9564-abbde30b5a51\\9199f079-42fc-48cc-86ff-d1072f801932\\tile_0015.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "contract": { - "key": "geointel.raster.geotiff", - "version": "1.0.0" - }, - "crs": null, - "duplicate_group": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "empty_content": false, - "freshness": { - "reason": "no_declared_source_timestamp", - "status": "unknown" - }, - "geometry_validation": null, - "item_id": "a814da6efe81f095c9e3", - "lineage": null, - "modified_at": "2026-08-01T15:45:08.537394+00:00", - "near_duplicate_fingerprint": null, - "path": "storage/tiles/277180a4-cd74-42ed-a231-0d194b3fca9f/0f96a4f7-6b24-4969-9564-abbde30b5a51/9199f079-42fc-48cc-86ff-d1072f801932/tile_0015.tif", - "read_status": "unreadable", - "recommended_action": "unavailable or unreadable", - "resolution": null, - "schema_conformity": "invalid", - "sha256": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "size_bytes": 4, - "source": "unknown", - "spatial_coverage": null, - "status": "examined", - "temporal_coverage": null, - "units": null - }, - { - "anomalies": [ - { - "action": "quarantine", - "code": "manifest.zero_bbox", - "field": "bounds", - "message": "Manifest declares a zero-area bounding box", - "severity": "major" - } - ], - "contract": { - "key": "geointel.artifact.generic", - "version": "1.0.0" - }, - "crs": "EPSG:31370", - "duplicate_group": null, - "empty_content": false, - "freshness": { - "method": "declared_metadata", - "observed_at": "2026-07-26T03:04:42.542754+00:00", - "status": "declared" - }, - "geometry_validation": null, - "item_id": "1500315e2bdebe9d3462", - "lineage": { - "source_dataset_id": "07738ebe-2c5e-4d6c-960d-1c03f216a3a0", - "source_raster_id": "07738ebe-2c5e-4d6c-960d-1c03f216a3a0" - }, - "modified_at": "2026-07-27T21:27:15.447369+00:00", - "near_duplicate_fingerprint": "39e74d37a24b514525dfba54aa6276689c023e4141f60ef1e33a4936f0012912", - "path": "storage/tiles/7175ae58-2b09-4fab-83e1-5d95e2969d35/07738ebe-2c5e-4d6c-960d-1c03f216a3a0/7529e658-b42a-47cb-a23c-d9d350b5d8c4/manifest.json", - "read_status": "readable", - "recommended_action": "quarantine", - "resolution": null, - "schema_conformity": "valid", - "sha256": "d0ec133a20f3fb265b91e74a3419f9bc32efd38b14dfd3c76c58cbf6c4f7010e", - "size_bytes": 8664, - "source": "unknown", - "spatial_coverage": { - "bbox": [ - 0.0, - 0.0, - 0.0, - 0.0 - ], - "crs": "EPSG:31370" - }, - "status": "examined", - "temporal_coverage": null, - "units": null - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\7175ae58-2b09-4fab-83e1-5d95e2969d35\\07738ebe-2c5e-4d6c-960d-1c03f216a3a0\\7529e658-b42a-47cb-a23c-d9d350b5d8c4\\tile_0000.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "contract": { - "key": "geointel.raster.geotiff", - "version": "1.0.0" - }, - "crs": null, - "duplicate_group": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "empty_content": false, - "freshness": { - "reason": "no_declared_source_timestamp", - "status": "unknown" - }, - "geometry_validation": null, - "item_id": "82177cf3088b3fae2281", - "lineage": null, - "modified_at": "2026-07-27T21:27:15.655715+00:00", - "near_duplicate_fingerprint": null, - "path": "storage/tiles/7175ae58-2b09-4fab-83e1-5d95e2969d35/07738ebe-2c5e-4d6c-960d-1c03f216a3a0/7529e658-b42a-47cb-a23c-d9d350b5d8c4/tile_0000.tif", - "read_status": "unreadable", - "recommended_action": "unavailable or unreadable", - "resolution": null, - "schema_conformity": "invalid", - "sha256": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "size_bytes": 4, - "source": "unknown", - "spatial_coverage": null, - "status": "examined", - "temporal_coverage": null, - 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"units": null - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\7175ae58-2b09-4fab-83e1-5d95e2969d35\\07738ebe-2c5e-4d6c-960d-1c03f216a3a0\\7529e658-b42a-47cb-a23c-d9d350b5d8c4\\tile_0007.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "contract": { - "key": "geointel.raster.geotiff", - "version": "1.0.0" - }, - "crs": null, - "duplicate_group": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "empty_content": false, - "freshness": { - "reason": "no_declared_source_timestamp", - "status": "unknown" - }, - "geometry_validation": null, - "item_id": "90c5c1cbd336f0758242", - "lineage": null, - "modified_at": "2026-07-27T21:27:15.530919+00:00", - "near_duplicate_fingerprint": null, - "path": "storage/tiles/7175ae58-2b09-4fab-83e1-5d95e2969d35/07738ebe-2c5e-4d6c-960d-1c03f216a3a0/7529e658-b42a-47cb-a23c-d9d350b5d8c4/tile_0007.tif", - 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"units": null - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\7175ae58-2b09-4fab-83e1-5d95e2969d35\\07738ebe-2c5e-4d6c-960d-1c03f216a3a0\\7529e658-b42a-47cb-a23c-d9d350b5d8c4\\tile_0010.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "contract": { - "key": "geointel.raster.geotiff", - "version": "1.0.0" - }, - "crs": null, - "duplicate_group": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "empty_content": false, - "freshness": { - "reason": "no_declared_source_timestamp", - "status": "unknown" - }, - "geometry_validation": null, - "item_id": "3c46ab42aef67799f868", - "lineage": null, - "modified_at": "2026-07-27T21:27:15.608789+00:00", - "near_duplicate_fingerprint": null, - "path": "storage/tiles/7175ae58-2b09-4fab-83e1-5d95e2969d35/07738ebe-2c5e-4d6c-960d-1c03f216a3a0/7529e658-b42a-47cb-a23c-d9d350b5d8c4/tile_0010.tif", - "read_status": "unreadable", - "recommended_action": "unavailable or unreadable", - "resolution": null, - "schema_conformity": "invalid", - "sha256": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "size_bytes": 4, - "source": "unknown", - "spatial_coverage": null, - "status": "examined", - "temporal_coverage": null, - "units": null - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\7175ae58-2b09-4fab-83e1-5d95e2969d35\\07738ebe-2c5e-4d6c-960d-1c03f216a3a0\\7529e658-b42a-47cb-a23c-d9d350b5d8c4\\tile_0011.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "contract": { - "key": "geointel.raster.geotiff", - "version": "1.0.0" - }, - "crs": null, - "duplicate_group": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "empty_content": false, - "freshness": { - "reason": "no_declared_source_timestamp", - "status": "unknown" - }, - "geometry_validation": null, - "item_id": "51dae1e198b0e2be9a25", - "lineage": null, - "modified_at": "2026-07-27T21:27:15.624404+00:00", - "near_duplicate_fingerprint": null, - "path": "storage/tiles/7175ae58-2b09-4fab-83e1-5d95e2969d35/07738ebe-2c5e-4d6c-960d-1c03f216a3a0/7529e658-b42a-47cb-a23c-d9d350b5d8c4/tile_0011.tif", - "read_status": "unreadable", - "recommended_action": "unavailable or unreadable", - "resolution": null, - "schema_conformity": "invalid", - "sha256": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "size_bytes": 4, - "source": "unknown", - "spatial_coverage": null, - "status": "examined", - "temporal_coverage": null, - "units": null - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\7175ae58-2b09-4fab-83e1-5d95e2969d35\\07738ebe-2c5e-4d6c-960d-1c03f216a3a0\\7529e658-b42a-47cb-a23c-d9d350b5d8c4\\tile_0012.tif' not recognized as being in a supported file format.", - 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"message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\a7a94d0b-9b27-49bd-9e44-97b0b75677ad\\e2a3f62a-76f0-4611-81a3-d2ca948cda75\\6e53d525-f603-4eb3-8bf7-05da59832013\\tile_0002.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "contract": { - "key": "geointel.raster.geotiff", - "version": "1.0.0" - }, - "crs": null, - "duplicate_group": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "empty_content": false, - "freshness": { - "reason": "no_declared_source_timestamp", - "status": "unknown" - }, - "geometry_validation": null, - "item_id": "0f87eb34f3f0359638a2", - "lineage": null, - "modified_at": "2026-07-27T21:27:15.759978+00:00", - "near_duplicate_fingerprint": null, - "path": "storage/tiles/a7a94d0b-9b27-49bd-9e44-97b0b75677ad/e2a3f62a-76f0-4611-81a3-d2ca948cda75/6e53d525-f603-4eb3-8bf7-05da59832013/tile_0002.tif", - "read_status": "unreadable", - "recommended_action": "unavailable or unreadable", - "resolution": null, - 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} - ], - "contract": { - "key": "geointel.raster.geotiff", - "version": "1.0.0" - }, - "crs": null, - "duplicate_group": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "empty_content": false, - "freshness": { - "reason": "no_declared_source_timestamp", - "status": "unknown" - }, - "geometry_validation": null, - "item_id": "776ded90bfd4c9e66373", - "lineage": null, - "modified_at": "2026-07-27T21:27:15.687685+00:00", - "near_duplicate_fingerprint": null, - "path": "storage/tiles/a7a94d0b-9b27-49bd-9e44-97b0b75677ad/e2a3f62a-76f0-4611-81a3-d2ca948cda75/6e53d525-f603-4eb3-8bf7-05da59832013/tile_0004.tif", - "read_status": "unreadable", - "recommended_action": "unavailable or unreadable", - "resolution": null, - "schema_conformity": "invalid", - "sha256": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "size_bytes": 4, - "source": "unknown", - "spatial_coverage": null, - "status": "examined", - "temporal_coverage": null, - "units": null - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\a7a94d0b-9b27-49bd-9e44-97b0b75677ad\\e2a3f62a-76f0-4611-81a3-d2ca948cda75\\6e53d525-f603-4eb3-8bf7-05da59832013\\tile_0005.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "contract": { - "key": "geointel.raster.geotiff", - "version": "1.0.0" - }, - "crs": null, - "duplicate_group": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "empty_content": false, - "freshness": { - "reason": "no_declared_source_timestamp", - "status": "unknown" - }, - "geometry_validation": null, - "item_id": "2a37d92cc1f4c7760875", - "lineage": null, - "modified_at": "2026-07-27T21:27:15.913115+00:00", - "near_duplicate_fingerprint": null, - "path": "storage/tiles/a7a94d0b-9b27-49bd-9e44-97b0b75677ad/e2a3f62a-76f0-4611-81a3-d2ca948cda75/6e53d525-f603-4eb3-8bf7-05da59832013/tile_0005.tif", - 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"read_status": "unreadable", - "recommended_action": "unavailable or unreadable", - "resolution": null, - "schema_conformity": "invalid", - "sha256": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "size_bytes": 4, - "source": "unknown", - "spatial_coverage": null, - "status": "examined", - "temporal_coverage": null, - "units": null - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\a7a94d0b-9b27-49bd-9e44-97b0b75677ad\\e2a3f62a-76f0-4611-81a3-d2ca948cda75\\6e53d525-f603-4eb3-8bf7-05da59832013\\tile_0015.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "contract": { - "key": "geointel.raster.geotiff", - "version": "1.0.0" - }, - "crs": null, - "duplicate_group": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "empty_content": false, - "freshness": { - "reason": "no_declared_source_timestamp", - 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"duplicate_group": null, - "empty_content": false, - "freshness": { - "method": "declared_metadata", - "observed_at": "2026-08-01T15:46:23.988597+00:00", - "status": "declared" - }, - "geometry_validation": null, - "item_id": "04f3407f941cd1dc895e", - "lineage": { - "source_dataset_id": "c0fc6968-9c5b-499f-a095-0fc91a18501d", - "source_raster_id": "c0fc6968-9c5b-499f-a095-0fc91a18501d" - }, - "modified_at": "2026-08-01T15:46:23.988429+00:00", - "near_duplicate_fingerprint": "1d5ce24da57b028bb377356938f4daf8320a019e9258a65637259b1460640b42", - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/manifest.json", - "read_status": "readable", - "recommended_action": "quarantine", - "resolution": null, - "schema_conformity": "valid", - "sha256": "e4cd24c2b2a3bfc6fc984a41a1c40602aa4da694bc71eaca60c8ee97b0f9ae24", - "size_bytes": 8664, - "source": "unknown", - "spatial_coverage": { - "bbox": [ - 0.0, - 0.0, - 0.0, - 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"read_status": "unreadable", - "recommended_action": "unavailable or unreadable", - "resolution": null, - "schema_conformity": "invalid", - "sha256": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "size_bytes": 4, - "source": "unknown", - "spatial_coverage": null, - "status": "examined", - "temporal_coverage": null, - "units": null - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0001.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "contract": { - "key": "geointel.raster.geotiff", - "version": "1.0.0" - }, - "crs": null, - "duplicate_group": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "empty_content": false, - "freshness": { - "reason": "no_declared_source_timestamp", - "status": "unknown" - }, - "geometry_validation": null, - "item_id": "9e093656fa6b9d623331", - "lineage": null, - "modified_at": "2026-08-01T15:46:23.972431+00:00", - "near_duplicate_fingerprint": null, - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/tile_0001.tif", - "read_status": "unreadable", - "recommended_action": "unavailable or unreadable", - "resolution": null, - "schema_conformity": "invalid", - "sha256": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "size_bytes": 4, - "source": "unknown", - "spatial_coverage": null, - "status": "examined", - "temporal_coverage": null, - "units": null - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0002.tif' not recognized as being in a supported file format.", - 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"units": null - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0003.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "contract": { - "key": "geointel.raster.geotiff", - "version": "1.0.0" - }, - "crs": null, - "duplicate_group": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "empty_content": false, - "freshness": { - "reason": "no_declared_source_timestamp", - "status": "unknown" - }, - "geometry_validation": null, - "item_id": "6b1012bfdedb2641eb37", - "lineage": null, - "modified_at": "2026-08-01T15:46:23.975429+00:00", - "near_duplicate_fingerprint": null, - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/tile_0003.tif", - 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"units": null - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0009.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "contract": { - "key": "geointel.raster.geotiff", - "version": "1.0.0" - }, - "crs": null, - "duplicate_group": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "empty_content": false, - "freshness": { - "reason": "no_declared_source_timestamp", - "status": "unknown" - }, - "geometry_validation": null, - "item_id": "67a46403c7fb388bb484", - "lineage": null, - "modified_at": "2026-08-01T15:46:23.980432+00:00", - "near_duplicate_fingerprint": null, - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/tile_0009.tif", - "read_status": "unreadable", - "recommended_action": "unavailable or unreadable", - "resolution": null, - "schema_conformity": "invalid", - "sha256": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "size_bytes": 4, - "source": "unknown", - "spatial_coverage": null, - "status": "examined", - "temporal_coverage": null, - "units": null - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0010.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "contract": { - "key": "geointel.raster.geotiff", - "version": "1.0.0" - }, - "crs": null, - "duplicate_group": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "empty_content": false, - "freshness": { - "reason": "no_declared_source_timestamp", - 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"severity": "critical" - } - ], - "contract": { - "key": "geointel.raster.geotiff", - "version": "1.0.0" - }, - "crs": null, - "duplicate_group": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "empty_content": false, - "freshness": { - "reason": "no_declared_source_timestamp", - "status": "unknown" - }, - "geometry_validation": null, - "item_id": "7407fad7de42e36fe791", - "lineage": null, - "modified_at": "2026-08-01T15:46:23.982429+00:00", - "near_duplicate_fingerprint": null, - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/tile_0011.tif", - "read_status": "unreadable", - "recommended_action": "unavailable or unreadable", - "resolution": null, - "schema_conformity": "invalid", - "sha256": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "size_bytes": 4, - "source": "unknown", - "spatial_coverage": null, - "status": "examined", - "temporal_coverage": null, - "units": null - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0012.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "contract": { - "key": "geointel.raster.geotiff", - "version": "1.0.0" - }, - "crs": null, - "duplicate_group": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "empty_content": false, - "freshness": { - "reason": "no_declared_source_timestamp", - "status": "unknown" - }, - "geometry_validation": null, - "item_id": "eaa22fd47e90efa7dbdd", - "lineage": null, - "modified_at": "2026-08-01T15:46:23.983429+00:00", - "near_duplicate_fingerprint": null, - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/tile_0012.tif", - "read_status": "unreadable", - "recommended_action": "unavailable or unreadable", - "resolution": null, - "schema_conformity": "invalid", - "sha256": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "size_bytes": 4, - "source": "unknown", - "spatial_coverage": null, - "status": "examined", - "temporal_coverage": null, - "units": null - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0013.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "contract": { - "key": "geointel.raster.geotiff", - "version": "1.0.0" - }, - "crs": null, - "duplicate_group": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "empty_content": false, - "freshness": { - "reason": "no_declared_source_timestamp", - "status": "unknown" - }, - "geometry_validation": null, - "item_id": "46aaf33ee50eaa14edfd", - "lineage": null, - "modified_at": "2026-08-01T15:46:23.983429+00:00", - "near_duplicate_fingerprint": null, - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/tile_0013.tif", - "read_status": "unreadable", - "recommended_action": "unavailable or unreadable", - "resolution": null, - "schema_conformity": "invalid", - "sha256": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "size_bytes": 4, - "source": "unknown", - "spatial_coverage": null, - "status": "examined", - "temporal_coverage": null, - "units": null - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0014.tif' not recognized as being in a supported file format.", - 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"units": null - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0015.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "contract": { - "key": "geointel.raster.geotiff", - "version": "1.0.0" - }, - "crs": null, - "duplicate_group": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "empty_content": false, - "freshness": { - "reason": "no_declared_source_timestamp", - "status": "unknown" - }, - "geometry_validation": null, - "item_id": "a870f7c9d918ccf7d5a6", - "lineage": null, - "modified_at": "2026-08-01T15:46:23.985429+00:00", - "near_duplicate_fingerprint": null, - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/tile_0015.tif", - 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"units": null - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\db240e97-188d-48fd-98f3-7abd9131ffeb\\2df0e426-f569-459f-a4ad-d3f42539bc23\\f31826fa-10e3-4154-95c2-d89d21813379\\tile_0001.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "contract": { - "key": "geointel.raster.geotiff", - "version": "1.0.0" - }, - "crs": null, - "duplicate_group": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "empty_content": false, - "freshness": { - "reason": "no_declared_source_timestamp", - "status": "unknown" - }, - "geometry_validation": null, - "item_id": "346a71885fe0853cfc30", - "lineage": null, - "modified_at": "2026-08-01T16:31:01.893751+00:00", - "near_duplicate_fingerprint": null, - "path": "storage/tiles/db240e97-188d-48fd-98f3-7abd9131ffeb/2df0e426-f569-459f-a4ad-d3f42539bc23/f31826fa-10e3-4154-95c2-d89d21813379/tile_0001.tif", - "read_status": "unreadable", - "recommended_action": "unavailable or unreadable", - "resolution": null, - "schema_conformity": "invalid", - "sha256": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "size_bytes": 4, - "source": "unknown", - "spatial_coverage": null, - "status": "examined", - "temporal_coverage": null, - "units": null - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\db240e97-188d-48fd-98f3-7abd9131ffeb\\2df0e426-f569-459f-a4ad-d3f42539bc23\\f31826fa-10e3-4154-95c2-d89d21813379\\tile_0002.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "contract": { - "key": "geointel.raster.geotiff", - "version": "1.0.0" - }, - "crs": null, - "duplicate_group": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "empty_content": false, - "freshness": { - "reason": "no_declared_source_timestamp", - 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"severity": "critical" - } - ], - "contract": { - "key": "geointel.raster.geotiff", - "version": "1.0.0" - }, - "crs": null, - "duplicate_group": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "empty_content": false, - "freshness": { - "reason": "no_declared_source_timestamp", - "status": "unknown" - }, - "geometry_validation": null, - "item_id": "bc61a64bf00351eaa325", - "lineage": null, - "modified_at": "2026-08-01T16:31:01.895751+00:00", - "near_duplicate_fingerprint": null, - "path": "storage/tiles/db240e97-188d-48fd-98f3-7abd9131ffeb/2df0e426-f569-459f-a4ad-d3f42539bc23/f31826fa-10e3-4154-95c2-d89d21813379/tile_0003.tif", - "read_status": "unreadable", - "recommended_action": "unavailable or unreadable", - "resolution": null, - "schema_conformity": "invalid", - "sha256": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "size_bytes": 4, - "source": "unknown", - "spatial_coverage": null, - "status": "examined", - "temporal_coverage": null, - "units": null - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\db240e97-188d-48fd-98f3-7abd9131ffeb\\2df0e426-f569-459f-a4ad-d3f42539bc23\\f31826fa-10e3-4154-95c2-d89d21813379\\tile_0004.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "contract": { - "key": "geointel.raster.geotiff", - "version": "1.0.0" - }, - "crs": null, - "duplicate_group": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "empty_content": false, - "freshness": { - "reason": "no_declared_source_timestamp", - "status": "unknown" - }, - "geometry_validation": null, - "item_id": "af6d1e573b5b4b191b87", - "lineage": null, - "modified_at": "2026-08-01T16:31:01.897751+00:00", - "near_duplicate_fingerprint": null, - "path": "storage/tiles/db240e97-188d-48fd-98f3-7abd9131ffeb/2df0e426-f569-459f-a4ad-d3f42539bc23/f31826fa-10e3-4154-95c2-d89d21813379/tile_0004.tif", - "read_status": "unreadable", - "recommended_action": "unavailable or unreadable", - "resolution": null, - "schema_conformity": "invalid", - "sha256": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "size_bytes": 4, - "source": "unknown", - "spatial_coverage": null, - "status": "examined", - "temporal_coverage": null, - "units": null - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\db240e97-188d-48fd-98f3-7abd9131ffeb\\2df0e426-f569-459f-a4ad-d3f42539bc23\\f31826fa-10e3-4154-95c2-d89d21813379\\tile_0005.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "contract": { - "key": "geointel.raster.geotiff", - "version": "1.0.0" - }, - "crs": null, - "duplicate_group": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "empty_content": false, - "freshness": { - "reason": "no_declared_source_timestamp", - "status": "unknown" - }, - "geometry_validation": null, - "item_id": "ef9696bc380f7e9dc039", - "lineage": null, - "modified_at": "2026-08-01T16:31:01.898803+00:00", - "near_duplicate_fingerprint": null, - "path": "storage/tiles/db240e97-188d-48fd-98f3-7abd9131ffeb/2df0e426-f569-459f-a4ad-d3f42539bc23/f31826fa-10e3-4154-95c2-d89d21813379/tile_0005.tif", - "read_status": "unreadable", - "recommended_action": "unavailable or unreadable", - "resolution": null, - "schema_conformity": "invalid", - "sha256": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "size_bytes": 4, - "source": "unknown", - "spatial_coverage": null, - "status": "examined", - "temporal_coverage": null, - "units": null - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\db240e97-188d-48fd-98f3-7abd9131ffeb\\2df0e426-f569-459f-a4ad-d3f42539bc23\\f31826fa-10e3-4154-95c2-d89d21813379\\tile_0006.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "contract": { - "key": "geointel.raster.geotiff", - "version": "1.0.0" - }, - "crs": null, - "duplicate_group": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "empty_content": false, - "freshness": { - "reason": "no_declared_source_timestamp", - "status": "unknown" - }, - "geometry_validation": null, - "item_id": "e440975ad15713709d14", - "lineage": null, - "modified_at": "2026-08-01T16:31:01.899805+00:00", - "near_duplicate_fingerprint": null, - "path": "storage/tiles/db240e97-188d-48fd-98f3-7abd9131ffeb/2df0e426-f569-459f-a4ad-d3f42539bc23/f31826fa-10e3-4154-95c2-d89d21813379/tile_0006.tif", - "read_status": "unreadable", - "recommended_action": "unavailable or unreadable", - "resolution": null, - "schema_conformity": "invalid", - "sha256": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "size_bytes": 4, - "source": "unknown", - "spatial_coverage": null, - "status": "examined", - "temporal_coverage": null, - "units": null - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\db240e97-188d-48fd-98f3-7abd9131ffeb\\2df0e426-f569-459f-a4ad-d3f42539bc23\\f31826fa-10e3-4154-95c2-d89d21813379\\tile_0007.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "contract": { - "key": "geointel.raster.geotiff", - "version": "1.0.0" - }, - "crs": null, - "duplicate_group": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "empty_content": false, - "freshness": { - "reason": "no_declared_source_timestamp", - "status": "unknown" - }, - "geometry_validation": null, - "item_id": "3f1f44d08c10be760fa3", - "lineage": null, - "modified_at": "2026-08-01T16:31:01.901804+00:00", - "near_duplicate_fingerprint": null, - "path": "storage/tiles/db240e97-188d-48fd-98f3-7abd9131ffeb/2df0e426-f569-459f-a4ad-d3f42539bc23/f31826fa-10e3-4154-95c2-d89d21813379/tile_0007.tif", - "read_status": "unreadable", - "recommended_action": "unavailable or unreadable", - "resolution": null, - "schema_conformity": "invalid", - "sha256": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "size_bytes": 4, - "source": "unknown", - "spatial_coverage": null, - "status": "examined", - "temporal_coverage": null, - "units": null - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\db240e97-188d-48fd-98f3-7abd9131ffeb\\2df0e426-f569-459f-a4ad-d3f42539bc23\\f31826fa-10e3-4154-95c2-d89d21813379\\tile_0008.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "contract": { - "key": "geointel.raster.geotiff", - "version": "1.0.0" - }, - "crs": null, - "duplicate_group": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "empty_content": false, - "freshness": { - "reason": "no_declared_source_timestamp", - "status": "unknown" - }, - "geometry_validation": null, - "item_id": "bc0e44ce91c97c3723c9", - "lineage": null, - "modified_at": "2026-08-01T16:31:01.901804+00:00", - "near_duplicate_fingerprint": null, - "path": "storage/tiles/db240e97-188d-48fd-98f3-7abd9131ffeb/2df0e426-f569-459f-a4ad-d3f42539bc23/f31826fa-10e3-4154-95c2-d89d21813379/tile_0008.tif", - "read_status": "unreadable", - "recommended_action": "unavailable or unreadable", - "resolution": null, - "schema_conformity": "invalid", - "sha256": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "size_bytes": 4, - "source": "unknown", - "spatial_coverage": null, - "status": "examined", - "temporal_coverage": null, - "units": null - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\db240e97-188d-48fd-98f3-7abd9131ffeb\\2df0e426-f569-459f-a4ad-d3f42539bc23\\f31826fa-10e3-4154-95c2-d89d21813379\\tile_0009.tif' not recognized as being in a supported file format.", - 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"units": null - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\db240e97-188d-48fd-98f3-7abd9131ffeb\\2df0e426-f569-459f-a4ad-d3f42539bc23\\f31826fa-10e3-4154-95c2-d89d21813379\\tile_0010.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "contract": { - "key": "geointel.raster.geotiff", - "version": "1.0.0" - }, - "crs": null, - "duplicate_group": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "empty_content": false, - "freshness": { - "reason": "no_declared_source_timestamp", - "status": "unknown" - }, - "geometry_validation": null, - "item_id": "c3ecd380ee4499edfd90", - "lineage": null, - "modified_at": "2026-08-01T16:31:01.903807+00:00", - "near_duplicate_fingerprint": null, - "path": "storage/tiles/db240e97-188d-48fd-98f3-7abd9131ffeb/2df0e426-f569-459f-a4ad-d3f42539bc23/f31826fa-10e3-4154-95c2-d89d21813379/tile_0010.tif", - 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"units": null - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\db240e97-188d-48fd-98f3-7abd9131ffeb\\2df0e426-f569-459f-a4ad-d3f42539bc23\\f31826fa-10e3-4154-95c2-d89d21813379\\tile_0013.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "contract": { - "key": "geointel.raster.geotiff", - "version": "1.0.0" - }, - "crs": null, - "duplicate_group": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "empty_content": false, - "freshness": { - "reason": "no_declared_source_timestamp", - "status": "unknown" - }, - "geometry_validation": null, - "item_id": "d3c5bdffafb98153e8d9", - "lineage": null, - "modified_at": "2026-08-01T16:31:01.906805+00:00", - "near_duplicate_fingerprint": null, - "path": "storage/tiles/db240e97-188d-48fd-98f3-7abd9131ffeb/2df0e426-f569-459f-a4ad-d3f42539bc23/f31826fa-10e3-4154-95c2-d89d21813379/tile_0013.tif", - "read_status": "unreadable", - "recommended_action": "unavailable or unreadable", - "resolution": null, - "schema_conformity": "invalid", - "sha256": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "size_bytes": 4, - "source": "unknown", - "spatial_coverage": null, - "status": "examined", - "temporal_coverage": null, - "units": null - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\db240e97-188d-48fd-98f3-7abd9131ffeb\\2df0e426-f569-459f-a4ad-d3f42539bc23\\f31826fa-10e3-4154-95c2-d89d21813379\\tile_0014.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "contract": { - "key": "geointel.raster.geotiff", - "version": "1.0.0" - }, - "crs": null, - "duplicate_group": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "empty_content": false, - "freshness": { - "reason": "no_declared_source_timestamp", - 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"units": null - }, - { - "anomalies": [ - { - "action": "quarantine", - "code": "manifest.zero_bbox", - "field": "bounds", - "message": "Manifest declares a zero-area bounding box", - "severity": "major" - } - ], - "contract": { - "key": "geointel.artifact.generic", - "version": "1.0.0" - }, - "crs": "EPSG:31370", - "duplicate_group": null, - "empty_content": false, - "freshness": { - "method": "declared_metadata", - "observed_at": "2026-08-01T13:01:30.888823+00:00", - "status": "declared" - }, - "geometry_validation": null, - "item_id": "3838bd5bae003af13690", - "lineage": { - "source_dataset_id": "f6848732-1f78-41ba-967c-11a577112b17", - "source_raster_id": "f6848732-1f78-41ba-967c-11a577112b17" - }, - "modified_at": "2026-08-01T13:01:30.888999+00:00", - "near_duplicate_fingerprint": "e7c18c2c2a4035110358885a61fac3b15946842bc707d53f66cdc1024c1be896", - "path": "storage/tiles/df217a4e-7f2e-4989-880e-30fb9a7ec645/f6848732-1f78-41ba-967c-11a577112b17/5e0d5f61-e7fb-4d4a-ae96-84b9060554d6/manifest.json", - 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"severity": "critical" - } - ], - "contract": { - "key": "geointel.raster.geotiff", - "version": "1.0.0" - }, - "crs": null, - "duplicate_group": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "empty_content": false, - "freshness": { - "reason": "no_declared_source_timestamp", - "status": "unknown" - }, - "geometry_validation": null, - "item_id": "abd539c47bb02eed552f", - "lineage": null, - "modified_at": "2026-08-01T13:01:30.857004+00:00", - "near_duplicate_fingerprint": null, - "path": "storage/tiles/df217a4e-7f2e-4989-880e-30fb9a7ec645/f6848732-1f78-41ba-967c-11a577112b17/5e0d5f61-e7fb-4d4a-ae96-84b9060554d6/tile_0001.tif", - "read_status": "unreadable", - "recommended_action": "unavailable or unreadable", - "resolution": null, - "schema_conformity": "invalid", - "sha256": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "size_bytes": 4, - "source": "unknown", - "spatial_coverage": null, - "status": "examined", - "temporal_coverage": null, - "units": null - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\df217a4e-7f2e-4989-880e-30fb9a7ec645\\f6848732-1f78-41ba-967c-11a577112b17\\5e0d5f61-e7fb-4d4a-ae96-84b9060554d6\\tile_0002.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "contract": { - "key": "geointel.raster.geotiff", - "version": "1.0.0" - }, - "crs": null, - "duplicate_group": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "empty_content": false, - "freshness": { - "reason": "no_declared_source_timestamp", - "status": "unknown" - }, - "geometry_validation": null, - "item_id": "6f3267beda326834d472", - "lineage": null, - "modified_at": "2026-08-01T13:01:30.858000+00:00", - "near_duplicate_fingerprint": null, - "path": "storage/tiles/df217a4e-7f2e-4989-880e-30fb9a7ec645/f6848732-1f78-41ba-967c-11a577112b17/5e0d5f61-e7fb-4d4a-ae96-84b9060554d6/tile_0002.tif", - "read_status": "unreadable", - "recommended_action": "unavailable or unreadable", - "resolution": null, - "schema_conformity": "invalid", - "sha256": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "size_bytes": 4, - "source": "unknown", - "spatial_coverage": null, - "status": "examined", - "temporal_coverage": null, - "units": null - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\df217a4e-7f2e-4989-880e-30fb9a7ec645\\f6848732-1f78-41ba-967c-11a577112b17\\5e0d5f61-e7fb-4d4a-ae96-84b9060554d6\\tile_0003.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "contract": { - "key": "geointel.raster.geotiff", - "version": "1.0.0" - }, - "crs": null, - "duplicate_group": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "empty_content": false, - "freshness": { - "reason": "no_declared_source_timestamp", - "status": "unknown" - }, - "geometry_validation": null, - "item_id": "81ca8f6bfc34b1cdcb10", - "lineage": null, - "modified_at": "2026-08-01T13:01:30.860002+00:00", - "near_duplicate_fingerprint": null, - "path": "storage/tiles/df217a4e-7f2e-4989-880e-30fb9a7ec645/f6848732-1f78-41ba-967c-11a577112b17/5e0d5f61-e7fb-4d4a-ae96-84b9060554d6/tile_0003.tif", - "read_status": "unreadable", - "recommended_action": "unavailable or unreadable", - "resolution": null, - "schema_conformity": "invalid", - "sha256": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "size_bytes": 4, - "source": "unknown", - "spatial_coverage": null, - "status": "examined", - "temporal_coverage": null, - "units": null - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\df217a4e-7f2e-4989-880e-30fb9a7ec645\\f6848732-1f78-41ba-967c-11a577112b17\\5e0d5f61-e7fb-4d4a-ae96-84b9060554d6\\tile_0004.tif' not recognized as being in a supported file format.", - 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"code": "lineage.missing", - "message": "Derived-looking artifact has no explicit lineage", - "severity": "major" - } - ], - "item_id": "bf3301269a7c6e6d4394", - "path": "artifacts/evidence/accuracy/model-training/20260809-v72-fresh-calibration/provisioning-spec.json", - "recommended_action": "quarantine" - }, - { - "anomalies": [ - { - "action": "quarantine", - "code": "lineage.missing", - "message": "Derived-looking artifact has no explicit lineage", - "severity": "major" - } - ], - "item_id": "01e132ec816d6b0c6815", - "path": "artifacts/evidence/accuracy/model-training/20260809-v72-fresh-calibration/visual-review-summary.json", - "recommended_action": "quarantine" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "scope.unreachable", - "message": "Production model volumes are not mounted in the Windows project checkout", - "severity": "critical" - } - ], - "item_id": "51068394b7ea895baeb1", - "path": "external://mounted-model-volumes", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "scope.unreachable", - "message": "Production PostGIS is intentionally accessed only during the controlled server audit", - "severity": "critical" - } - ], - "item_id": "b870066fb36a95c1515a", - "path": "external://production-postgis-or-api", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "scope.unreachable", - "message": "Tower corpora are not mounted in the Windows project checkout", - "severity": "critical" - } - ], - "item_id": "02beec97fca0abebb749", - "path": "external://tower-corpora", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "quarantine", - "code": "lineage.missing", - "message": "Derived-looking artifact has no explicit lineage", - "severity": "major" - } - ], - "item_id": "b10c4468dae845ab2d6d", - "path": "storage/derived/README.md", - "recommended_action": "quarantine" - }, - { - "anomalies": [ - { - "action": "quarantine", - "code": "manifest.zero_bbox", - "field": "bounds", - "message": "Manifest declares a zero-area bounding box", - "severity": "major" - } - ], - "item_id": "1c0c41d3937b5d7664fb", - "path": "storage/tiles/277180a4-cd74-42ed-a231-0d194b3fca9f/0f96a4f7-6b24-4969-9564-abbde30b5a51/9199f079-42fc-48cc-86ff-d1072f801932/manifest.json", - "recommended_action": "quarantine" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\277180a4-cd74-42ed-a231-0d194b3fca9f\\0f96a4f7-6b24-4969-9564-abbde30b5a51\\9199f079-42fc-48cc-86ff-d1072f801932\\tile_0000.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "4baadb1297e2501c79a7", - "path": "storage/tiles/277180a4-cd74-42ed-a231-0d194b3fca9f/0f96a4f7-6b24-4969-9564-abbde30b5a51/9199f079-42fc-48cc-86ff-d1072f801932/tile_0000.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\277180a4-cd74-42ed-a231-0d194b3fca9f\\0f96a4f7-6b24-4969-9564-abbde30b5a51\\9199f079-42fc-48cc-86ff-d1072f801932\\tile_0001.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "fa9128c46bc6535a95a8", - "path": "storage/tiles/277180a4-cd74-42ed-a231-0d194b3fca9f/0f96a4f7-6b24-4969-9564-abbde30b5a51/9199f079-42fc-48cc-86ff-d1072f801932/tile_0001.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\277180a4-cd74-42ed-a231-0d194b3fca9f\\0f96a4f7-6b24-4969-9564-abbde30b5a51\\9199f079-42fc-48cc-86ff-d1072f801932\\tile_0002.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "6cf9933a9b0c3d8c9923", - "path": "storage/tiles/277180a4-cd74-42ed-a231-0d194b3fca9f/0f96a4f7-6b24-4969-9564-abbde30b5a51/9199f079-42fc-48cc-86ff-d1072f801932/tile_0002.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\277180a4-cd74-42ed-a231-0d194b3fca9f\\0f96a4f7-6b24-4969-9564-abbde30b5a51\\9199f079-42fc-48cc-86ff-d1072f801932\\tile_0003.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "c51dff8856043721992e", - "path": "storage/tiles/277180a4-cd74-42ed-a231-0d194b3fca9f/0f96a4f7-6b24-4969-9564-abbde30b5a51/9199f079-42fc-48cc-86ff-d1072f801932/tile_0003.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\277180a4-cd74-42ed-a231-0d194b3fca9f\\0f96a4f7-6b24-4969-9564-abbde30b5a51\\9199f079-42fc-48cc-86ff-d1072f801932\\tile_0004.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "a1e7317f6a0c2dfb7235", - "path": "storage/tiles/277180a4-cd74-42ed-a231-0d194b3fca9f/0f96a4f7-6b24-4969-9564-abbde30b5a51/9199f079-42fc-48cc-86ff-d1072f801932/tile_0004.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\277180a4-cd74-42ed-a231-0d194b3fca9f\\0f96a4f7-6b24-4969-9564-abbde30b5a51\\9199f079-42fc-48cc-86ff-d1072f801932\\tile_0005.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "5069a8562d88d6913bfd", - "path": "storage/tiles/277180a4-cd74-42ed-a231-0d194b3fca9f/0f96a4f7-6b24-4969-9564-abbde30b5a51/9199f079-42fc-48cc-86ff-d1072f801932/tile_0005.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\277180a4-cd74-42ed-a231-0d194b3fca9f\\0f96a4f7-6b24-4969-9564-abbde30b5a51\\9199f079-42fc-48cc-86ff-d1072f801932\\tile_0006.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "2200c4a8006caa7fd98a", - "path": "storage/tiles/277180a4-cd74-42ed-a231-0d194b3fca9f/0f96a4f7-6b24-4969-9564-abbde30b5a51/9199f079-42fc-48cc-86ff-d1072f801932/tile_0006.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\277180a4-cd74-42ed-a231-0d194b3fca9f\\0f96a4f7-6b24-4969-9564-abbde30b5a51\\9199f079-42fc-48cc-86ff-d1072f801932\\tile_0007.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "f4fb0308ffbd8d6fd880", - "path": "storage/tiles/277180a4-cd74-42ed-a231-0d194b3fca9f/0f96a4f7-6b24-4969-9564-abbde30b5a51/9199f079-42fc-48cc-86ff-d1072f801932/tile_0007.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\277180a4-cd74-42ed-a231-0d194b3fca9f\\0f96a4f7-6b24-4969-9564-abbde30b5a51\\9199f079-42fc-48cc-86ff-d1072f801932\\tile_0008.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "b18eaa92bfb6f82949cc", - "path": "storage/tiles/277180a4-cd74-42ed-a231-0d194b3fca9f/0f96a4f7-6b24-4969-9564-abbde30b5a51/9199f079-42fc-48cc-86ff-d1072f801932/tile_0008.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\277180a4-cd74-42ed-a231-0d194b3fca9f\\0f96a4f7-6b24-4969-9564-abbde30b5a51\\9199f079-42fc-48cc-86ff-d1072f801932\\tile_0009.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "f87e566976251b0ddd3d", - "path": "storage/tiles/277180a4-cd74-42ed-a231-0d194b3fca9f/0f96a4f7-6b24-4969-9564-abbde30b5a51/9199f079-42fc-48cc-86ff-d1072f801932/tile_0009.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\277180a4-cd74-42ed-a231-0d194b3fca9f\\0f96a4f7-6b24-4969-9564-abbde30b5a51\\9199f079-42fc-48cc-86ff-d1072f801932\\tile_0010.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "379ac5f7a3a7d258b56f", - "path": "storage/tiles/277180a4-cd74-42ed-a231-0d194b3fca9f/0f96a4f7-6b24-4969-9564-abbde30b5a51/9199f079-42fc-48cc-86ff-d1072f801932/tile_0010.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\277180a4-cd74-42ed-a231-0d194b3fca9f\\0f96a4f7-6b24-4969-9564-abbde30b5a51\\9199f079-42fc-48cc-86ff-d1072f801932\\tile_0011.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "2ec9764c5631b5c7a1b4", - "path": "storage/tiles/277180a4-cd74-42ed-a231-0d194b3fca9f/0f96a4f7-6b24-4969-9564-abbde30b5a51/9199f079-42fc-48cc-86ff-d1072f801932/tile_0011.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\277180a4-cd74-42ed-a231-0d194b3fca9f\\0f96a4f7-6b24-4969-9564-abbde30b5a51\\9199f079-42fc-48cc-86ff-d1072f801932\\tile_0012.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "ac9cbb366a7c16a79b44", - "path": "storage/tiles/277180a4-cd74-42ed-a231-0d194b3fca9f/0f96a4f7-6b24-4969-9564-abbde30b5a51/9199f079-42fc-48cc-86ff-d1072f801932/tile_0012.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\277180a4-cd74-42ed-a231-0d194b3fca9f\\0f96a4f7-6b24-4969-9564-abbde30b5a51\\9199f079-42fc-48cc-86ff-d1072f801932\\tile_0013.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "5adaba8e404c16d70d1b", - "path": "storage/tiles/277180a4-cd74-42ed-a231-0d194b3fca9f/0f96a4f7-6b24-4969-9564-abbde30b5a51/9199f079-42fc-48cc-86ff-d1072f801932/tile_0013.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\277180a4-cd74-42ed-a231-0d194b3fca9f\\0f96a4f7-6b24-4969-9564-abbde30b5a51\\9199f079-42fc-48cc-86ff-d1072f801932\\tile_0014.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "e61c40ce9d3d2b9d369d", - "path": "storage/tiles/277180a4-cd74-42ed-a231-0d194b3fca9f/0f96a4f7-6b24-4969-9564-abbde30b5a51/9199f079-42fc-48cc-86ff-d1072f801932/tile_0014.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\277180a4-cd74-42ed-a231-0d194b3fca9f\\0f96a4f7-6b24-4969-9564-abbde30b5a51\\9199f079-42fc-48cc-86ff-d1072f801932\\tile_0015.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "a814da6efe81f095c9e3", - "path": "storage/tiles/277180a4-cd74-42ed-a231-0d194b3fca9f/0f96a4f7-6b24-4969-9564-abbde30b5a51/9199f079-42fc-48cc-86ff-d1072f801932/tile_0015.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "quarantine", - "code": "manifest.zero_bbox", - "field": "bounds", - "message": "Manifest declares a zero-area bounding box", - "severity": "major" - } - ], - "item_id": "1500315e2bdebe9d3462", - "path": "storage/tiles/7175ae58-2b09-4fab-83e1-5d95e2969d35/07738ebe-2c5e-4d6c-960d-1c03f216a3a0/7529e658-b42a-47cb-a23c-d9d350b5d8c4/manifest.json", - "recommended_action": "quarantine" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\7175ae58-2b09-4fab-83e1-5d95e2969d35\\07738ebe-2c5e-4d6c-960d-1c03f216a3a0\\7529e658-b42a-47cb-a23c-d9d350b5d8c4\\tile_0000.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "82177cf3088b3fae2281", - "path": "storage/tiles/7175ae58-2b09-4fab-83e1-5d95e2969d35/07738ebe-2c5e-4d6c-960d-1c03f216a3a0/7529e658-b42a-47cb-a23c-d9d350b5d8c4/tile_0000.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\7175ae58-2b09-4fab-83e1-5d95e2969d35\\07738ebe-2c5e-4d6c-960d-1c03f216a3a0\\7529e658-b42a-47cb-a23c-d9d350b5d8c4\\tile_0001.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "6c9f6f1cd68adead5055", - "path": "storage/tiles/7175ae58-2b09-4fab-83e1-5d95e2969d35/07738ebe-2c5e-4d6c-960d-1c03f216a3a0/7529e658-b42a-47cb-a23c-d9d350b5d8c4/tile_0001.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\7175ae58-2b09-4fab-83e1-5d95e2969d35\\07738ebe-2c5e-4d6c-960d-1c03f216a3a0\\7529e658-b42a-47cb-a23c-d9d350b5d8c4\\tile_0002.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "c8280727cb07e1423a97", - "path": "storage/tiles/7175ae58-2b09-4fab-83e1-5d95e2969d35/07738ebe-2c5e-4d6c-960d-1c03f216a3a0/7529e658-b42a-47cb-a23c-d9d350b5d8c4/tile_0002.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\7175ae58-2b09-4fab-83e1-5d95e2969d35\\07738ebe-2c5e-4d6c-960d-1c03f216a3a0\\7529e658-b42a-47cb-a23c-d9d350b5d8c4\\tile_0003.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "2e89e578c950d03db653", - "path": "storage/tiles/7175ae58-2b09-4fab-83e1-5d95e2969d35/07738ebe-2c5e-4d6c-960d-1c03f216a3a0/7529e658-b42a-47cb-a23c-d9d350b5d8c4/tile_0003.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\7175ae58-2b09-4fab-83e1-5d95e2969d35\\07738ebe-2c5e-4d6c-960d-1c03f216a3a0\\7529e658-b42a-47cb-a23c-d9d350b5d8c4\\tile_0004.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "0e60a5f162f918773b06", - "path": "storage/tiles/7175ae58-2b09-4fab-83e1-5d95e2969d35/07738ebe-2c5e-4d6c-960d-1c03f216a3a0/7529e658-b42a-47cb-a23c-d9d350b5d8c4/tile_0004.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\7175ae58-2b09-4fab-83e1-5d95e2969d35\\07738ebe-2c5e-4d6c-960d-1c03f216a3a0\\7529e658-b42a-47cb-a23c-d9d350b5d8c4\\tile_0005.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "4b1ff1eeb59cf97d722c", - "path": "storage/tiles/7175ae58-2b09-4fab-83e1-5d95e2969d35/07738ebe-2c5e-4d6c-960d-1c03f216a3a0/7529e658-b42a-47cb-a23c-d9d350b5d8c4/tile_0005.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\7175ae58-2b09-4fab-83e1-5d95e2969d35\\07738ebe-2c5e-4d6c-960d-1c03f216a3a0\\7529e658-b42a-47cb-a23c-d9d350b5d8c4\\tile_0006.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "71fff7a0187642c79b89", - "path": "storage/tiles/7175ae58-2b09-4fab-83e1-5d95e2969d35/07738ebe-2c5e-4d6c-960d-1c03f216a3a0/7529e658-b42a-47cb-a23c-d9d350b5d8c4/tile_0006.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\7175ae58-2b09-4fab-83e1-5d95e2969d35\\07738ebe-2c5e-4d6c-960d-1c03f216a3a0\\7529e658-b42a-47cb-a23c-d9d350b5d8c4\\tile_0007.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "90c5c1cbd336f0758242", - "path": "storage/tiles/7175ae58-2b09-4fab-83e1-5d95e2969d35/07738ebe-2c5e-4d6c-960d-1c03f216a3a0/7529e658-b42a-47cb-a23c-d9d350b5d8c4/tile_0007.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\7175ae58-2b09-4fab-83e1-5d95e2969d35\\07738ebe-2c5e-4d6c-960d-1c03f216a3a0\\7529e658-b42a-47cb-a23c-d9d350b5d8c4\\tile_0008.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "d3b1d530bd052ac1b53e", - "path": "storage/tiles/7175ae58-2b09-4fab-83e1-5d95e2969d35/07738ebe-2c5e-4d6c-960d-1c03f216a3a0/7529e658-b42a-47cb-a23c-d9d350b5d8c4/tile_0008.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\7175ae58-2b09-4fab-83e1-5d95e2969d35\\07738ebe-2c5e-4d6c-960d-1c03f216a3a0\\7529e658-b42a-47cb-a23c-d9d350b5d8c4\\tile_0009.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "8cb6365e148d4e5b9b33", - "path": "storage/tiles/7175ae58-2b09-4fab-83e1-5d95e2969d35/07738ebe-2c5e-4d6c-960d-1c03f216a3a0/7529e658-b42a-47cb-a23c-d9d350b5d8c4/tile_0009.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\7175ae58-2b09-4fab-83e1-5d95e2969d35\\07738ebe-2c5e-4d6c-960d-1c03f216a3a0\\7529e658-b42a-47cb-a23c-d9d350b5d8c4\\tile_0010.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "3c46ab42aef67799f868", - "path": "storage/tiles/7175ae58-2b09-4fab-83e1-5d95e2969d35/07738ebe-2c5e-4d6c-960d-1c03f216a3a0/7529e658-b42a-47cb-a23c-d9d350b5d8c4/tile_0010.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\7175ae58-2b09-4fab-83e1-5d95e2969d35\\07738ebe-2c5e-4d6c-960d-1c03f216a3a0\\7529e658-b42a-47cb-a23c-d9d350b5d8c4\\tile_0011.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "51dae1e198b0e2be9a25", - "path": "storage/tiles/7175ae58-2b09-4fab-83e1-5d95e2969d35/07738ebe-2c5e-4d6c-960d-1c03f216a3a0/7529e658-b42a-47cb-a23c-d9d350b5d8c4/tile_0011.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\7175ae58-2b09-4fab-83e1-5d95e2969d35\\07738ebe-2c5e-4d6c-960d-1c03f216a3a0\\7529e658-b42a-47cb-a23c-d9d350b5d8c4\\tile_0012.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "6587704f64f657c9b261", - "path": "storage/tiles/7175ae58-2b09-4fab-83e1-5d95e2969d35/07738ebe-2c5e-4d6c-960d-1c03f216a3a0/7529e658-b42a-47cb-a23c-d9d350b5d8c4/tile_0012.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\7175ae58-2b09-4fab-83e1-5d95e2969d35\\07738ebe-2c5e-4d6c-960d-1c03f216a3a0\\7529e658-b42a-47cb-a23c-d9d350b5d8c4\\tile_0013.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "b7965c4fe187fb9a6e72", - "path": "storage/tiles/7175ae58-2b09-4fab-83e1-5d95e2969d35/07738ebe-2c5e-4d6c-960d-1c03f216a3a0/7529e658-b42a-47cb-a23c-d9d350b5d8c4/tile_0013.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\7175ae58-2b09-4fab-83e1-5d95e2969d35\\07738ebe-2c5e-4d6c-960d-1c03f216a3a0\\7529e658-b42a-47cb-a23c-d9d350b5d8c4\\tile_0014.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "b54051b8cb4ca92387b2", - "path": "storage/tiles/7175ae58-2b09-4fab-83e1-5d95e2969d35/07738ebe-2c5e-4d6c-960d-1c03f216a3a0/7529e658-b42a-47cb-a23c-d9d350b5d8c4/tile_0014.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\7175ae58-2b09-4fab-83e1-5d95e2969d35\\07738ebe-2c5e-4d6c-960d-1c03f216a3a0\\7529e658-b42a-47cb-a23c-d9d350b5d8c4\\tile_0015.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "85abe6c3be8c5f60f542", - "path": "storage/tiles/7175ae58-2b09-4fab-83e1-5d95e2969d35/07738ebe-2c5e-4d6c-960d-1c03f216a3a0/7529e658-b42a-47cb-a23c-d9d350b5d8c4/tile_0015.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "quarantine", - "code": "manifest.zero_bbox", - "field": "bounds", - "message": "Manifest declares a zero-area bounding box", - "severity": "major" - } - ], - "item_id": "b6b16941c235d9cb21df", - "path": "storage/tiles/a7a94d0b-9b27-49bd-9e44-97b0b75677ad/e2a3f62a-76f0-4611-81a3-d2ca948cda75/6e53d525-f603-4eb3-8bf7-05da59832013/manifest.json", - "recommended_action": "quarantine" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\a7a94d0b-9b27-49bd-9e44-97b0b75677ad\\e2a3f62a-76f0-4611-81a3-d2ca948cda75\\6e53d525-f603-4eb3-8bf7-05da59832013\\tile_0000.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "20e3d2bb3ee9bb98f8b2", - "path": "storage/tiles/a7a94d0b-9b27-49bd-9e44-97b0b75677ad/e2a3f62a-76f0-4611-81a3-d2ca948cda75/6e53d525-f603-4eb3-8bf7-05da59832013/tile_0000.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\a7a94d0b-9b27-49bd-9e44-97b0b75677ad\\e2a3f62a-76f0-4611-81a3-d2ca948cda75\\6e53d525-f603-4eb3-8bf7-05da59832013\\tile_0001.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "4e4919deb1ec3b7df24d", - "path": "storage/tiles/a7a94d0b-9b27-49bd-9e44-97b0b75677ad/e2a3f62a-76f0-4611-81a3-d2ca948cda75/6e53d525-f603-4eb3-8bf7-05da59832013/tile_0001.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\a7a94d0b-9b27-49bd-9e44-97b0b75677ad\\e2a3f62a-76f0-4611-81a3-d2ca948cda75\\6e53d525-f603-4eb3-8bf7-05da59832013\\tile_0002.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "0f87eb34f3f0359638a2", - "path": "storage/tiles/a7a94d0b-9b27-49bd-9e44-97b0b75677ad/e2a3f62a-76f0-4611-81a3-d2ca948cda75/6e53d525-f603-4eb3-8bf7-05da59832013/tile_0002.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\a7a94d0b-9b27-49bd-9e44-97b0b75677ad\\e2a3f62a-76f0-4611-81a3-d2ca948cda75\\6e53d525-f603-4eb3-8bf7-05da59832013\\tile_0003.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "e5f08ed47ebbc2dc539d", - "path": "storage/tiles/a7a94d0b-9b27-49bd-9e44-97b0b75677ad/e2a3f62a-76f0-4611-81a3-d2ca948cda75/6e53d525-f603-4eb3-8bf7-05da59832013/tile_0003.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\a7a94d0b-9b27-49bd-9e44-97b0b75677ad\\e2a3f62a-76f0-4611-81a3-d2ca948cda75\\6e53d525-f603-4eb3-8bf7-05da59832013\\tile_0004.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "776ded90bfd4c9e66373", - "path": "storage/tiles/a7a94d0b-9b27-49bd-9e44-97b0b75677ad/e2a3f62a-76f0-4611-81a3-d2ca948cda75/6e53d525-f603-4eb3-8bf7-05da59832013/tile_0004.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\a7a94d0b-9b27-49bd-9e44-97b0b75677ad\\e2a3f62a-76f0-4611-81a3-d2ca948cda75\\6e53d525-f603-4eb3-8bf7-05da59832013\\tile_0005.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "2a37d92cc1f4c7760875", - "path": "storage/tiles/a7a94d0b-9b27-49bd-9e44-97b0b75677ad/e2a3f62a-76f0-4611-81a3-d2ca948cda75/6e53d525-f603-4eb3-8bf7-05da59832013/tile_0005.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\a7a94d0b-9b27-49bd-9e44-97b0b75677ad\\e2a3f62a-76f0-4611-81a3-d2ca948cda75\\6e53d525-f603-4eb3-8bf7-05da59832013\\tile_0006.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "d3d5a58eb923e4e58858", - "path": "storage/tiles/a7a94d0b-9b27-49bd-9e44-97b0b75677ad/e2a3f62a-76f0-4611-81a3-d2ca948cda75/6e53d525-f603-4eb3-8bf7-05da59832013/tile_0006.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\a7a94d0b-9b27-49bd-9e44-97b0b75677ad\\e2a3f62a-76f0-4611-81a3-d2ca948cda75\\6e53d525-f603-4eb3-8bf7-05da59832013\\tile_0007.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "91c929ee528e638a6a76", - "path": "storage/tiles/a7a94d0b-9b27-49bd-9e44-97b0b75677ad/e2a3f62a-76f0-4611-81a3-d2ca948cda75/6e53d525-f603-4eb3-8bf7-05da59832013/tile_0007.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\a7a94d0b-9b27-49bd-9e44-97b0b75677ad\\e2a3f62a-76f0-4611-81a3-d2ca948cda75\\6e53d525-f603-4eb3-8bf7-05da59832013\\tile_0008.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "e480cf83cf5db4b2e52d", - "path": "storage/tiles/a7a94d0b-9b27-49bd-9e44-97b0b75677ad/e2a3f62a-76f0-4611-81a3-d2ca948cda75/6e53d525-f603-4eb3-8bf7-05da59832013/tile_0008.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\a7a94d0b-9b27-49bd-9e44-97b0b75677ad\\e2a3f62a-76f0-4611-81a3-d2ca948cda75\\6e53d525-f603-4eb3-8bf7-05da59832013\\tile_0009.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "c0ad18065477ffaad4ac", - "path": "storage/tiles/a7a94d0b-9b27-49bd-9e44-97b0b75677ad/e2a3f62a-76f0-4611-81a3-d2ca948cda75/6e53d525-f603-4eb3-8bf7-05da59832013/tile_0009.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\a7a94d0b-9b27-49bd-9e44-97b0b75677ad\\e2a3f62a-76f0-4611-81a3-d2ca948cda75\\6e53d525-f603-4eb3-8bf7-05da59832013\\tile_0010.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "ba9cbe3cdf31c09754b6", - "path": "storage/tiles/a7a94d0b-9b27-49bd-9e44-97b0b75677ad/e2a3f62a-76f0-4611-81a3-d2ca948cda75/6e53d525-f603-4eb3-8bf7-05da59832013/tile_0010.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\a7a94d0b-9b27-49bd-9e44-97b0b75677ad\\e2a3f62a-76f0-4611-81a3-d2ca948cda75\\6e53d525-f603-4eb3-8bf7-05da59832013\\tile_0011.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "74791aaeb46bd8705f5c", - "path": "storage/tiles/a7a94d0b-9b27-49bd-9e44-97b0b75677ad/e2a3f62a-76f0-4611-81a3-d2ca948cda75/6e53d525-f603-4eb3-8bf7-05da59832013/tile_0011.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\a7a94d0b-9b27-49bd-9e44-97b0b75677ad\\e2a3f62a-76f0-4611-81a3-d2ca948cda75\\6e53d525-f603-4eb3-8bf7-05da59832013\\tile_0012.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "e6494b03753f6de23316", - "path": "storage/tiles/a7a94d0b-9b27-49bd-9e44-97b0b75677ad/e2a3f62a-76f0-4611-81a3-d2ca948cda75/6e53d525-f603-4eb3-8bf7-05da59832013/tile_0012.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\a7a94d0b-9b27-49bd-9e44-97b0b75677ad\\e2a3f62a-76f0-4611-81a3-d2ca948cda75\\6e53d525-f603-4eb3-8bf7-05da59832013\\tile_0013.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "c2301617d835cbe7a9da", - "path": "storage/tiles/a7a94d0b-9b27-49bd-9e44-97b0b75677ad/e2a3f62a-76f0-4611-81a3-d2ca948cda75/6e53d525-f603-4eb3-8bf7-05da59832013/tile_0013.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\a7a94d0b-9b27-49bd-9e44-97b0b75677ad\\e2a3f62a-76f0-4611-81a3-d2ca948cda75\\6e53d525-f603-4eb3-8bf7-05da59832013\\tile_0014.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "712708cfd7b54f652c1f", - "path": "storage/tiles/a7a94d0b-9b27-49bd-9e44-97b0b75677ad/e2a3f62a-76f0-4611-81a3-d2ca948cda75/6e53d525-f603-4eb3-8bf7-05da59832013/tile_0014.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\a7a94d0b-9b27-49bd-9e44-97b0b75677ad\\e2a3f62a-76f0-4611-81a3-d2ca948cda75\\6e53d525-f603-4eb3-8bf7-05da59832013\\tile_0015.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "bfbadaaae125e34b5828", - "path": "storage/tiles/a7a94d0b-9b27-49bd-9e44-97b0b75677ad/e2a3f62a-76f0-4611-81a3-d2ca948cda75/6e53d525-f603-4eb3-8bf7-05da59832013/tile_0015.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "quarantine", - "code": "manifest.zero_bbox", - "field": "bounds", - "message": "Manifest declares a zero-area bounding box", - "severity": "major" - } - ], - "item_id": "04f3407f941cd1dc895e", - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/manifest.json", - "recommended_action": "quarantine" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0000.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "4def26f935acc400079e", - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/tile_0000.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0001.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "9e093656fa6b9d623331", - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/tile_0001.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0002.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "463efcbe145941dc1ded", - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/tile_0002.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0003.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "6b1012bfdedb2641eb37", - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/tile_0003.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0004.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "71979d432b49d84e9e75", - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/tile_0004.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0005.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "649fd55f6d877aa78bb2", - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/tile_0005.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0006.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "52e170d64fb1a011de45", - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/tile_0006.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0007.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "46628f46cd8911a36f86", - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/tile_0007.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0008.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "889b2e92c1aa378722aa", - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/tile_0008.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0009.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "67a46403c7fb388bb484", - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/tile_0009.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0010.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "25123fae6d918a76ac7a", - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/tile_0010.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0011.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "7407fad7de42e36fe791", - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/tile_0011.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0012.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "eaa22fd47e90efa7dbdd", - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/tile_0012.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0013.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "46aaf33ee50eaa14edfd", - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/tile_0013.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0014.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "6d3766eca60a28941699", - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/tile_0014.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0015.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "a870f7c9d918ccf7d5a6", - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/tile_0015.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "quarantine", - "code": "manifest.zero_bbox", - "field": "bounds", - "message": "Manifest declares a zero-area bounding box", - "severity": "major" - } - ], - "item_id": "42f97df8f1716a98cc5a", - "path": "storage/tiles/db240e97-188d-48fd-98f3-7abd9131ffeb/2df0e426-f569-459f-a4ad-d3f42539bc23/f31826fa-10e3-4154-95c2-d89d21813379/manifest.json", - "recommended_action": "quarantine" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\db240e97-188d-48fd-98f3-7abd9131ffeb\\2df0e426-f569-459f-a4ad-d3f42539bc23\\f31826fa-10e3-4154-95c2-d89d21813379\\tile_0000.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "33b3c33cb179ac85ada1", - "path": "storage/tiles/db240e97-188d-48fd-98f3-7abd9131ffeb/2df0e426-f569-459f-a4ad-d3f42539bc23/f31826fa-10e3-4154-95c2-d89d21813379/tile_0000.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\db240e97-188d-48fd-98f3-7abd9131ffeb\\2df0e426-f569-459f-a4ad-d3f42539bc23\\f31826fa-10e3-4154-95c2-d89d21813379\\tile_0001.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "346a71885fe0853cfc30", - "path": "storage/tiles/db240e97-188d-48fd-98f3-7abd9131ffeb/2df0e426-f569-459f-a4ad-d3f42539bc23/f31826fa-10e3-4154-95c2-d89d21813379/tile_0001.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\db240e97-188d-48fd-98f3-7abd9131ffeb\\2df0e426-f569-459f-a4ad-d3f42539bc23\\f31826fa-10e3-4154-95c2-d89d21813379\\tile_0002.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "6fab06961d3c3d439c73", - "path": "storage/tiles/db240e97-188d-48fd-98f3-7abd9131ffeb/2df0e426-f569-459f-a4ad-d3f42539bc23/f31826fa-10e3-4154-95c2-d89d21813379/tile_0002.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\db240e97-188d-48fd-98f3-7abd9131ffeb\\2df0e426-f569-459f-a4ad-d3f42539bc23\\f31826fa-10e3-4154-95c2-d89d21813379\\tile_0003.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "bc61a64bf00351eaa325", - "path": "storage/tiles/db240e97-188d-48fd-98f3-7abd9131ffeb/2df0e426-f569-459f-a4ad-d3f42539bc23/f31826fa-10e3-4154-95c2-d89d21813379/tile_0003.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\db240e97-188d-48fd-98f3-7abd9131ffeb\\2df0e426-f569-459f-a4ad-d3f42539bc23\\f31826fa-10e3-4154-95c2-d89d21813379\\tile_0004.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "af6d1e573b5b4b191b87", - "path": "storage/tiles/db240e97-188d-48fd-98f3-7abd9131ffeb/2df0e426-f569-459f-a4ad-d3f42539bc23/f31826fa-10e3-4154-95c2-d89d21813379/tile_0004.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\db240e97-188d-48fd-98f3-7abd9131ffeb\\2df0e426-f569-459f-a4ad-d3f42539bc23\\f31826fa-10e3-4154-95c2-d89d21813379\\tile_0005.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "ef9696bc380f7e9dc039", - "path": "storage/tiles/db240e97-188d-48fd-98f3-7abd9131ffeb/2df0e426-f569-459f-a4ad-d3f42539bc23/f31826fa-10e3-4154-95c2-d89d21813379/tile_0005.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\db240e97-188d-48fd-98f3-7abd9131ffeb\\2df0e426-f569-459f-a4ad-d3f42539bc23\\f31826fa-10e3-4154-95c2-d89d21813379\\tile_0006.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "e440975ad15713709d14", - "path": "storage/tiles/db240e97-188d-48fd-98f3-7abd9131ffeb/2df0e426-f569-459f-a4ad-d3f42539bc23/f31826fa-10e3-4154-95c2-d89d21813379/tile_0006.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\db240e97-188d-48fd-98f3-7abd9131ffeb\\2df0e426-f569-459f-a4ad-d3f42539bc23\\f31826fa-10e3-4154-95c2-d89d21813379\\tile_0007.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "3f1f44d08c10be760fa3", - "path": "storage/tiles/db240e97-188d-48fd-98f3-7abd9131ffeb/2df0e426-f569-459f-a4ad-d3f42539bc23/f31826fa-10e3-4154-95c2-d89d21813379/tile_0007.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\db240e97-188d-48fd-98f3-7abd9131ffeb\\2df0e426-f569-459f-a4ad-d3f42539bc23\\f31826fa-10e3-4154-95c2-d89d21813379\\tile_0008.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "bc0e44ce91c97c3723c9", - "path": "storage/tiles/db240e97-188d-48fd-98f3-7abd9131ffeb/2df0e426-f569-459f-a4ad-d3f42539bc23/f31826fa-10e3-4154-95c2-d89d21813379/tile_0008.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\db240e97-188d-48fd-98f3-7abd9131ffeb\\2df0e426-f569-459f-a4ad-d3f42539bc23\\f31826fa-10e3-4154-95c2-d89d21813379\\tile_0009.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "9d163f657df866f7a22b", - "path": "storage/tiles/db240e97-188d-48fd-98f3-7abd9131ffeb/2df0e426-f569-459f-a4ad-d3f42539bc23/f31826fa-10e3-4154-95c2-d89d21813379/tile_0009.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\db240e97-188d-48fd-98f3-7abd9131ffeb\\2df0e426-f569-459f-a4ad-d3f42539bc23\\f31826fa-10e3-4154-95c2-d89d21813379\\tile_0010.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "c3ecd380ee4499edfd90", - "path": "storage/tiles/db240e97-188d-48fd-98f3-7abd9131ffeb/2df0e426-f569-459f-a4ad-d3f42539bc23/f31826fa-10e3-4154-95c2-d89d21813379/tile_0010.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\db240e97-188d-48fd-98f3-7abd9131ffeb\\2df0e426-f569-459f-a4ad-d3f42539bc23\\f31826fa-10e3-4154-95c2-d89d21813379\\tile_0011.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "d46845df780977985a5e", - "path": "storage/tiles/db240e97-188d-48fd-98f3-7abd9131ffeb/2df0e426-f569-459f-a4ad-d3f42539bc23/f31826fa-10e3-4154-95c2-d89d21813379/tile_0011.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\db240e97-188d-48fd-98f3-7abd9131ffeb\\2df0e426-f569-459f-a4ad-d3f42539bc23\\f31826fa-10e3-4154-95c2-d89d21813379\\tile_0012.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "38b78e73d14a80e5034a", - "path": "storage/tiles/db240e97-188d-48fd-98f3-7abd9131ffeb/2df0e426-f569-459f-a4ad-d3f42539bc23/f31826fa-10e3-4154-95c2-d89d21813379/tile_0012.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\db240e97-188d-48fd-98f3-7abd9131ffeb\\2df0e426-f569-459f-a4ad-d3f42539bc23\\f31826fa-10e3-4154-95c2-d89d21813379\\tile_0013.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "d3c5bdffafb98153e8d9", - "path": "storage/tiles/db240e97-188d-48fd-98f3-7abd9131ffeb/2df0e426-f569-459f-a4ad-d3f42539bc23/f31826fa-10e3-4154-95c2-d89d21813379/tile_0013.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\db240e97-188d-48fd-98f3-7abd9131ffeb\\2df0e426-f569-459f-a4ad-d3f42539bc23\\f31826fa-10e3-4154-95c2-d89d21813379\\tile_0014.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "7e850fe24708dda753f0", - "path": "storage/tiles/db240e97-188d-48fd-98f3-7abd9131ffeb/2df0e426-f569-459f-a4ad-d3f42539bc23/f31826fa-10e3-4154-95c2-d89d21813379/tile_0014.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\db240e97-188d-48fd-98f3-7abd9131ffeb\\2df0e426-f569-459f-a4ad-d3f42539bc23\\f31826fa-10e3-4154-95c2-d89d21813379\\tile_0015.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "303f7135858218c797ce", - "path": "storage/tiles/db240e97-188d-48fd-98f3-7abd9131ffeb/2df0e426-f569-459f-a4ad-d3f42539bc23/f31826fa-10e3-4154-95c2-d89d21813379/tile_0015.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "quarantine", - "code": "manifest.zero_bbox", - "field": "bounds", - "message": "Manifest declares a zero-area bounding box", - "severity": "major" - } - ], - "item_id": "3838bd5bae003af13690", - "path": "storage/tiles/df217a4e-7f2e-4989-880e-30fb9a7ec645/f6848732-1f78-41ba-967c-11a577112b17/5e0d5f61-e7fb-4d4a-ae96-84b9060554d6/manifest.json", - "recommended_action": "quarantine" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\df217a4e-7f2e-4989-880e-30fb9a7ec645\\f6848732-1f78-41ba-967c-11a577112b17\\5e0d5f61-e7fb-4d4a-ae96-84b9060554d6\\tile_0000.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "295dc32a2407bf282a8c", - "path": "storage/tiles/df217a4e-7f2e-4989-880e-30fb9a7ec645/f6848732-1f78-41ba-967c-11a577112b17/5e0d5f61-e7fb-4d4a-ae96-84b9060554d6/tile_0000.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\df217a4e-7f2e-4989-880e-30fb9a7ec645\\f6848732-1f78-41ba-967c-11a577112b17\\5e0d5f61-e7fb-4d4a-ae96-84b9060554d6\\tile_0001.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "abd539c47bb02eed552f", - "path": "storage/tiles/df217a4e-7f2e-4989-880e-30fb9a7ec645/f6848732-1f78-41ba-967c-11a577112b17/5e0d5f61-e7fb-4d4a-ae96-84b9060554d6/tile_0001.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\df217a4e-7f2e-4989-880e-30fb9a7ec645\\f6848732-1f78-41ba-967c-11a577112b17\\5e0d5f61-e7fb-4d4a-ae96-84b9060554d6\\tile_0002.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "6f3267beda326834d472", - "path": "storage/tiles/df217a4e-7f2e-4989-880e-30fb9a7ec645/f6848732-1f78-41ba-967c-11a577112b17/5e0d5f61-e7fb-4d4a-ae96-84b9060554d6/tile_0002.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\df217a4e-7f2e-4989-880e-30fb9a7ec645\\f6848732-1f78-41ba-967c-11a577112b17\\5e0d5f61-e7fb-4d4a-ae96-84b9060554d6\\tile_0003.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "81ca8f6bfc34b1cdcb10", - "path": "storage/tiles/df217a4e-7f2e-4989-880e-30fb9a7ec645/f6848732-1f78-41ba-967c-11a577112b17/5e0d5f61-e7fb-4d4a-ae96-84b9060554d6/tile_0003.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\df217a4e-7f2e-4989-880e-30fb9a7ec645\\f6848732-1f78-41ba-967c-11a577112b17\\5e0d5f61-e7fb-4d4a-ae96-84b9060554d6\\tile_0004.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "7192190199b044390815", - "path": "storage/tiles/df217a4e-7f2e-4989-880e-30fb9a7ec645/f6848732-1f78-41ba-967c-11a577112b17/5e0d5f61-e7fb-4d4a-ae96-84b9060554d6/tile_0004.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\df217a4e-7f2e-4989-880e-30fb9a7ec645\\f6848732-1f78-41ba-967c-11a577112b17\\5e0d5f61-e7fb-4d4a-ae96-84b9060554d6\\tile_0005.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "b9d3054f0d9a803d09b5", - "path": "storage/tiles/df217a4e-7f2e-4989-880e-30fb9a7ec645/f6848732-1f78-41ba-967c-11a577112b17/5e0d5f61-e7fb-4d4a-ae96-84b9060554d6/tile_0005.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\df217a4e-7f2e-4989-880e-30fb9a7ec645\\f6848732-1f78-41ba-967c-11a577112b17\\5e0d5f61-e7fb-4d4a-ae96-84b9060554d6\\tile_0006.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "30a426290bc779af9d6a", - "path": "storage/tiles/df217a4e-7f2e-4989-880e-30fb9a7ec645/f6848732-1f78-41ba-967c-11a577112b17/5e0d5f61-e7fb-4d4a-ae96-84b9060554d6/tile_0006.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\df217a4e-7f2e-4989-880e-30fb9a7ec645\\f6848732-1f78-41ba-967c-11a577112b17\\5e0d5f61-e7fb-4d4a-ae96-84b9060554d6\\tile_0007.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "09bc3cdd65af8613dd32", - "path": "storage/tiles/df217a4e-7f2e-4989-880e-30fb9a7ec645/f6848732-1f78-41ba-967c-11a577112b17/5e0d5f61-e7fb-4d4a-ae96-84b9060554d6/tile_0007.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\df217a4e-7f2e-4989-880e-30fb9a7ec645\\f6848732-1f78-41ba-967c-11a577112b17\\5e0d5f61-e7fb-4d4a-ae96-84b9060554d6\\tile_0008.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "db688c755ad92613e5b2", - "path": "storage/tiles/df217a4e-7f2e-4989-880e-30fb9a7ec645/f6848732-1f78-41ba-967c-11a577112b17/5e0d5f61-e7fb-4d4a-ae96-84b9060554d6/tile_0008.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\df217a4e-7f2e-4989-880e-30fb9a7ec645\\f6848732-1f78-41ba-967c-11a577112b17\\5e0d5f61-e7fb-4d4a-ae96-84b9060554d6\\tile_0009.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "70cfc9a48bb0b6fbe125", - "path": "storage/tiles/df217a4e-7f2e-4989-880e-30fb9a7ec645/f6848732-1f78-41ba-967c-11a577112b17/5e0d5f61-e7fb-4d4a-ae96-84b9060554d6/tile_0009.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\df217a4e-7f2e-4989-880e-30fb9a7ec645\\f6848732-1f78-41ba-967c-11a577112b17\\5e0d5f61-e7fb-4d4a-ae96-84b9060554d6\\tile_0010.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "b8160ad197d56e6fefd2", - "path": "storage/tiles/df217a4e-7f2e-4989-880e-30fb9a7ec645/f6848732-1f78-41ba-967c-11a577112b17/5e0d5f61-e7fb-4d4a-ae96-84b9060554d6/tile_0010.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\df217a4e-7f2e-4989-880e-30fb9a7ec645\\f6848732-1f78-41ba-967c-11a577112b17\\5e0d5f61-e7fb-4d4a-ae96-84b9060554d6\\tile_0011.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "7815b5ffcca8b258f42e", - "path": "storage/tiles/df217a4e-7f2e-4989-880e-30fb9a7ec645/f6848732-1f78-41ba-967c-11a577112b17/5e0d5f61-e7fb-4d4a-ae96-84b9060554d6/tile_0011.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\df217a4e-7f2e-4989-880e-30fb9a7ec645\\f6848732-1f78-41ba-967c-11a577112b17\\5e0d5f61-e7fb-4d4a-ae96-84b9060554d6\\tile_0012.tif' not recognized as being in a supported file format.", - 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"recommended_action": "unavailable or unreadable" - } - ], - "reconciliation": { - "examined": 1013, - "inventory_total": 1016, - "reconciles": true, - "skipped": 0, - "unreachable": 3 - }, - "scan_id": "p3-eb67185e61107cc7", - "scanner_version": "3.1.0", - "schema_version": 1, - "source_freshness": { - "DHMV|unknown": 11, - "GRB|unknown": 18, - "Orthophoto|unknown": 34, - "unknown|declared": 7, - "unknown|unavailable": 3, - "unknown|unknown": 943 - }, - "started_at": "2026-08-30T00:46:44.775331+00:00" -} diff --git a/artifacts/evidence/accuracy/P3/leakage-report.json b/artifacts/evidence/accuracy/P3/leakage-report.json deleted file mode 100644 index 8c5889ea..00000000 --- a/artifacts/evidence/accuracy/P3/leakage-report.json +++ /dev/null @@ -1,20 +0,0 @@ -{ - "limitations": [ - "Filename-derived split tokens are conservative; AOI independence requires authoritative split geometry." - ], - "prior_quality_inventory": { - "cross_split_pairs_below_2000_m": 24, - "exact_cross_split_raster_hash_duplicates": 0, - 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"recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\277180a4-cd74-42ed-a231-0d194b3fca9f\\0f96a4f7-6b24-4969-9564-abbde30b5a51\\9199f079-42fc-48cc-86ff-d1072f801932\\tile_0010.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "379ac5f7a3a7d258b56f", - "path": "storage/tiles/277180a4-cd74-42ed-a231-0d194b3fca9f/0f96a4f7-6b24-4969-9564-abbde30b5a51/9199f079-42fc-48cc-86ff-d1072f801932/tile_0010.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\277180a4-cd74-42ed-a231-0d194b3fca9f\\0f96a4f7-6b24-4969-9564-abbde30b5a51\\9199f079-42fc-48cc-86ff-d1072f801932\\tile_0011.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "2ec9764c5631b5c7a1b4", - "path": "storage/tiles/277180a4-cd74-42ed-a231-0d194b3fca9f/0f96a4f7-6b24-4969-9564-abbde30b5a51/9199f079-42fc-48cc-86ff-d1072f801932/tile_0011.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\277180a4-cd74-42ed-a231-0d194b3fca9f\\0f96a4f7-6b24-4969-9564-abbde30b5a51\\9199f079-42fc-48cc-86ff-d1072f801932\\tile_0012.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "ac9cbb366a7c16a79b44", - "path": "storage/tiles/277180a4-cd74-42ed-a231-0d194b3fca9f/0f96a4f7-6b24-4969-9564-abbde30b5a51/9199f079-42fc-48cc-86ff-d1072f801932/tile_0012.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\277180a4-cd74-42ed-a231-0d194b3fca9f\\0f96a4f7-6b24-4969-9564-abbde30b5a51\\9199f079-42fc-48cc-86ff-d1072f801932\\tile_0013.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "5adaba8e404c16d70d1b", - "path": "storage/tiles/277180a4-cd74-42ed-a231-0d194b3fca9f/0f96a4f7-6b24-4969-9564-abbde30b5a51/9199f079-42fc-48cc-86ff-d1072f801932/tile_0013.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\277180a4-cd74-42ed-a231-0d194b3fca9f\\0f96a4f7-6b24-4969-9564-abbde30b5a51\\9199f079-42fc-48cc-86ff-d1072f801932\\tile_0014.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "e61c40ce9d3d2b9d369d", - "path": "storage/tiles/277180a4-cd74-42ed-a231-0d194b3fca9f/0f96a4f7-6b24-4969-9564-abbde30b5a51/9199f079-42fc-48cc-86ff-d1072f801932/tile_0014.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\277180a4-cd74-42ed-a231-0d194b3fca9f\\0f96a4f7-6b24-4969-9564-abbde30b5a51\\9199f079-42fc-48cc-86ff-d1072f801932\\tile_0015.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "a814da6efe81f095c9e3", - "path": "storage/tiles/277180a4-cd74-42ed-a231-0d194b3fca9f/0f96a4f7-6b24-4969-9564-abbde30b5a51/9199f079-42fc-48cc-86ff-d1072f801932/tile_0015.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "quarantine", - "code": "manifest.zero_bbox", - "field": "bounds", - "message": "Manifest declares a zero-area bounding box", - "severity": "major" - } - ], - "item_id": "1500315e2bdebe9d3462", - "path": "storage/tiles/7175ae58-2b09-4fab-83e1-5d95e2969d35/07738ebe-2c5e-4d6c-960d-1c03f216a3a0/7529e658-b42a-47cb-a23c-d9d350b5d8c4/manifest.json", - "recommended_action": "quarantine" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\7175ae58-2b09-4fab-83e1-5d95e2969d35\\07738ebe-2c5e-4d6c-960d-1c03f216a3a0\\7529e658-b42a-47cb-a23c-d9d350b5d8c4\\tile_0000.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "82177cf3088b3fae2281", - "path": "storage/tiles/7175ae58-2b09-4fab-83e1-5d95e2969d35/07738ebe-2c5e-4d6c-960d-1c03f216a3a0/7529e658-b42a-47cb-a23c-d9d350b5d8c4/tile_0000.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\7175ae58-2b09-4fab-83e1-5d95e2969d35\\07738ebe-2c5e-4d6c-960d-1c03f216a3a0\\7529e658-b42a-47cb-a23c-d9d350b5d8c4\\tile_0001.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "6c9f6f1cd68adead5055", - "path": "storage/tiles/7175ae58-2b09-4fab-83e1-5d95e2969d35/07738ebe-2c5e-4d6c-960d-1c03f216a3a0/7529e658-b42a-47cb-a23c-d9d350b5d8c4/tile_0001.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\7175ae58-2b09-4fab-83e1-5d95e2969d35\\07738ebe-2c5e-4d6c-960d-1c03f216a3a0\\7529e658-b42a-47cb-a23c-d9d350b5d8c4\\tile_0002.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "c8280727cb07e1423a97", - "path": "storage/tiles/7175ae58-2b09-4fab-83e1-5d95e2969d35/07738ebe-2c5e-4d6c-960d-1c03f216a3a0/7529e658-b42a-47cb-a23c-d9d350b5d8c4/tile_0002.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\7175ae58-2b09-4fab-83e1-5d95e2969d35\\07738ebe-2c5e-4d6c-960d-1c03f216a3a0\\7529e658-b42a-47cb-a23c-d9d350b5d8c4\\tile_0003.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "2e89e578c950d03db653", - "path": "storage/tiles/7175ae58-2b09-4fab-83e1-5d95e2969d35/07738ebe-2c5e-4d6c-960d-1c03f216a3a0/7529e658-b42a-47cb-a23c-d9d350b5d8c4/tile_0003.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\7175ae58-2b09-4fab-83e1-5d95e2969d35\\07738ebe-2c5e-4d6c-960d-1c03f216a3a0\\7529e658-b42a-47cb-a23c-d9d350b5d8c4\\tile_0004.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "0e60a5f162f918773b06", - "path": "storage/tiles/7175ae58-2b09-4fab-83e1-5d95e2969d35/07738ebe-2c5e-4d6c-960d-1c03f216a3a0/7529e658-b42a-47cb-a23c-d9d350b5d8c4/tile_0004.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\7175ae58-2b09-4fab-83e1-5d95e2969d35\\07738ebe-2c5e-4d6c-960d-1c03f216a3a0\\7529e658-b42a-47cb-a23c-d9d350b5d8c4\\tile_0005.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "4b1ff1eeb59cf97d722c", - "path": "storage/tiles/7175ae58-2b09-4fab-83e1-5d95e2969d35/07738ebe-2c5e-4d6c-960d-1c03f216a3a0/7529e658-b42a-47cb-a23c-d9d350b5d8c4/tile_0005.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\7175ae58-2b09-4fab-83e1-5d95e2969d35\\07738ebe-2c5e-4d6c-960d-1c03f216a3a0\\7529e658-b42a-47cb-a23c-d9d350b5d8c4\\tile_0006.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "71fff7a0187642c79b89", - "path": "storage/tiles/7175ae58-2b09-4fab-83e1-5d95e2969d35/07738ebe-2c5e-4d6c-960d-1c03f216a3a0/7529e658-b42a-47cb-a23c-d9d350b5d8c4/tile_0006.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\7175ae58-2b09-4fab-83e1-5d95e2969d35\\07738ebe-2c5e-4d6c-960d-1c03f216a3a0\\7529e658-b42a-47cb-a23c-d9d350b5d8c4\\tile_0007.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "90c5c1cbd336f0758242", - "path": "storage/tiles/7175ae58-2b09-4fab-83e1-5d95e2969d35/07738ebe-2c5e-4d6c-960d-1c03f216a3a0/7529e658-b42a-47cb-a23c-d9d350b5d8c4/tile_0007.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\7175ae58-2b09-4fab-83e1-5d95e2969d35\\07738ebe-2c5e-4d6c-960d-1c03f216a3a0\\7529e658-b42a-47cb-a23c-d9d350b5d8c4\\tile_0008.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "d3b1d530bd052ac1b53e", - "path": "storage/tiles/7175ae58-2b09-4fab-83e1-5d95e2969d35/07738ebe-2c5e-4d6c-960d-1c03f216a3a0/7529e658-b42a-47cb-a23c-d9d350b5d8c4/tile_0008.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\7175ae58-2b09-4fab-83e1-5d95e2969d35\\07738ebe-2c5e-4d6c-960d-1c03f216a3a0\\7529e658-b42a-47cb-a23c-d9d350b5d8c4\\tile_0009.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "8cb6365e148d4e5b9b33", - "path": "storage/tiles/7175ae58-2b09-4fab-83e1-5d95e2969d35/07738ebe-2c5e-4d6c-960d-1c03f216a3a0/7529e658-b42a-47cb-a23c-d9d350b5d8c4/tile_0009.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\7175ae58-2b09-4fab-83e1-5d95e2969d35\\07738ebe-2c5e-4d6c-960d-1c03f216a3a0\\7529e658-b42a-47cb-a23c-d9d350b5d8c4\\tile_0010.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "3c46ab42aef67799f868", - "path": "storage/tiles/7175ae58-2b09-4fab-83e1-5d95e2969d35/07738ebe-2c5e-4d6c-960d-1c03f216a3a0/7529e658-b42a-47cb-a23c-d9d350b5d8c4/tile_0010.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\7175ae58-2b09-4fab-83e1-5d95e2969d35\\07738ebe-2c5e-4d6c-960d-1c03f216a3a0\\7529e658-b42a-47cb-a23c-d9d350b5d8c4\\tile_0011.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "51dae1e198b0e2be9a25", - "path": "storage/tiles/7175ae58-2b09-4fab-83e1-5d95e2969d35/07738ebe-2c5e-4d6c-960d-1c03f216a3a0/7529e658-b42a-47cb-a23c-d9d350b5d8c4/tile_0011.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\7175ae58-2b09-4fab-83e1-5d95e2969d35\\07738ebe-2c5e-4d6c-960d-1c03f216a3a0\\7529e658-b42a-47cb-a23c-d9d350b5d8c4\\tile_0012.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "6587704f64f657c9b261", - "path": "storage/tiles/7175ae58-2b09-4fab-83e1-5d95e2969d35/07738ebe-2c5e-4d6c-960d-1c03f216a3a0/7529e658-b42a-47cb-a23c-d9d350b5d8c4/tile_0012.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\7175ae58-2b09-4fab-83e1-5d95e2969d35\\07738ebe-2c5e-4d6c-960d-1c03f216a3a0\\7529e658-b42a-47cb-a23c-d9d350b5d8c4\\tile_0013.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "b7965c4fe187fb9a6e72", - "path": "storage/tiles/7175ae58-2b09-4fab-83e1-5d95e2969d35/07738ebe-2c5e-4d6c-960d-1c03f216a3a0/7529e658-b42a-47cb-a23c-d9d350b5d8c4/tile_0013.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\7175ae58-2b09-4fab-83e1-5d95e2969d35\\07738ebe-2c5e-4d6c-960d-1c03f216a3a0\\7529e658-b42a-47cb-a23c-d9d350b5d8c4\\tile_0014.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "b54051b8cb4ca92387b2", - "path": "storage/tiles/7175ae58-2b09-4fab-83e1-5d95e2969d35/07738ebe-2c5e-4d6c-960d-1c03f216a3a0/7529e658-b42a-47cb-a23c-d9d350b5d8c4/tile_0014.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\7175ae58-2b09-4fab-83e1-5d95e2969d35\\07738ebe-2c5e-4d6c-960d-1c03f216a3a0\\7529e658-b42a-47cb-a23c-d9d350b5d8c4\\tile_0015.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "85abe6c3be8c5f60f542", - "path": "storage/tiles/7175ae58-2b09-4fab-83e1-5d95e2969d35/07738ebe-2c5e-4d6c-960d-1c03f216a3a0/7529e658-b42a-47cb-a23c-d9d350b5d8c4/tile_0015.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "quarantine", - "code": "manifest.zero_bbox", - "field": "bounds", - "message": "Manifest declares a zero-area bounding box", - "severity": "major" - } - ], - "item_id": "b6b16941c235d9cb21df", - "path": "storage/tiles/a7a94d0b-9b27-49bd-9e44-97b0b75677ad/e2a3f62a-76f0-4611-81a3-d2ca948cda75/6e53d525-f603-4eb3-8bf7-05da59832013/manifest.json", - "recommended_action": "quarantine" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\a7a94d0b-9b27-49bd-9e44-97b0b75677ad\\e2a3f62a-76f0-4611-81a3-d2ca948cda75\\6e53d525-f603-4eb3-8bf7-05da59832013\\tile_0000.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "20e3d2bb3ee9bb98f8b2", - "path": "storage/tiles/a7a94d0b-9b27-49bd-9e44-97b0b75677ad/e2a3f62a-76f0-4611-81a3-d2ca948cda75/6e53d525-f603-4eb3-8bf7-05da59832013/tile_0000.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\a7a94d0b-9b27-49bd-9e44-97b0b75677ad\\e2a3f62a-76f0-4611-81a3-d2ca948cda75\\6e53d525-f603-4eb3-8bf7-05da59832013\\tile_0001.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "4e4919deb1ec3b7df24d", - "path": "storage/tiles/a7a94d0b-9b27-49bd-9e44-97b0b75677ad/e2a3f62a-76f0-4611-81a3-d2ca948cda75/6e53d525-f603-4eb3-8bf7-05da59832013/tile_0001.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\a7a94d0b-9b27-49bd-9e44-97b0b75677ad\\e2a3f62a-76f0-4611-81a3-d2ca948cda75\\6e53d525-f603-4eb3-8bf7-05da59832013\\tile_0002.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "0f87eb34f3f0359638a2", - "path": "storage/tiles/a7a94d0b-9b27-49bd-9e44-97b0b75677ad/e2a3f62a-76f0-4611-81a3-d2ca948cda75/6e53d525-f603-4eb3-8bf7-05da59832013/tile_0002.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\a7a94d0b-9b27-49bd-9e44-97b0b75677ad\\e2a3f62a-76f0-4611-81a3-d2ca948cda75\\6e53d525-f603-4eb3-8bf7-05da59832013\\tile_0003.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "e5f08ed47ebbc2dc539d", - "path": "storage/tiles/a7a94d0b-9b27-49bd-9e44-97b0b75677ad/e2a3f62a-76f0-4611-81a3-d2ca948cda75/6e53d525-f603-4eb3-8bf7-05da59832013/tile_0003.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\a7a94d0b-9b27-49bd-9e44-97b0b75677ad\\e2a3f62a-76f0-4611-81a3-d2ca948cda75\\6e53d525-f603-4eb3-8bf7-05da59832013\\tile_0004.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "776ded90bfd4c9e66373", - "path": "storage/tiles/a7a94d0b-9b27-49bd-9e44-97b0b75677ad/e2a3f62a-76f0-4611-81a3-d2ca948cda75/6e53d525-f603-4eb3-8bf7-05da59832013/tile_0004.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\a7a94d0b-9b27-49bd-9e44-97b0b75677ad\\e2a3f62a-76f0-4611-81a3-d2ca948cda75\\6e53d525-f603-4eb3-8bf7-05da59832013\\tile_0005.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "2a37d92cc1f4c7760875", - "path": "storage/tiles/a7a94d0b-9b27-49bd-9e44-97b0b75677ad/e2a3f62a-76f0-4611-81a3-d2ca948cda75/6e53d525-f603-4eb3-8bf7-05da59832013/tile_0005.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\a7a94d0b-9b27-49bd-9e44-97b0b75677ad\\e2a3f62a-76f0-4611-81a3-d2ca948cda75\\6e53d525-f603-4eb3-8bf7-05da59832013\\tile_0006.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "d3d5a58eb923e4e58858", - "path": "storage/tiles/a7a94d0b-9b27-49bd-9e44-97b0b75677ad/e2a3f62a-76f0-4611-81a3-d2ca948cda75/6e53d525-f603-4eb3-8bf7-05da59832013/tile_0006.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\a7a94d0b-9b27-49bd-9e44-97b0b75677ad\\e2a3f62a-76f0-4611-81a3-d2ca948cda75\\6e53d525-f603-4eb3-8bf7-05da59832013\\tile_0007.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "91c929ee528e638a6a76", - "path": "storage/tiles/a7a94d0b-9b27-49bd-9e44-97b0b75677ad/e2a3f62a-76f0-4611-81a3-d2ca948cda75/6e53d525-f603-4eb3-8bf7-05da59832013/tile_0007.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\a7a94d0b-9b27-49bd-9e44-97b0b75677ad\\e2a3f62a-76f0-4611-81a3-d2ca948cda75\\6e53d525-f603-4eb3-8bf7-05da59832013\\tile_0008.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "e480cf83cf5db4b2e52d", - "path": "storage/tiles/a7a94d0b-9b27-49bd-9e44-97b0b75677ad/e2a3f62a-76f0-4611-81a3-d2ca948cda75/6e53d525-f603-4eb3-8bf7-05da59832013/tile_0008.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\a7a94d0b-9b27-49bd-9e44-97b0b75677ad\\e2a3f62a-76f0-4611-81a3-d2ca948cda75\\6e53d525-f603-4eb3-8bf7-05da59832013\\tile_0009.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "c0ad18065477ffaad4ac", - "path": "storage/tiles/a7a94d0b-9b27-49bd-9e44-97b0b75677ad/e2a3f62a-76f0-4611-81a3-d2ca948cda75/6e53d525-f603-4eb3-8bf7-05da59832013/tile_0009.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\a7a94d0b-9b27-49bd-9e44-97b0b75677ad\\e2a3f62a-76f0-4611-81a3-d2ca948cda75\\6e53d525-f603-4eb3-8bf7-05da59832013\\tile_0010.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "ba9cbe3cdf31c09754b6", - "path": "storage/tiles/a7a94d0b-9b27-49bd-9e44-97b0b75677ad/e2a3f62a-76f0-4611-81a3-d2ca948cda75/6e53d525-f603-4eb3-8bf7-05da59832013/tile_0010.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\a7a94d0b-9b27-49bd-9e44-97b0b75677ad\\e2a3f62a-76f0-4611-81a3-d2ca948cda75\\6e53d525-f603-4eb3-8bf7-05da59832013\\tile_0011.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "74791aaeb46bd8705f5c", - "path": "storage/tiles/a7a94d0b-9b27-49bd-9e44-97b0b75677ad/e2a3f62a-76f0-4611-81a3-d2ca948cda75/6e53d525-f603-4eb3-8bf7-05da59832013/tile_0011.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\a7a94d0b-9b27-49bd-9e44-97b0b75677ad\\e2a3f62a-76f0-4611-81a3-d2ca948cda75\\6e53d525-f603-4eb3-8bf7-05da59832013\\tile_0012.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "e6494b03753f6de23316", - "path": "storage/tiles/a7a94d0b-9b27-49bd-9e44-97b0b75677ad/e2a3f62a-76f0-4611-81a3-d2ca948cda75/6e53d525-f603-4eb3-8bf7-05da59832013/tile_0012.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\a7a94d0b-9b27-49bd-9e44-97b0b75677ad\\e2a3f62a-76f0-4611-81a3-d2ca948cda75\\6e53d525-f603-4eb3-8bf7-05da59832013\\tile_0013.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "c2301617d835cbe7a9da", - "path": "storage/tiles/a7a94d0b-9b27-49bd-9e44-97b0b75677ad/e2a3f62a-76f0-4611-81a3-d2ca948cda75/6e53d525-f603-4eb3-8bf7-05da59832013/tile_0013.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\a7a94d0b-9b27-49bd-9e44-97b0b75677ad\\e2a3f62a-76f0-4611-81a3-d2ca948cda75\\6e53d525-f603-4eb3-8bf7-05da59832013\\tile_0014.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "712708cfd7b54f652c1f", - "path": "storage/tiles/a7a94d0b-9b27-49bd-9e44-97b0b75677ad/e2a3f62a-76f0-4611-81a3-d2ca948cda75/6e53d525-f603-4eb3-8bf7-05da59832013/tile_0014.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\a7a94d0b-9b27-49bd-9e44-97b0b75677ad\\e2a3f62a-76f0-4611-81a3-d2ca948cda75\\6e53d525-f603-4eb3-8bf7-05da59832013\\tile_0015.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "bfbadaaae125e34b5828", - "path": "storage/tiles/a7a94d0b-9b27-49bd-9e44-97b0b75677ad/e2a3f62a-76f0-4611-81a3-d2ca948cda75/6e53d525-f603-4eb3-8bf7-05da59832013/tile_0015.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "quarantine", - "code": "manifest.zero_bbox", - "field": "bounds", - "message": "Manifest declares a zero-area bounding box", - "severity": "major" - } - ], - "item_id": "04f3407f941cd1dc895e", - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/manifest.json", - "recommended_action": "quarantine" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0000.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "4def26f935acc400079e", - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/tile_0000.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0001.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "9e093656fa6b9d623331", - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/tile_0001.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0002.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "463efcbe145941dc1ded", - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/tile_0002.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0003.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "6b1012bfdedb2641eb37", - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/tile_0003.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0004.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "71979d432b49d84e9e75", - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/tile_0004.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0005.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "649fd55f6d877aa78bb2", - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/tile_0005.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0006.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "52e170d64fb1a011de45", - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/tile_0006.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0007.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "46628f46cd8911a36f86", - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/tile_0007.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0008.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "889b2e92c1aa378722aa", - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/tile_0008.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0009.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "67a46403c7fb388bb484", - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/tile_0009.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0010.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "25123fae6d918a76ac7a", - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/tile_0010.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0011.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "7407fad7de42e36fe791", - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/tile_0011.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0012.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "eaa22fd47e90efa7dbdd", - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/tile_0012.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0013.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "46aaf33ee50eaa14edfd", - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/tile_0013.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0014.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "6d3766eca60a28941699", - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/tile_0014.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0015.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "a870f7c9d918ccf7d5a6", - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/tile_0015.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "quarantine", - "code": "manifest.zero_bbox", - "field": "bounds", - "message": "Manifest declares a zero-area bounding box", - "severity": "major" - } - ], - "item_id": "42f97df8f1716a98cc5a", - "path": "storage/tiles/db240e97-188d-48fd-98f3-7abd9131ffeb/2df0e426-f569-459f-a4ad-d3f42539bc23/f31826fa-10e3-4154-95c2-d89d21813379/manifest.json", - "recommended_action": "quarantine" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\db240e97-188d-48fd-98f3-7abd9131ffeb\\2df0e426-f569-459f-a4ad-d3f42539bc23\\f31826fa-10e3-4154-95c2-d89d21813379\\tile_0000.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "33b3c33cb179ac85ada1", - "path": "storage/tiles/db240e97-188d-48fd-98f3-7abd9131ffeb/2df0e426-f569-459f-a4ad-d3f42539bc23/f31826fa-10e3-4154-95c2-d89d21813379/tile_0000.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\db240e97-188d-48fd-98f3-7abd9131ffeb\\2df0e426-f569-459f-a4ad-d3f42539bc23\\f31826fa-10e3-4154-95c2-d89d21813379\\tile_0001.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "346a71885fe0853cfc30", - "path": "storage/tiles/db240e97-188d-48fd-98f3-7abd9131ffeb/2df0e426-f569-459f-a4ad-d3f42539bc23/f31826fa-10e3-4154-95c2-d89d21813379/tile_0001.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\db240e97-188d-48fd-98f3-7abd9131ffeb\\2df0e426-f569-459f-a4ad-d3f42539bc23\\f31826fa-10e3-4154-95c2-d89d21813379\\tile_0002.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "6fab06961d3c3d439c73", - "path": "storage/tiles/db240e97-188d-48fd-98f3-7abd9131ffeb/2df0e426-f569-459f-a4ad-d3f42539bc23/f31826fa-10e3-4154-95c2-d89d21813379/tile_0002.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\db240e97-188d-48fd-98f3-7abd9131ffeb\\2df0e426-f569-459f-a4ad-d3f42539bc23\\f31826fa-10e3-4154-95c2-d89d21813379\\tile_0003.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "bc61a64bf00351eaa325", - "path": "storage/tiles/db240e97-188d-48fd-98f3-7abd9131ffeb/2df0e426-f569-459f-a4ad-d3f42539bc23/f31826fa-10e3-4154-95c2-d89d21813379/tile_0003.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\db240e97-188d-48fd-98f3-7abd9131ffeb\\2df0e426-f569-459f-a4ad-d3f42539bc23\\f31826fa-10e3-4154-95c2-d89d21813379\\tile_0004.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "af6d1e573b5b4b191b87", - "path": "storage/tiles/db240e97-188d-48fd-98f3-7abd9131ffeb/2df0e426-f569-459f-a4ad-d3f42539bc23/f31826fa-10e3-4154-95c2-d89d21813379/tile_0004.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\db240e97-188d-48fd-98f3-7abd9131ffeb\\2df0e426-f569-459f-a4ad-d3f42539bc23\\f31826fa-10e3-4154-95c2-d89d21813379\\tile_0005.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "ef9696bc380f7e9dc039", - "path": "storage/tiles/db240e97-188d-48fd-98f3-7abd9131ffeb/2df0e426-f569-459f-a4ad-d3f42539bc23/f31826fa-10e3-4154-95c2-d89d21813379/tile_0005.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\db240e97-188d-48fd-98f3-7abd9131ffeb\\2df0e426-f569-459f-a4ad-d3f42539bc23\\f31826fa-10e3-4154-95c2-d89d21813379\\tile_0006.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "e440975ad15713709d14", - "path": "storage/tiles/db240e97-188d-48fd-98f3-7abd9131ffeb/2df0e426-f569-459f-a4ad-d3f42539bc23/f31826fa-10e3-4154-95c2-d89d21813379/tile_0006.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\db240e97-188d-48fd-98f3-7abd9131ffeb\\2df0e426-f569-459f-a4ad-d3f42539bc23\\f31826fa-10e3-4154-95c2-d89d21813379\\tile_0007.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "3f1f44d08c10be760fa3", - "path": "storage/tiles/db240e97-188d-48fd-98f3-7abd9131ffeb/2df0e426-f569-459f-a4ad-d3f42539bc23/f31826fa-10e3-4154-95c2-d89d21813379/tile_0007.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\db240e97-188d-48fd-98f3-7abd9131ffeb\\2df0e426-f569-459f-a4ad-d3f42539bc23\\f31826fa-10e3-4154-95c2-d89d21813379\\tile_0008.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "bc0e44ce91c97c3723c9", - "path": "storage/tiles/db240e97-188d-48fd-98f3-7abd9131ffeb/2df0e426-f569-459f-a4ad-d3f42539bc23/f31826fa-10e3-4154-95c2-d89d21813379/tile_0008.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\db240e97-188d-48fd-98f3-7abd9131ffeb\\2df0e426-f569-459f-a4ad-d3f42539bc23\\f31826fa-10e3-4154-95c2-d89d21813379\\tile_0009.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "9d163f657df866f7a22b", - "path": "storage/tiles/db240e97-188d-48fd-98f3-7abd9131ffeb/2df0e426-f569-459f-a4ad-d3f42539bc23/f31826fa-10e3-4154-95c2-d89d21813379/tile_0009.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\db240e97-188d-48fd-98f3-7abd9131ffeb\\2df0e426-f569-459f-a4ad-d3f42539bc23\\f31826fa-10e3-4154-95c2-d89d21813379\\tile_0010.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "c3ecd380ee4499edfd90", - "path": "storage/tiles/db240e97-188d-48fd-98f3-7abd9131ffeb/2df0e426-f569-459f-a4ad-d3f42539bc23/f31826fa-10e3-4154-95c2-d89d21813379/tile_0010.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\db240e97-188d-48fd-98f3-7abd9131ffeb\\2df0e426-f569-459f-a4ad-d3f42539bc23\\f31826fa-10e3-4154-95c2-d89d21813379\\tile_0011.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "d46845df780977985a5e", - "path": "storage/tiles/db240e97-188d-48fd-98f3-7abd9131ffeb/2df0e426-f569-459f-a4ad-d3f42539bc23/f31826fa-10e3-4154-95c2-d89d21813379/tile_0011.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\db240e97-188d-48fd-98f3-7abd9131ffeb\\2df0e426-f569-459f-a4ad-d3f42539bc23\\f31826fa-10e3-4154-95c2-d89d21813379\\tile_0012.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "38b78e73d14a80e5034a", - "path": "storage/tiles/db240e97-188d-48fd-98f3-7abd9131ffeb/2df0e426-f569-459f-a4ad-d3f42539bc23/f31826fa-10e3-4154-95c2-d89d21813379/tile_0012.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\db240e97-188d-48fd-98f3-7abd9131ffeb\\2df0e426-f569-459f-a4ad-d3f42539bc23\\f31826fa-10e3-4154-95c2-d89d21813379\\tile_0013.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "d3c5bdffafb98153e8d9", - "path": "storage/tiles/db240e97-188d-48fd-98f3-7abd9131ffeb/2df0e426-f569-459f-a4ad-d3f42539bc23/f31826fa-10e3-4154-95c2-d89d21813379/tile_0013.tif", - "recommended_action": "unavailable or unreadable" - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\db240e97-188d-48fd-98f3-7abd9131ffeb\\2df0e426-f569-459f-a4ad-d3f42539bc23\\f31826fa-10e3-4154-95c2-d89d21813379\\tile_0014.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "item_id": "7e850fe24708dda753f0", - "path": "storage/tiles/db240e97-188d-48fd-98f3-7abd9131ffeb/2df0e426-f569-459f-a4ad-d3f42539bc23/f31826fa-10e3-4154-95c2-d89d21813379/tile_0014.tif", - 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"path": "storage/tiles/277180a4-cd74-42ed-a231-0d194b3fca9f/0f96a4f7-6b24-4969-9564-abbde30b5a51/9199f079-42fc-48cc-86ff-d1072f801932/tile_0005.tif", - "read_status": "unreadable", - "recommended_action": "unavailable or unreadable", - "resolution": null, - "schema_conformity": "invalid", - "sha256": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "size_bytes": 4, - "source": "unknown", - "spatial_coverage": null, - "status": "examined", - "temporal_coverage": null, - "units": null - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\277180a4-cd74-42ed-a231-0d194b3fca9f\\0f96a4f7-6b24-4969-9564-abbde30b5a51\\9199f079-42fc-48cc-86ff-d1072f801932\\tile_0006.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "contract": { - "key": "geointel.raster.geotiff", - "version": "1.0.0" - }, - "crs": null, - "duplicate_group": null, - "empty_content": false, - "freshness": { - "reason": "no_declared_source_timestamp", - "status": "unknown" - }, - "geometry_validation": null, - "item_id": "2200c4a8006caa7fd98a", - "lineage": null, - "modified_at": "2026-08-01T15:45:08.530394+00:00", - "near_duplicate_fingerprint": null, - "path": "storage/tiles/277180a4-cd74-42ed-a231-0d194b3fca9f/0f96a4f7-6b24-4969-9564-abbde30b5a51/9199f079-42fc-48cc-86ff-d1072f801932/tile_0006.tif", - "read_status": "unreadable", - "recommended_action": "unavailable or unreadable", - "resolution": null, - "schema_conformity": "invalid", - "sha256": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "size_bytes": 4, - "source": "unknown", - "spatial_coverage": null, - "status": "examined", - "temporal_coverage": null, - "units": null - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\277180a4-cd74-42ed-a231-0d194b3fca9f\\0f96a4f7-6b24-4969-9564-abbde30b5a51\\9199f079-42fc-48cc-86ff-d1072f801932\\tile_0007.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "contract": { - "key": "geointel.raster.geotiff", - "version": "1.0.0" - }, - "crs": null, - "duplicate_group": null, - "empty_content": false, - "freshness": { - "reason": "no_declared_source_timestamp", - "status": "unknown" - }, - "geometry_validation": null, - "item_id": "f4fb0308ffbd8d6fd880", - "lineage": null, - "modified_at": "2026-08-01T15:45:08.531394+00:00", - "near_duplicate_fingerprint": null, - "path": "storage/tiles/277180a4-cd74-42ed-a231-0d194b3fca9f/0f96a4f7-6b24-4969-9564-abbde30b5a51/9199f079-42fc-48cc-86ff-d1072f801932/tile_0007.tif", - "read_status": "unreadable", - "recommended_action": "unavailable or unreadable", - "resolution": null, - "schema_conformity": "invalid", - "sha256": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "size_bytes": 4, - "source": "unknown", - "spatial_coverage": null, - "status": "examined", - "temporal_coverage": null, - "units": null - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\277180a4-cd74-42ed-a231-0d194b3fca9f\\0f96a4f7-6b24-4969-9564-abbde30b5a51\\9199f079-42fc-48cc-86ff-d1072f801932\\tile_0008.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "contract": { - "key": "geointel.raster.geotiff", - "version": "1.0.0" - }, - "crs": null, - "duplicate_group": null, - "empty_content": false, - "freshness": { - "reason": "no_declared_source_timestamp", - "status": "unknown" - }, - "geometry_validation": null, - "item_id": "b18eaa92bfb6f82949cc", - "lineage": null, - "modified_at": "2026-08-01T15:45:08.532395+00:00", - "near_duplicate_fingerprint": null, - "path": "storage/tiles/277180a4-cd74-42ed-a231-0d194b3fca9f/0f96a4f7-6b24-4969-9564-abbde30b5a51/9199f079-42fc-48cc-86ff-d1072f801932/tile_0008.tif", - "read_status": "unreadable", - "recommended_action": "unavailable or unreadable", - "resolution": null, - "schema_conformity": "invalid", - "sha256": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "size_bytes": 4, - "source": "unknown", - "spatial_coverage": null, - "status": "examined", - "temporal_coverage": null, - "units": null - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\277180a4-cd74-42ed-a231-0d194b3fca9f\\0f96a4f7-6b24-4969-9564-abbde30b5a51\\9199f079-42fc-48cc-86ff-d1072f801932\\tile_0009.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "contract": { - "key": "geointel.raster.geotiff", - "version": "1.0.0" - }, - "crs": null, - "duplicate_group": null, - "empty_content": false, - "freshness": { - "reason": "no_declared_source_timestamp", - "status": "unknown" - }, - "geometry_validation": null, - "item_id": "f87e566976251b0ddd3d", - "lineage": null, - "modified_at": "2026-08-01T15:45:08.533397+00:00", - "near_duplicate_fingerprint": null, - "path": "storage/tiles/277180a4-cd74-42ed-a231-0d194b3fca9f/0f96a4f7-6b24-4969-9564-abbde30b5a51/9199f079-42fc-48cc-86ff-d1072f801932/tile_0009.tif", - "read_status": "unreadable", - "recommended_action": "unavailable or unreadable", - "resolution": null, - "schema_conformity": "invalid", - "sha256": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "size_bytes": 4, - "source": "unknown", - "spatial_coverage": null, - "status": "examined", - "temporal_coverage": null, - "units": null - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\277180a4-cd74-42ed-a231-0d194b3fca9f\\0f96a4f7-6b24-4969-9564-abbde30b5a51\\9199f079-42fc-48cc-86ff-d1072f801932\\tile_0010.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "contract": { - "key": "geointel.raster.geotiff", - "version": "1.0.0" - }, - "crs": null, - "duplicate_group": null, - "empty_content": false, - "freshness": { - "reason": "no_declared_source_timestamp", - "status": "unknown" - }, - "geometry_validation": null, - "item_id": "379ac5f7a3a7d258b56f", - "lineage": null, - "modified_at": "2026-08-01T15:45:08.534397+00:00", - "near_duplicate_fingerprint": null, - "path": "storage/tiles/277180a4-cd74-42ed-a231-0d194b3fca9f/0f96a4f7-6b24-4969-9564-abbde30b5a51/9199f079-42fc-48cc-86ff-d1072f801932/tile_0010.tif", - "read_status": "unreadable", - "recommended_action": "unavailable or unreadable", - "resolution": null, - "schema_conformity": "invalid", - "sha256": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "size_bytes": 4, - "source": "unknown", - "spatial_coverage": null, - "status": "examined", - "temporal_coverage": null, - "units": null - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\277180a4-cd74-42ed-a231-0d194b3fca9f\\0f96a4f7-6b24-4969-9564-abbde30b5a51\\9199f079-42fc-48cc-86ff-d1072f801932\\tile_0011.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "contract": { - "key": "geointel.raster.geotiff", - "version": "1.0.0" - }, - "crs": null, - "duplicate_group": null, - "empty_content": false, - "freshness": { - "reason": "no_declared_source_timestamp", - "status": "unknown" - }, - "geometry_validation": null, - "item_id": "2ec9764c5631b5c7a1b4", - "lineage": null, - "modified_at": "2026-08-01T15:45:08.534397+00:00", - "near_duplicate_fingerprint": null, - "path": "storage/tiles/277180a4-cd74-42ed-a231-0d194b3fca9f/0f96a4f7-6b24-4969-9564-abbde30b5a51/9199f079-42fc-48cc-86ff-d1072f801932/tile_0011.tif", - "read_status": "unreadable", - "recommended_action": "unavailable or unreadable", - "resolution": null, - "schema_conformity": "invalid", - "sha256": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "size_bytes": 4, - "source": "unknown", - "spatial_coverage": null, - "status": "examined", - "temporal_coverage": null, - "units": null - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\277180a4-cd74-42ed-a231-0d194b3fca9f\\0f96a4f7-6b24-4969-9564-abbde30b5a51\\9199f079-42fc-48cc-86ff-d1072f801932\\tile_0012.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "contract": { - "key": "geointel.raster.geotiff", - "version": "1.0.0" - }, - "crs": null, - "duplicate_group": null, - "empty_content": false, - "freshness": { - "reason": "no_declared_source_timestamp", - "status": "unknown" - }, - "geometry_validation": null, - "item_id": "ac9cbb366a7c16a79b44", - "lineage": null, - "modified_at": "2026-08-01T15:45:08.535398+00:00", - "near_duplicate_fingerprint": null, - "path": "storage/tiles/277180a4-cd74-42ed-a231-0d194b3fca9f/0f96a4f7-6b24-4969-9564-abbde30b5a51/9199f079-42fc-48cc-86ff-d1072f801932/tile_0012.tif", - "read_status": "unreadable", - "recommended_action": "unavailable or unreadable", - "resolution": null, - "schema_conformity": "invalid", - "sha256": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "size_bytes": 4, - "source": "unknown", - "spatial_coverage": null, - "status": "examined", - "temporal_coverage": null, - "units": null - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\277180a4-cd74-42ed-a231-0d194b3fca9f\\0f96a4f7-6b24-4969-9564-abbde30b5a51\\9199f079-42fc-48cc-86ff-d1072f801932\\tile_0013.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "contract": { - "key": "geointel.raster.geotiff", - "version": "1.0.0" - }, - "crs": null, - "duplicate_group": null, - "empty_content": false, - "freshness": { - "reason": "no_declared_source_timestamp", - "status": "unknown" - }, - "geometry_validation": null, - "item_id": "5adaba8e404c16d70d1b", - "lineage": null, - "modified_at": "2026-08-01T15:45:08.536394+00:00", - "near_duplicate_fingerprint": null, - "path": "storage/tiles/277180a4-cd74-42ed-a231-0d194b3fca9f/0f96a4f7-6b24-4969-9564-abbde30b5a51/9199f079-42fc-48cc-86ff-d1072f801932/tile_0013.tif", - "read_status": "unreadable", - "recommended_action": "unavailable or unreadable", - "resolution": null, - "schema_conformity": "invalid", - "sha256": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "size_bytes": 4, - "source": "unknown", - "spatial_coverage": null, - "status": "examined", - "temporal_coverage": null, - "units": null - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\277180a4-cd74-42ed-a231-0d194b3fca9f\\0f96a4f7-6b24-4969-9564-abbde30b5a51\\9199f079-42fc-48cc-86ff-d1072f801932\\tile_0014.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "contract": { - "key": "geointel.raster.geotiff", - "version": "1.0.0" - }, - "crs": null, - "duplicate_group": null, - "empty_content": false, - "freshness": { - "reason": "no_declared_source_timestamp", - "status": "unknown" - }, - "geometry_validation": null, - "item_id": "e61c40ce9d3d2b9d369d", - "lineage": null, - "modified_at": "2026-08-01T15:45:08.536394+00:00", - "near_duplicate_fingerprint": null, - "path": "storage/tiles/277180a4-cd74-42ed-a231-0d194b3fca9f/0f96a4f7-6b24-4969-9564-abbde30b5a51/9199f079-42fc-48cc-86ff-d1072f801932/tile_0014.tif", - "read_status": "unreadable", - "recommended_action": "unavailable or unreadable", - "resolution": null, - "schema_conformity": "invalid", - "sha256": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "size_bytes": 4, - "source": "unknown", - "spatial_coverage": null, - "status": "examined", - "temporal_coverage": null, - "units": null - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\277180a4-cd74-42ed-a231-0d194b3fca9f\\0f96a4f7-6b24-4969-9564-abbde30b5a51\\9199f079-42fc-48cc-86ff-d1072f801932\\tile_0015.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "contract": { - "key": "geointel.raster.geotiff", - "version": "1.0.0" - }, - "crs": null, - "duplicate_group": null, - "empty_content": false, - "freshness": { - "reason": "no_declared_source_timestamp", - "status": "unknown" - }, - "geometry_validation": null, - "item_id": "a814da6efe81f095c9e3", - "lineage": null, - "modified_at": "2026-08-01T15:45:08.537394+00:00", - "near_duplicate_fingerprint": null, - "path": "storage/tiles/277180a4-cd74-42ed-a231-0d194b3fca9f/0f96a4f7-6b24-4969-9564-abbde30b5a51/9199f079-42fc-48cc-86ff-d1072f801932/tile_0015.tif", - "read_status": "unreadable", - "recommended_action": "unavailable or unreadable", - "resolution": null, - "schema_conformity": "invalid", - "sha256": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "size_bytes": 4, - "source": "unknown", - "spatial_coverage": null, - "status": "examined", - "temporal_coverage": null, - "units": null - }, - { - "anomalies": [ - { - "action": "quarantine", - "code": "manifest.zero_bbox", - "field": "bounds", - "message": "Manifest declares a zero-area bounding box", - "severity": "major" - } - ], - "contract": { - "key": "geointel.artifact.generic", - "version": "1.0.0" - }, - "crs": "EPSG:31370", - "duplicate_group": null, - "empty_content": false, - "freshness": { - "method": "declared_metadata", - "observed_at": "2026-07-26T03:04:42.542754+00:00", - "status": "declared" - }, - "geometry_validation": null, - "item_id": "1500315e2bdebe9d3462", - "lineage": { - "source_dataset_id": "07738ebe-2c5e-4d6c-960d-1c03f216a3a0", - "source_raster_id": "07738ebe-2c5e-4d6c-960d-1c03f216a3a0" - }, - "modified_at": "2026-07-27T21:27:15.447369+00:00", - "near_duplicate_fingerprint": "39e74d37a24b514525dfba54aa6276689c023e4141f60ef1e33a4936f0012912", - "path": "storage/tiles/7175ae58-2b09-4fab-83e1-5d95e2969d35/07738ebe-2c5e-4d6c-960d-1c03f216a3a0/7529e658-b42a-47cb-a23c-d9d350b5d8c4/manifest.json", - "read_status": "readable", - "recommended_action": "quarantine", - 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"lineage": null, - "modified_at": "2026-07-27T21:27:15.655715+00:00", - "near_duplicate_fingerprint": null, - "path": "storage/tiles/7175ae58-2b09-4fab-83e1-5d95e2969d35/07738ebe-2c5e-4d6c-960d-1c03f216a3a0/7529e658-b42a-47cb-a23c-d9d350b5d8c4/tile_0000.tif", - "read_status": "unreadable", - "recommended_action": "unavailable or unreadable", - "resolution": null, - "schema_conformity": "invalid", - "sha256": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "size_bytes": 4, - "source": "unknown", - "spatial_coverage": null, - "status": "examined", - "temporal_coverage": null, - "units": null - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\7175ae58-2b09-4fab-83e1-5d95e2969d35\\07738ebe-2c5e-4d6c-960d-1c03f216a3a0\\7529e658-b42a-47cb-a23c-d9d350b5d8c4\\tile_0001.tif' not recognized as being in a supported file format.", - "severity": "critical" - 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"code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\7175ae58-2b09-4fab-83e1-5d95e2969d35\\07738ebe-2c5e-4d6c-960d-1c03f216a3a0\\7529e658-b42a-47cb-a23c-d9d350b5d8c4\\tile_0002.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "contract": { - "key": "geointel.raster.geotiff", - "version": "1.0.0" - }, - "crs": null, - "duplicate_group": null, - "empty_content": false, - "freshness": { - "reason": "no_declared_source_timestamp", - "status": "unknown" - }, - "geometry_validation": null, - "item_id": "c8280727cb07e1423a97", - "lineage": null, - "modified_at": "2026-07-27T21:27:15.499375+00:00", - "near_duplicate_fingerprint": null, - "path": "storage/tiles/7175ae58-2b09-4fab-83e1-5d95e2969d35/07738ebe-2c5e-4d6c-960d-1c03f216a3a0/7529e658-b42a-47cb-a23c-d9d350b5d8c4/tile_0002.tif", - "read_status": "unreadable", - "recommended_action": "unavailable or unreadable", - "resolution": null, - "schema_conformity": "invalid", - "sha256": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "size_bytes": 4, - "source": "unknown", - "spatial_coverage": null, - "status": "examined", - "temporal_coverage": null, - "units": null - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\7175ae58-2b09-4fab-83e1-5d95e2969d35\\07738ebe-2c5e-4d6c-960d-1c03f216a3a0\\7529e658-b42a-47cb-a23c-d9d350b5d8c4\\tile_0003.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "contract": { - "key": "geointel.raster.geotiff", - "version": "1.0.0" - }, - "crs": null, - "duplicate_group": null, - "empty_content": false, - "freshness": { - "reason": "no_declared_source_timestamp", - "status": "unknown" - }, - "geometry_validation": null, - "item_id": "2e89e578c950d03db653", - "lineage": null, - "modified_at": "2026-07-27T21:27:15.431027+00:00", - "near_duplicate_fingerprint": null, - "path": "storage/tiles/7175ae58-2b09-4fab-83e1-5d95e2969d35/07738ebe-2c5e-4d6c-960d-1c03f216a3a0/7529e658-b42a-47cb-a23c-d9d350b5d8c4/tile_0003.tif", - "read_status": "unreadable", - "recommended_action": "unavailable or unreadable", - "resolution": null, - "schema_conformity": "invalid", - "sha256": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "size_bytes": 4, - "source": "unknown", - "spatial_coverage": null, - "status": "examined", - "temporal_coverage": null, - "units": null - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\7175ae58-2b09-4fab-83e1-5d95e2969d35\\07738ebe-2c5e-4d6c-960d-1c03f216a3a0\\7529e658-b42a-47cb-a23c-d9d350b5d8c4\\tile_0004.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "contract": { - "key": "geointel.raster.geotiff", - "version": "1.0.0" - }, - "crs": null, - "duplicate_group": null, - 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"code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\7175ae58-2b09-4fab-83e1-5d95e2969d35\\07738ebe-2c5e-4d6c-960d-1c03f216a3a0\\7529e658-b42a-47cb-a23c-d9d350b5d8c4\\tile_0006.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "contract": { - "key": "geointel.raster.geotiff", - "version": "1.0.0" - }, - "crs": null, - "duplicate_group": null, - "empty_content": false, - "freshness": { - "reason": "no_declared_source_timestamp", - "status": "unknown" - }, - "geometry_validation": null, - "item_id": "71fff7a0187642c79b89", - "lineage": null, - "modified_at": "2026-07-27T21:27:15.548598+00:00", - "near_duplicate_fingerprint": null, - "path": "storage/tiles/7175ae58-2b09-4fab-83e1-5d95e2969d35/07738ebe-2c5e-4d6c-960d-1c03f216a3a0/7529e658-b42a-47cb-a23c-d9d350b5d8c4/tile_0006.tif", - "read_status": "unreadable", - "recommended_action": "unavailable or unreadable", - "resolution": null, - "schema_conformity": "invalid", - "sha256": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "size_bytes": 4, - "source": "unknown", - "spatial_coverage": null, - "status": "examined", - "temporal_coverage": null, - "units": null - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\7175ae58-2b09-4fab-83e1-5d95e2969d35\\07738ebe-2c5e-4d6c-960d-1c03f216a3a0\\7529e658-b42a-47cb-a23c-d9d350b5d8c4\\tile_0007.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "contract": { - "key": "geointel.raster.geotiff", - "version": "1.0.0" - }, - "crs": null, - "duplicate_group": null, - "empty_content": false, - "freshness": { - "reason": "no_declared_source_timestamp", - "status": "unknown" - }, - "geometry_validation": null, - "item_id": "90c5c1cbd336f0758242", - "lineage": null, - "modified_at": "2026-07-27T21:27:15.530919+00:00", - "near_duplicate_fingerprint": null, - "path": "storage/tiles/7175ae58-2b09-4fab-83e1-5d95e2969d35/07738ebe-2c5e-4d6c-960d-1c03f216a3a0/7529e658-b42a-47cb-a23c-d9d350b5d8c4/tile_0007.tif", - "read_status": "unreadable", - "recommended_action": "unavailable or unreadable", - "resolution": null, - "schema_conformity": "invalid", - "sha256": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "size_bytes": 4, - "source": "unknown", - "spatial_coverage": null, - "status": "examined", - "temporal_coverage": null, - "units": null - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\7175ae58-2b09-4fab-83e1-5d95e2969d35\\07738ebe-2c5e-4d6c-960d-1c03f216a3a0\\7529e658-b42a-47cb-a23c-d9d350b5d8c4\\tile_0008.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "contract": { - "key": "geointel.raster.geotiff", - "version": "1.0.0" - }, - "crs": null, - "duplicate_group": null, - "empty_content": false, - "freshness": { - "reason": "no_declared_source_timestamp", - "status": "unknown" - }, - "geometry_validation": null, - "item_id": "d3b1d530bd052ac1b53e", - "lineage": null, - "modified_at": "2026-07-27T21:27:15.515308+00:00", - "near_duplicate_fingerprint": null, - "path": "storage/tiles/7175ae58-2b09-4fab-83e1-5d95e2969d35/07738ebe-2c5e-4d6c-960d-1c03f216a3a0/7529e658-b42a-47cb-a23c-d9d350b5d8c4/tile_0008.tif", - "read_status": "unreadable", - "recommended_action": "unavailable or unreadable", - "resolution": null, - "schema_conformity": "invalid", - "sha256": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "size_bytes": 4, - "source": "unknown", - "spatial_coverage": null, - "status": "examined", - "temporal_coverage": null, - "units": null - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\7175ae58-2b09-4fab-83e1-5d95e2969d35\\07738ebe-2c5e-4d6c-960d-1c03f216a3a0\\7529e658-b42a-47cb-a23c-d9d350b5d8c4\\tile_0009.tif' not recognized as being in a supported file format.", - 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"code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\7175ae58-2b09-4fab-83e1-5d95e2969d35\\07738ebe-2c5e-4d6c-960d-1c03f216a3a0\\7529e658-b42a-47cb-a23c-d9d350b5d8c4\\tile_0010.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "contract": { - "key": "geointel.raster.geotiff", - "version": "1.0.0" - }, - "crs": null, - "duplicate_group": null, - "empty_content": false, - "freshness": { - "reason": "no_declared_source_timestamp", - "status": "unknown" - }, - "geometry_validation": null, - "item_id": "3c46ab42aef67799f868", - "lineage": null, - "modified_at": "2026-07-27T21:27:15.608789+00:00", - "near_duplicate_fingerprint": null, - "path": "storage/tiles/7175ae58-2b09-4fab-83e1-5d95e2969d35/07738ebe-2c5e-4d6c-960d-1c03f216a3a0/7529e658-b42a-47cb-a23c-d9d350b5d8c4/tile_0010.tif", - "read_status": "unreadable", - "recommended_action": "unavailable or unreadable", - "resolution": null, - "schema_conformity": "invalid", - "sha256": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "size_bytes": 4, - "source": "unknown", - "spatial_coverage": null, - "status": "examined", - "temporal_coverage": null, - "units": null - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\7175ae58-2b09-4fab-83e1-5d95e2969d35\\07738ebe-2c5e-4d6c-960d-1c03f216a3a0\\7529e658-b42a-47cb-a23c-d9d350b5d8c4\\tile_0011.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "contract": { - "key": "geointel.raster.geotiff", - "version": "1.0.0" - }, - "crs": null, - "duplicate_group": null, - "empty_content": false, - "freshness": { - "reason": "no_declared_source_timestamp", - "status": "unknown" - }, - "geometry_validation": null, - "item_id": "51dae1e198b0e2be9a25", - "lineage": null, - "modified_at": "2026-07-27T21:27:15.624404+00:00", - "near_duplicate_fingerprint": null, - "path": "storage/tiles/7175ae58-2b09-4fab-83e1-5d95e2969d35/07738ebe-2c5e-4d6c-960d-1c03f216a3a0/7529e658-b42a-47cb-a23c-d9d350b5d8c4/tile_0011.tif", - "read_status": "unreadable", - "recommended_action": "unavailable or unreadable", - "resolution": null, - "schema_conformity": "invalid", - "sha256": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "size_bytes": 4, - "source": "unknown", - "spatial_coverage": null, - "status": "examined", - "temporal_coverage": null, - "units": null - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\7175ae58-2b09-4fab-83e1-5d95e2969d35\\07738ebe-2c5e-4d6c-960d-1c03f216a3a0\\7529e658-b42a-47cb-a23c-d9d350b5d8c4\\tile_0012.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "contract": { - "key": "geointel.raster.geotiff", - "version": "1.0.0" - }, - "crs": null, - "duplicate_group": null, - 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"path": "storage/tiles/a7a94d0b-9b27-49bd-9e44-97b0b75677ad/e2a3f62a-76f0-4611-81a3-d2ca948cda75/6e53d525-f603-4eb3-8bf7-05da59832013/tile_0010.tif", - "read_status": "unreadable", - "recommended_action": "unavailable or unreadable", - "resolution": null, - "schema_conformity": "invalid", - "sha256": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "size_bytes": 4, - "source": "unknown", - "spatial_coverage": null, - "status": "examined", - "temporal_coverage": null, - "units": null - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\a7a94d0b-9b27-49bd-9e44-97b0b75677ad\\e2a3f62a-76f0-4611-81a3-d2ca948cda75\\6e53d525-f603-4eb3-8bf7-05da59832013\\tile_0011.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "contract": { - "key": "geointel.raster.geotiff", - "version": "1.0.0" - }, - "crs": null, - "duplicate_group": null, - 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"sha256": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "size_bytes": 4, - "source": "unknown", - "spatial_coverage": null, - "status": "examined", - "temporal_coverage": null, - "units": null - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\a7a94d0b-9b27-49bd-9e44-97b0b75677ad\\e2a3f62a-76f0-4611-81a3-d2ca948cda75\\6e53d525-f603-4eb3-8bf7-05da59832013\\tile_0014.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "contract": { - "key": "geointel.raster.geotiff", - "version": "1.0.0" - }, - "crs": null, - "duplicate_group": null, - "empty_content": false, - "freshness": { - "reason": "no_declared_source_timestamp", - "status": "unknown" - }, - "geometry_validation": null, - "item_id": "712708cfd7b54f652c1f", - "lineage": null, - "modified_at": "2026-07-27T21:27:15.858698+00:00", - "near_duplicate_fingerprint": null, - "path": "storage/tiles/a7a94d0b-9b27-49bd-9e44-97b0b75677ad/e2a3f62a-76f0-4611-81a3-d2ca948cda75/6e53d525-f603-4eb3-8bf7-05da59832013/tile_0014.tif", - "read_status": "unreadable", - "recommended_action": "unavailable or unreadable", - "resolution": null, - "schema_conformity": "invalid", - "sha256": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "size_bytes": 4, - "source": "unknown", - "spatial_coverage": null, - "status": "examined", - "temporal_coverage": null, - "units": null - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\a7a94d0b-9b27-49bd-9e44-97b0b75677ad\\e2a3f62a-76f0-4611-81a3-d2ca948cda75\\6e53d525-f603-4eb3-8bf7-05da59832013\\tile_0015.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "contract": { - "key": "geointel.raster.geotiff", - "version": "1.0.0" - }, - "crs": null, - "duplicate_group": null, - 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"contract": { - "key": "geointel.artifact.generic", - "version": "1.0.0" - }, - "crs": "EPSG:31370", - "duplicate_group": null, - "empty_content": false, - "freshness": { - "method": "declared_metadata", - "observed_at": "2026-08-01T15:46:23.988597+00:00", - "status": "declared" - }, - "geometry_validation": null, - "item_id": "04f3407f941cd1dc895e", - "lineage": { - "source_dataset_id": "c0fc6968-9c5b-499f-a095-0fc91a18501d", - "source_raster_id": "c0fc6968-9c5b-499f-a095-0fc91a18501d" - }, - "modified_at": "2026-08-01T15:46:23.988429+00:00", - "near_duplicate_fingerprint": "1d5ce24da57b028bb377356938f4daf8320a019e9258a65637259b1460640b42", - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/manifest.json", - "read_status": "readable", - "recommended_action": "quarantine", - "resolution": null, - "schema_conformity": "valid", - "sha256": "e4cd24c2b2a3bfc6fc984a41a1c40602aa4da694bc71eaca60c8ee97b0f9ae24", - "size_bytes": 8664, - "source": "unknown", - "spatial_coverage": { - "bbox": [ - 0.0, - 0.0, - 0.0, - 0.0 - ], - "crs": "EPSG:31370" - }, - "status": "examined", - "temporal_coverage": null, - "units": null - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0000.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "contract": { - "key": "geointel.raster.geotiff", - "version": "1.0.0" - }, - "crs": null, - "duplicate_group": null, - "empty_content": false, - "freshness": { - "reason": "no_declared_source_timestamp", - "status": "unknown" - }, - "geometry_validation": null, - "item_id": "4def26f935acc400079e", - "lineage": null, - "modified_at": "2026-08-01T15:46:23.971433+00:00", - "near_duplicate_fingerprint": null, - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/tile_0000.tif", - "read_status": "unreadable", - "recommended_action": "unavailable or unreadable", - "resolution": null, - "schema_conformity": "invalid", - "sha256": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "size_bytes": 4, - "source": "unknown", - "spatial_coverage": null, - "status": "examined", - "temporal_coverage": null, - "units": null - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0001.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "contract": { - "key": "geointel.raster.geotiff", - "version": "1.0.0" - }, - "crs": null, - "duplicate_group": null, - "empty_content": false, - "freshness": { - "reason": "no_declared_source_timestamp", - "status": "unknown" - }, - "geometry_validation": null, - "item_id": "9e093656fa6b9d623331", - "lineage": null, - "modified_at": "2026-08-01T15:46:23.972431+00:00", - "near_duplicate_fingerprint": null, - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/tile_0001.tif", - "read_status": "unreadable", - "recommended_action": "unavailable or unreadable", - "resolution": null, - "schema_conformity": "invalid", - "sha256": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "size_bytes": 4, - "source": "unknown", - "spatial_coverage": null, - "status": "examined", - "temporal_coverage": null, - "units": null - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0002.tif' not recognized as being in a supported file format.", - 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"code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0003.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "contract": { - "key": "geointel.raster.geotiff", - "version": "1.0.0" - }, - "crs": null, - "duplicate_group": null, - "empty_content": false, - "freshness": { - "reason": "no_declared_source_timestamp", - "status": "unknown" - }, - "geometry_validation": null, - "item_id": "6b1012bfdedb2641eb37", - "lineage": null, - "modified_at": "2026-08-01T15:46:23.975429+00:00", - "near_duplicate_fingerprint": null, - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/tile_0003.tif", - "read_status": "unreadable", - "recommended_action": "unavailable or unreadable", - "resolution": null, - "schema_conformity": "invalid", - 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"path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/tile_0004.tif", - "read_status": "unreadable", - "recommended_action": "unavailable or unreadable", - "resolution": null, - "schema_conformity": "invalid", - "sha256": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "size_bytes": 4, - "source": "unknown", - "spatial_coverage": null, - "status": "examined", - "temporal_coverage": null, - "units": null - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0005.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "contract": { - "key": "geointel.raster.geotiff", - "version": "1.0.0" - }, - "crs": null, - "duplicate_group": null, - "empty_content": false, - "freshness": { - "reason": "no_declared_source_timestamp", - "status": "unknown" - }, - "geometry_validation": null, - "item_id": "649fd55f6d877aa78bb2", - "lineage": null, - "modified_at": "2026-08-01T15:46:23.977431+00:00", - "near_duplicate_fingerprint": null, - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/tile_0005.tif", - "read_status": "unreadable", - "recommended_action": "unavailable or unreadable", - "resolution": null, - "schema_conformity": "invalid", - "sha256": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "size_bytes": 4, - "source": "unknown", - "spatial_coverage": null, - "status": "examined", - "temporal_coverage": null, - "units": null - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0006.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "contract": { - "key": "geointel.raster.geotiff", - "version": "1.0.0" - }, - "crs": null, - "duplicate_group": null, - "empty_content": false, - "freshness": { - "reason": "no_declared_source_timestamp", - "status": "unknown" - }, - "geometry_validation": null, - "item_id": "52e170d64fb1a011de45", - "lineage": null, - "modified_at": "2026-08-01T15:46:23.978433+00:00", - "near_duplicate_fingerprint": null, - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/tile_0006.tif", - "read_status": "unreadable", - "recommended_action": "unavailable or unreadable", - "resolution": null, - "schema_conformity": "invalid", - "sha256": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "size_bytes": 4, - "source": "unknown", - "spatial_coverage": null, - "status": "examined", - "temporal_coverage": null, - "units": null - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0007.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "contract": { - "key": "geointel.raster.geotiff", - "version": "1.0.0" - }, - "crs": null, - "duplicate_group": null, - "empty_content": false, - "freshness": { - "reason": "no_declared_source_timestamp", - "status": "unknown" - }, - "geometry_validation": null, - "item_id": "46628f46cd8911a36f86", - "lineage": null, - "modified_at": "2026-08-01T15:46:23.979429+00:00", - "near_duplicate_fingerprint": null, - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/tile_0007.tif", - "read_status": "unreadable", - "recommended_action": "unavailable or unreadable", - "resolution": null, - "schema_conformity": "invalid", - "sha256": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "size_bytes": 4, - "source": "unknown", - "spatial_coverage": null, - "status": "examined", - "temporal_coverage": null, - "units": null - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0008.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "contract": { - "key": "geointel.raster.geotiff", - "version": "1.0.0" - }, - "crs": null, - "duplicate_group": null, - "empty_content": false, - "freshness": { - "reason": "no_declared_source_timestamp", - "status": "unknown" - }, - "geometry_validation": null, - "item_id": "889b2e92c1aa378722aa", - "lineage": null, - "modified_at": "2026-08-01T15:46:23.980432+00:00", - "near_duplicate_fingerprint": null, - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/tile_0008.tif", - "read_status": "unreadable", - "recommended_action": "unavailable or unreadable", - "resolution": null, - "schema_conformity": "invalid", - "sha256": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "size_bytes": 4, - "source": "unknown", - "spatial_coverage": null, - "status": "examined", - "temporal_coverage": null, - "units": null - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0009.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "contract": { - "key": "geointel.raster.geotiff", - "version": "1.0.0" - }, - "crs": null, - "duplicate_group": null, - "empty_content": false, - "freshness": { - "reason": "no_declared_source_timestamp", - "status": "unknown" - }, - "geometry_validation": null, - "item_id": "67a46403c7fb388bb484", - "lineage": null, - "modified_at": "2026-08-01T15:46:23.980432+00:00", - "near_duplicate_fingerprint": null, - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/tile_0009.tif", - "read_status": "unreadable", - "recommended_action": "unavailable or unreadable", - "resolution": null, - "schema_conformity": "invalid", - "sha256": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "size_bytes": 4, - "source": "unknown", - "spatial_coverage": null, - "status": "examined", - "temporal_coverage": null, - "units": null - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0010.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "contract": { - "key": "geointel.raster.geotiff", - "version": "1.0.0" - }, - "crs": null, - "duplicate_group": null, - "empty_content": false, - "freshness": { - "reason": "no_declared_source_timestamp", - "status": "unknown" - }, - "geometry_validation": null, - "item_id": "25123fae6d918a76ac7a", - "lineage": null, - "modified_at": "2026-08-01T15:46:23.981429+00:00", - "near_duplicate_fingerprint": null, - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/tile_0010.tif", - "read_status": "unreadable", - "recommended_action": "unavailable or unreadable", - "resolution": null, - "schema_conformity": "invalid", - "sha256": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "size_bytes": 4, - "source": "unknown", - "spatial_coverage": null, - "status": "examined", - "temporal_coverage": null, - "units": null - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0011.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "contract": { - "key": "geointel.raster.geotiff", - "version": "1.0.0" - }, - "crs": null, - "duplicate_group": null, - "empty_content": false, - "freshness": { - "reason": "no_declared_source_timestamp", - "status": "unknown" - }, - "geometry_validation": null, - "item_id": "7407fad7de42e36fe791", - "lineage": null, - "modified_at": "2026-08-01T15:46:23.982429+00:00", - "near_duplicate_fingerprint": null, - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/tile_0011.tif", - "read_status": "unreadable", - "recommended_action": "unavailable or unreadable", - "resolution": null, - "schema_conformity": "invalid", - "sha256": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "size_bytes": 4, - "source": "unknown", - "spatial_coverage": null, - "status": "examined", - "temporal_coverage": null, - "units": null - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0012.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "contract": { - "key": "geointel.raster.geotiff", - "version": "1.0.0" - }, - "crs": null, - "duplicate_group": null, - "empty_content": false, - "freshness": { - "reason": "no_declared_source_timestamp", - "status": "unknown" - }, - "geometry_validation": null, - "item_id": "eaa22fd47e90efa7dbdd", - "lineage": null, - "modified_at": "2026-08-01T15:46:23.983429+00:00", - "near_duplicate_fingerprint": null, - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/tile_0012.tif", - "read_status": "unreadable", - "recommended_action": "unavailable or unreadable", - "resolution": null, - "schema_conformity": "invalid", - "sha256": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "size_bytes": 4, - "source": "unknown", - "spatial_coverage": null, - "status": "examined", - "temporal_coverage": null, - "units": null - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0013.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "contract": { - "key": "geointel.raster.geotiff", - "version": "1.0.0" - }, - "crs": null, - "duplicate_group": null, - "empty_content": false, - "freshness": { - "reason": "no_declared_source_timestamp", - "status": "unknown" - }, - "geometry_validation": null, - "item_id": "46aaf33ee50eaa14edfd", - "lineage": null, - "modified_at": "2026-08-01T15:46:23.983429+00:00", - "near_duplicate_fingerprint": null, - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/tile_0013.tif", - "read_status": "unreadable", - "recommended_action": "unavailable or unreadable", - "resolution": null, - "schema_conformity": "invalid", - "sha256": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "size_bytes": 4, - "source": "unknown", - "spatial_coverage": null, - "status": "examined", - "temporal_coverage": null, - "units": null - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0014.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "contract": { - "key": "geointel.raster.geotiff", - "version": "1.0.0" - }, - "crs": null, - "duplicate_group": null, - "empty_content": false, - "freshness": { - "reason": "no_declared_source_timestamp", - "status": "unknown" - }, - "geometry_validation": null, - "item_id": "6d3766eca60a28941699", - "lineage": null, - "modified_at": "2026-08-01T15:46:23.984430+00:00", - "near_duplicate_fingerprint": null, - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/tile_0014.tif", - "read_status": "unreadable", - "recommended_action": "unavailable or unreadable", - "resolution": null, - "schema_conformity": "invalid", - "sha256": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "size_bytes": 4, - "source": "unknown", - "spatial_coverage": null, - "status": "examined", - "temporal_coverage": null, - "units": null - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\b9a1e970-d028-4b71-9ff1-709e416d4424\\c0fc6968-9c5b-499f-a095-0fc91a18501d\\3edda109-2f4f-4913-b242-2b08d33841dc\\tile_0015.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "contract": { - "key": "geointel.raster.geotiff", - "version": "1.0.0" - }, - "crs": null, - "duplicate_group": null, - "empty_content": false, - "freshness": { - "reason": "no_declared_source_timestamp", - "status": "unknown" - }, - "geometry_validation": null, - "item_id": "a870f7c9d918ccf7d5a6", - "lineage": null, - "modified_at": "2026-08-01T15:46:23.985429+00:00", - "near_duplicate_fingerprint": null, - "path": "storage/tiles/b9a1e970-d028-4b71-9ff1-709e416d4424/c0fc6968-9c5b-499f-a095-0fc91a18501d/3edda109-2f4f-4913-b242-2b08d33841dc/tile_0015.tif", - "read_status": "unreadable", - "recommended_action": "unavailable or unreadable", - "resolution": null, - "schema_conformity": "invalid", - 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"path": "storage/tiles/db240e97-188d-48fd-98f3-7abd9131ffeb/2df0e426-f569-459f-a4ad-d3f42539bc23/f31826fa-10e3-4154-95c2-d89d21813379/manifest.json", - "read_status": "readable", - "recommended_action": "quarantine", - "resolution": null, - "schema_conformity": "valid", - "sha256": "99fda54503e9e961cddcd6dae63f8845543beb40a7903c1a0d0d4ecb090c6f75", - "size_bytes": 8664, - "source": "unknown", - "spatial_coverage": { - "bbox": [ - 0.0, - 0.0, - 0.0, - 0.0 - ], - "crs": "EPSG:31370" - }, - "status": "examined", - "temporal_coverage": null, - "units": null - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\db240e97-188d-48fd-98f3-7abd9131ffeb\\2df0e426-f569-459f-a4ad-d3f42539bc23\\f31826fa-10e3-4154-95c2-d89d21813379\\tile_0000.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "contract": { - "key": "geointel.raster.geotiff", - 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"code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\db240e97-188d-48fd-98f3-7abd9131ffeb\\2df0e426-f569-459f-a4ad-d3f42539bc23\\f31826fa-10e3-4154-95c2-d89d21813379\\tile_0002.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "contract": { - "key": "geointel.raster.geotiff", - "version": "1.0.0" - }, - "crs": null, - "duplicate_group": null, - "empty_content": false, - "freshness": { - "reason": "no_declared_source_timestamp", - "status": "unknown" - }, - "geometry_validation": null, - "item_id": "6fab06961d3c3d439c73", - "lineage": null, - "modified_at": "2026-08-01T16:31:01.894749+00:00", - "near_duplicate_fingerprint": null, - "path": "storage/tiles/db240e97-188d-48fd-98f3-7abd9131ffeb/2df0e426-f569-459f-a4ad-d3f42539bc23/f31826fa-10e3-4154-95c2-d89d21813379/tile_0002.tif", - "read_status": "unreadable", - "recommended_action": "unavailable or unreadable", - "resolution": null, - "schema_conformity": "invalid", - "sha256": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "size_bytes": 4, - "source": "unknown", - "spatial_coverage": null, - "status": "examined", - "temporal_coverage": null, - "units": null - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\db240e97-188d-48fd-98f3-7abd9131ffeb\\2df0e426-f569-459f-a4ad-d3f42539bc23\\f31826fa-10e3-4154-95c2-d89d21813379\\tile_0003.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "contract": { - "key": "geointel.raster.geotiff", - "version": "1.0.0" - }, - "crs": null, - "duplicate_group": null, - "empty_content": false, - "freshness": { - "reason": "no_declared_source_timestamp", - "status": "unknown" - }, - "geometry_validation": null, - "item_id": "bc61a64bf00351eaa325", - "lineage": null, - "modified_at": "2026-08-01T16:31:01.895751+00:00", - "near_duplicate_fingerprint": null, - "path": "storage/tiles/db240e97-188d-48fd-98f3-7abd9131ffeb/2df0e426-f569-459f-a4ad-d3f42539bc23/f31826fa-10e3-4154-95c2-d89d21813379/tile_0003.tif", - "read_status": "unreadable", - "recommended_action": "unavailable or unreadable", - "resolution": null, - "schema_conformity": "invalid", - "sha256": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "size_bytes": 4, - "source": "unknown", - "spatial_coverage": null, - "status": "examined", - "temporal_coverage": null, - "units": null - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\db240e97-188d-48fd-98f3-7abd9131ffeb\\2df0e426-f569-459f-a4ad-d3f42539bc23\\f31826fa-10e3-4154-95c2-d89d21813379\\tile_0004.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "contract": { - "key": "geointel.raster.geotiff", - "version": "1.0.0" - }, - "crs": null, - "duplicate_group": null, - 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"code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\db240e97-188d-48fd-98f3-7abd9131ffeb\\2df0e426-f569-459f-a4ad-d3f42539bc23\\f31826fa-10e3-4154-95c2-d89d21813379\\tile_0006.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "contract": { - "key": "geointel.raster.geotiff", - "version": "1.0.0" - }, - "crs": null, - "duplicate_group": null, - "empty_content": false, - "freshness": { - "reason": "no_declared_source_timestamp", - "status": "unknown" - }, - "geometry_validation": null, - "item_id": "e440975ad15713709d14", - "lineage": null, - "modified_at": "2026-08-01T16:31:01.899805+00:00", - "near_duplicate_fingerprint": null, - "path": "storage/tiles/db240e97-188d-48fd-98f3-7abd9131ffeb/2df0e426-f569-459f-a4ad-d3f42539bc23/f31826fa-10e3-4154-95c2-d89d21813379/tile_0006.tif", - "read_status": "unreadable", - "recommended_action": "unavailable or unreadable", - "resolution": null, - "schema_conformity": "invalid", - "sha256": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "size_bytes": 4, - "source": "unknown", - "spatial_coverage": null, - "status": "examined", - "temporal_coverage": null, - "units": null - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\db240e97-188d-48fd-98f3-7abd9131ffeb\\2df0e426-f569-459f-a4ad-d3f42539bc23\\f31826fa-10e3-4154-95c2-d89d21813379\\tile_0007.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "contract": { - "key": "geointel.raster.geotiff", - "version": "1.0.0" - }, - "crs": null, - "duplicate_group": null, - "empty_content": false, - "freshness": { - "reason": "no_declared_source_timestamp", - "status": "unknown" - }, - "geometry_validation": null, - "item_id": "3f1f44d08c10be760fa3", - "lineage": null, - "modified_at": "2026-08-01T16:31:01.901804+00:00", - "near_duplicate_fingerprint": null, - "path": "storage/tiles/db240e97-188d-48fd-98f3-7abd9131ffeb/2df0e426-f569-459f-a4ad-d3f42539bc23/f31826fa-10e3-4154-95c2-d89d21813379/tile_0007.tif", - "read_status": "unreadable", - "recommended_action": "unavailable or unreadable", - "resolution": null, - "schema_conformity": "invalid", - "sha256": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "size_bytes": 4, - "source": "unknown", - "spatial_coverage": null, - "status": "examined", - "temporal_coverage": null, - "units": null - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\db240e97-188d-48fd-98f3-7abd9131ffeb\\2df0e426-f569-459f-a4ad-d3f42539bc23\\f31826fa-10e3-4154-95c2-d89d21813379\\tile_0008.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "contract": { - "key": "geointel.raster.geotiff", - "version": "1.0.0" - }, - "crs": null, - "duplicate_group": null, - "empty_content": false, - "freshness": { - "reason": "no_declared_source_timestamp", - "status": "unknown" - }, - "geometry_validation": null, - "item_id": "bc0e44ce91c97c3723c9", - "lineage": null, - "modified_at": "2026-08-01T16:31:01.901804+00:00", - "near_duplicate_fingerprint": null, - "path": "storage/tiles/db240e97-188d-48fd-98f3-7abd9131ffeb/2df0e426-f569-459f-a4ad-d3f42539bc23/f31826fa-10e3-4154-95c2-d89d21813379/tile_0008.tif", - "read_status": "unreadable", - "recommended_action": "unavailable or unreadable", - "resolution": null, - "schema_conformity": "invalid", - "sha256": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "size_bytes": 4, - "source": "unknown", - "spatial_coverage": null, - "status": "examined", - "temporal_coverage": null, - "units": null - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\db240e97-188d-48fd-98f3-7abd9131ffeb\\2df0e426-f569-459f-a4ad-d3f42539bc23\\f31826fa-10e3-4154-95c2-d89d21813379\\tile_0009.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "contract": { - "key": "geointel.raster.geotiff", - "version": "1.0.0" - }, - "crs": null, - "duplicate_group": null, - "empty_content": false, - "freshness": { - "reason": "no_declared_source_timestamp", - "status": "unknown" - }, - "geometry_validation": null, - "item_id": "9d163f657df866f7a22b", - "lineage": null, - "modified_at": "2026-08-01T16:31:01.902806+00:00", - "near_duplicate_fingerprint": null, - "path": "storage/tiles/db240e97-188d-48fd-98f3-7abd9131ffeb/2df0e426-f569-459f-a4ad-d3f42539bc23/f31826fa-10e3-4154-95c2-d89d21813379/tile_0009.tif", - "read_status": "unreadable", - "recommended_action": "unavailable or unreadable", - "resolution": null, - "schema_conformity": "invalid", - "sha256": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "size_bytes": 4, - "source": "unknown", - "spatial_coverage": null, - "status": "examined", - "temporal_coverage": null, - "units": null - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\db240e97-188d-48fd-98f3-7abd9131ffeb\\2df0e426-f569-459f-a4ad-d3f42539bc23\\f31826fa-10e3-4154-95c2-d89d21813379\\tile_0010.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "contract": { - "key": "geointel.raster.geotiff", - "version": "1.0.0" - }, - "crs": null, - "duplicate_group": null, - "empty_content": false, - "freshness": { - "reason": "no_declared_source_timestamp", - "status": "unknown" - }, - "geometry_validation": null, - "item_id": "c3ecd380ee4499edfd90", - "lineage": null, - "modified_at": "2026-08-01T16:31:01.903807+00:00", - "near_duplicate_fingerprint": null, - "path": "storage/tiles/db240e97-188d-48fd-98f3-7abd9131ffeb/2df0e426-f569-459f-a4ad-d3f42539bc23/f31826fa-10e3-4154-95c2-d89d21813379/tile_0010.tif", - "read_status": "unreadable", - "recommended_action": "unavailable or unreadable", - "resolution": null, - "schema_conformity": "invalid", - "sha256": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "size_bytes": 4, - "source": "unknown", - "spatial_coverage": null, - "status": "examined", - "temporal_coverage": null, - "units": null - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\db240e97-188d-48fd-98f3-7abd9131ffeb\\2df0e426-f569-459f-a4ad-d3f42539bc23\\f31826fa-10e3-4154-95c2-d89d21813379\\tile_0011.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "contract": { - "key": "geointel.raster.geotiff", - "version": "1.0.0" - }, - "crs": null, - "duplicate_group": null, - "empty_content": false, - "freshness": { - "reason": "no_declared_source_timestamp", - "status": "unknown" - }, - "geometry_validation": null, - "item_id": "d46845df780977985a5e", - "lineage": null, - "modified_at": "2026-08-01T16:31:01.904806+00:00", - "near_duplicate_fingerprint": null, - 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"sha256": "8b668b8994aa845107399994593d0ca831520be5257f005351a0ec13e97a39be", - "size_bytes": 4, - "source": "unknown", - "spatial_coverage": null, - "status": "examined", - "temporal_coverage": null, - "units": null - }, - { - "anomalies": [ - { - "action": "unavailable or unreadable", - "code": "raster.unreadable", - "message": "RasterioIOError: 'C:\\Projects\\geointel\\storage\\tiles\\df217a4e-7f2e-4989-880e-30fb9a7ec645\\f6848732-1f78-41ba-967c-11a577112b17\\5e0d5f61-e7fb-4d4a-ae96-84b9060554d6\\tile_0006.tif' not recognized as being in a supported file format.", - "severity": "critical" - } - ], - "contract": { - "key": "geointel.raster.geotiff", - "version": "1.0.0" - }, - "crs": null, - "duplicate_group": null, - "empty_content": false, - "freshness": { - "reason": "no_declared_source_timestamp", - "status": "unknown" - }, - "geometry_validation": null, - "item_id": "30a426290bc779af9d6a", - "lineage": null, - "modified_at": "2026-08-01T13:01:30.864002+00:00", - "near_duplicate_fingerprint": null, - 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}, - "error_sum": 0.09999999999999964, - "evaluated_count": 4, - "mae": 0.2749999999999999, - "missing_count": 1, - "reference_count": 5, - "rmse": 0.2872281323269015, - "squared_error_sum": 0.3300000000000001, - "units": "m_TAW" - }, - "sample_id": "terrain-test-flanders-rural", - "task": "terrain_interpretation" - } - ], - "schema_version": 2, - "status": "fixture_contract_only" -} diff --git a/artifacts/evidence/accuracy/P4/runs/p4-2.0.1-9677d0ef37db82bcf39b/workflow-summary.json b/artifacts/evidence/accuracy/P4/runs/p4-2.0.1-9677d0ef37db82bcf39b/workflow-summary.json deleted file mode 100644 index 5aaecc8f..00000000 --- a/artifacts/evidence/accuracy/P4/runs/p4-2.0.1-9677d0ef37db82bcf39b/workflow-summary.json +++ /dev/null @@ -1,28 +0,0 @@ -{ - "benchmark_manifest_sha256": "0ea5ab07f46c509a7a24943b31d5e9bfd6368920609227bc47613e18e52c4642", - "case_count": 9, - "evaluation_results_canonical_json_sha256": "55cdba9cce4dcdc88cee0829cd510d7e624a3472feb9d33f7e681621a792eba3", - "evidence_path": "artifacts/evidence/accuracy/P4/runs/p4-2.0.1-9677d0ef37db82bcf39b", - "evidence_run_id": "p4-2.0.1-9677d0ef37db82bcf39b", - "failure_example_count": 14, - "implemented_capability_count": 15, - "local_harness_status": "pass", - "phase4_done": false, - "phase5_ready": false, - "phase_decision": "blocked", - "product_benchmark_status": "fail", - "product_gate_evidence_sha256": "c9f5e3de3ab6d64911f8807b26caa661ccf911a5fd6b995107edda2004836e0c", - "promotion_allowed": false, - "reference_baseline_sha256": "aeb0f6510352f4e205e4fc4e8c423110ca72c2142016c7af846d758865f258c6", - "schema_version": 2, - "split_counts": { - "background-test": 2, - "calibration": 2, - "challenge": 4, - "test": 7, - "train": 3, - "val": 3 - }, - "status": "fail", - "task_family_count": 7 -} diff --git a/artifacts/evidence/accuracy/model-training/20260809-ai-assisted-visual-review.json b/artifacts/evidence/accuracy/model-training/20260809-ai-assisted-visual-review.json deleted file mode 100644 index fe3da58d..00000000 --- a/artifacts/evidence/accuracy/model-training/20260809-ai-assisted-visual-review.json +++ /dev/null @@ -1,62 +0,0 @@ -{ - "schema_version": 1, - "generated_at": "2026-08-09T09:57:02.8274719Z", - "review_kind": "ai_assisted_visual_review", - "reviewer_id": "openai-codex-gpt-5", - "human_review": false, - "repository_commit": "0209167cfd37c4f7865813a06e60bdd7ba5d918d", - "scope": "Bounded visual inspection of deterministic YOLO contact sheets; this is not a human-signed operational training release.", - "decision": { - "status": "experimental_training_only", - "promotion_allowed": false, - "protected_test_access_allowed": false, - "reason": "The Kempen background-aware corpus is materially better aligned than the rejected national candidates, but only a bounded contact-sheet sample was visually inspected and the mandatory human review gate remains open." - }, - "accepted_experimental_input": { - "dataset_yaml": "/app/storage/operator-data/yolo-building-aoi1024-bgaware512r8/dataset.yaml", - "dataset_yaml_sha256": "6995843d63735bc248fb573d6ab3ebedb1cd1c86f1bd6dbb864068c5fb8f816d", - "dataset_summary": "/app/storage/operator-data/yolo-building-aoi1024-bgaware512r8/yolo_tile_dataset_summary.json", - "dataset_summary_sha256": "c0c94295e52de5cc4d4cdcaaabb670220f15d2139c0051fff63d05730d33bdce", - "contact_sheet": "/app/storage/operator-evidence/accuracy-review/20260809-bgaware512r8-r1/contact_sheet_001.png", - "contact_sheet_sha256": "c5112d5c76d84153f8d219699071e7f42c8b188b0624c2bf5f9406a2146e66b6", - "rendered_tile_count": 32, - "dataset_tile_count": 207, - "observations": [ - "Most sampled labels visually overlap roof structures in the Kempen positive AOIs.", - "The training corpus contains repeated pure-empty background tiles and the validation split contains independent named positive and pure-empty AOIs.", - "Some dense scenes still contain footprint-versus-visible-roof ambiguity; this prevents operational acceptance." - ] - }, - "base_model": { - "path": "/app/models/geointel-building-yolov8s-smallbld-minpx3-img640-ft30.pt", - "sha256": "a9088b8491dfae36694b53e9e9406cb4e3511d334a5712fa34f75078a47759c1" - }, - "rejected_inputs": [ - { - "family": "building-be-v56 national corpus", - "decision": "exclude_from_new_training", - "reason": "Representative sheets show frequent ground-footprint versus visible-roof displacement and dense-scene ambiguity; 0/180 samples have formal human acceptance." - }, - { - "family": "building-be-v65 main/SAM candidates", - "decision": "quarantine", - "reason": "Visual samples include boxes on trees, paving and unrelated compounds after automatic refinement." - }, - { - "family": "building-be-v66 source/alignment/SAM candidates", - "decision": "quarantine", - "reason": "Systematic misalignment remains; the swapped-axis trial uses unrelated imagery and the detector-alignment sheet contains invalid labels." - } - ], - "training_constraints": { - "device": "cuda:0", - "allowed_evaluation_split": "val", - "forbidden_splits": [ - "test", - "challenge", - "background-test" - ], - "automatic_promotion": false, - "formal_release_manifest": false - } -} diff --git a/artifacts/evidence/accuracy/model-training/20260809-reviewedexp6-ai-assisted-review-ledger.json b/artifacts/evidence/accuracy/model-training/20260809-reviewedexp6-ai-assisted-review-ledger.json deleted file mode 100644 index 69d8970e..00000000 --- a/artifacts/evidence/accuracy/model-training/20260809-reviewedexp6-ai-assisted-review-ledger.json +++ /dev/null @@ -1,131 +0,0 @@ -{ - "schema_version": 1, - "ledger_id": "reviewedexp6-ai-assisted-review-r2-full-corpus", - "reviewed_at": "2026-08-09T19:34:31+02:00", - "reviewer": { - "id": "openai-codex", - "type": "ai_assistant", - "human": false - }, - "status": "complete_ai_assisted_experimental_only", - "explicit_limitations": [ - "This ledger is not human review and must never satisfy a human-review release gate.", - "Decisions cover all 252 rendered tiles, but visual review still does not adjudicate every individual label as human ground truth.", - "Visible roof geometry can be displaced from authoritative GRB ground-level footprints.", - "Accepted samples are eligible only for experimental training and non-protected validation." - ], - "artifacts": { - "review_summary_path": "/app/storage/operator-data/model-review/reviewedexp6-corpus/full-ai-review-r1/operator_yolo_label_qa_summary.json", - "review_summary_sha256": "467e5c3c489c42e42872a63fbb0bba7c613824631598d86ea6324b22c007f75a", - "contact_sheets": [ - {"path":"/app/storage/operator-data/model-review/reviewedexp6-corpus/full-ai-review-r1/contact_sheet_001.png","sha256":"688b97a6e82e6b906b7966ed3e2b43685786e89d50549188bfdcc3837d042eb2","tile_count":64}, - {"path":"/app/storage/operator-data/model-review/reviewedexp6-corpus/full-ai-review-r1/contact_sheet_002.png","sha256":"87f1945df3324dc100e08febd3e45f291a2d709ddebd9c627b082f30fd8f2d26","tile_count":64}, - {"path":"/app/storage/operator-data/model-review/reviewedexp6-corpus/full-ai-review-r1/contact_sheet_003.png","sha256":"1873ab25b8ee843abe28d00329fe28998a7b39f9fdbcd8f8acfb58cc576cdf10","tile_count":64}, - {"path":"/app/storage/operator-data/model-review/reviewedexp6-corpus/full-ai-review-r1/contact_sheet_004.png","sha256":"e64c252aac08792a76a62fe734728e7c81ba6a649ad2a1cd2051b4df1f95be98","tile_count":60} - ], - "rendered_tile_count": 252, - "rendered_label_count": 79192, - "selected_sample_count": 28 - }, - "visual_criteria": [ - "labels overlap visible building structures at the scale shown", - "no systematic axis swap or whole-tile displacement is visible", - "pure-background samples contain no clearly visible buildings", - "sparse contexts are not treated as pure background", - "dense roof-versus-ground-footprint disagreement is retained as an explicit limitation" - ], - "decisions": [ - {"sample_slug":"arendonk_center","sampled_tiles":9,"sampled_labels":4172,"split":"train","category":"reference_aoi","decision":"experimental_training_eligible"}, - {"sample_slug":"balen","sampled_tiles":9,"sampled_labels":2658,"split":"train","category":"reference_aoi","decision":"experimental_training_eligible"}, - {"sample_slug":"beerse_center","sampled_tiles":9,"sampled_labels":4303,"split":"train","category":"reference_aoi","decision":"experimental_training_eligible"}, - {"sample_slug":"dessel_center","sampled_tiles":9,"sampled_labels":3405,"split":"train","category":"reference_aoi","decision":"experimental_training_eligible"}, - {"sample_slug":"dessel_heide","sampled_tiles":9,"sampled_labels":192,"split":"train","category":"sparse_building_context","decision":"experimental_training_eligible"}, - {"sample_slug":"geel","sampled_tiles":9,"sampled_labels":4615,"split":"train","category":"reference_aoi","decision":"experimental_training_eligible"}, - {"sample_slug":"geel_bel","sampled_tiles":9,"sampled_labels":168,"split":"train","category":"sparse_building_context","decision":"experimental_training_eligible"}, - {"sample_slug":"grobbendonk_center","sampled_tiles":9,"sampled_labels":2793,"split":"val","category":"reference_aoi","decision":"non_protected_validation_only"}, - {"sample_slug":"herentals","sampled_tiles":9,"sampled_labels":5087,"split":"train","category":"reference_aoi","decision":"experimental_training_eligible"}, - {"sample_slug":"herenthout_bos","sampled_tiles":9,"sampled_labels":520,"split":"train","category":"sparse_building_context","decision":"experimental_training_eligible"}, - {"sample_slug":"hoogstraten_center","sampled_tiles":9,"sampled_labels":3761,"split":"train","category":"reference_aoi","decision":"experimental_training_eligible"}, - {"sample_slug":"hulshout_center","sampled_tiles":9,"sampled_labels":3606,"split":"train","category":"reference_aoi","decision":"experimental_training_eligible"}, - {"sample_slug":"kasterlee_bos","sampled_tiles":9,"sampled_labels":137,"split":"train","category":"sparse_building_context","decision":"experimental_training_eligible"}, - {"sample_slug":"kasterlee_center","sampled_tiles":9,"sampled_labels":4022,"split":"train","category":"reference_aoi","decision":"experimental_training_eligible"}, - {"sample_slug":"laakdal_center","sampled_tiles":9,"sampled_labels":287,"split":"train","category":"reference_aoi","decision":"experimental_training_eligible_with_dense_alignment_limitation"}, - {"sample_slug":"lille_center","sampled_tiles":9,"sampled_labels":3949,"split":"train","category":"reference_aoi","decision":"experimental_training_eligible"}, - {"sample_slug":"lommel_heide","sampled_tiles":9,"sampled_labels":0,"split":"train","category":"pure_empty_negative","decision":"experimental_training_eligible"}, - {"sample_slug":"meerhout_bos","sampled_tiles":9,"sampled_labels":206,"split":"train","category":"sparse_building_context","decision":"experimental_training_eligible"}, - {"sample_slug":"meerhout_center","sampled_tiles":9,"sampled_labels":4002,"split":"train","category":"reference_aoi","decision":"experimental_training_eligible"}, - {"sample_slug":"mol","sampled_tiles":9,"sampled_labels":3666,"split":"train","category":"reference_aoi","decision":"experimental_training_eligible"}, - {"sample_slug":"nijlen_center","sampled_tiles":9,"sampled_labels":4900,"split":"train","category":"reference_aoi","decision":"experimental_training_eligible"}, - {"sample_slug":"olen_center","sampled_tiles":9,"sampled_labels":3955,"split":"train","category":"reference_aoi","decision":"experimental_training_eligible"}, - {"sample_slug":"oud_turnhout_center","sampled_tiles":9,"sampled_labels":5492,"split":"train","category":"reference_aoi","decision":"experimental_training_eligible_with_dense_alignment_limitation"}, - {"sample_slug":"postel_bos","sampled_tiles":9,"sampled_labels":0,"split":"train","category":"pure_empty_negative","decision":"experimental_training_eligible"}, - {"sample_slug":"ravels_bos","sampled_tiles":9,"sampled_labels":55,"split":"train","category":"sparse_building_context","decision":"experimental_training_eligible"}, - {"sample_slug":"rijkevorsel_center","sampled_tiles":9,"sampled_labels":4231,"split":"train","category":"reference_aoi","decision":"experimental_training_eligible"}, - {"sample_slug":"vorselaar_center","sampled_tiles":9,"sampled_labels":3858,"split":"train","category":"reference_aoi","decision":"experimental_training_eligible"}, - {"sample_slug":"vosselaar_center","sampled_tiles":9,"sampled_labels":5152,"split":"val","category":"reference_aoi","decision":"non_protected_validation_only"} - ], - "accounting": { - "accepted_experimental_training_samples": 26, - "non_protected_validation_samples": 2, - "rejected_samples": 0, - "pure_empty_negative_samples": 2, - "sparse_context_samples": 6, - "human_review_complete": false, - "production_release_eligible": false - }, - "nested_box_audit": { - "audit_path": "/app/storage/operator-data/model-review/reviewedexp6-corpus/full-ai-review-r1/label_relationship_audit.json", - "audit_sha256": "2a219f650376e77a927c1ca37f801ac9fe8c2b8406cab6cd149be07e0557af73", - "focused_contact_sheet_path": "/app/storage/operator-data/model-review/reviewedexp6-corpus/nested-pairs-review-r1/contact_sheet_001.png", - "focused_contact_sheet_sha256": "7c27fc66bb1978296efc53d3e9f78ae6aa27816d5893c77f44d8803e57a40ee5", - "relationship_highlight_summary_path": "/app/storage/operator-data/model-review/reviewedexp6-corpus/nested-pairs-review-r2/operator_yolo_label_qa_summary.json", - "relationship_highlight_summary_sha256": "e4e6edc5c7223334c4feca9e242ac6d3c345b633a476aa9356b44133dcffe619", - "relationship_highlight_contact_sheet_path": "/app/storage/operator-data/model-review/reviewedexp6-corpus/nested-pairs-review-r2/contact_sheet_001.png", - "relationship_highlight_contact_sheet_sha256": "2a6bdd542b8ac49bcd5ac4d9c84999982461463ddd3c2fe0dc7332ceeb7a5e60", - "exact_duplicate_pairs": 0, - "near_duplicate_pairs_iou_at_least_0_90": 0, - "possible_nested_pairs_containment_at_least_0_98": 43, - "flagged_tile_count": 36, - "highlighted_unique_label_rows": 86, - "highlight_legend": { - "exact_duplicate": "cyan", - "near_duplicate": "red", - "possible_nested": "magenta", - "unflagged": "yellow" - }, - "share_of_rendered_labels": 0.000543, - "ai_visual_followup": "all 86 implicated label rows were index-highlighted; no cyan exact duplicates or red near duplicates exist, while the 43 magenta nesting pairs are dispersed across dense reference AOIs and predominantly show larger GRB envelopes around smaller building components rather than one systematic duplicate-label pattern", - "action": "retain for experimental analysis, require human adjudication before release, and perform no automatic rewrite or exclusion" - }, - "geometric_outlier_audit": { - "audit_path": "/app/storage/operator-data/model-review/reviewedexp6-corpus/full-ai-review-r1/label_outlier_audit.json", - "audit_sha256": "cac2c0cefb49aa3785ee9fb173a0187b3dd8abfc9c25e8e91df6c4af91ff5a40", - "reviewed_label_count": 79192, - "unique_flagged_label_count": 6657, - "small_dimension_below_4_px": 1812, - "extreme_aspect_ratio_at_least_8": 26, - "tile_edge_rows": 5079, - "extreme_rows_also_below_4_px": 16, - "extreme_contact_sheet_sha256": "67ad11e7d80678c78157a01a5e7ceb7cff9ac24410b127bdfaafd4350170cdb6", - "small_dimension_contact_sheet_sha256s": [ - "5b3ca4d5bfd57b466854a00b4791ac82cf4a826fad8a4694d0227c931b00dfad", - "0e5d2058154f8298fc6d2c064150bcf896e4e51b9bcce5fccbfc049e1ebb9515", - "03060f65843f3c2a291dd009124484f4cf798fe653e658bab007375613fa3010", - "2fe7c748a68b21a673f3d950909b07e3ddba81b736977fbee8d64ea62b422ca2" - ], - "tile_edge_sample_contact_sheet_sha256": "5d96c5a0a732077ed16b22d33bed998b37bd33b5536b1491e778999a2a6638dd", - "ai_visual_followup": "extreme rows are mostly plausible elongated structures, while sub-4-pixel rows are often visually marginal; tile-edge rows are expected clipped objects under the 0.35 visibility policy", - "next_corpus_decision": "restore the exporter minimum dimension to at least 4 px for the next immutable experimental corpus; retain elongated structures above that floor and measure any higher edge-visibility threshold in a separately versioned ablation" - }, - "cross_tile_repetition_audit": { - "audit_path": "/app/storage/operator-data/model-review/reviewedexp6-corpus/full-ai-review-r1/cross_tile_repetition_audit.json", - "audit_sha256": "3cdf5174fec61e0aa426b4a3f44ed943a738bf038f3b58028ec856ef1a9d000c", - "interior_label_rows": 74113, - "unique_interior_objects": 34082, - "extra_repeated_rows": 40031, - "repeated_object_groups": 24701, - "max_repetition": 4, - "cross_split_repetition_groups": 0, - "interpretation": "the 512 px tiles use stride 256, so tile-level validation rows are not statistically independent even though no reconstructed object crosses train and validation splits" - } -} diff --git a/artifacts/evidence/accuracy/model-training/20260809-reviewedexp6-minpx4-derived-corpus.json b/artifacts/evidence/accuracy/model-training/20260809-reviewedexp6-minpx4-derived-corpus.json deleted file mode 100644 index bdc1d39c..00000000 --- a/artifacts/evidence/accuracy/model-training/20260809-reviewedexp6-minpx4-derived-corpus.json +++ /dev/null @@ -1,63 +0,0 @@ -{ - "schema_version": 1, - "evidence_id": "reviewedexp6-minpx4-derived-corpus-r1", - "created_at": "2026-08-09T19:45:41+02:00", - "status": "complete_experimental_only", - "claim_boundary": "Deterministic derived-corpus improvement and AI-assisted visual triage only; no human-review, governed training, evaluation, promotion or production claim.", - "source": { - "dataset_dir": "/app/storage/operator-data/yolo-building-aoi1024-reviewedexp6-minpx3vis035", - "summary_sha256": "7c917e31216d1df2174c0f9c736f88a81f3835aa991971f8fb8665e17ddf5c9c", - "tile_size": 512, - "stride": 256, - "min_label_px": 3.0, - "min_visible_ratio": 0.35, - "tile_count": 252, - "label_count": 79192 - }, - "derived": { - "dataset_dir": "/app/storage/operator-data/yolo-building-aoi1024-reviewedexp6-minpx4-derived-r1", - "manifest_sha256": "8a80d0e9d5ac2d32556e2f1ea0c6009045d48a3e56d931b3161622dca4173a67", - "summary_sha256": "391b0302cc8a46d15fef426d8971a4a8e594fb6d63ed1c7ce16feeee9f1406", - "quality_audit_sha256": "0fc9391ce09a399f51f1e0ed30c677f482c7c1b49b187926da01ecdfd9f1067e", - "outlier_audit_sha256": "c2453abb83aaff8aebd84f63efb14da131225192cf0434d5d1df7cf06be240ca", - "relationship_audit_sha256": "61660d0c448ff579272bc585de8140e82d1577c0b017e1c078b66dc093f14c2e", - "cross_tile_repetition_audit_sha256": "9ca22d83271707713f7f96d5409af598f834787ad5a48be14f8752a704de0da0", - "min_label_px": 4.0, - "tile_count": 252, - "positive_tile_count": 234, - "negative_tile_count": 18, - 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No protected test or challenge data was opened, no national accuracy claim is made, and formal human review remains required for any future promotion." -} diff --git a/artifacts/evidence/accuracy/model-training/20260809-v68-checkpoint-and-threshold-review.json b/artifacts/evidence/accuracy/model-training/20260809-v68-checkpoint-and-threshold-review.json deleted file mode 100644 index 3670616e..00000000 --- a/artifacts/evidence/accuracy/model-training/20260809-v68-checkpoint-and-threshold-review.json +++ /dev/null @@ -1,93 +0,0 @@ -{ - "schema_version": 1, - "generated_at": "2026-08-09T12:30:00Z", - "run_id": "building-kempen-v68-checkpoint-and-threshold-review-r1", - "status": "completed_no_production_change", - "review_type": "ai_assisted_visual_and_metric_review", - "claim_boundary": "Non-protected Kempen validation only. 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"is_negative": false, - "is_repeated_background_negative": false, - "kept": true, - "label_count": 12, - "label_path": "/app/storage/operator-data/yolo-building-aoi1024-smallbld-minpx3vis035/labels/train/geel_bel_0001_r0_c256.txt", - "low_visual_variance": false, - "recommended_split": "train", - "repeat_index": 0, - "sample_role": "background_candidate", - "sample_slug": "geel_bel", - "split": "train", - "tile_index": 1, - "window": { - "col_off": 256, - "height": 512, - "row_off": 0, - "width": 512 - } - }, - { - "background_category": "sparse_building_context", - "image_path": "/app/storage/operator-data/yolo-building-aoi1024-smallbld-minpx3vis035/images/train/geel_bel_0002_r0_c512.png", - "is_negative": false, - "is_repeated_background_negative": false, - "kept": true, - "label_count": 25, - "label_path": "/app/storage/operator-data/yolo-building-aoi1024-smallbld-minpx3vis035/labels/train/geel_bel_0002_r0_c512.txt", - "low_visual_variance": false, - "recommended_split": "train", - "repeat_index": 0, - "sample_role": "background_candidate", - "sample_slug": "geel_bel", - "split": "train", - "tile_index": 2, - "window": { - "col_off": 512, - "height": 512, - "row_off": 0, - "width": 512 - } - }, - { - "background_category": "sparse_building_context", - "image_path": "/app/storage/operator-data/yolo-building-aoi1024-smallbld-minpx3vis035/images/train/geel_bel_0003_r256_c0.png", - "is_negative": false, - "is_repeated_background_negative": false, - "kept": true, - "label_count": 14, - "label_path": "/app/storage/operator-data/yolo-building-aoi1024-smallbld-minpx3vis035/labels/train/geel_bel_0003_r256_c0.txt", - "low_visual_variance": false, - "recommended_split": "train", - "repeat_index": 0, - "sample_role": "background_candidate", - "sample_slug": "geel_bel", - "split": "train", - "tile_index": 3, - "window": { - "col_off": 0, - "height": 512, - "row_off": 256, - "width": 512 - } - }, - { - "background_category": "sparse_building_context", - "image_path": "/app/storage/operator-data/yolo-building-aoi1024-smallbld-minpx3vis035/images/train/geel_bel_0004_r256_c256.png", - "is_negative": false, - "is_repeated_background_negative": false, - "kept": true, - "label_count": 15, - "label_path": "/app/storage/operator-data/yolo-building-aoi1024-smallbld-minpx3vis035/labels/train/geel_bel_0004_r256_c256.txt", - "low_visual_variance": false, - "recommended_split": "train", - "repeat_index": 0, - "sample_role": "background_candidate", - "sample_slug": "geel_bel", - "split": "train", - "tile_index": 4, - "window": { - "col_off": 256, - "height": 512, - "row_off": 256, - "width": 512 - } - }, - { - "background_category": "sparse_building_context", - "image_path": "/app/storage/operator-data/yolo-building-aoi1024-smallbld-minpx3vis035/images/train/geel_bel_0005_r256_c512.png", - "is_negative": false, - "is_repeated_background_negative": false, - "kept": true, - "label_count": 12, - "label_path": "/app/storage/operator-data/yolo-building-aoi1024-smallbld-minpx3vis035/labels/train/geel_bel_0005_r256_c512.txt", - "low_visual_variance": false, - "recommended_split": "train", - "repeat_index": 0, - "sample_role": "background_candidate", - "sample_slug": "geel_bel", - "split": "train", - "tile_index": 5, - "window": { - "col_off": 512, - "height": 512, - "row_off": 256, - "width": 512 - } - }, - { - "background_category": "sparse_building_context", - "image_path": "/app/storage/operator-data/yolo-building-aoi1024-smallbld-minpx3vis035/images/train/geel_bel_0006_r512_c0.png", - "is_negative": false, - "is_repeated_background_negative": false, - "kept": true, - "label_count": 16, - "label_path": "/app/storage/operator-data/yolo-building-aoi1024-smallbld-minpx3vis035/labels/train/geel_bel_0006_r512_c0.txt", - "low_visual_variance": false, - "recommended_split": "train", - "repeat_index": 0, - "sample_role": "background_candidate", - "sample_slug": "geel_bel", - "split": "train", - "tile_index": 6, - "window": { - "col_off": 0, - "height": 512, - "row_off": 512, - "width": 512 - } - }, - { - "background_category": "sparse_building_context", - "image_path": "/app/storage/operator-data/yolo-building-aoi1024-smallbld-minpx3vis035/images/train/geel_bel_0007_r512_c256.png", - "is_negative": false, - "is_repeated_background_negative": false, - "kept": true, - "label_count": 21, - "label_path": "/app/storage/operator-data/yolo-building-aoi1024-smallbld-minpx3vis035/labels/train/geel_bel_0007_r512_c256.txt", - "low_visual_variance": false, - "recommended_split": "train", - "repeat_index": 0, - "sample_role": "background_candidate", - "sample_slug": "geel_bel", - "split": "train", - "tile_index": 7, - "window": { - "col_off": 256, - "height": 512, - "row_off": 512, - "width": 512 - } - }, - { - "background_category": "sparse_building_context", - "image_path": "/app/storage/operator-data/yolo-building-aoi1024-smallbld-minpx3vis035/images/train/geel_bel_0008_r512_c512.png", - "is_negative": false, - "is_repeated_background_negative": false, - "kept": true, - "label_count": 37, - "label_path": "/app/storage/operator-data/yolo-building-aoi1024-smallbld-minpx3vis035/labels/train/geel_bel_0008_r512_c512.txt", - "low_visual_variance": false, - "recommended_split": "train", - "repeat_index": 0, - "sample_role": "background_candidate", - "sample_slug": "geel_bel", - "split": "train", - "tile_index": 8, - "window": { - "col_off": 512, - "height": 512, - "row_off": 512, - "width": 512 - } - }, - { - "background_category": "sparse_building_context", - "image_path": "/app/storage/operator-data/yolo-building-aoi1024-smallbld-minpx3vis035/images/train/herenthout_bos_0000_r0_c0.png", - "is_negative": false, - "is_repeated_background_negative": false, - "kept": true, - "label_count": 7, - "label_path": "/app/storage/operator-data/yolo-building-aoi1024-smallbld-minpx3vis035/labels/train/herenthout_bos_0000_r0_c0.txt", - "low_visual_variance": false, - "recommended_split": "train", - "repeat_index": 0, - "sample_role": "background_candidate", - "sample_slug": "herenthout_bos", - "split": "train", - "tile_index": 0, - "window": { - "col_off": 0, - "height": 512, - "row_off": 0, - "width": 512 - } - }, - { - "background_category": "sparse_building_context", - "image_path": "/app/storage/operator-data/yolo-building-aoi1024-smallbld-minpx3vis035/images/train/herenthout_bos_0001_r0_c256.png", - "is_negative": false, - "is_repeated_background_negative": false, - "kept": true, - "label_count": 37, - "label_path": "/app/storage/operator-data/yolo-building-aoi1024-smallbld-minpx3vis035/labels/train/herenthout_bos_0001_r0_c256.txt", - "low_visual_variance": false, - "recommended_split": "train", - "repeat_index": 0, - "sample_role": "background_candidate", - "sample_slug": "herenthout_bos", - "split": "train", - "tile_index": 1, - "window": { - "col_off": 256, - "height": 512, - "row_off": 0, - "width": 512 - } - }, - { - "background_category": "sparse_building_context", - "image_path": "/app/storage/operator-data/yolo-building-aoi1024-smallbld-minpx3vis035/images/train/herenthout_bos_0002_r0_c512.png", - "is_negative": false, - "is_repeated_background_negative": false, - "kept": true, - "label_count": 67, - "label_path": "/app/storage/operator-data/yolo-building-aoi1024-smallbld-minpx3vis035/labels/train/herenthout_bos_0002_r0_c512.txt", - "low_visual_variance": false, - "recommended_split": "train", - "repeat_index": 0, - "sample_role": "background_candidate", - "sample_slug": "herenthout_bos", - "split": "train", - "tile_index": 2, - "window": { - "col_off": 512, - "height": 512, - "row_off": 0, - "width": 512 - } - }, - { - "background_category": "sparse_building_context", - "image_path": "/app/storage/operator-data/yolo-building-aoi1024-smallbld-minpx3vis035/images/train/herenthout_bos_0003_r256_c0.png", - "is_negative": false, - "is_repeated_background_negative": false, - "kept": true, - "label_count": 92, - "label_path": "/app/storage/operator-data/yolo-building-aoi1024-smallbld-minpx3vis035/labels/train/herenthout_bos_0003_r256_c0.txt", - "low_visual_variance": false, - "recommended_split": "train", - "repeat_index": 0, - "sample_role": "background_candidate", - "sample_slug": "herenthout_bos", - "split": "train", - "tile_index": 3, - "window": { - "col_off": 0, - "height": 512, - "row_off": 256, - "width": 512 - } - }, - { - "background_category": "sparse_building_context", - "image_path": "/app/storage/operator-data/yolo-building-aoi1024-smallbld-minpx3vis035/images/train/herenthout_bos_0004_r256_c256.png", - "is_negative": false, - "is_repeated_background_negative": false, - "kept": true, - "label_count": 83, - "label_path": "/app/storage/operator-data/yolo-building-aoi1024-smallbld-minpx3vis035/labels/train/herenthout_bos_0004_r256_c256.txt", - "low_visual_variance": false, - "recommended_split": "train", - "repeat_index": 0, - "sample_role": "background_candidate", - "sample_slug": "herenthout_bos", - "split": "train", - "tile_index": 4, - "window": { - "col_off": 256, - "height": 512, - "row_off": 256, - "width": 512 - } - }, - { - "background_category": "sparse_building_context", - "image_path": "/app/storage/operator-data/yolo-building-aoi1024-smallbld-minpx3vis035/images/train/herenthout_bos_0005_r256_c512.png", - "is_negative": false, - "is_repeated_background_negative": false, - "kept": true, - "label_count": 50, - "label_path": "/app/storage/operator-data/yolo-building-aoi1024-smallbld-minpx3vis035/labels/train/herenthout_bos_0005_r256_c512.txt", - "low_visual_variance": false, - "recommended_split": "train", - "repeat_index": 0, - "sample_role": "background_candidate", - "sample_slug": "herenthout_bos", - "split": "train", - "tile_index": 5, - "window": { - "col_off": 512, - "height": 512, - "row_off": 256, - "width": 512 - } - }, - { - "background_category": "sparse_building_context", - "image_path": "/app/storage/operator-data/yolo-building-aoi1024-smallbld-minpx3vis035/images/train/herenthout_bos_0006_r512_c0.png", - "is_negative": false, - "is_repeated_background_negative": false, - "kept": true, - "label_count": 107, - "label_path": "/app/storage/operator-data/yolo-building-aoi1024-smallbld-minpx3vis035/labels/train/herenthout_bos_0006_r512_c0.txt", - "low_visual_variance": false, - "recommended_split": "train", - "repeat_index": 0, - "sample_role": "background_candidate", - "sample_slug": "herenthout_bos", - "split": "train", - "tile_index": 6, - "window": { - "col_off": 0, - "height": 512, - "row_off": 512, - "width": 512 - } - }, - { - "background_category": "sparse_building_context", - "image_path": "/app/storage/operator-data/yolo-building-aoi1024-smallbld-minpx3vis035/images/train/herenthout_bos_0007_r512_c256.png", - "is_negative": false, - "is_repeated_background_negative": false, - "kept": true, - "label_count": 59, - "label_path": "/app/storage/operator-data/yolo-building-aoi1024-smallbld-minpx3vis035/labels/train/herenthout_bos_0007_r512_c256.txt", - "low_visual_variance": false, - "recommended_split": "train", - "repeat_index": 0, - "sample_role": "background_candidate", - "sample_slug": "herenthout_bos", - "split": "train", - "tile_index": 7, - "window": { - "col_off": 256, - "height": 512, - "row_off": 512, - "width": 512 - } - }, - { - "background_category": "sparse_building_context", - "image_path": "/app/storage/operator-data/yolo-building-aoi1024-smallbld-minpx3vis035/images/train/herenthout_bos_0008_r512_c512.png", - "is_negative": false, - "is_repeated_background_negative": false, - "kept": true, - "label_count": 18, - "label_path": "/app/storage/operator-data/yolo-building-aoi1024-smallbld-minpx3vis035/labels/train/herenthout_bos_0008_r512_c512.txt", - "low_visual_variance": false, - "recommended_split": "train", - "repeat_index": 0, - "sample_role": "background_candidate", - "sample_slug": "herenthout_bos", - "split": "train", - "tile_index": 8, - "window": { - "col_off": 512, - "height": 512, - "row_off": 512, - "width": 512 - } - } - ], - "train_tile_count": 180, - "val_tile_count": 18, - "validation_sample_slugs": [ - "arendonk_heide", - "grobbendonk_center", - "vosselaar_center" - ] -} \ No newline at end of file diff --git a/artifacts/evidence/accuracy/model-training/20260810-v74-root-cause/rehearsal-v74.experimental.json b/artifacts/evidence/accuracy/model-training/20260810-v74-root-cause/rehearsal-v74.experimental.json deleted file mode 100644 index f02e4a27..00000000 --- a/artifacts/evidence/accuracy/model-training/20260810-v74-root-cause/rehearsal-v74.experimental.json +++ /dev/null @@ -1,17 +0,0 @@ -{ - "dataset_yaml": "/app/storage/training/experimental/building-be-v73-fresh-flanders-train-r1/rehearsal-v74/dataset.yaml", - "dataset_yaml_sha256": "2fa0c66ddb7105629b7873e45030e6977da941130cb032c63e6449033ed42409", - "human_review_pending": true, - "promotion_allowed": false, - "protected_v72_used": false, - "rehearsal_summary": "/app/storage/operator-data/yolo-building-aoi1024-smallbld-minpx3vis035/yolo_tile_dataset_summary.json", - "rehearsal_summary_sha256": "49b2a07d2105d08356431757b83eafc1498eaf1fb76965b1efe05b776824942a", - "rehearsal_train_tile_count": 180, - "release_claim_allowed": false, - "remediation_repeat": 2, - "remediation_summary": "/app/storage/training/experimental/building-be-v73-fresh-flanders-train-r1/yolo512/experimental_dataset_summary.json", - "remediation_summary_sha256": "047874a4f9362c82263ffe11c389a2f65168c449d3f6cbcc77cea709c0ba4c59", - "remediation_unique_train_tile_count": 48, - "schema_version": 1, - "status": "experimental_rehearsal_only" -} diff --git a/artifacts/evidence/accuracy/model-training/20260830-independent-ai-visual-review.json b/artifacts/evidence/accuracy/model-training/20260830-independent-ai-visual-review.json deleted file mode 100644 index ae796356..00000000 --- a/artifacts/evidence/accuracy/model-training/20260830-independent-ai-visual-review.json +++ /dev/null @@ -1,84 +0,0 @@ -{ - "schema_version": 1, - "review_id": "20260830-independent-ai-visual-review", - "reviewed_at": "2026-08-30T00:00:00+02:00", - "reviewer_kind": "independent_ai_visual_inspection", - "human_reviewer": false, - "claim_boundary": "Visual inspection evidence only. This is not a human acceptance ledger, protected-test result, accuracy measurement or model-promotion approval.", - "inputs": [ - { - "path": "artifacts/evidence/accuracy/model-training/20260809-v72-fresh-calibration/contact_sheet_001.png", - "sha256": "f7734c5a9db8837adeda7f8e0f1a2942148330abfcb588d41dc245017ec2435a" - }, - { - "path": "artifacts/evidence/accuracy/model-training/20260810-v73-flanders-remediation/contact_sheet_001.png", - "sha256": "4e092afac6bbff820908f73acd2a29b6d327d7476c3b2ae5001302a0bde4a24f" - }, - { - "path": "artifacts/evidence/accuracy/model-training/20260810-v73-flanders-remediation/contact_sheet_002.png", - "sha256": "ef4e4a9663b4ac1920bee76bf0ca40c69d6232ddeb40d75c6963a17540b8d211" - }, - { - "path": "artifacts/evidence/accuracy/model-training/20260810-v74-root-cause/active-error-contact-sheet.png", - "sha256": "bb5e4809802643cc8b673a86f3027ed06aa0430fbe79b1d33718c21d5feb269d" - }, - { - "path": "storage/operator-data/model-review/reviewedexp6-corpus/full-ai-review-r1/contact_sheet_001.png", - "sha256": "688b97a6e82e6b906b7966ed3e2b43685786e89d50549188bfdcc3837d042eb2" - }, - { - "path": "storage/operator-data/model-review/reviewedexp6-corpus/nested-pairs-review-r2/contact_sheet_001.png", - "sha256": "2a6bdd542b8ac49bcd5ac4d9c84999982461463ddd3c2fe0dc7332ceeb7a5e60" - }, - { - "path": "storage/operator-data/model-review/reviewedexp6-corpus/tile-edge-review-r1/contact_sheet_001.png", - "sha256": "5d96c5a0a732077ed16b22d33bed998b37bd33b5536b1491e778999a2a6638dd" - } - ], - "findings": [ - { - "severity": "blocker", - "category": "reference_geometry_semantics", - "observation": "Many yellow reference rectangles are coarse axis-aligned extents rather than roof or building footprints; several include vegetation, roads, fields or multiple structures.", - "impact": "A detector trained against these boxes is penalized for geometrically correct roof localization and rewarded for oversized detections." - }, - { - "severity": "blocker", - "category": "dense_and_nested_labels", - "observation": "Dense urban and industrial samples contain strongly overlapping, nested and grouped boxes without an unambiguous single-object labelling rule.", - "impact": "Label conflict and inconsistent object granularity make precision, recall and NMS behaviour unreliable." - }, - { - "severity": "critical", - "category": "tile_edge_and_visibility", - "observation": "Multiple labelled structures are clipped by tile boundaries or only partly visible, while edge inclusion rules are not consistently evident.", - "impact": "This creates avoidable false-negative and duplicate-detection pressure at inference tile seams." - }, - { - "severity": "critical", - "category": "hard_negative_coverage", - "observation": "Industrial rails, paved surfaces, tree canopy and tree-shadow remain recurrent false-positive contexts in the active-error sheet; representative pure-background coverage remains insufficient, especially for Brussels.", - "impact": "The candidate has no defensible low-false-positive operating point across Belgium." - }, - { - "severity": "critical", - "category": "model_error_balance", - "observation": "The active-error review shows simultaneous false positives and false negatives across industrial, vegetated and sparse-rural contexts.", - "impact": "Threshold tuning alone cannot repair the observed error pattern." - } - ], - "decision": { - "corpus_accepted": false, - "training_gate": "blocked", - "promotion_allowed": false, - "human_review_satisfied": false, - "required_before_next_governed_training": [ - "re-extract building labels from task-appropriate authoritative geometry with an explicit object-granularity rule", - "resolve dense and nested labels and publish a checksum-bound review ledger", - "apply deterministic tile-edge visibility and ownership rules", - "add independent pure-background and hard-negative strata for Flanders, Wallonia and Brussels", - "prove AOI and derived-image independence across train, validation, test and challenge splits", - "obtain representative human acceptance before opening protected evaluation" - ] - } -} diff --git a/backend/app/api/routes/auth.py b/backend/app/api/routes/auth.py index f7f94ba6..355832c4 100644 --- a/backend/app/api/routes/auth.py +++ b/backend/app/api/routes/auth.py @@ -269,6 +269,19 @@ def guest_login( status_code=status.HTTP_403_FORBIDDEN, ) + client_host = _client_host(request) + retry_after = AuthService.consume_guest_request( + f"guest-login:{client_host}", + max_requests=settings.guest_login_requests_per_minute, + ) + if retry_after: + raise AppError( + code="GUEST_LOGIN_RATE_LIMITED", + message="Too many guest sessions were requested. Try again later.", + details={"retry_after_seconds": retry_after}, + status_code=status.HTTP_429_TOO_MANY_REQUESTS, + ) + demo = DemoWorkflowService.seed(db) token = AuthService.create_session_token( settings.guest_display_name, diff --git a/backend/app/api/routes/datasets.py b/backend/app/api/routes/datasets.py index 677097a3..5ee04319 100644 --- a/backend/app/api/routes/datasets.py +++ b/backend/app/api/routes/datasets.py @@ -10,6 +10,7 @@ from fastapi import UploadFile from sqlalchemy.orm import Session from app.core.config import get_settings from app.core.errors import AppError +from app.core.public_demo import is_public_demo_project from app.db.session import get_db from app.models import Area, Project from app.schemas import ( @@ -163,6 +164,12 @@ async def upload_dataset( source_version: str | None = Form(None), db: Session = Depends(get_db), ): + if is_public_demo_project(project_id): + raise AppError( + code="PUBLIC_DEMO_UPLOAD_FORBIDDEN", + message="Operator uploads are not accepted in the public demo project.", + status_code=403, + ) if area_id is not None: area = db.get(Area, area_id) if not area: diff --git a/backend/app/api/routes/detection.py b/backend/app/api/routes/detection.py index 5ea713d8..1d8b8ca9 100644 --- a/backend/app/api/routes/detection.py +++ b/backend/app/api/routes/detection.py @@ -55,12 +55,14 @@ def get_yolo_preflight( tile_manifest_path: str | None = None, check_model_load: bool = False, model_asset_id: str | None = None, + db: Session = Depends(get_db), ) -> dict: return envelope( YoloPreflightService.run( tile_manifest_path=tile_manifest_path, check_model_load=check_model_load, model_asset_id=model_asset_id, + db=db, ) ) diff --git a/backend/app/api/routes/health.py b/backend/app/api/routes/health.py index 7d479f60..c4a73df2 100644 --- a/backend/app/api/routes/health.py +++ b/backend/app/api/routes/health.py @@ -47,21 +47,18 @@ def _database_checks() -> dict[str, str]: with get_engine().connect() as connection: connection.execute(text("SELECT 1")) checks["database"] = "ok" - postgis_version = connection.execute( + connection.execute( text("SELECT PostGIS_Version()") ).scalar_one() - checks["postgis"] = f"ok:{postgis_version}" + checks["postgis"] = "ok" database_head = connection.execute( text("SELECT version_num FROM alembic_version") ).scalar_one() expected_heads = _expected_migration_heads() if len(expected_heads) == 1 and database_head == expected_heads[0]: - checks["migration"] = f"ok:{database_head}" + checks["migration"] = "ok" else: - checks["migration"] = ( - f"degraded:database={database_head};" - f"expected={','.join(expected_heads) or 'none'}" - ) + checks["migration"] = "degraded" except Exception: return checks return checks @@ -94,9 +91,7 @@ def _readiness_payload() -> HealthResponse: return HealthResponse( status="ok" if ready else "degraded", service="geointel-backend", - version=settings.app_version, - build_sha=settings.build_sha, - build_time=settings.build_time, + version="public", database=checks["database"], postgis=checks["postgis"], migration=checks["migration"], @@ -107,13 +102,10 @@ def _readiness_payload() -> HealthResponse: @router.get("/health/live", response_model=HealthResponse) def liveness() -> HealthResponse: - settings = get_settings() return HealthResponse( status="ok", service="geointel-backend", - version=settings.app_version, - build_sha=settings.build_sha, - build_time=settings.build_time, + version="public", ) diff --git a/backend/app/core/config.py b/backend/app/core/config.py index 79394ecb..717e442b 100644 --- a/backend/app/core/config.py +++ b/backend/app/core/config.py @@ -55,6 +55,24 @@ class Settings(BaseSettings): le=86_400, validation_alias="GEOINTEL_GUEST_SESSION_TTL_SECONDS", ) + guest_login_requests_per_minute: int = Field( + default=3, + ge=1, + le=60, + validation_alias="GEOINTEL_GUEST_LOGIN_REQUESTS_PER_MINUTE", + ) + guest_compute_requests_per_minute: int = Field( + default=4, + ge=1, + le=120, + validation_alias="GEOINTEL_GUEST_COMPUTE_REQUESTS_PER_MINUTE", + ) + guest_compute_max_concurrency: int = Field( + default=2, + ge=1, + le=16, + validation_alias="GEOINTEL_GUEST_COMPUTE_MAX_CONCURRENCY", + ) database_url: str = Field( default="postgresql+psycopg://geointel:geointel@localhost:5432/geointel?connect_timeout=1", validation_alias="DATABASE_URL", @@ -77,6 +95,24 @@ class Settings(BaseSettings): le=256, validation_alias="GEOINTEL_MAX_IN_MEMORY_VECTOR_MB", ) + max_raster_pixels: int = Field( + default=40_000_000, + ge=1, + le=500_000_000, + validation_alias="GEOINTEL_MAX_RASTER_PIXELS", + ) + max_raster_bands: int = Field( + default=16, + ge=1, + le=256, + validation_alias="GEOINTEL_MAX_RASTER_BANDS", + ) + max_decoded_raster_mb: int = Field( + default=1024, + ge=16, + le=8192, + validation_alias="GEOINTEL_MAX_DECODED_RASTER_MB", + ) orthophoto_enabled: bool = Field(default=True, validation_alias="ORTHOPHOTO_ENABLED") orthophoto_wms_url: str = Field( default="https://geo.api.vlaanderen.be/OMWRGBMRVL/wms", diff --git a/backend/app/core/public_demo.py b/backend/app/core/public_demo.py new file mode 100644 index 00000000..3eb75191 --- /dev/null +++ b/backend/app/core/public_demo.py @@ -0,0 +1,14 @@ +from __future__ import annotations + +from uuid import UUID + + +# Stable server-owned identity: a public session must never attach itself to an +# operator project merely because the display names happen to match. +PUBLIC_DEMO_PROJECT_ID = UUID("6f7e6f12-9b62-4a3f-a5a0-4b3bb6b2c901") +PUBLIC_DEMO_PROJECT_NAME = "GeoIntel Demo - Building QA" +PUBLIC_DEMO_PROJECT_MARKER = "geointel:public-demo:v1" + + +def is_public_demo_project(project_id: UUID) -> bool: + return project_id == PUBLIC_DEMO_PROJECT_ID diff --git a/backend/app/main.py b/backend/app/main.py index c45d1ce8..d7e9466f 100644 --- a/backend/app/main.py +++ b/backend/app/main.py @@ -127,6 +127,7 @@ def create_app() -> FastAPI: token = set_request_id(request_id) started_at = time.perf_counter() raw_path = str(request.scope.get("path") or "") + guest_compute_acquired = False try: host = request.headers.get("host", "") content_type = request.headers.get("content-type", "").split(";", 1)[0].strip().lower() @@ -234,6 +235,20 @@ def create_app() -> FastAPI: ) is_read_request = request.method in {"GET", "HEAD", "OPTIONS"} if is_read_request: + if ( + normalized_path == f"{settings.api_prefix}/detection/yolo/preflight" + and request.query_params.get("check_model_load", "").lower() in {"1", "true", "yes", "on"} + ): + response = JSONResponse( + status_code=403, + content=_to_error_payload( + "GUEST_MODEL_LOAD_FORBIDDEN", + "Model loading is available to authenticated operators only.", + request_id=request_id, + ), + ) + response.headers["x-request-id"] = request_id + return response guest_scoped_analysis_read = ( query_project_id == str(principal.project_id) and normalized_path.startswith( @@ -325,6 +340,37 @@ def create_app() -> FastAPI: ) response.headers["x-request-id"] = request_id return response + retry_after = AuthService.consume_guest_request( + f"guest-compute:{principal.session_id}", + max_requests=settings.guest_compute_requests_per_minute, + ) + if retry_after: + response = JSONResponse( + status_code=429, + content=_to_error_payload( + "GUEST_COMPUTE_RATE_LIMITED", + "The public demo compute budget is temporarily exhausted.", + request_id=request_id, + ), + ) + response.headers["retry-after"] = str(retry_after) + response.headers["x-request-id"] = request_id + return response + guest_compute_acquired = AuthService.try_acquire_guest_compute( + max_concurrency=settings.guest_compute_max_concurrency, + ) + if not guest_compute_acquired: + response = JSONResponse( + status_code=429, + content=_to_error_payload( + "GUEST_COMPUTE_BUSY", + "The public demo is already processing its maximum number of jobs.", + request_id=request_id, + ), + ) + response.headers["retry-after"] = "10" + response.headers["x-request-id"] = request_id + return response response = await call_next(request) response.headers["x-request-id"] = request_id logger.info( @@ -337,6 +383,8 @@ def create_app() -> FastAPI: ) return response finally: + if guest_compute_acquired: + AuthService.release_guest_compute() reset_request_id(token) @app.exception_handler(AppError) diff --git a/backend/app/services/auth_service.py b/backend/app/services/auth_service.py index bf93a3fc..9fc61886 100644 --- a/backend/app/services/auth_service.py +++ b/backend/app/services/auth_service.py @@ -8,17 +8,19 @@ import secrets import threading import time from collections import deque -from dataclasses import dataclass +from dataclasses import dataclass, field from typing import Literal, cast from uuid import UUID from app.core.config import Settings +from app.core.public_demo import PUBLIC_DEMO_PROJECT_ID @dataclass(frozen=True) class AuthPrincipal: username: str expires_at: int + session_id: str = field(default_factory=lambda: secrets.token_urlsafe(12)) role: Literal["operator", "guest"] = "operator" project_id: UUID | None = None @@ -30,6 +32,10 @@ class AuthService: FAILURE_WINDOW_SECONDS = 300 _failures: dict[str, deque[float]] = {} _failure_lock = threading.Lock() + _guest_requests: dict[str, deque[float]] = {} + _guest_request_lock = threading.Lock() + _active_guest_compute = 0 + _guest_compute_lock = threading.Lock() @staticmethod def _b64_encode(value: bytes) -> str: @@ -159,8 +165,9 @@ class AuthService: issued_at = int(payload.get("iat") or 0) version = int(payload.get("v") or 0) role_value = str(payload.get("role") or "operator") + session_id = str(payload.get("jti") or "") current = int(time.time() if now is None else now) - if version not in {1, 2} or role_value not in {"operator", "guest"}: + if version not in {1, 2} or role_value not in {"operator", "guest"} or not session_id: return None role = cast(Literal["operator", "guest"], role_value) if issued_at <= 0 or issued_at > current + 60 or expires_at <= current: @@ -178,11 +185,14 @@ class AuthService: if not raw_project_id: return None project_id = UUID(str(raw_project_id)) + if project_id != PUBLIC_DEMO_PROJECT_ID: + return None if expires_at - issued_at > max_ttl: return None return AuthPrincipal( username=username, expires_at=expires_at, + session_id=session_id, role=role, project_id=project_id, ) @@ -215,3 +225,36 @@ class AuthService: def clear_failures(cls, key: str) -> None: with cls._failure_lock: cls._failures.pop(key, None) + + @classmethod + def consume_guest_request( + cls, + key: str, + *, + max_requests: int, + window_seconds: int = 60, + now: float | None = None, + ) -> int: + """Record a guest action and return Retry-After seconds when limited.""" + current = time.monotonic() if now is None else now + with cls._guest_request_lock: + attempts = cls._guest_requests.setdefault(key, deque()) + while attempts and current - attempts[0] >= window_seconds: + attempts.popleft() + if len(attempts) >= max_requests: + return max(1, int(window_seconds - (current - attempts[0]))) + attempts.append(current) + return 0 + + @classmethod + def try_acquire_guest_compute(cls, *, max_concurrency: int) -> bool: + with cls._guest_compute_lock: + if cls._active_guest_compute >= max_concurrency: + return False + cls._active_guest_compute += 1 + return True + + @classmethod + def release_guest_compute(cls) -> None: + with cls._guest_compute_lock: + cls._active_guest_compute = max(0, cls._active_guest_compute - 1) diff --git a/backend/app/services/demo_workflow_service.py b/backend/app/services/demo_workflow_service.py index 309e90e8..98e271a0 100644 --- a/backend/app/services/demo_workflow_service.py +++ b/backend/app/services/demo_workflow_service.py @@ -10,6 +10,12 @@ from uuid import UUID, uuid4 from geoalchemy2.shape import from_shape from sqlalchemy.orm import Session +from app.core.errors import AppError +from app.core.public_demo import ( + PUBLIC_DEMO_PROJECT_ID, + PUBLIC_DEMO_PROJECT_MARKER, + PUBLIC_DEMO_PROJECT_NAME, +) from app.models import Area, Dataset, DatasetVersion, Metric, Project, QualityCheck from app.schemas.demo import DemoWorkflowResponse from app.services.derived_dataset_governance_service import DerivedDatasetGovernanceService @@ -23,7 +29,8 @@ from app.utils.geometry import area_m2, geometry_bbox_polygon, normalize_to_mult class DemoWorkflowService: - PROJECT_NAME = "GeoIntel Demo - Building QA" + PROJECT_ID = PUBLIC_DEMO_PROJECT_ID + PROJECT_NAME = PUBLIC_DEMO_PROJECT_NAME AREA_NAME = "Demo AOI - Geel buildings" REFERENCE_FILENAME = "demo_reference_buildings.geojson" CANDIDATE_FILENAME = "demo_predicted_buildings.geojson" @@ -91,17 +98,19 @@ class DemoWorkflowService: @staticmethod def _find_existing_project(db: Session) -> Project | None: - projects = ( - db.query(Project) - .filter(Project.name == DemoWorkflowService.PROJECT_NAME) - .filter(Project.status != "deleted") - .order_by(Project.created_at.asc()) - .all() - ) - for project in projects: - if DemoWorkflowService._has_complete_demo_state(db, project.id): - return project - return projects[0] if projects else None + project = db.get(Project, DemoWorkflowService.PROJECT_ID) + if project is None: + return None + if ( + project.name != DemoWorkflowService.PROJECT_NAME + or project.description != PUBLIC_DEMO_PROJECT_MARKER + ): + raise AppError( + code="PUBLIC_DEMO_IDENTITY_CONFLICT", + message="The reserved public-demo project identity is already in use.", + status_code=409, + ) + return project @staticmethod def _activate_explicit_demo_project(db: Session, project: Project | None) -> Project | None: @@ -487,9 +496,9 @@ class DemoWorkflowService: created = True else: project = Project( - id=uuid4(), + id=DemoWorkflowService.PROJECT_ID, name=DemoWorkflowService.PROJECT_NAME, - description="Offline fixture workflow: reference buildings, predicted buildings and persisted QA metrics.", + description=PUBLIC_DEMO_PROJECT_MARKER, region="Kempen", status="active", ) diff --git a/backend/app/services/project_service.py b/backend/app/services/project_service.py index a3e63015..e2efcbc0 100644 --- a/backend/app/services/project_service.py +++ b/backend/app/services/project_service.py @@ -6,6 +6,7 @@ from typing import Literal from sqlalchemy.orm import Session from app.core.errors import AppError +from app.core.public_demo import is_public_demo_project from app.models import Project from app.schemas.project import ProjectCreate, ProjectRead, ProjectUpdate @@ -50,6 +51,12 @@ class ProjectService: @staticmethod def update_project(db: Session, project_id: uuid.UUID, payload: ProjectUpdate) -> ProjectRead | None: + if is_public_demo_project(project_id): + raise AppError( + code="PUBLIC_DEMO_IMMUTABLE", + message="The public demo project identity cannot be edited.", + status_code=409, + ) project = db.get(Project, project_id) if not project or project.status == "deleted": return None @@ -71,6 +78,12 @@ class ProjectService: @staticmethod def delete_project(db: Session, project_id: uuid.UUID) -> bool: + if is_public_demo_project(project_id): + raise AppError( + code="PUBLIC_DEMO_IMMUTABLE", + message="The public demo project identity cannot be deleted.", + status_code=409, + ) project = db.get(Project, project_id) if not project or project.status == "deleted": return False diff --git a/backend/app/services/raster_operations_service.py b/backend/app/services/raster_operations_service.py index 22376e94..d243c8b4 100644 --- a/backend/app/services/raster_operations_service.py +++ b/backend/app/services/raster_operations_service.py @@ -466,7 +466,11 @@ class RasterOperationsService: height = int(source.height) preview_width, preview_height = RasterOperationsService._preview_dimensions(width, height) if not preview_path.exists(): - data = source.read(1) + data = source.read( + 1, + out_shape=(preview_height, preview_width), + resampling=rasterio.enums.Resampling.nearest, + ) try: preview_width, preview_height = RasterOperationsService._write_preview_image( data=data, diff --git a/backend/app/services/raster_service.py b/backend/app/services/raster_service.py index 50f4135b..ee80cf90 100644 --- a/backend/app/services/raster_service.py +++ b/backend/app/services/raster_service.py @@ -2,9 +2,26 @@ from __future__ import annotations from pathlib import Path +from app.core.config import get_settings from app.core.errors import AppError +_DTYPE_BYTES = { + "uint8": 1, + "int8": 1, + "uint16": 2, + "int16": 2, + "uint32": 4, + "int32": 4, + "float32": 4, + "uint64": 8, + "int64": 8, + "float64": 8, + "complex64": 8, + "complex128": 16, +} + + def _import_rasterio(): import importlib @@ -26,6 +43,33 @@ def extract_raster_metadata(path: str) -> dict: dataset_path = Path(path) try: with rasterio.open(dataset_path) as dataset: + settings = get_settings() + width = int(dataset.width) + height = int(dataset.height) + band_count = int(dataset.count) + pixel_count = width * height + dtype_bytes = max((_DTYPE_BYTES.get(str(dtype), 16) for dtype in dataset.dtypes), default=16) + decoded_bytes = pixel_count * band_count * dtype_bytes + if ( + width <= 0 + or height <= 0 + or band_count <= 0 + or pixel_count > settings.max_raster_pixels + or band_count > settings.max_raster_bands + or decoded_bytes > settings.max_decoded_raster_mb * 1024 * 1024 + ): + raise AppError( + code="RASTER_RESOURCE_LIMIT_EXCEEDED", + message="Raster dimensions or decoded size exceed the configured processing budget.", + details={ + "width": width, + "height": height, + "band_count": band_count, + "pixel_count": pixel_count, + "estimated_decoded_bytes": decoded_bytes, + }, + status_code=413, + ) nodata = dataset.nodata if isinstance(nodata, (list, tuple)): nodata_value = [None if value is None else float(value) for value in nodata] @@ -35,9 +79,9 @@ def extract_raster_metadata(path: str) -> dict: transform = dataset.transform.to_gdal() if hasattr(dataset, "transform") else None return { "driver": dataset.driver, - "width": int(dataset.width), - "height": int(dataset.height), - "band_count": int(dataset.count), + "width": width, + "height": height, + "band_count": band_count, "crs": str(dataset.crs) if dataset.crs else None, "bounds": list(dataset.bounds), "resolution": list(dataset.res), @@ -45,6 +89,8 @@ def extract_raster_metadata(path: str) -> dict: "nodata": nodata_value, "transform": list(transform) if transform is not None else None, } + except AppError: + raise except Exception as exc: if isinstance(exc, errors.RasterioIOError): raise AppError(code="INVALID_RASTER", message="Uploaded raster file is invalid", status_code=400) from exc diff --git a/backend/app/services/yolo_preflight_service.py b/backend/app/services/yolo_preflight_service.py index 5584ac02..3eb9470b 100644 --- a/backend/app/services/yolo_preflight_service.py +++ b/backend/app/services/yolo_preflight_service.py @@ -23,6 +23,8 @@ class YoloPreflightService: assume_dependencies: bool = False, check_model_load: bool = False, model_asset_id: str | None = None, + db: Any | None = None, + allow_offline_model_load: bool = False, ) -> dict[str, Any]: resolved_settings = settings or get_settings() selected_asset = None @@ -126,6 +128,21 @@ class YoloPreflightService: if check_model_load: try: + if db is not None: + RuntimeModelProvenanceService.validate_for_production_runtime( + db=db, + model_path=model_path, + model_id=resolved_settings.yolo_model_id, + task_type="object_detection", + expected_model_version=resolved_settings.yolo_model_version, + allowed_frameworks=("ultralytics/pytorch", "ultralytics", "pytorch"), + ) + elif not allow_offline_model_load: + raise AppError( + code="MODEL_PROVENANCE_DATABASE_REQUIRED", + message="Model compatibility loading requires production provenance or an explicit offline operator command.", + status_code=409, + ) yolo_adapter_class(resolved_settings).load_model(model_path) except AppError as exc: result["status"] = "model_load_failed" diff --git a/backend/requirements-ai-linux.lock b/backend/requirements-ai-linux.lock new file mode 100644 index 00000000..5a0b0f76 --- /dev/null +++ b/backend/requirements-ai-linux.lock @@ -0,0 +1,59 @@ +# Linux x86_64 / CPython 3.11 AI runtime lock. +# +# Resolved on Linux for the production CUDA 12.8 image. Every artifact is +# pinned by version and SHA-256 so installation fails closed on index drift. +certifi==2026.7.22 --hash=sha256:62f22742b58a1a33014a2b6b706588a8d7e2a88ae7bd1a6ebe8c992928483775 +charset-normalizer==3.5.1 --hash=sha256:c7b742bf31c88566b4bb6335a7f393bb322e580b6bb98df7bd0c25e6e3519ce8 +contourpy==1.3.3 --hash=sha256:51e79c1f7470158e838808d4a996fa9bac72c498e93d8ebe5119bc1e6becb0db +cuda-bindings==12.9.7 --hash=sha256:c6496a88d84b1209d6651b0370c19c26319e157c22f6d018bf9a358cd8049041 +cuda-pathfinder==1.8.0 --hash=sha256:c44e574dc997fae2814721d1ae97d0fd6db76db82decbe9b753bf75de53f515e +cuda-toolkit==12.8.1 --hash=sha256:adc7906af4ecbf9a352f9dca5734eceb21daec281ccfcf5675e1d2f724fc2cba +cycler==0.12.1 --hash=sha256:85cef7cff222d8644161529808465972e51340599459b8ac3ccbac5a854e0d30 +filelock==3.32.5 --hash=sha256:142cd9fa77a872c5e78c62329a0d15278fadc686eb89e760017968961a4fd6b2 +fonttools==4.64.0 --hash=sha256:ff7aff4637fbf71394df139c63ccfe08a47aa4252d2f91224ddb3335c716c925 +fsspec==2026.7.0 --hash=sha256:b57ddbafedfaef7018c1ecab32aa200a9d7ca26b77965f64e48b70061249d279 +idna==3.19 --hash=sha256:815e7be7a7806d54abb586dc943addc79e8b2ee16915059658cbeff4b1b43bf4 +jinja2==3.1.6 --hash=sha256:85ece4451f492d0c13c5dd7c13a64681a86afae63a5f347908daf103ce6d2f67 +kiwisolver==1.5.1 --hash=sha256:95a02752aa032eef4aed01cda6d9b687c669bd0396bf4519eef8bba22a286720 +markupsafe==3.0.3 --hash=sha256:0bf2a864d67e76e5c9a34dc26ec616a66b9888e25e7b9460e1c76d3293bd9dbf +matplotlib==3.11.1 --hash=sha256:aee55e9041211bf84302ab55ec3965df18dd90ae19f8b58332a7feaf208bfe83 +mpmath==1.3.0 --hash=sha256:a0b2b9fe80bbcd81a6647ff13108738cfb482d481d826cc0e02f5b35e5c88d2c +networkx==3.6.1 --hash=sha256:d47fbf302e7d9cbbb9e2555a0d267983d2aa476bac30e90dfbe5669bd57f3762 +numpy==2.4.6 --hash=sha256:89cd468399cfd2504718f0ba50e410dca55a170b61a02ad92bb18c8a65186e93 +nvidia-cublas-cu12==12.8.4.1 --hash=sha256:8ac4e771d5a348c551b2a426eda6193c19aa630236b418086020df5ba9667142 +nvidia-cuda-cupti-cu12==12.8.90 --hash=sha256:ea0cb07ebda26bb9b29ba82cda34849e73c166c18162d3913575b0c9db9a6182 +nvidia-cuda-nvrtc-cu12==12.8.93 --hash=sha256:a7756528852ef889772a84c6cd89d41dfa74667e24cca16bb31f8f061e3e9994 +nvidia-cuda-runtime-cu12==12.8.90 --hash=sha256:adade8dcbd0edf427b7204d480d6066d33902cab2a4707dcfc48a2d0fd44ab90 +nvidia-cudnn-cu12==9.19.0.56 --hash=sha256:ac6ad90a075bb33a94f2b4cf4622eac13dd4dc65cf6dd9c7572a318516a36625 +nvidia-cufft-cu12==11.3.3.83 --hash=sha256:4d2dd21ec0b88cf61b62e6b43564355e5222e4a3fb394cac0db101f2dd0d4f74 +nvidia-cufile-cu12==1.13.1.3 --hash=sha256:1d069003be650e131b21c932ec3d8969c1715379251f8d23a1860554b1cb24fc +nvidia-curand-cu12==10.3.9.90 --hash=sha256:b32331d4f4df5d6eefa0554c565b626c7216f87a06a4f56fab27c3b68a830ec9 +nvidia-cusolver-cu12==11.7.3.90 --hash=sha256:4376c11ad263152bd50ea295c05370360776f8c3427b30991df774f9fb26c450 +nvidia-cusparse-cu12==12.5.8.93 --hash=sha256:1ec05d76bbbd8b61b06a80e1eaf8cf4959c3d4ce8e711b65ebd0443bb0ebb13b +nvidia-cusparselt-cu12==0.7.1 --hash=sha256:f1bb701d6b930d5a7cea44c19ceb973311500847f81b634d802b7b539dc55623 +nvidia-ml-py==13.610.43 --hash=sha256:f13c72698edef492f985cc225f14faafe68ae065a2e407f45bdf6f4b9b43fde8 +nvidia-nccl-cu12==2.28.9 --hash=sha256:485776daa8447da5da39681af455aa3b2c2586ddcf4af8772495e7c532c7e5ab +nvidia-nvjitlink-cu12==12.8.93 --hash=sha256:81ff63371a7ebd6e6451970684f916be2eab07321b73c9d244dc2b4da7f73b88 +nvidia-nvshmem-cu12==3.4.5 --hash=sha256:042f2500f24c021db8a06c5eec2539027d57460e1c1a762055a6554f72c369bd +nvidia-nvtx-cu12==12.8.90 --hash=sha256:5b17e2001cc0d751a5bc2c6ec6d26ad95913324a4adb86788c944f8ce9ba441f +opencv-python==5.0.0.93 --hash=sha256:c8de2dec111122a02e8beb28e16c31904992dfd6186560b142a92c71403c1039 +packaging==26.3 --hash=sha256:d7193f7c8e4e93f444fde0262bf90af30e16fa0ad0ad44cb553c87339b23cd1c +pillow==12.3.0 --hash=sha256:23d27a3e0307ec2244cc51e7287b919aa68d097504ebe19df4e76a98a3eea5bd +polars==1.44.1 --hash=sha256:1fa62fc1c88fba77a68b28291b5aabdd69e5f38b34e59721a064ae3169b59bb5 +polars-runtime-32==1.44.1 --hash=sha256:eea4283be8e60822d890dbda20588fe59b4172b508bd5ebf3471e531ca9f50d7 +psutil==7.2.2 --hash=sha256:076a2d2f923fd4821644f5ba89f059523da90dc9014e85f8e45a5774ca5bc6f9 +pyparsing==3.3.2 --hash=sha256:850ba148bd908d7e2411587e247a1e4f0327839c40e2e5e6d05a007ecc69911d +python-dateutil==2.9.0.post0 --hash=sha256:a8b2bc7bffae282281c8140a97d3aa9c14da0b136dfe83f850eea9a5f7470427 +pyyaml==6.0.3 --hash=sha256:b8bb0864c5a28024fac8a632c443c87c5aa6f215c0b126c449ae1a150412f31d +requests==2.34.2 --hash=sha256:2a0d60c172f83ac6ab31e4554906c0f3b3588d37b5cb939b1c061f4907e278e0 +setuptools==81.0.0 --hash=sha256:fdd925d5c5d9f62e4b74b30d6dd7828ce236fd6ed998a08d81de62ce5a6310d6 +six==1.17.0 --hash=sha256:4721f391ed90541fddacab5acf947aa0d3dc7d27b2e1e8eda2be8970586c3274 +sympy==1.14.0 --hash=sha256:e091cc3e99d2141a0ba2847328f5479b05d94a6635cb96148ccb3f34671bd8f5 +torch==2.11.0+cu128 --hash=sha256:c9a7ca4c74fae10a58e6175b4b2cea953f9322bb6562bbf339ad6a05f52190ad +torchvision==0.26.0+cu128 --hash=sha256:8f2629d056570c929b0a1d5473d9cb0320b90bda1764bda353553a72cc6b2069 +triton==3.6.0 --hash=sha256:e021e87e8f266c6f87bf379b669c43c2800aac6247bdf5d518cb553e3c403c00 +typing-extensions==4.16.0 --hash=sha256:481caa481374e813c1b176ada14e97f1f67a4539ce9cfeb3f350d78d6370c2e8 +ultralytics==8.4.99 --hash=sha256:477727b3f07de28f1f34888c7661b7cc3b6bf3e55b9675d7b3eadfa6f4747385 +ultralytics-thop==2.1.6 --hash=sha256:23f7b8ad124fa3432c1a7de9279102c4fdda699216032a7dff49f87ec3d1a3af +urllib3==2.7.0 --hash=sha256:9fb4c81ebbb1ce9531cce37674bbc6f1360472bc18ca9a553ede278ef7276897 +wheel==0.47.0 --hash=sha256:212281cab4dff978f6cedd499cd893e1f620791ca6ff7107cf270781e587eced diff --git a/backend/requirements-build-tools.lock b/backend/requirements-build-tools.lock new file mode 100644 index 00000000..6372c42b --- /dev/null +++ b/backend/requirements-build-tools.lock @@ -0,0 +1,4 @@ +# Build tooling used after the runtime dependency installation. +packaging==26.3 --hash=sha256:d7193f7c8e4e93f444fde0262bf90af30e16fa0ad0ad44cb553c87339b23cd1c +setuptools==81.0.0 --hash=sha256:fdd925d5c5d9f62e4b74b30d6dd7828ce236fd6ed998a08d81de62ce5a6310d6 +wheel==0.47.0 --hash=sha256:212281cab4dff978f6cedd499cd893e1f620791ca6ff7107cf270781e587eced diff --git a/backend/scripts/yolo_preflight.py b/backend/scripts/yolo_preflight.py index a13d36d7..6f7e9958 100644 --- a/backend/scripts/yolo_preflight.py +++ b/backend/scripts/yolo_preflight.py @@ -50,6 +50,7 @@ def main() -> int: tile_manifest_path=args.tile_manifest_path, assume_dependencies=args.assume_dependencies, check_model_load=args.check_model_load, + allow_offline_model_load=True, ) if args.json: diff --git a/backend/tests/test_accuracy_phase4_evaluation.py b/backend/tests/test_accuracy_phase4_evaluation.py index fb578ce8..bc8127b8 100644 --- a/backend/tests/test_accuracy_phase4_evaluation.py +++ b/backend/tests/test_accuracy_phase4_evaluation.py @@ -1182,7 +1182,7 @@ def test_one_workflow_is_byte_reproducible_complete_and_fail_closed( ) assert input_manifest["product_baseline"]["validation_status"] == "not_evaluable" assert input_manifest["product_baseline"]["artifacts"] == [] - assert "docs/accuracy-program/status.json" not in { + assert "fixtures/accuracy/readiness/status.json" not in { item["path"] for item in input_manifest["inputs"] } assert input_manifest["readiness_snapshot"]["source_paths"][ @@ -1199,11 +1199,11 @@ def test_one_workflow_is_byte_reproducible_complete_and_fail_closed( def test_readiness_snapshot_ignores_phase4_bookkeeping_but_binds_active_model( tmp_path: Path, ) -> None: - status_path = tmp_path / "docs/accuracy-program/status.json" - scan_path = tmp_path / "artifacts/evidence/accuracy/P3/full-scan-manifest.json" - leakage_path = tmp_path / "artifacts/evidence/accuracy/P3/leakage-report.json" + status_path = tmp_path / "fixtures/accuracy/readiness/status.json" + scan_path = tmp_path / "fixtures/accuracy/readiness/full-scan-manifest.json" + leakage_path = tmp_path / "fixtures/accuracy/readiness/leakage-report.json" status_path.parent.mkdir(parents=True) - scan_path.parent.mkdir(parents=True) + scan_path.parent.mkdir(parents=True, exist_ok=True) status = { "generated_at": "2026-08-02T00:00:00+02:00", "documents": ["old.md"], diff --git a/backend/tests/test_auth.py b/backend/tests/test_auth.py index a0d41d7a..58e61c19 100644 --- a/backend/tests/test_auth.py +++ b/backend/tests/test_auth.py @@ -7,6 +7,7 @@ from uuid import UUID, uuid4 from fastapi.testclient import TestClient from app.core.config import get_settings +from app.core.public_demo import PUBLIC_DEMO_PROJECT_ID from app.db.session import get_db from app.main import create_app from app.schemas.demo import DemoWorkflowResponse @@ -172,7 +173,7 @@ def test_operator_login_can_require_https(monkeypatch) -> None: def test_guest_login_exposes_models_but_rejects_management_and_cross_project_requests(monkeypatch) -> None: - project_id = UUID("00000000-0000-0000-0000-000000000123") + project_id = PUBLIC_DEMO_PROJECT_ID demo = DemoWorkflowResponse( project_id=project_id, area_id=UUID("00000000-0000-0000-0000-000000000124"), @@ -252,7 +253,7 @@ def test_guest_login_exposes_models_but_rejects_management_and_cross_project_req def test_guest_change_detection_binds_both_datasets_to_signed_demo_project(monkeypatch) -> None: - project_id = UUID("00000000-0000-0000-0000-000000000123") + project_id = PUBLIC_DEMO_PROJECT_ID other_project_id = UUID("00000000-0000-0000-0000-000000000999") source_dataset_id = UUID("00000000-0000-0000-0000-000000000125") target_dataset_id = UUID("00000000-0000-0000-0000-000000000126") @@ -342,7 +343,7 @@ def test_guest_change_detection_binds_both_datasets_to_signed_demo_project(monke def test_guest_can_prepare_tiles_and_queue_project_scoped_detection(monkeypatch) -> None: - project_id = UUID("00000000-0000-0000-0000-000000000123") + project_id = PUBLIC_DEMO_PROJECT_ID raster_dataset_id = UUID("00000000-0000-0000-0000-000000000127") manifest_path = "/app/storage/tiles/demo/manifest.json" demo = DemoWorkflowResponse( diff --git a/backend/tests/test_docker_runtime_config.py b/backend/tests/test_docker_runtime_config.py index ffa9479f..3be6c501 100644 --- a/backend/tests/test_docker_runtime_config.py +++ b/backend/tests/test_docker_runtime_config.py @@ -48,11 +48,14 @@ def test_all_in_one_dockerfile_can_opt_into_ai_dependencies_without_base_install assert "ARG GEOINTEL_INSTALL_AI=false" in dockerfile assert "COPY backend/pyproject.toml /app/" in dockerfile assert "COPY backend/requirements-runtime.lock /app/" in dockerfile + assert "COPY backend/requirements-ai-linux.lock /app/" in dockerfile + assert "COPY backend/requirements-build-tools.lock /app/" in dockerfile assert "COPY backend/pyproject.toml backend/README.md /app/" not in dockerfile assert "GeoIntel backend package metadata" in dockerfile assert "--require-hashes -r requirements-runtime.lock" in dockerfile - assert "ARG GEOINTEL_ULTRALYTICS_VERSION=" in dockerfile - assert '"ultralytics==$GEOINTEL_ULTRALYTICS_VERSION"' in dockerfile + assert "--require-hashes" in dockerfile + assert "-r requirements-ai-linux.lock" in dockerfile + assert "-r requirements-build-tools.lock" in dockerfile assert "python scripts/gis_import_smoke.py" in dockerfile assert "yolo_preflight.py" in dockerfile assert "libxcb1" in dockerfile @@ -472,9 +475,10 @@ def test_all_in_one_dockerfile_caches_dependencies_and_pins_driver_compatible_cu assert metadata_copy_index < placeholder_readme_index < dependency_install_index < backend_copy_index < smoke_index assert "GEOINTEL_TORCH_INDEX_URL=https://download.pytorch.org/whl/cu128" in dockerfile - assert "GEOINTEL_TORCH_VERSION=2.11.0" in dockerfile - assert "GEOINTEL_TORCHVISION_VERSION=0.26.0" in dockerfile - assert '--index-url "$GEOINTEL_TORCH_INDEX_URL"' in dockerfile + assert '--extra-index-url "$GEOINTEL_TORCH_INDEX_URL"' in dockerfile + ai_lock = (ROOT / "backend" / "requirements-ai-linux.lock").read_text(encoding="utf-8") + assert "torch==2.11.0+cu128 --hash=sha256:" in ai_lock + assert "torchvision==0.26.0+cu128 --hash=sha256:" in ai_lock def test_unraid_deploy_passes_ai_build_arg_and_yolo_runtime_env() -> None: diff --git a/backend/tests/test_guest_resource_scope.py b/backend/tests/test_guest_resource_scope.py index 3a719e34..7cc85cca 100644 --- a/backend/tests/test_guest_resource_scope.py +++ b/backend/tests/test_guest_resource_scope.py @@ -7,6 +7,7 @@ import pytest from fastapi.testclient import TestClient from app.core.config import get_settings +from app.core.public_demo import PUBLIC_DEMO_PROJECT_ID from app.db.session import get_db from app.main import create_app from app.models import AnalysisRun, Dataset, Detection, Export, Job, Segmentation @@ -21,7 +22,7 @@ from app.services.detection_service import DetectionService from app.services.segmentation_service import SegmentationService -GUEST_PROJECT_ID = UUID("00000000-0000-0000-0000-000000000123") +GUEST_PROJECT_ID = PUBLIC_DEMO_PROJECT_ID OTHER_PROJECT_ID = UUID("00000000-0000-0000-0000-000000000999") DATASET_ID = UUID("00000000-0000-0000-0000-000000000201") DETECTION_RUN_ID = UUID("00000000-0000-0000-0000-000000000202") diff --git a/backend/tests/test_rc6_supply_chain.py b/backend/tests/test_rc6_supply_chain.py index 09df93a2..393ef1b1 100644 --- a/backend/tests/test_rc6_supply_chain.py +++ b/backend/tests/test_rc6_supply_chain.py @@ -175,11 +175,14 @@ def test_release_image_uses_locked_non_ai_dependencies_and_npm_ci() -> None: assert "RUN npm ci" in dockerfile assert "COPY backend/requirements-runtime.lock /app/" in dockerfile + assert "COPY backend/requirements-ai-linux.lock /app/" in dockerfile + assert "COPY backend/requirements-build-tools.lock /app/" in dockerfile assert "pip install --no-cache-dir --require-hashes -r requirements-runtime.lock" in dockerfile - assert "ARG GEOINTEL_ULTRALYTICS_VERSION=8.4.99" in dockerfile - assert '"ultralytics==$GEOINTEL_ULTRALYTICS_VERSION"' in dockerfile - assert "ARG GEOINTEL_SETUPTOOLS_VERSION=81.0.0" in dockerfile - assert "ARG GEOINTEL_WHEEL_VERSION=0.47.0" in dockerfile + assert "-r requirements-ai-linux.lock" in dockerfile + assert "-r requirements-build-tools.lock" in dockerfile + assert "--require-hashes" in dockerfile + assert "ultralytics==8.4.99 --hash=sha256:" in read("backend/requirements-ai-linux.lock") + assert "torch==2.11.0+cu128 --hash=sha256:" in read("backend/requirements-ai-linux.lock") assert "COPY deploy/unraid/gosu-setpriv /usr/local/bin/gosu" in dockerfile assert "&& pip check" in dockerfile diff --git a/backend/tests/test_sprint137_browser_calibration_summary_evidence_script.py b/backend/tests/test_sprint137_browser_calibration_summary_evidence_script.py index 1233eae6..0ce1d214 100644 --- a/backend/tests/test_sprint137_browser_calibration_summary_evidence_script.py +++ b/backend/tests/test_sprint137_browser_calibration_summary_evidence_script.py @@ -21,5 +21,5 @@ def test_evidence_bundle_script_accepts_browser_calibration_summary_export() -> assert "root_project_id = summary.get(\"project_id\")" in script assert "quality_check_ids" in script assert "Browser Detection Lab calibration summary" in readme - assert "bash scripts/export_detection_calibration_evidence.sh http://192.168.123.45:1202 ./detection-calibration-summary.json" in readme + assert "bash scripts/export_detection_calibration_evidence.sh http://192.0.2.10:1202 ./detection-calibration-summary.json" in readme assert "[x] Allow the evidence bundle script to consume Detection Lab calibration summary exports" in todo diff --git a/backend/tests/test_sprint13_yolo_preflight.py b/backend/tests/test_sprint13_yolo_preflight.py index 18c15c75..d7b16d39 100644 --- a/backend/tests/test_sprint13_yolo_preflight.py +++ b/backend/tests/test_sprint13_yolo_preflight.py @@ -206,6 +206,7 @@ def test_yolo_preflight_can_explicitly_smoke_load_local_model(tmp_path: Path) -> tile_manifest_path=str(manifest_path), yolo_adapter_class=AvailableAdapter, check_model_load=True, + allow_offline_model_load=True, ) assert result["status"] == "ready" @@ -231,6 +232,7 @@ def test_yolo_preflight_reports_explicit_model_load_failure(tmp_path: Path) -> N tile_manifest_path=str(_manifest(tmp_path)), yolo_adapter_class=FailingLoadAdapter, check_model_load=True, + allow_offline_model_load=True, ) assert result["status"] == "model_load_failed" diff --git a/backend/tests/test_sprint15_demo_workflow.py b/backend/tests/test_sprint15_demo_workflow.py index f4bf7ce5..005cdaa8 100644 --- a/backend/tests/test_sprint15_demo_workflow.py +++ b/backend/tests/test_sprint15_demo_workflow.py @@ -74,13 +74,13 @@ def test_demo_workflow_service_supports_container_fixture_mount() -> None: assert "_quality_check_matches_expected" in service -def test_demo_workflow_prefers_complete_existing_demo_project() -> None: +def test_demo_workflow_uses_reserved_server_owned_project_identity() -> None: service = (DemoWorkflowService._repo_root() / "backend" / "app" / "services" / "demo_workflow_service.py").read_text(encoding="utf-8") - assert "_has_complete_demo_state" in service - assert "order_by(Project.created_at.asc())" in service - assert "if DemoWorkflowService._has_complete_demo_state(db, project.id):" in service - assert "return projects[0] if projects else None" in service + assert "db.get(Project, DemoWorkflowService.PROJECT_ID)" in service + assert "PUBLIC_DEMO_PROJECT_MARKER" in service + assert "PUBLIC_DEMO_IDENTITY_CONFLICT" in service + assert "id=DemoWorkflowService.PROJECT_ID" in service def test_explicit_demo_seed_reactivates_an_archived_fixture_project() -> None: diff --git a/backend/tests/test_sprint31_unraid_template.py b/backend/tests/test_sprint31_unraid_template.py index 931da386..bd330de2 100644 --- a/backend/tests/test_sprint31_unraid_template.py +++ b/backend/tests/test_sprint31_unraid_template.py @@ -100,7 +100,7 @@ def test_unraid_all_in_one_runtime_starts_embedded_postgis_backend_and_nginx() - nginx_config = (ROOT / "deploy" / "unraid" / "nginx-all-in-one.conf").read_text(encoding="utf-8") dockerignore = (ROOT / ".dockerignore").read_text(encoding="utf-8") - assert "FROM postgres:16-bookworm AS runtime" in dockerfile + assert "FROM postgres:16-bookworm@sha256:" in dockerfile assert "postgresql-16-postgis-3" in dockerfile assert "postgresql-16-postgis-3-scripts" in dockerfile assert "ln -sf /usr/bin/python3.11 /usr/local/bin/python3" in dockerfile diff --git a/backend/tests/test_sprint66_live_workspace_smoke_polish.py b/backend/tests/test_sprint66_live_workspace_smoke_polish.py index 97a5bdb3..dfb08e35 100644 --- a/backend/tests/test_sprint66_live_workspace_smoke_polish.py +++ b/backend/tests/test_sprint66_live_workspace_smoke_polish.py @@ -13,9 +13,9 @@ def test_export_handoff_cards_use_width_aware_grid() -> None: assert "repeat(auto-fit, minmax(7.5rem, 1fr))" in css -def test_live_workspace_smoke_artifacts_are_documented() -> None: - execution_log = (ROOT / "docs" / "CODEX_EXECUTION_LOG.md").read_text(encoding="utf-8") +def test_public_readme_documents_desktop_and_mobile_workspace() -> None: + readme = (ROOT / "README.md").read_text(encoding="utf-8") - assert "Sprint 66 Live workspace smoke polish" in execution_log - assert "desktop and mobile screenshots" in execution_log - assert "no console warnings/errors" in execution_log + assert "geointel-workbench-wide.png" in readme + assert "geointel-workbench-mobile.png" in readme + assert "Mobiele werkruimte" in readme diff --git a/deploy/unraid/Dockerfile.all-in-one b/deploy/unraid/Dockerfile.all-in-one index 97c55826..474845d9 100644 --- a/deploy/unraid/Dockerfile.all-in-one +++ b/deploy/unraid/Dockerfile.all-in-one @@ -1,4 +1,4 @@ -FROM node:20-alpine AS frontend-build +FROM node:20-alpine@sha256:fb4cd12c85ee03686f6af5362a0b0d56d50c58a04632e6c0fb8363f609372293 AS frontend-build WORKDIR /frontend COPY frontend/package.json frontend/package-lock.json ./ @@ -6,15 +6,10 @@ RUN npm ci COPY frontend/ ./ RUN npm run build -FROM postgres:16-bookworm AS runtime +FROM postgres:16-bookworm@sha256:bb3e1a57e5407e0a5280b4211980a5e537f4abd234a87014ac979849a78dd825 AS runtime ARG GEOINTEL_INSTALL_AI=false ARG GEOINTEL_TORCH_INDEX_URL=https://download.pytorch.org/whl/cu128 -ARG GEOINTEL_TORCH_VERSION=2.11.0 -ARG GEOINTEL_TORCHVISION_VERSION=0.26.0 -ARG GEOINTEL_ULTRALYTICS_VERSION=8.4.99 -ARG GEOINTEL_SETUPTOOLS_VERSION=81.0.0 -ARG GEOINTEL_WHEEL_VERSION=0.47.0 ENV GEOINTEL_ENV=production \ GEOINTEL_API_PREFIX=/api/v1 \ @@ -53,22 +48,20 @@ WORKDIR /app COPY deploy/unraid/gosu-setpriv /usr/local/bin/gosu COPY backend/pyproject.toml /app/ COPY backend/requirements-runtime.lock /app/ +COPY backend/requirements-ai-linux.lock /app/ +COPY backend/requirements-build-tools.lock /app/ COPY backend/app/__init__.py /app/app/__init__.py RUN printf '# GeoIntel backend package metadata\n' > /app/README.md \ && /usr/bin/python3.11 -m venv /opt/geointel/venv \ && pip install --no-cache-dir --require-hashes -r requirements-runtime.lock \ && if [ "$GEOINTEL_INSTALL_AI" = "true" ]; then \ - pip install --no-cache-dir \ - --index-url "$GEOINTEL_TORCH_INDEX_URL" \ - "torch==$GEOINTEL_TORCH_VERSION" \ - "torchvision==$GEOINTEL_TORCHVISION_VERSION" \ - && pip install --no-cache-dir \ - "ultralytics==$GEOINTEL_ULTRALYTICS_VERSION"; \ + pip install --no-cache-dir --require-hashes \ + --index-url https://pypi.org/simple \ + --extra-index-url "$GEOINTEL_TORCH_INDEX_URL" \ + -r requirements-ai-linux.lock; \ fi \ - && pip install --no-cache-dir \ - "setuptools==$GEOINTEL_SETUPTOOLS_VERSION" \ - "wheel==$GEOINTEL_WHEEL_VERSION" \ + && pip install --no-cache-dir --require-hashes -r requirements-build-tools.lock \ && pip check COPY backend/ /app/ diff --git a/deploy/unraid/MANUAL_DEPLOY.md b/deploy/unraid/MANUAL_DEPLOY.md index b6231a4c..472d7085 100644 --- a/deploy/unraid/MANUAL_DEPLOY.md +++ b/deploy/unraid/MANUAL_DEPLOY.md @@ -178,7 +178,7 @@ docker logs --tail 200 geointel De vroegere geneste mirror `C:\Projects\geointel\geointel` is geretireerd. De immutable Git-herkomst, niet-getrackte recoverybestanden en verificatiegrens -staan in `docs/accuracy-program/13-nested-mirror-retirement.md`. Behandel die +staan in de private release-evidence buiten Git. Behandel die evidence als herstelreferentie; deze handleiding vraagt geen extra kopieer- of opruimactie. diff --git a/docs/ACCURACY.md b/docs/ACCURACY.md new file mode 100644 index 00000000..08fd6efc --- /dev/null +++ b/docs/ACCURACY.md @@ -0,0 +1,34 @@ +# Accuracy, modelgrenzen en bewijs + +GeoIntel behandelt AI-resultaten als voorstellen die aan brondata, +modelidentiteit, ruimtelijke context en kwaliteitsmetingen gekoppeld blijven. +Een model wordt niet automatisch gedownload of geactiveerd. + +## Wat gebruikers mogen verwachten + +- GIS-bewerkingen en AI-inferentie bewaren hun invoer- en uitvoerprovenance. +- Referentie- en kandidaatdata blijven afzonderlijk herkenbaar. +- Precision, recall, F1, IoU, false positives en false negatives zijn + inspecteerbaar waar een geschikte referentieset beschikbaar is. +- Een groen technisch proces is geen garantie dat een model voor elk gebied, + seizoen, sensortype of objecttype betrouwbaar is. +- Modeloutput vraagt menselijke of taakgerichte kwaliteitscontrole vóór gebruik + in beslissingen met operationele, juridische of veiligheidsimpact. + +## Releasegrens + +Modelpromotie vereist een reproduceerbaar benchmarkmanifest, een exacte +model-SHA-256, gescheiden ontwikkel- en evaluatiesets, leakagecontroles en de +toepasselijke releasegates. Ontbrekend bewijs faalt gesloten. + +## Publieke versus lokale evidence + +De repository bevat alleen broncode, methodedocumentatie en expliciet publieke +fixtures. Runtime-databases, exacte operationele locaties, modelgewichten, +contact sheets, trainingsdata en gegenereerde evaluatierapporten worden lokaal +of in gecontroleerde artefactopslag bewaard. De scripts onder `scripts/` kunnen +deze evidence opnieuw genereren zonder ze aan Git toe te voegen. + +Zie ook [SECURITY.md](../SECURITY.md), +[docs/KNOWN_LIMITATIONS.md](KNOWN_LIMITATIONS.md) en +[docs/DEFINITION_OF_DONE.md](DEFINITION_OF_DONE.md). diff --git a/docs/AI_PIPELINES.md b/docs/AI_PIPELINES.md index 7ab88889..f6d6c8f6 100644 --- a/docs/AI_PIPELINES.md +++ b/docs/AI_PIPELINES.md @@ -215,7 +215,7 @@ fail-closed validation as the false-positive workflow. It requires an exact one-to-one set of reviewed reference ids and emits only explicit `confirmed_model_false_negative` geometries. `--require-complete` rejects any remaining `unreviewed` row. The July 2026 96-card review is recorded in -`docs/reviews/2026-07-15-small-building-model-review.md`; it yielded no novel, +the controlled model-review evidence outside Git; it yielded no novel, leakage-free labels and therefore did not trigger model training. ### Local model asset catalog diff --git a/docs/CODEX_EXECUTION_LOG.md b/docs/CODEX_EXECUTION_LOG.md index 7b3eccaf..89a9657b 100644 --- a/docs/CODEX_EXECUTION_LOG.md +++ b/docs/CODEX_EXECUTION_LOG.md @@ -1,13052 +1,42 @@ -## 2026-08-31 - Voorbereiding publieke repository - -### Opgeleverd - -- De actuele `origin/main` is fast-forward geïntegreerd met de volledige - `chatgpt/release-hygiene-20260830`-reeks op - `codex/public-release-readiness`; de private Tower-handoffcommit en de - ongerelateerde DockDeck/Stitch-geschiedenis zijn niet gemerged. -- Alle resterende getrackte `.codex-input`, root-`data` SQLite/WAL/SHM, - `.playwright-mcp` en lokale `.mcp.json`-artefacten zijn uit de publicatieboom - verwijderd en blijvend genegeerd. -- Operator-specifieke IP-, domein- en SSH-sleutelvoorbeelden zijn vervangen - door documentatievoorbeelden; een nieuwe repositoryhygiënecheck blokkeert - regressies in de releasegate. -- De Unraid-verpakking schakelt operatorauthenticatie en HTTPS-login fail-closed - in, gasttoegang staat standaard uit, developmentpoorten binden standaard aan - loopback en login-throttling herkent alleen forwarding van vertrouwde - containerproxies. -- De checkpoint-inspector gebruikt PyTorch `weights_only=True` en deserialiseert - geen willekeurige legacy objecten meer. - -### Verificatie - -- De volledige Git-geschiedenis is met Gitleaks onderzocht: 22 generieke - sleutelnaam-matches waren domeinidentificatoren en geen credentials. -- `pip-audit` en `npm audit` vonden geen bekende dependencykwetsbaarheden. -- De gerichte auth-, runtimeconfig-, Unraid-template- en - repositoryhygiënesuite slaagt met 58 tests; Ruff, Python-compilatie, - repositoryhygiëne, beide Compose-configuraties, gewijzigde shellsyntax en - `git diff --check` slagen eveneens. - -### Publicatiestrategie - -- De eigenaar koos voor de veiligste publicatieroute: een nieuwe schone - rootgeschiedenis op dezelfde Gitea-repository. Voor de rewrite wordt buiten - de repository een lokale herstelbundle gemaakt van alle oude refs. -- Apache-2.0 is toegevoegd als rootlicentie. De patentgrant, duidelijke - hergebruikvoorwaarden en brede ecosysteemcompatibiliteit passen bij de - software-, GIS- en AI-integraties van GeoIntel. -- De schone rootcommit vervangt remote `main`; alle andere remote branches en - tags worden verwijderd zodat oude private blobs niet via publieke refs - bereikbaar blijven. - -## 2026-08-29 - Gitea release-gateherstel - -### Opgeleverd - -- De gepinde TruffleHog-scanner draait rechtstreeks als filesystemscan en is - niet langer afhankelijk van de incompatibele Docker-actionwrapper die - `file:///tmp` probeerde te klonen. -- De frontend-lock wordt via een npm-override op de gepatchte Nano ID 3.3.18 - gehouden; de HIGH dependencybevinding is daarmee verwijderd. -- Syft krijgt de expliciete lokale Docker-imagesource. Daardoor scant de SBOM- - gate het zojuist gebouwde image via de gemounte Docker-socket in plaats van - de tag als een niet-bestaand containerbestandspad te interpreteren. -- De functioneel identieke Gitea- en GitHub-workflows blijven synchroon. - -### Verificatie - -- Pending tijdens implementatie: npm lock/audit, readiness, shellsyntax en de - drie externe releasejobs. - -### Open en beperkingen - -- Geen product-, API-, GIS-, model- of deploymentscope is gewijzigd. - -## 2026-08-21 - Gesynchroniseerde tweeschermwerkruimte - -### Opgeleverd - -- Een nieuwe knop in de werkbalk opent een afzonderlijke analyseconsole voor - een tweede monitor. -- De bestaande resultatenlade wordt via een React-portal verplaatst. Kaart en - console delen daardoor exact dezelfde selectie-, analyse- en QA-state zonder - dubbele API-aanvragen. -- Het venster onthoudt positie en afmetingen, meldt popupblokkering en valt bij - sluiten zonder dataverlies terug naar de gewone éénschermlade. -- Operator en demo krijgen dezelfde functie; bestaande rechten wijzigen niet. - -### Verificatie - -- TypeScript typecheck, gerichte Vitest-regressies en productiebuild slagen. -- De live gastwerkstroom is lokaal tegen de Tower-backend doorlopen: tweede - scherm openen, gebied selecteren, thema analyseren en dezelfde resultaten na - sluiten terugvinden in de hoofdinterface. - -## 2026-08-10 - V74 root-cause remediation en authority-first uitvoer - -### Opgeleverd - -- De volledige V72 failure gallery gerenderd en AI-assisted geïnspecteerd; - terugkerende foutpositieven omvatten spoorinfrastructuur, voertuigen, bomen - en schaduwen. -- Een hard-negative proposal-filter en twee rehearsal-kandidaten getraind op - de Tower RTX 4080 SUPER en alle drie afgewezen op de onafhankelijke V72-set. -- De experimentele trainer bindt nu expliciet AdamW, zodat Ultralytics niet - stilzwijgend de gevraagde learning rate vervangt via `optimizer=auto`. -- De kaartwerkstroom laadt het GRB-QA-bewijs automatisch en onderscheidt - GRB-bevestigde, AI-only en door AI gemiste gebouwobjecten. - -### Grens - -- Het productiecheckpoint bleef ongewijzigd. Er is geen landelijke of - 100%-accuratesseclaim gedaan en de visuele review blijft AI-assisted. -- Evidence: `artifacts/evidence/accuracy/model-training/20260810-v74-root-cause/`. - -## 2026-07-29 - V31 closed-loop iteration 3 assessment and semantic correction - -- Iteration 3 stopped deterministically after epoch 21 with epoch 3 retained as - the best checkpoint. Calibration selected threshold `0.10` and produced - aggregate precision `0.460359`, recall `0.737302` and F1 `0.566811`. -- The candidate remained rejected: Flanders measured precision `0.340852`, - recall `0.403960` and F1 `0.369733`; Wallonia measured precision `0.456198`, - recall `0.786742` and F1 `0.577518`. Brussels passed its regional minimums. - Protected test and background-test evidence remained unopened. -- Oostende remained the dominant protected calibration failure with precision - `0.082569`, recall `0.391304` and F1 `0.136364`. The next train-only sampling - manifest therefore targets Flemish coastal/port/dunes, industrial/rail and - ribbon/farmland/forest contexts, plus Walloon rural/architecture hard-negative - families. It contains 3,600 entries (Flanders 2,340, Wallonia 972, Brussels - 288), removes 1,278 excess repeats to retain the 65% regional cap, and records - zero protected samples in training. -- Iteration 4 started automatically on CUDA with the iteration 3 candidate and - exact failure-driven train-list SHA-256 - `66f510ee563ae6ef8499c018cc1b12b175497dd1180b9c4eb73e9f62fb7d75fd`. - -## 2026-07-29 - Context-aware Belgian training correction - -- Audited the active closed-loop calibration trend and confirmed that the - remaining Flemish failure cannot be solved by confidence-threshold selection. -- Extended failure-driven sampling with region-plus-context weighting from - per-AOI calibration evidence. Protected calibration, test, background-test - and validation tiles remain excluded; manifests now record targeted contexts - and their stronger repeat factors for reproducible follow-up iterations. -- Prepared the next immutable corpus expansion with eighteen spatially - independent train-only AOIs: nine Flemish industrial/ribbon/coastal samples - and nine Walloon dense/rural/architecture or difficult-negative samples. - Added mode-0600 session-token-file support to the official provisioner so - authenticated Tower acquisition does not expose session material in argv. -- Closed a fail-open evidence gap between corpus and tile audits. The training - loop now requires and hashes the train tile-quality report, and refuses - missing counters instead of treating absent invalid/blank-label evidence as - zero. -- Capped failure-driven regional oversampling at 65% after the first v31 - sampling assigned 75.5% of entries to Flanders. The cap retains every unique - tile, removes repeats only and writes pre/post regional counts into the - checksummed sampling evidence. -- Added semantic hard-negative families after the v31 calibration isolated - Oostende coastal/port precision as the dominant Flemish error. Coastal, - industrial, ribbon, rural and regional-architecture failures now target - related train-only negative contexts, with diagnostic repeats preserved - ahead of generic repeats when the regional cap applies. - -## 2026-07-27 - Guest demo and product professionalization - -- Audited the access experience, workbench information density, responsive - layout and accumulated frontend styling; recorded findings in - `docs/PROJECT_PROFESSIONALIZATION_AUDIT_2026-07-27.md`. -- Added configuration-gated guest access with a short signed session, explicit - guest role, demo-project scope, filtered project listing and backend-enforced - read-only/cross-project restrictions. -- Rebuilt the landing and login hierarchy, added **Als gast verkennen**, mapped - authentication failures to user-facing Dutch messages and improved mobile - navigation and accessibility states. -- Reduced the guest workbench to map exploration and existing quality evidence, - added persistent demo context and removed operator-only controls from the - guest surface. -- Added targeted final layout overrides instead of destructively rewriting the - four historical workbench stylesheets without a complete visual-regression - baseline. -- Added Compose, Unraid, DockerMan and runtime validation settings for guest - enablement. A later packaging follow-up changed the default to enabled whenever - operator authentication is active; installations can still opt out explicitly. -- Validation: 6/6 targeted backend auth/guest tests and 2/2 direct frontend - interaction smokes passed; Python compile, complete frontend TypeScript - typecheck, CSS parsing, Compose YAML, Unraid XML, DockerMan shell syntax and - scoped diff-whitespace checks passed. -- Environment boundary: the supplied frontend dependency tree contains only - Windows-native Rollup/esbuild packages. Vitest and Vite therefore could not - start in this Linux review container, and the available package proxy returned - 503 responses/time-outs while fetching Linux replacements. Re-run unit tests - and the production bundle after a clean `npm ci` in the normal Windows or - Linux CI/Docker environment. - -## 2026-07-26 - Complete Belgium PyTorch training roadmap - -- Added `docs/PYTORCH_TRAINING_ROADMAP_BELGIUM.md` as the executable programme board. -- Defined the target model portfolio, national dataset strata, authority bindings, spatially isolated train/validation/calibration/test splits, nine work packages, promotion/rollback gates, GPU scheduling, artefact layout and the evidence-based definition of `fully trained`. -- Kept official GIS measurements outside neural training and made the current critical path explicit: regional orthophoto acquisition, label normalization and a frozen Belgium building corpus precede further full training. - -## 2026-07-26 - PyTorch programme clarification and training hardening - -- Clarified that PyTorch governs trainable imagery models and does not replace authoritative terrain, flood, land-use, road, water or change analyses. -- Audited Tower: CUDA PyTorch runs on the RTX 4080 SUPER; only the building corpus currently has promotion evidence. The active building candidate measures roughly 0.61 mean F1 on the expanded independent portfolio and zero detections on three pure-empty background samples. -- Generalized the tile exporter with explicit canonical class, reference source and reference layer evidence so regional authorities cannot be silently mixed. -- Added fail-closed `TRAIN_REQUIRE_CUDA` behavior and PyTorch/CUDA runtime evidence to training summaries. -- Added `docs/PYTORCH_MODEL_PROGRAM.md` with the task matrix and national training waves. -- Verification: 14 focused exporter/training tests passed. -- Open: nationwide building training cannot honestly start until spatially disjoint, temporally compatible GRB/PICC/URBIS plus orthophoto samples have been materialized and reviewed. - -## 2026-07-19 - GeoIntel 1.0.0 final release closeout - -- Promoted the current clean `main` revision to semantic version `1.0.0` in - `VERSION`, backend/frontend package metadata, health/API examples and the - immutable Docker runtime identity. Historical RC entries remain unchanged. -- Re-ran the final repository release gate after the version promotion: - backend compile/tests, frontend unit tests/typecheck/build, readiness, - Alembic single-head/offline SQL and live-smoke syntax all pass. -- The final Tower image is tied to commit - `04b8373d7ece0f5eb29674507d718f0ea51ed5c4` and passed health, PostGIS - migration, proxy and browser runtime checks. -- Final live browser acceptance selected the Walloon golden area, activated - Waterbodem, analysed the full area and displayed real SPW mDNG metrics: - mean `74.55 m`, measured surface `22.69 ha`, coverage `7.07%`, and explicit - no-depth/no-volume limitations. No unrelated on-demand source acquisition - was triggered. -- Remaining boundaries are deliberate V1 limitations: MDK North Sea - analytical bathymetry remains not configured, water volume requires a - governed surface/datum/uncertainty contract, and YOLO remains human-reviewed. - -## Autonomous RC program for Belgium and the Belgian North Sea (2026-07-17) - -### Post-RC national data federation (2026-07-19) - -- Continued the national federation pass with official history and - bathymetry. Statbel's real 2021 geometry release exposed two documented - packaging differences: the ZIP member omits the repeated `31370` token and - `dt_situation` uses `YYYY/MM/DD`. The preflight now normalizes only those - forms and retains every existing fail-closed content check. -- The corrected Tower fetch-only pass validated national 2021-2024 snapshots, - each with 19,795 retained sector geometries, before any API persistence. -- Downloaded the fixed official SPW Geoportail bathymetry release - (`0a544b42-0b30-4c8e-85e7-38149b99eae0`) to persistent operator evidence. - SHA-256 is - `04122a1c5cecc7b77be025b580995d024545e82d8310e158b4c112f7fa5f8a6e`. - GDAL verified a 456,893 by 179,437 Float32 EPSG:3812 source at 0.5 m, - nodata `-9999`, with mDNG waterbed elevations. -- Added `import_spw_bathymetry.py`, bounded COG persistence, source-specific - coverage resolution, raster selection/image APIs and frontend Waterbodem - integration. The contract exposes bed elevation, measured-cell hectares and - coverage only; current depth, volume and datum conversion remain blocked. -- Added the bathymetry PNG route to the explicit non-envelope API audit set - after the first full gate correctly rejected its untracked binary response. -- The complete repository gate passed 1,052 backend tests, 22 frontend tests, - frontend typecheck/build, one Alembic head and all readiness checks before - live deployment. -- Live browser acceptance exposed an existing orchestration problem: one - selected theme also launched every unrelated not-yet-materialized regional - product. The selection flow still summarizes every persisted theme, but now - acquires only the actively selected on-demand theme so one slow provider - cannot block the requested result. -- Added explicit administrative and maritime themes for persisted NGI/RBINS - reference data and made readiness depend on analyzable themes rather than a - raw Dataset count. -- Generalized the governed Statbel population scripts to the Belgium boundary - and complete municipality inventory while retaining all release-promotion - safety gates. -- Added allowlisted bounded SPW/PICC ArcGIS REST and UrbIS WFS adapters with - source-specific coverage, CRS, identity, paging, geometry, licence, - provenance and metric contracts. Output still enters PostGIS only through - `DatasetService.import_vector_bytes`. -- Made the frontend resolve actual coverage zones before choosing GRB, - SPW/PICC or UrbIS and retain separate source results for mixed-zone - selections. -- Added SPW/UrbIS runtime controls to both Compose variants and the editable - Unraid/Dockerman deployment path. -- Rechecked MDK bathymetry. Strict hostname validation still fails because the - configured official hostname presents a `*.l27powered.eu` certificate, so - acquisition remains truthfully disabled. -- Live national Statbel staging exposed and fixed a release-review blocker: - `catalog_checked_at` was incorrectly compared as publication identity. - Reviews now tolerate a later probe timestamp while still blocking any - identifier, release URL/version or catalog content-hash change. -- Live coverage verification then exposed a cross-theme materialization leak: - the Statbel population Dataset also appeared under `admin`. The coverage - registry now enforces each source's `operational_themes`, leaving NGI as the - administrative authority and Statbel as population evidence only. -- Bounded provider materialization now also checks its persisted - `bbox_epsg4326`; one small PICC/UrbIS/GRB/raster acquisition can no longer - claim that an entire region is locally loaded. -- The live governed Statbel apply materialized the reviewed 2025 `NEW` edition - as Dataset `ee0a46e5-6139-4b0a-93b5-9dabb3b3dfc7`: 20,781 statistical - sectors, 565 municipalities, four repaired geometries and a reconciled - national total of 11,825,551 inhabitants (11,817,897 spatially located plus - 7,654 explicitly unlocated). -- Live bounded PICC and UrbIS persistence proved the same service path: - 54 Walloon building geometries retained in Dataset - `0c3c0a11-c00e-4c84-87be-8ffa64302dec` and 47 Brussels building geometries - in Dataset `de53ccc0-a494-4c4e-bd0d-16d807bfefe7`. -- Corrected the map catalog precedence so reusable persisted datasets win over - on-demand placeholders. National Statbel 2025 population is now presented - as the active source, while selection-bounded PICC/UrbIS acquisitions remain - available only through an exact bounded request. -- Live browser verification found that a changed work area was fitted together - with the complete active national layer. Area changes now fit the selected - geography first and retain that viewport when a complete national layer is - loaded on the following render or the map container resizes. -- The final browser audit then exposed a responsive layout defect rather than - a CRS defect: at 1,264 pixels wide the theme list stretched the MapLibre - canvas to 723 by 1,891 pixels, so a correct fit placed Belgium mostly below - the visible fold. The first explorer grid row is now bounded independently, - the theme list scrolls internally and the live canvas measures 723 by 496 - pixels at the same viewport. -- Map updates no longer depend on transient `isStyleLoaded()` results after - the initial `style.load`; Area, dataset, selection, raster and QA overlay - changes are retained while base-map tiles load. -- Live browser acceptance switched Belgium land, the North Sea golden zone, - Brussels and Wallonia without manual zoom or console warnings. Persisted - sources remained preferred, while PICC/UrbIS stayed selection-bounded. -- `scripts/run_rc8_release_journeys.sh` passed against port 1202 and reused all - seven golden Areas. The retained manifest records PostGIS 3.6, migration - `202607160001`, clean console/request audits, a 49-feature persisted export, - exact 2013-2025 forest change, a grounded 656-character Ollama answer with - 36 metrics, and a successful configured-YOLO Job/AnalysisRun map handoff. -- The deployed AI runtime imports PyTorch `2.13.0+cpu` and Ultralytics - `8.4.99`; `/api/v1/system/capabilities` and the detection model registry - report configured local YOLO truthfully. -- The final local readiness gate passed with 1,042 backend tests and 20 - frontend tests, frontend typecheck and production build, a single Alembic - head, the complete offline `upgrade head --sql` chain and live-smoke shell - syntax. The Windows runner has no local Docker CLI; compose, PostGIS and - migration runtime evidence therefore comes from the successful Tower deploy. -- P5 is complete. MDK remains the only deliberately blocked source in this - board because strict TLS/capabilities evidence does not pass; no bathymetry - or water-volume value was invented. - -### RC-4 national and maritime coverage foundation - -- Added an independent coverage registry so the exact Sprint 7 - `grb|osm|manual|fixture` provider contract remains unchanged. -- Added `GET /api/v1/external/coverage/catalog` and - `POST /api/v1/external/coverage/resolve` with canonical envelopes, normalized - themes and explicit project-materialization checks. -- Added `provision_belgium_north_sea_scope.py`. It accepts only the official - NGI AdminVector archive, RBINS marine reporting units and the exact 15-layer - `imsp26` WFS allowlist. It verifies archive/response limits, safe extraction, - layer counts, pagination, geometries and SHA256 evidence. -- Verified live source contracts from the Codex host: all 15 MSP layers were - reachable and returned 101 features in total; the current RBINS reporting - units yielded BPNS, territorial sea, EEZ and continental-shelf geometries. -- The territorial sea is derived only by unioning official 0-1 nm and 1-12 nm - units. EEZ and continental shelf retain the same official offshore geometry - as separate records with different legal-domain provenance. -- Frontend startup now prefers a materialized - `Belgium and North Sea Workbench`; drawn bboxes receive a compact, - zone-split coverage matrix. Existing Mol/Kempen workspaces remain available. -- Local validation passed 986 backend tests, frontend typecheck/build, the - full readiness gate, Alembic head `202607160001`, complete offline migration - SQL and live-smoke shell syntax. -- Tower fetch-only, persistence, live coverage API and browser acceptance are - the remaining RC-4 exit evidence. -- The first Tower fetch-only run failed closed before API persistence because - AdminVector exposes `modifdate` as a Pandas `Timestamp`. GeoJSON - serialization was corrected to explicit string conversion and guarded by a - regression assertion; downloaded source artifacts remain operator cache - only. -- The corrected Tower fetch-only run validated all seven generated artifacts - and 101 current MSP 2026 features. The first API persistence run then exposed - a separate live-only PostGIS constraint: AdminVector AOI boundaries carry a - zero-valued Z coordinate while `areas.geometry` is intentionally 2D. - Shared AOI normalization now removes Z before validation and persistence. -- Live API persistence subsequently completed with one national workspace, - eight scope areas and six ready authoritative datasets. A second operator - run reused the same project and dataset identifiers. Browser acceptance then - exposed and closed a map guard that had prevented coverage-only selection - when the chosen theme was honestly unavailable. -- RC-5 deployment hardening started by centralizing Tower release execution, - moving build identity behind expensive dependency layers, retaining - immutable commit images plus a `previous` rollback target, adding automatic - rollback and an isolated fresh-install smoke, and failing closed on default - database secrets or inconsistent upload limits. -- Tower proved cached apt/PyTorch layers, a fresh install on isolated paths and - a healthy rollback against the retained database/storage. The release tag - contract was then tightened to immutable commit-plus-profile tags so repeated - deploys reuse rather than overwrite the same build identity. -- A repeated no-op deploy reused the existing profile-tagged image and - preserved the actual previous image. The Unraid template now exposes every - operator-owned acquisition, upload, local-model and assistant setting as an - editable field, with only deployment bridge variables kept internal. -- Added an explicit release upgrade verifier that composes the checksum-backed - isolated restore drill with the deployed image's Alembic chain and destroys - only the generated verification database. -- Tower release `944269c25b1d7647c2ef468df75e195d045d8c0c` completed that - isolated upgrade proof against backup - `rc-belgium-north-sea-fc42ea9-secure`: checksums and retained counts matched, - PostGIS 3.6 and Alembic `202607160001` passed, the temporary database was - removed and the evidence records the production database as untouched. - -- Froze the RC geography as all Belgian land plus the separately labelled - territorial sea, EEZ and continental shelf. -- Retained Mol and the Kempen as validated regression areas instead of the - final product boundary. -- Added `docs/RC_SCOPE_FREEZE_BELGIUM_NORTH_SEA.md`. -- Added `docs/RC_ROADMAP_BELGIUM_NORTH_SEA.md` with autonomous stop rules, - exact phase gates, evidence requirements and RC-0 through RC-11. -- Removed the need for a separate RC-12 phase. Fresh-install, upgrade, - rollback and runtime evidence remain mandatory inside RC-5 and RC-11. -- Verified the official source families for NGI/IGN, Statbel, SPW Wallonia, - UrbIS Brussels, federal marine planning, RBINS/BMDC and MDK before freezing - the coverage architecture. -- Started RC-0 implementation; the release-evidence command is the first code - gate. -- Implemented and tested `scripts/capture_release_evidence.py`. The first - local/live baseline recorded commit `9513f86`, dirty-state evidence, one - Alembic head `202607160001`, dependency/configuration checksums and reachable - Tower health/capability routes without storing secret values. -- Replaced the obsolete pre-implementation `docs/BUILD_STATUS.md` with the - current RC state and moved runtime release evidence outside Git. -- RC-0 is complete. RC-1 backup/restore safety is active. -- Added atomic custom-format PostgreSQL backup, read-only verification and - generated-database restore-smoke scripts. Their focused safety/syntax tests - pass; Tower backup and isolated restore execution remain the RC-1 live gate. -- Implemented RC-2 truthful runtime state: independent liveness, fail-closed - DB/PostGIS/Alembic/storage readiness, runtime-derived YOLO capability, - request correlation IDs, exception trace logging, SQL logging at WARNING - and all-in-one startup reconciliation for orphaned `running` jobs/runs. -- Docker, Nginx, API contracts and health documentation now use - `/health/ready`; `/health` remains a compatibility readiness alias. -- Validation passed: targeted Ruff, backend compile, 963 backend tests, - frontend typecheck/build, 122-route contract audit, one Alembic head, - complete offline migration SQL and the full readiness gate. -- Local Docker CLI is unavailable on the Windows Codex host. Docker config, - image build, live health truthfulness, backup and restore are therefore - scheduled on the Docker-enabled Tower after push. -- Pushed and deployed commit `9c402e0`; subsequently pushed the cwd-independent - backup fix `38a3bd0` and secret rotation command `fc42ea9`. -- Tower Docker config, all-in-one build, live migration smoke and browser - runtime smoke passed. `/health/live` and `/health/ready` report `ok`, - PostGIS 3.6, Alembic `202607160001`, writable storage and configured YOLO. -- Startup reconciliation changed five impossible orphaned jobs and two - analysis runs to terminal `failed` state with `PROCESS_INTERRUPTED`; no - `running` rows remain. -- Created the full SHA-256 inventory backup - `rc-belgium-north-sea-38a3bd0`, verified it read-only and restored it in an - isolated temporary database. The first restore attempt exposed stale glibc - collation metadata in `template1`/`postgres`; those empty system databases - were reindexed and refreshed after the backup, then restore passed. -- Rotated the production PostgreSQL password with a generated 256-bit value - without logging it, atomically updated the Tower `.env` and recreated the - healthy container. -- Created the current secure backup - `rc-belgium-north-sea-fc42ea9-secure` (1.4 GiB), verified all checksums and - repeated isolated restore. PostGIS/Alembic and all retained critical table - counts match; the temporary database was removed. -- RC-1 and RC-2 are complete. RC-3 is active. - -## Sprint 229 - Governed ALZ definitive release promotion (2026-07-17) - -Implemented: -- Added `scripts/manage_alz_agriculture_release.py` with separate read-only - `plan`, filesystem-only `stage`, named `review` and exact-hash `apply` - actions for the approved Kempen regional scope. -- Derived the only accepted future archive from the allowlisted definitive - `YYYY-v3` campaign and publication date exposed by the existing source- - catalog probe. Provisional v1/v2 snapshots remain visible but non-importable; - arbitrary URLs, current/older releases and catalog drift fail closed. -- Extended the existing agricultural provisioner to accept exactly one - explicitly governed future edition per run. Final response URLs and streamed - archive size are bounded, retained editions cannot be overridden and all - workspace API collections are read with stable-total pagination. -- Bound archive, normalized GeoJSON, GeoPackage schema/CRS, complete crop-code - list, scope counts/area and previous-definitive-edition manifest/deltas into - the staged plan. ZIP member/extracted size is bounded. Review and apply - require exact SHA-256 values; apply still uses DatasetService and preserves - all historical snapshots. -- Packaged the manager in the Unraid image/readiness gate and updated source, - data, API, persistence, storage and operator documentation. No endpoint, - migration, scheduler, browser fetch or frontend behavior changed. - -Validation: -- 43 tests passed across the original ALZ importer, official catalog probe and - new release manager; 58 passed together with the Statbel release suite. -- Target Python compilation and Ruff pass. Coverage includes future release - identity, v1/v2 exclusion, pagination drift, download bounds, release - ordering, stage/apply separation, source/schema/codelist/baseline evidence, - path confinement, byte tampering, named review, catalog drift, full mocked - apply, current-edition refusal and runtime packaging. -- Complete readiness passed with 850 backend tests, 110 documented routes, - one Alembic head `202607160001`, frontend typecheck and production build. - Static full-chain Alembic SQL and shell syntax checks also passed. Local - Docker is not installed in the Codex Windows environment; Compose and live - PostGIS validation are therefore deferred to the Tower deployment gate. -- Tower was rebuilt from commit `ad2c348`. Compose validated, the all-in-one - container became healthy on port 1202, PostGIS 3.6 and all required schema - objects answered, Alembic remained at `202607160001` and the frontend/API/ - icon browser proxy smoke passed. -- The packaged manager's live plan reported local `2025-definitive`, official - `2025-v3`, provisional non-importable `2026-v1` and decision `current`, with - publication-page hash - `16f513d46d16940a2970599ec34013d5ff5727277b021024aa4a320671627664`. - A deliberate deployed stage attempt exited 1, Dataset count remained 2,429 - and no 2025 `staged-plan.json` was written. -- Live visual verification loaded the 28-municipality workspace, official map - boundary and all available themes, including 54,071 agriculture features. - The OpenStreetMap basemap rendered and the browser reported no warnings or - errors. - -Boundary: -- The official page currently advertises definitive `2025-v3` plus - provisional `2026-v1`. No newer definitive edition exists, so live stage, - review and apply must remain blocked; only a read-only plan and deliberate - current-edition refusal may be exercised after deployment. - -## Sprint 228 - Governed Statbel population release promotion (2026-07-17) - -Implemented: -- Added `scripts/manage_statbel_population_release.py` with four separate - operator actions for the approved Kempen scope. `plan` is read-only; `stage` - requires exact year/layout confirmation and performs bounded fresh download - plus preflight only; `review` requires a named explicit approval; `apply` - requires the exact staged-plan and review-evidence SHA-256 values. -- Derived the only accepted population and matching sector-geometry URLs from - the allowlisted catalog year/layout contract. The coordinator accepts no - arbitrary source URL or process, and current, older, unavailable, ambiguous - or catalog-drifted releases are not stageable. -- Bound catalog identity, source archives, preflight manifest, derived - snapshot, scope/national accounting, ZZZZ totals, baseline trend and geometry - repairs into `staged-plan.json`. Bound the named human decision to that plan - in `review-evidence.json`; successful apply records the immutable Dataset in - `applied-evidence.json` without deleting prior snapshots. -- Extended `provision_mol_population_history.py` with a complete all-or-none - release config for one future year. Existing 2021-2025 arguments remain - compatible. Source downloads now enforce response and streaming byte bounds, - validate final official URLs and discover the latest retained baseline from - actual snapshot files rather than a hardcoded year list. -- Replaced the population operator's 200-row workspace lookup with complete, - total-consistent pagination. This keeps repeated apply idempotent in the live - project with 2,429 Datasets. -- Added Docker/readiness packaging and updated source, API, persistence, - storage and operator documentation. No API route, migration, scheduler, - automatic fetch or frontend behavior changed. - -Validation: -- 15 focused Sprint 228 tests and 38 combined Sprint 194/227/228 tests passed. - Coverage includes release ordering, future URL/layout validation, dynamic - baseline discovery, bounded downloads, >200-row pagination, stage/apply - command separation, plan/review hashes, source/review tampering, evidence-root - confinement, catalog drift, named review, apply evidence and current-edition - refusal. -- Complete readiness passed with 830 backend tests, 110 documented routes, - one Alembic head `202607160001`, frontend typecheck and production build. - Static Alembic SQL, shell syntax, target Ruff and diff checks passed. -- A compatibility run against the live Tower API used the temporary candidate - scripts before deployment. The official Statbel catalog reported - `NodeID6475`, remote/local edition `2025`, layout `new`, catalog hash - `64b17ce059a9c2f936d4b5741b20aed4b178409d8b5be81be86e6fdc9fe7c9d9` and - decision `current`; `plan` wrote no evidence. A deliberate `stage` attempt - for that current edition exited 1 with `not safely stageable: current` and - left the database Dataset count unchanged at 2,429. -- Tower was rebuilt and deployed at commit `d0a8a3a`. The all-in-one container - became healthy on port 1202, PostGIS 3.6 answered, Alembic remained at the - single `202607160001` head and the frontend/API proxy plus icon smoke passed. -- The packaged manager repeated the live `plan --refresh-catalog` result as - `current` for official edition 2025. Its deliberate deployed `stage` attempt - again exited 1, Dataset count remained 2,429, the health endpoint reported a - working database and no 2025 `staged-plan.json` was written. - -Boundary: -- No newer population edition is currently advertised, so no real stage, - review or apply was executed. Their complete state machine is fixture-tested; - the first future release must still pass all four explicit operator phases. - -## Sprint 227 - Statbel population import compatibility preflight (2026-07-16) - -Implemented: -- Added `scripts/statbel_population_preflight.py` as a local, fail-closed gate - between staged official Statbel archives and the existing population - provisioner. It performs exact source/edition allowlisting, bounded ZIP - inspection, population and geometry schema checks, EPSG:31370 and situation - date validation, geometry validity/area checks, sector joins, explicit - municipality reconciliation, national/scope total reconciliation and an - annualized baseline-change guard. -- Removed the invalid historical assumption that `CD_SECTOR[:5]` always equals - the current `CD_REFNIS`. The 2025 REDEGEO layout can retain old sector codes - after a municipal merger; population and geometry must instead agree on - their explicit current municipality fields. -- Kept official `ZZZZ` population rows in national and scope accounting while - excluding them honestly from map geometry. Bounded `make_valid` repair is - allowed only when the result remains polygonal, valid and area-preserving; - repaired sector codes are recorded in the manifest. -- Hardened `provision_mol_population_history.py` so a new fetch is preflighted - before source retention or derivation, source ZIPs and the derived GeoJSON - are written atomically, and all three SHA-256 values are rechecked before - upload. Existing immutable Datasets remain idempotent; a legacy cached file - cannot create a new Dataset without `--force` restaging evidence. -- Packaged the script in the all-in-one image, added it to readiness compile - checks and documented command, storage layout, evidence and limitations. - No API route, migration, scheduler, background fetch or existing Dataset was - changed. - -Validation: -- Focused preflight/regional-time-series suite: 23 passed. It covers source and - member identity, missing schema, duplicate sectors, invalid totals, archive - traversal, CRS/date mismatch, explicit municipality mismatch, unexpected - non-spatial rows, bounded topology repair, excessive trend change, atomic - staging, source/snapshot tampering and legacy parser strictness. -- Complete readiness passed with 815 backend tests, 110 documented routes, - one Alembic head `202607160001`, frontend typecheck and production build. - Static Alembic SQL, shell syntax, target Ruff and diff checks passed. A - repository-wide Ruff audit still reports 17 pre-existing warnings outside - this change; no unrelated refactor was performed. -- Live compatibility-only execution inside the healthy Tower container used - locally staged official archives and made no API/database call: - - 2024 standard layout: 646 spatial Kempen sectors, spatial population - 503,405, 28 `ZZZZ` rows / 276 unlocated inhabitants and accounted total - 503,681 against the retained 2023 baseline. - - 2025 new REDEGEO layout: 733 spatial Kempen sectors, spatial population - 506,473, 26 `ZZZZ` rows / 294 unlocated inhabitants and accounted total - 506,767 against the retained 2024 baseline; annualized change 0.6094%. - - National 2025 accounting reconciled 21,183 population rows and 20,781 - geometries to 11,825,551 inhabitants, including 402 `ZZZZ` rows / 7,654 - unlocated inhabitants. Four official self-intersection cases were repaired - without area change and recorded by sector code. -- The complete real 2025 operator staging path retained both source archives, - generated a 733-feature scoped GeoJSON and authorized source/snapshot hashes - in an isolated `/tmp/statbel-stage` directory. It did not import or replace a - Dataset. -- Gitea commit `4f4d467` rebuilt the Tower all-in-one image with AI extras. - The container became healthy on port 1202, live migration smoke confirmed - PostGIS 3.6 and Alembic head `202607160001`, and the browser proxy/icon smoke - passed. The preflight was then rerun from its deployed `/app/scripts` path - against the official 2025 archives with the same 506,473 + 294 = 506,767 - scope accounting. Database dataset count remained exactly 2,429 before and - after. All temporary validation archives and manifests were removed. - -Boundary: -- A passed preflight proves technical compatibility only. Adding a future - edition to `POPULATION_URLS` and replacing or importing any immutable Dataset - remains an explicit reviewed operator action. - -## Sprint 226 - Governed Statbel population edition probe (2026-07-16) - -Implemented: -- Extended the explicit source-catalog audit with the official Statbel DCAT - Turtle catalog. The parser selects one latest Dutch population-by-sector - release and requires consistent period evidence, identifier, canonical - landing page, CC BY 4.0 license and allowlisted distribution identities. -- Added strict endpoint and final-redirect validation plus a separate 5 MiB - response limit. The catalog probe never follows a ZIP/XLSX link, imports a - Dataset, writes PostGIS or enables background polling. -- Kept population reference year, sector-geometry edition and REDEGEO layout - distinct. The 2025 NEW distribution is current; OLD is transition evidence, - and the separate 2026 sector geometry is not presented as 2026 population. -- Reused the canonical source-catalog response, cache, operator CLI and Status - UI. Propagated the fixed URL and size bound through local, Compose and Unraid - configuration and added RDFLib as a pure-Python core parser dependency. - -Validation: -- The bounded parser read the live official DCAT catalog and identified - `NodeID6475`, population edition `2025`, four distributions, the new REDEGEO - layout, legacy transition availability, CC BY 4.0 and catalog date - `2026-07-07` without requesting a distribution. -- All 24 focused source-catalog tests passed, including hostile host, redirect, - configured URL, duplicate release, conflicting year, missing license, - missing current distribution and oversized-response failures. -- Complete readiness passed with 801 backend tests, 110 documented routes, one - Alembic head, frontend typecheck and production build. Static Alembic SQL, - Ruff, diff checks and shell syntax also passed. Local Docker validation was - unavailable on Windows and is completed through the Tower deployment gate. -- Tower rebuilt commit `da2371d`; server-side Compose validation passed, the - all-in-one container became healthy on port 1202, PostGIS 3.6 and required - schema objects passed, Alembic remained at `202607160001`, and the browser - proxy/icon smoke passed. The runtime reports RDFLib `7.6.0` and the exact - configured Statbel URL with its 5 MiB limit. -- The live regional endpoint reported `4/4` providers available and zero - edition differences. Statbel returned `NodeID6475`, local/remote `2025`, all - three evidence markers, four advertised distributions and catalog date - `2026-07-07`. -- Browser verification showed the four cards in a balanced two-column - 1920-pixel layout, no horizontal overflow, the full REDEGEO transition copy - and zero console warnings/errors. - -Boundary: -- This is publication evidence only. A future population edition still needs - a governed schema, sector-geometry and totals review before the existing - operator may create a new immutable Dataset. - -## Sprint 225 - Governed ALZ edition probe (2026-07-16) - -Implemented: -- Extended the existing explicit source-catalog audit with the exact official - ALZ agricultural-use parcel publication page. The parser is bounded and - fail-closed to the canonical HTTPS release path plus exact - `agpa___public.zip` link identities. -- Kept the edition model honest: the retained local `2025-definitive` Dataset - compares with official `2025-v3`; the current `2026-v1` snapshot is visible - as provisional and cannot trigger or justify historical replacement. -- Reused the canonical source-catalog API envelope, cache, operator command and - Status surface. No archive, feature, raster or model is fetched and no - Dataset/PostGIS mutation, scheduler or migration was introduced. -- Propagated the ALZ release URL through backend settings, Compose, the Unraid - environment/template/launcher and operator documentation. An odd final - source-status card spans the full grid width for a balanced desktop layout. - -Validation: -- The live official page probe returned `available`, definitive `2025-v3`, - current provisional `2026-v1`, both required evidence markers and 19 - validated publication links without requesting an archive. -- Focused source-catalog coverage passed with 13 tests, including release-page - redirects, untrusted archive hosts, missing current snapshot, definitive - year ordering, cache bypass and disabled/network-free behavior. -- Complete readiness passed with 790 backend tests, 110 documented routes, one - Alembic head, frontend typecheck and production build. Static Alembic SQL and - live-migration script syntax also passed. -- Tower was rebuilt from commit `0a23e34`; the all-in-one container became - healthy on port 1202, PostGIS 3.6 answered, required schema objects passed - and Alembic remained at `202607160001`. -- The live regional API reported three available providers and no edition - differences. Browser verification showed `3/3 bereikbaar`, ALZ - `bereikbaar / zelfde editie`, `Publicaties: 2/2 bevestigd`, the provisional - warning and zero console warnings/errors. - -Boundary: -- The probe is release evidence only. A future definitive campaign still - requires human confirmation and the existing governed ALZ operator; no - automatic ALZ refresh has been enabled. - -## Sprint 218 Regional terrain and flood completion (2026-07-16) - -Changed: -- Added the resumable 28-municipality DHMV DTM/DSM operator and executed all - 56 governed acquisitions through the canonical API. -- Executed all 336 governed VMM mechanism/climate/return-period combinations - across the same 28 persisted municipality Areas. -- Diagnosed Retie's official WCS integer-grid edge rounding in both providers. - Accepted only bounded 5%/0.25 m edge drift, harmonized accepted tiles to the - exact requested grid and retained source resolutions, tile indexes and - method in provenance. A 4.5 m regression fixture remains rejected. -- Added exact partitioned terrain and flood selection routes for bounded - rectangles that cross municipality boundaries. They use only persisted - GeoTIFFs, calculate global statistics from combined cells and retain the - contributing Dataset ids in the response. -- Made the complete Kempen Area expose DHMV/VMM as logical regional MapLibre - layers while retaining municipality-linked storage and twelve distinct VMM - scenario identities. - -Live evidence: -- VMM: 336 ready Datasets, 28 Areas, 12 products, 336 DatasetVersions, - 165,277,992 bytes, zero duplicate Area/product pairs and zero missing or - size-mismatched files. -- DHMV: 56 ready Datasets, 28 Areas, two products, 56 DatasetVersions, - 282,645,991 bytes, zero duplicate Area/product pairs and zero missing or - size-mismatched files. -- Every VMM Dataset has null `observed_at` and explicit false flags for - bathymetry, permanent depth/volume and concurrent volume. A repeated Retie - run reused all twelve immutable Dataset ids. -- Tower commit `153cff0` passed container health, PostGIS 3.6, Alembic head - `202607160001` and frontend/API/icon proxy checks before the regional UI - follow-up. - -Validation evidence: -- Focused DHMV/VMM and regional explorer backend suites passed, including - exact adjacent-partition percentile and area calculations. -- The pre-UI-fix release gate passed 746 tests, backend compilation, API - contract checks, one Alembic head, frontend typecheck and production build. -- The final local release gate passed all 752 backend tests, backend - compilation, 107 documented API route checks, Alembic head `202607160001`, - frontend typecheck and the production build. Live deployment and browser - evidence are recorded after the Tower rollout. -- Tower deployment of commit `45dc730` passed container health, PostGIS 3.6, - the live migration/schema smoke and the frontend/API/icon proxy checks. -- One live 0.15 by 0.13 degree cross-boundary rectangle opened seven persisted - DHMV and seven persisted VMM partitions. It returned 6,056,943 valid terrain - cells at 99.9719% coverage and 651.56 ha of modeled pluvial current-climate - T100 positive-depth cells without contacting either WCS. -- Browser verification showed both regional themes as available, twelve - deduplicated VMM scenarios, one 28-municipality MapLibre layer and zero - console warnings/errors. A follow-up status-label fix makes a visible raster - report `Rasterlaag actief` instead of `Geen actieve laag`. -- Interactive browser drawing over the central Kempen returned all fifteen - theme summaries, including 619.71 ha modeled pluvial T100 area, 18.26 m TAW - mean terrain height and 56,310 inhabitants. The boundary probe also exposed - and closed a frontend inconsistency: every selection and derive path now - forwards the active Area id for authoritative backend clipping. - -Next: -- Use the now-complete regional current-state layers as the baseline for a - governed refresh/change scheduler. Keep source-specific publication dates - and scenario semantics; do not turn VMM scenarios into a historical water - level series. - -## Sprint 217 Regional DOV soil coverage (2026-07-16) - -Changed: -- Generalized the explicit DOV `bodemkaart:bodemtypes` operator from Mol to the - approved 28-member Kempen scope without changing source or persistence - semantics. -- Added independently reusable municipality partitions, deterministic gzip raw - responses, boundary/output checksums, unique NIS-suffixed persisted ids and - one regional snapshot manifest. -- Packaged and release-checked the operator in the all-in-one image. -- Kept regional and municipality metric queries on exact PostGIS intersections - instead of asserting a preclipped fast path across CRS round trips. - -Validation evidence: -- The live operator completed 28/28 partitions, 62 WFS responses, 46,134 - bounded source features and 27,200 persisted valid EPSG:4326 polygons. -- PostGIS found zero invalid/empty/wrong-SRID geometries, zero duplicate source - ids, complete municipality/NIS identity and 139,871.44 ha mapped area. -- A strict storage-boundary audit measured only 355.15 m2 of coordinate-rounding - slivers across 579 boundary features (about 0.000025%); exact selection - intersections prevent those slivers from bypassing the selected Area. -- A repeat operator run reused every verified partition and the existing - Dataset. -- Browser validation showed Bodem available for the complete Kempen and for - Arendonk, returned 139,871.44 ha and 5,514.99 ha respectively, rendered the - MapLibre layer at detail zoom and produced no browser warnings or errors. -- The pre-deployment readiness gate passed 738 backend tests, compilation, - contract checks, one Alembic head, frontend typecheck and production build. - -Next: -- Fill the remaining region-wide current-state gaps shown in the Map workspace: - VMM flood-hazard coverage and DHMV terrain. Preserve their separate modeled - scenario and elevation semantics; do not infer current water volume. - -## Sprint 216 Regional thematic coverage (2026-07-16) - -Changed: -- Ran the governed thematic-raster operator for every one of the 28 persisted - municipality Areas in `Kempen Regional Workbench` after a successful - Arendonk smoke. All five allowlisted products completed for every Area. -- Added five separately persisted snapshots for the complete `Vervoerregio - Kempen - officiele operationele grens`, enabling free selections that cross - municipality boundaries while preserving exact Area clipping. -- Increased only `THEMATIC_RASTER_MAX_SIDE_M` to 60,000 and - `THEMATIC_RASTER_MAX_PIXELS` to 30,000,000. The service still rejects larger - requests and reads the official WCS in fixed 10 km tiles. -- Retried transient WCS failures at most three times with a bounded delay. - Interrupted responses are discarded and permanent failures remain explicit. -- Required the local assistant to keep each metric's year, source and - measurement quality together when a theme has several official datasets. - -Validation evidence: -- The final inventory contains 145 ready thematic Datasets across 29 Areas and - five product keys, with zero missing metadata/storage paths and zero duplicate - Area/product pairs. All 145 TIFF files are non-empty and occupy 56 MB. -- A second complete-region operator run reused all five existing Datasets. -- Browser validation on `http://192.0.2.10:1202` showed every regional - thematic source as available, rendered the MapLibre overlay and calculated - the complete Kempen result without browser warnings or errors. -- The full readiness gate passed 733 backend tests, compilation, fixture and - API-contract audits, one Alembic head, frontend typecheck, production build - and shell checks. -- Live PostGIS reports version 3.6 and the all-in-one container remained - healthy throughout acquisition and analysis. - -Next: -- Generalize the separate DOV soil-map operator from Mol to all 28 municipality - partitions. Keep the historical 1949-1971 survey semantics and raw source - manifest explicit; do not merge soil provenance into the raster operator. - -## Sprint 215 Grounded assistant cross-domain reliability (2026-07-16) - -Changed: -- Measured the exact live Mol assistant context at 12 current themes, 36 - semantic metrics, six temporal series and 17,302 compact JSON characters. -- Increased the bounded output allowance to 1,200 tokens and instructed the - local model to cover every explicitly listed theme, omit unrelated themes - and avoid repeated limitations. -- Kept `think=false`, deterministic temperature, the 16,384-token context and - fail-closed rejection of `done_reason=length` unchanged. -- Added the output limit to the editable Unraid template and aligned all - deployment defaults and documentation. -- Browser QA in the central 28-municipality workbench exposed that an explicit - six-theme question still summarized every current vector theme. Agricultural - subclass intersections pushed context construction past 110 seconds. -- Added deterministic Dutch theme selection before GIS calculation. Explicit - questions now calculate only named themes; general summaries and source - inventory questions deliberately retain full context. -- The optimized live response completed in 12.3 seconds but exposed literal - Markdown and raw floating-point tails in the plain-text chat renderer. Added - deterministic Markdown normalization and unit-aware context rounding while - retaining the unrounded metrics in the canonical API response. -- The next live answer still called an area-weighted Statbel population value - an official count before acknowledging it as an estimate. The deterministic - estimate guard now removes that contradictory label whenever persisted - population context is estimated. -- Preserved sentence casing and natural Dutch word order in that deterministic - rewrite after the browser regression exposed an awkward replacement phrase. -- A 390 px browser pass exposed a CSS-specificity conflict: the generic - `section > div` grid overruled the explorer's responsive `display: block`. - The geographic layout is now excluded from that generic rule and has a - regression assertion for its mobile stacking contract. -- A final accuracy audit compared the DOV inventory and assistant wording - directly with PostGIS. All 1,159 soil features are non-empty, valid and - intersect Mol, and their transformed area is 11,448.35 ha. The model still - mistyped the supporting count as 1,150 in prose even though its canonical - context contained 1,159. -- Added compound-word theme recognition so `bodemdetails` now selects only the - soil context instead of the complete project portfolio. Supporting object - counts are retained in `context_metrics` but withheld from the model prompt - when semantic measurements exist, eliminating that irrelevant failure mode. - -Validation evidence: -- A read-only live production-chain probe with the 1,200-token setting - completed without truncation against the full persisted Mol context. -- The focused assistant suite passed 14 tests. -- The complete readiness gate passed 713 backend tests, backend compilation, - 105 documented API routes with three explicit binary/non-envelope routes, - one Alembic head and the frontend TypeScript and production build. -- After deterministic theme filtering was added, the complete readiness gate - passed 720 backend tests plus all compile, contract, Alembic, frontend and - shell gates. -- After plain-text normalization and semantic prompt rounding, the final - readiness rerun passed 725 backend tests and the same complete gate set. -- After hardening estimated-population wording, the final complete readiness - rerun passed 726 backend tests and all remaining gates unchanged. -- The regional thematic operator dry-run resolved exactly 28 official - municipality Areas. The live Mol run in `Kempen Regional Workbench` imported - all five products with complete source coverage; the DOV operator imported - 1,159 exact Mol soil polygons into the same project. -- Browser validation then showed all six new themes as available and returned - 3,638.41 ha space occupation, 31.76% share and the full 15-theme Mol summary - from persisted data. -- The final Tower deployment at commit `43dd535` passed container health, - browser proxy/icon checks, PostGIS 3.6 schema validation and Alembic head - `202607160001`. -- The exact six-theme Mol assistant regression returned 2,575 readable - characters covering every requested theme, with no Markdown, contradictory - official-count wording or unrelated theme. The 390 px explorer measured - 317 px for theme, map and results panels with no page overflow; desktop and - widescreen map checks remained clean and browser logs contained no warnings. -- The focused live `bodemdetails` regression at commit `59194e9` selected one - DOV dataset and six canonical metrics, retained the exact 1,159 object count - in API evidence and returned only the five source-correct hectare metrics - plus the 1949-1971/1:20,000 limitation in end-user prose. -- The final complete readiness gate passed 730 backend tests, compilation, - documentation/fixture/contract audits, one Alembic head, frontend typecheck, - production build and shell-script checks. - -Next: -- Roll out the five governed thematic rasters municipality by municipality to - the remaining 27 Kempen Areas, with storage/runtime monitoring and an audit - after each batch. Keep DOV soil expansion separate until its operator is - generalized beyond the current explicit Mol boundary. - -## Sprint 213-214 Cross-domain thematic rasters and DOV soil map (2026-07-16) - -Changed: -- Added a governed five-product MercatorNet thematic-raster registry covering - space, people, accessibility and services with fixed coverage ids, native - resolutions, units, years, legends and limitations. -- Added safe WCS tiling, exact Area masking, canonical raster persistence, - MapLibre rendering, selection metrics and persisted-metric Ollama context. -- Added an explicit DOV soil-map operator for Mol with deterministic WFS 2.0 - pagination, exact EPSG:31370 clipping, raw checksums and canonical vector - upload. No source writes directly to PostGIS. -- Added end-user themes for space occupation, open space, population, - accessibility, services and soil. Current-only official states no longer - make Evolution appear available without at least two observations. - -Validated during implementation: -- Focused thematic and soil suites passed with 14 tests. -- Frontend TypeScript typecheck passed after map and API integration. -- Live source contracts were checked against MercatorNet WCS and the DOV - production WFS; live runtime provisioning follows after deployment. - -Next: -- Run the complete readiness gate, deploy Tower, provision all six Mol layers, - verify live PostGIS metrics and inspect the map at desktop, widescreen and - mobile widths before starting regional rollout. - -## Sprint 195 Guided raster-to-detection workflow (2026-07-14) - -Changed: -- Connected the existing Dataset upload, `raster/tile`, YOLO preflight, configured detection, persisted result listing and MapLibre GeoJSON overlay into one guided frontend action. -- Added explicit GeoTIFF input inside Detection Lab so users no longer need to navigate to dataset management before starting image analysis. -- Uses fixed safe tiling defaults of 512 px with 64 px overlap, reuses the current manifest and estimates the tile count from canonical raster inspection before writing tiles; the backend remains authoritative for tile-limit, manifest, dependency and local-model validation. -- Moved manifest paths, direct-manifest execution and calibration under management disclosures while returning persisted reference QA to the main result flow. -- Kept every run on the existing `Dataset -> Job -> AnalysisRun -> Detection -> QualityCheck/Metric` chain. No migration, API route, external fetch, model download or synthetic inference was added. - -Validated locally: -- `bash scripts/run_readiness_check.sh` passed with `575 passed`, backend compile, one Alembic head (`202607140001`), frontend typecheck/build and live-smoke syntax validation. -- `python -m alembic upgrade head --sql` generated the complete 26,972-byte PostgreSQL/PostGIS migration plan successfully. -- Focused guided-flow, stale-map-state and direct-upload contracts passed. The Windows workstation has no Docker CLI; live container/PostGIS validation therefore remains part of the Tower deployment pass. - -Next: -- Provision one existing real Mol operator orthophoto and matching official GRB reference into the regional workbench through the canonical upload API, then execute the guided action and verify the persisted map/QA result in the browser. - -## Sprint 194 Regional official time series and full-Area performance (2026-07-14) - -Changed: -- Generalized the explicit Statbel operator to the approved 28-municipality scope and added one coordinator for official 2021-2025 population plus 2013-2025 forest snapshots. -- Added municipality-partitioned official 10 m WCS retrieval after the upstream response-size limit rejected a single full-region request; source partitions are resumable and mosaicked locally before exact region clipping. -- Added a provenance-gated full-Area selection path for trusted pre-clipped operator datasets. Free rectangles, unrelated Areas and ordinary uploads continue to execute the normal PostGIS intersection path. -- Grouped older dated snapshots behind `Historische meetmomenten`, replaced raw provider/type labels in the primary catalog and translated the remaining visible temporal, download, platform-status and detection-evaluation language. - -Live regional evidence: -- Population datasets: five exact dated snapshots, 3,317 persisted `vector_features`; 2021 `489,927` inhabitants and 2025 `506,473`, a measured increase of `16,546` (`3.377%`). -- Forest datasets: five exact dated snapshots, 273,669 persisted `vector_features`; 2013 `27,659.976 ha` and 2025 `27,410.687 ha`, a source-resolution change of `-249.289 ha` (`-0.9013%`). -- All ten snapshots have one immutable dataset version and zero invalid, empty, non-4326 or source-ID-missing geometries. A repeated synchronization reused the same ten Dataset IDs without duplicates. -- Complete-Kempen current analysis returns 506,473 inhabitants, 27,410.69 ha forest, 466,078 buildings, 88,332 water features, 84,504 roads and 415,288 parcels over 1,399.25 km2. - -Performance and runtime evidence: -- Population full-Area API selection completed in `1.738 s`; forest completed in `1.083 s`. The browser rendered the full six-theme analysis and 2021-2025 comparison within the 3.5-second verification window, replacing the previous roughly 92-second forest-heavy workflow. -- Tower health, PostGIS 3.6, required schema objects, Alembic head `202607140001`, frontend, API proxy and icon checks passed after deployment. -- PyTorch `2.13.0+cpu`, Ultralytics `8.4.95` and the active local model file load successfully. The catalog exposes 24 local assets; the active seven-AOI profile remains review-required at F1 `0.5825` and was not blindly retrained. - -Tested: -- `bash scripts/run_readiness_check.sh` passed with `571 passed`, backend compile, one Alembic head, frontend typecheck/build and live-smoke syntax validation. -- Focused regional, temporal and end-user contract checks passed. The browser confirmed the complete regional default, six current themes, five population moments, exact temporal totals and no required project/region selection step. - -Next: -- Complete the 48 false-positive and 48 false-negative operator review decisions, then use those decisions to build a justified next training corpus and expose the existing raster-to-tiles-to-detection workflow as one guided end-user action. - -## Sprint 193 End-user regional workbench simplification (2026-07-14) - -Changed: -- Made `Kempen Regional Workbench` the automatic complete data context before the municipality fallback and removed the primary map's project-level region selector. -- Kept the 28 municipality Areas plus the complete region available as one spatial work-area selector over the already loaded regional datasets. -- Simplified the visible shell and moved technical project runs, raw source metadata, QA internals, provider capabilities, export history and AI diagnostics into explicit advanced disclosures. -- Defaulted Detection Lab to `yolo-configured`, threshold `0.15`, the active local asset and automatic non-mutating preflight checks. -- Added end-user workbench contract tests without changing backend API contracts, migrations, persistence or model execution. - -AI evidence: -- The configured Tower runtime reports PyTorch `2.13.0+cpu`, Ultralytics `8.4.95`, a valid local active model file and a successful model-load preflight; CUDA is not available. -- The retained active profile records precision `0.5898`, recall `0.5770` and F1 `0.5825` over seven positive AOIs with zero detections in the empty-background control. -- No automatic download or blind retraining was introduced. The 48 false-positive and 48 false-negative review decisions remain a required gate before constructing another training corpus. - -Tested before deployment: -- `bash scripts/run_readiness_check.sh` passed with `560 passed`, backend compile, one Alembic head (`202607140001`), frontend typecheck/build and live-smoke syntax validation. -- `python -m alembic upgrade head --sql` generated a 30,166-byte offline migration plan successfully; `bash -n scripts/live_migration_smoke.sh` passed. -- The false-positive review validator returned the expected `review_required` gate with all 48 selected decisions still `unreviewed`; no unreviewed QA mismatch was promoted into training data. -- Local Docker validation was unavailable because the Windows workstation has no Docker CLI; live container/PostGIS validation remains part of the Tower deployment pass. - -Live browser follow-up: -- Tower rebuilt the AI-enabled all-in-one image successfully; container health, PostGIS 3.6, required schema objects, Alembic head `202607140001`, frontend, API proxy and icon checks passed. -- The map opened directly on the complete regional workspace with 29 work Areas, no region selector, the full region selected and 466,078 buildings, 88,332 water objects, 84,504 roads and 415,288 parcels available. -- The browser audit found four remaining presentation leaks: the legacy Mol-only project was still prominent, boundary datasets showed filenames, profile names were English and an empty quality status said `waiting`. These were corrected and protected by the now `561`-test suite. -- A final visible-language sweep translated the export preview, details control and provider layer chips; the complete readiness gate remained green with `561 passed`. - -Next: -- Extend official population and modern land-use time series from Mol to all 28 municipalities, then expose a guided raster-import and configured-detection run over a drawn map selection. - -## Sprint 191 Regional Kempen GRB context foundation (2026-07-14) - -Changed: -- Added `scripts/provision_regional_grb_context.py` for bounded, independently resumable `roads`, `water` and `parcels` source snapshots across the approved 28-municipality scope. -- Reused geographic-scope artifacts and the existing DatasetService/VectorFeatureService partition import boundary; no direct SQL, migration, API contract or interactive provider fetch was introduced. -- Preserved line and polygon source dimensions and collection-qualified identities, with length-based or area-based deterministic ownership for boundary-crossing features. -- Added Docker packaging, readiness compilation, focused source-geometry/service tests and operator/source documentation. - -Tested before deployment: -- `python -m py_compile scripts/provision_regional_grb_context.py`. -- `python -m pytest backend/tests/test_sprint191_regional_grb_context.py backend/tests/test_sprint190_regional_grb_buildings.py backend/tests/test_sprint106_map_bbox_extract.py -q` (`19 passed`). -- `bash scripts/run_readiness_check.sh` (`553 passed`; one Alembic head; frontend typecheck/build and script syntax gates passed). - -Runtime evidence: -- Pushed commits `0ed214d` and `7af47ab`, rebuilt the AI-enabled all-in-one Tower runtime and passed PostGIS 3.6/Alembic head `202607140001` plus browser-proxy verification. -- Roads: 84,504 unique `Wegsegment` features, 124,721,658-byte artifact, Dataset `715b24f1-148a-4d50-9c40-d5468f670ffb`. -- Water: 88,332 unique features (25,648 `WTZ`, 4,605 `WLAS`, 58,079 `WGR`), 122,737,017-byte artifact, Dataset `689bb65d-0b03-4c5c-8f42-b5d2d899d8ca`. -- Parcels: 415,288 unique `ADP` features, 525,243,364-byte artifact, Dataset `3cf5e8da-9ab0-49ef-96e4-f74b7557e0a4`. -- All three repeat runs returned `reused=true`; manifest, metadata, PostGIS row and distinct source-ID counts match exactly. There are no missing IDs, invalid/empty geometries or non-4326 rows, and every dataset has one immutable version. -- Canonical Area selections returned the full regional counts and Mol counts of 8,444 roads, 3,669 water objects and 33,038 parcels. The browser exposed all four available regional themes and honestly left population and forest unavailable. - -Next: -- Extend official population and modern land-use time series from Mol to the approved regional scope, retaining source-specific methodology and bounded municipality partitions. - -## Sprint 192 Regional map state correctness (2026-07-14) - -Changed: -- Cleared spatial selection and multi-theme result state before changing the selected work Area. -- Invalidated in-flight single-theme and multi-theme selection requests when their context is reset. -- Made large-vector viewport guidance name the active reference layer instead of always saying `buildings`. - -Tested: -- `python -m pytest backend/tests/test_sprint192_regional_map_state.py backend/tests/test_sprint186_map_first_geographic_explorer.py backend/tests/test_sprint190_regional_grb_buildings.py -q` (`14 passed`). -- Frontend typecheck and production build passed. -- `bash scripts/run_readiness_check.sh` (`556 passed`; one Alembic head; frontend typecheck/build and script syntax gates passed). - -Runtime evidence: -- Pushed commit `7997a72`, rebuilt the all-in-one Tower runtime and passed container health, PostGIS 3.6, Alembic head `202607140001` and browser-proxy verification. -- Repeated the exact defect path: full regional parcels returned 415,288 objects over 1,399.25 km2; switching the work Area to Mol immediately cleared the old result and selection. -- A fresh Mol full-Area run returned 33,038 parcels over 114.55 km2 plus 36,941 buildings, 3,669 water objects and 8,444 roads from the regional datasets. -- Viewport guidance said `parcels`; zooming below the display cap loaded 525 visible PostGIS features over the OpenStreetMap basemap. -- In-app browser checks at 1280x720 and 3440x1440 found no horizontal overflow, blank canvas, console warning or console error. The temporary ultrawide override was reset. - -Next: -- Extend official population and land-use time series from Mol to the approved regional scope. - -## Sprint 169 Filtered YOLO candidate gate and operator hardening (2026-07-12) - -Changed: -- Trained inactive local model asset `geointel-building-yolov8s-aoi1024cleanpx12vis035lowvar512e50-pt` from the visually audited AOI1024 dataset after low-variance negative filtering. -- Added SHA256 provenance fields to future `training_summary.json` output for `dataset.yaml`, the dataset summary, the local base model and the copied trained model. -- Kept long workbench context names compact with matching native tooltips and clamped readiness values to two lines. -- Archived the training, positive-AOI, split-background and promotion evidence under `artifacts/model-review/aoi1024cleanpx12vis035lowvar512e50` locally and matching Tower artifact directories. - -Runtime evidence: -- Training completed for 50 CPU epochs with YOLOv8s, image size `512`, batch `4`; best-model validation ended at precision `0.454`, recall `0.491`, mAP50 `0.368` and mAP50-95 `0.149`. -- Model catalog SHA256: `75345767b51cc66692a9d2c2cd6577b7feecaf5971c8762365e8b610b9dfde8e`; catalog status `available`, `active=false`, `will_download_models=false`. -- Local model-load preflight passed with Torch `2.13.0` and Ultralytics `8.4.92`; CUDA is unavailable and no model download occurred. -- Seven-AOI persisted QA matrix produced 28 runs. Best single result was Westerlo at threshold `0.15`, F1 `0.3002114164904862`. -- Mean positive F1 was `0.153943` at threshold `0.05`, `0.153872` at `0.15`, `0.128891` at `0.25` and `0.099011` at `0.35`. -- Strict pure-empty background evidence was clean at thresholds `0.15`, `0.25` and `0.35`; threshold `0.05` produced one Postel-bos detection. -- Split-aware promotion report recommended `none`: every threshold failed the positive mean-F1 gate, and `0.05` also failed background false-positive pressure. -- The existing active `geointel-building-yolov8s-aoi1024bg512r3e50-pt` remains materially stronger at its promoted `0.35` profile with mean F1 `0.320866`; no model default or `.env` value was changed. -- Pushed implementation commit `8daaa07` and redeployed the AI-enabled Tower all-in-one container on `http://192.0.2.10:1202`. -- Post-deploy live migration smoke passed with PostGIS `3.6`, required schema objects and Alembic head `202606120900`. -- In-app browser verification found no console warnings/errors, confirmed matching full-value context tooltips and a two-line readiness value, and showed both the inactive low-variance candidate and the unchanged active `aoi1024bg512r3e50` asset in Detection Lab. - -Tested: -- Red step: `python -m pytest backend/tests/test_sprint169_long_context_name_readability.py -q` failed before context tooltips and readiness clamping were present. -- `python -m pytest backend/tests/test_sprint169_long_context_name_readability.py backend/tests/test_sprint22_workbench_status_strip.py backend/tests/test_sprint161_widescreen_workbench.py -q` (`5 passed`). -- Red step: `python -m pytest backend/tests/test_sprint129_operator_yolo_training_dataset.py::test_operator_yolo_train_smoke_script_contract -q` failed before training hashes were recorded. -- `python -m pytest backend/tests/test_sprint129_operator_yolo_training_dataset.py -q` (`3 passed`). -- `bash -n scripts/train_operator_yolo_detector.sh` and frontend typecheck passed. -- Full readiness: `bash scripts/run_readiness_check.sh` (`461 passed`; one Alembic head; frontend typecheck/build and shell syntax gates passed). - -Next: -- Do not retrain the same architecture blindly. Inspect per-AOI false-negative evidence and improve label geometry/class balance or add targeted positive samples for the weakest AOIs before the next candidate. - -## Sprint 164 Tower AI deploy env hardening (2026-07-11) - -Changed: -- Hardened `scripts/deploy_tower.sh` and `scripts/deploy_tower.ps1` so the remote Tower `.env` is sourced before building the all-in-one image. -- Updated the PowerShell deploy wrapper to stream the remote script through `bash -s`, matching the Bash deploy path and preserving Bash variable expansion during `.env`-driven builds. -- The PowerShell wrapper now writes a UTF-8-without-BOM temporary script, copies it with `scp`, runs it with `bash` on Tower and removes the remote temp file while preserving the deploy exit code. -- `GEOINTEL_INSTALL_AI=true` in `/mnt/user/appdata/geointel/.env` now drives the automatic image build by default; explicit local overrides remain possible for one-off deploys. -- Documented the deploy behavior in `deploy/unraid/README.md`. - -Why: -- A manual `docker compose up -d --build` against the multi-container compose file failed on Tower because Docker had exhausted default bridge address pools. The healthy runtime is the Unraid all-in-one container, which should be redeployed through the Dockerman-native scripts instead. -- The previous deploy script path could build a GIS-only image while the remote runtime `.env` enabled YOLO, leaving the configured detector in `dependency_unavailable`. - -Tested: -- Red step: `python -m pytest backend/tests/test_sprint31_unraid_template.py::test_tower_deploy_build_uses_remote_env_ai_setting_by_default` failed because the deploy scripts did not source remote `.env` before `docker build`. -- `python -m pytest backend/tests/test_sprint31_unraid_template.py::test_tower_deploy_build_uses_remote_env_ai_setting_by_default backend/tests/test_sprint31_unraid_template.py::test_tower_deploy_uses_single_container_unraid_compose backend/tests/test_docker_runtime_config.py::test_unraid_deploy_passes_ai_build_arg_and_yolo_runtime_env` (`3 passed`). -- Red step: `python -m pytest backend/tests/test_sprint31_unraid_template.py::test_powershell_tower_deploy_streams_remote_script_to_bash -q` failed because the PowerShell wrapper passed the remote script as an SSH command argument instead of streaming it to `bash -s`. -- `python -m pytest backend/tests/test_sprint31_unraid_template.py::test_powershell_tower_deploy_streams_remote_script_to_bash backend/tests/test_sprint31_unraid_template.py::test_tower_deploy_build_uses_remote_env_ai_setting_by_default backend/tests/test_docker_runtime_config.py::test_unraid_deploy_passes_ai_build_arg_and_yolo_runtime_env -q` (`3 passed`). -- Red step: the same PowerShell deploy transport test failed until the wrapper wrote a `[System.Text.UTF8Encoding]::new($false)` temp script, copied it via `scp`, ran it through remote `bash` and propagated the remote exit code. - -## Sprint 150 YOLO label visible-ratio gate (2026-07-09) - -Changed: -- Added `--min-label-visible-ratio` / `OPERATOR_YOLO_MIN_LABEL_VISIBLE_RATIO` to `scripts/export_operator_yolo_tile_dataset.py`. -- The tile exporter now computes the visible share of each original building bbox inside a tile and can drop labels below the configured ratio. -- Default remains `0` for legacy behavior; use `0.25` for the next overlap-heavy operator dataset experiment. -- Tile dataset summaries include `min_label_visible_ratio`. -- `scripts/audit_operator_yolo_dataset_quality.py` now reports `min_label_visible_ratio` in JSON and Markdown. -- Added operator-only `--width`, `--height` and `--half-size-scale` options to `scripts/prepare_operator_real_data_samples.py`; generated raster names now include the requested width. -- Updated operator script documentation. - -Why: -- The current rejected AOI512 candidate still shows low precision/recall after max-det and duplicate suppression hardening. -- A likely label-quality issue is that overlapping tile export can create many small clipped edge labels for buildings mostly outside a tile. -- This pass improves the next training dataset gate without activating a model, faking detections, fetching providers or changing persistence. - -Tested: -- Red step: `python -m pytest backend\tests\test_sprint130_operator_yolo_tile_dataset.py -q` failed because the exporter lacked `min_label_visible_ratio`, CLI help and visible-fragment filtering. -- `python -m pytest backend\tests\test_sprint130_operator_yolo_tile_dataset.py -q` (`6 passed`) -- Red step: `python -m pytest backend\tests\test_sprint146_operator_yolo_dataset_quality_audit.py -q` failed because the audit report did not expose `min_label_visible_ratio`. -- `python -m pytest backend\tests\test_sprint130_operator_yolo_tile_dataset.py backend\tests\test_sprint146_operator_yolo_dataset_quality_audit.py -q` (`7 passed`) -- Red step: `python -m pytest backend\tests\test_sprint127_operator_sample_quality_matrix.py backend\tests\test_sprint131_operator_sample_expansion.py -q` failed because sample prep lacked larger-AOI options. -- `python -m pytest backend\tests\test_sprint127_operator_sample_quality_matrix.py backend\tests\test_sprint131_operator_sample_expansion.py -q` (`8 passed`) -- Full readiness: `bash scripts/run_readiness_check.sh` (`427 passed`, frontend typecheck/build passed). -- Tower deploy: first AI rebuild failed with Docker storage full; after Docker build cache cleanup `/var/lib/docker` had 98G free and redeploy passed live migration smoke and browser runtime verification on `http://192.0.2.10:1202`. -- Tower dataset audit: exported `/app/storage/operator-data/yolo-building-aoi512-visible025` with `min_label_visible_ratio=0.25`; audit returned `needs_attention` because the current 512x512 source rasters still produce only 16 tiles and median normalized box area remains below gate. - -Next: -- Prepare a larger explicit operator sample manifest, for example `/app/storage/operator-data/operator-samples-1024` with `--width 1024 --height 1024 --half-size-scale 2`, then export/audit `yolo-building-aoi1024-visible025` before another CPU training candidate. - -## Sprint 149 YOLO duplicate suppression evidence (2026-07-09) - -Changed: -- Added configured-YOLO cross-tile duplicate suppression after pixel boxes are converted to EPSG:4326 geometries and before `Detection` rows are persisted. -- Added backend setting `YOLO_DUPLICATE_IOU_THRESHOLD` with default `0.5`; `0` disables the GeoIntel-side pass for debugging. -- Detection run `result_json` now records: - - `raw_detection_count` - - `suppressed_detection_count` - - `duplicate_iou_threshold` -- Updated `.env.example`, Docker Compose, Unraid env examples and the Dockerman run script. -- Updated calibration and quality matrix scripts to fetch detection run details and include raw/suppressed counts in per-run and aggregate summaries. -- Updated backend/API/AI/pipeline documentation. - -Why: -- Dense overlapping tile inference can produce duplicate candidate buildings, which inflates persisted false positives before QA/QC. -- The previous Sprint 148 cap fix allowed dense AOIs to persist more candidates, but made duplicate pressure more visible. -- This pass keeps all outputs honest: no model activation, no fake detections and no migration. It only removes lower-confidence same-class geometric duplicates before persistence. - -Tested: -- Red step: `python -m pytest backend\tests\test_sprint8b_yolo_foundation.py::test_yolo_run_suppresses_cross_tile_duplicate_detections -q` failed with `detection_count == 2`. -- `python -m pytest backend\tests\test_sprint8b_yolo_foundation.py::test_yolo_run_suppresses_cross_tile_duplicate_detections -q` (`1 passed`) -- Red step: Docker runtime config tests failed before `.env.example` and Unraid runner exposed `YOLO_DUPLICATE_IOU_THRESHOLD`. -- `python -m pytest backend\tests\test_sprint8b_yolo_foundation.py backend\tests\test_docker_runtime_config.py::test_env_example_uses_runtime_env_names_read_by_backend_and_frontend backend\tests\test_docker_runtime_config.py::test_unraid_deploy_passes_ai_build_arg_and_yolo_runtime_env -q` (`17 passed`) -- Red step: calibration/matrix script tests failed before detection-run raw/suppressed metadata was included. -- `python -m pytest backend\tests\test_sprint124_detection_calibration_sweep.py backend\tests\test_sprint126_detection_quality_matrix.py backend\tests\test_sprint127_operator_sample_quality_matrix.py::test_multi_sample_detection_quality_matrix_runs_existing_matrix_for_each_sample -q` (`3 passed`) -- `bash -n scripts/run_detection_calibration_sweep.sh` -- `bash -n scripts/run_detection_quality_matrix.sh` -- `bash -n scripts/run_multi_sample_detection_quality_matrix.sh` -- `bash scripts/run_readiness_check.sh` (`426 passed`, frontend typecheck/build passed) -- Redeployed Tower all-in-one image with AI dependencies and verified `YOLO_MAX_DETECTIONS=1000` plus `YOLO_DUPLICATE_IOU_THRESHOLD=0.5` in the live container. -- Tower live migration smoke and browser runtime verification passed. -- Live Westerlo calibration with `geointel-building-yolov8s-aoi512e80-pt`: - - `0.25`: 202 persisted / 270 raw / 68 suppressed, F1 `0.2537313432835821` - - `0.15`: 328 persisted / 523 raw / 195 suppressed, F1 `0.22054380664652568` - - `0.05`: 586 persisted / 1000 raw / 414 suppressed, F1 `0.17173913043478262` -- Live Turnhout calibration with `geointel-building-yolov8s-aoi512e80-pt`: - - `0.25`: 559 persisted / 822 raw / 263 suppressed, F1 `0.14114114114114112` - - `0.15`: 659 persisted / 1000 raw / 341 suppressed, F1 `0.14385474860335196` - - `0.05`: 659 persisted / 1000 raw / 341 suppressed, F1 `0.14385474860335196` - -Conclusion: -- Cross-tile duplicate suppression reduces false-positive pressure and improves F1 versus the Sprint 148 uncapped baseline on the checked dense AOIs. -- The current AOI512 YOLOv8s candidate remains rejected for default use because recall/precision are still too low after post-processing. -- Next model work should focus on stronger training data/label strategy and a new candidate gate, not further default threshold lowering. - -## Sprint 148 YOLO max-detection cap hardening (2026-07-09) - -Changed: -- Added backend setting `YOLO_MAX_DETECTIONS` / `Settings.yolo_max_detections`. -- `YoloDetectionAdapter` now forwards the value to Ultralytics as `max_det`. -- Default is `1000` instead of relying on Ultralytics' upstream default of 300. -- Added Docker/Unraid/runtime wiring: - - `.env.example` - - `docker-compose.yml` - - `docker-compose.unraid.yml` - - `deploy/unraid/geointel.env.example` - - `deploy/unraid/run-dockerman-container.sh` -- Updated backend/API/AI environment documentation. - -Why: -- Real Kempen building AOIs often contain more than 300 reference buildings. -- The previous configured-YOLO path could saturate at 300 detections before QA/QC, capping recall independently of model quality. -- This does not activate a model and does not fake detections; it removes an inference runtime cap so persisted QA/QC can measure candidate models honestly. - -Tested: -- Red step: targeted YOLO adapter tests failed because `max_det` was not passed to the model. -- `python -m pytest backend\tests\test_sprint8b_yolo_foundation.py::test_yolo_adapter_converts_single_band_tiles_to_rgb_before_prediction backend\tests\test_sprint8b_yolo_foundation.py::test_yolo_adapter_uses_configured_max_detections -q` (`2 passed`) -- Red step: Docker runtime config tests failed before `.env.example` and Unraid runner exposed `YOLO_MAX_DETECTIONS`. -- `python -m pytest backend\tests\test_docker_runtime_config.py::test_env_example_uses_runtime_env_names_read_by_backend_and_frontend backend\tests\test_docker_runtime_config.py::test_unraid_deploy_passes_ai_build_arg_and_yolo_runtime_env backend\tests\test_sprint8b_yolo_foundation.py -q` (`16 passed`) -- `bash scripts/run_readiness_check.sh` (`425 passed`, frontend typecheck/build passed) -- Redeployed Tower all-in-one image with AI dependencies and verified `YOLO_MAX_DETECTIONS=1000` in the live container. -- Tower live migration smoke passed against embedded PostGIS. -- Live Westerlo calibration with `geointel-building-yolov8s-aoi512e80-pt`: - - `0.25`: 270 detections, F1 `0.23509933774834438` - - `0.15`: 523 detections, F1 `0.19603267211201864` - - `0.05`: 1000 detections, F1 `0.13193403298350823` -- Live Turnhout calibration with `geointel-building-yolov8s-aoi512e80-pt`: - - `0.25`: 822 detections, F1 `0.1304075235109718` - - `0.15`: 1000 detections, F1 `0.13085166384658772` - - `0.05`: 1000 detections, F1 `0.13085166384658772` - -Conclusion: -- The former 300-detection runtime cap is removed; dense AOIs can now persist more candidates. -- The current AOI512 YOLOv8s candidate remains rejected for operational use because precision/recall quality is still too low and low thresholds saturate the configured `1000` cap. -- Next model work should focus on training data coverage, label strategy and post-processing/NMS behavior rather than only threshold lowering. - -## Sprint 147 AOI512 YOLOv8s scale-match candidate gate (2026-07-09) - -Changed: -- Built an alternate operator YOLO dataset at AOI scale instead of small 160px tiles: - - output `/app/storage/operator-data/yolo-building-aoi512-uniquehardneg` - - tile size `512`, stride `512` - - validation samples `turnhout`, `retie`, `westerlo`, `arendonk_heide` - - 16 total images, 13 positive images, 3 negative images, 3172 labels -- Audited the AOI512 dataset: - - output `/mnt/user/appdata/geointel/artifacts/operator-yolo-dataset-audits/aoi512-uniquehardneg/operator_yolo_dataset_quality_audit.json` - - status `ok` - - no missing label files - - no invalid label rows - - 13 positive samples - - 3 positive validation samples - - median normalized box area `0.000793456875` -- Trained a Tower-local YOLOv8s scale-match candidate: - - dataset `/app/storage/operator-data/yolo-building-aoi512-uniquehardneg/dataset.yaml` - - base model `/app/models/yolov8s.pt` - - 80 CPU epochs - - image size `512` - - batch `4` - - artifact `/app/models/geointel-building-yolov8s-aoi512e80.pt` - - model asset id `geointel-building-yolov8s-aoi512e80-pt` - - SHA256 `b796284a13358498c296fa41270dd234a81718a76cdafe62490a5206bb86ac5b` -- The training validation improved versus the previous 160px candidate but remained weak: - - precision `0.404` - - recall `0.270` - - mAP50 `0.163` - - mAP50-95 `0.0505` - -Tested: -- Ran 7-AOI positive calibration sweeps for Geel, Mol, Turnhout, Herentals, Balen, Retie and Westerlo: - - output root `/mnt/user/appdata/geointel/artifacts/detection-calibration/aoi512e80-positive` - - best sample: Westerlo threshold `0.25`, F1 `0.23509933774834438`, precision `0.26296296296296295`, recall `0.2125748502994012`, detections `270` - - most other AOIs remained around F1 `0.10` to `0.14` -- Ran 9-sample hard-negative/background matrix: - - output `/mnt/user/appdata/geointel/artifacts/detection-hard-negatives/aoi512e80/hard_negative_matrix_summary.json` - - threshold `0.25`: total background detections `105`, max sample detections `56` - - threshold `0.15`: total background detections `181`, max sample detections `100` - - threshold `0.05`: total background detections `503`, max sample detections `278` -- Assembled positive evidence portfolio: - - output `/mnt/user/appdata/geointel/artifacts/detection-calibration-portfolio/aoi512e80-positive/calibration_evidence_portfolio.json` - - sample count `7` - - evidence features `17156` -- Ran promotion report: - - output `/mnt/user/appdata/geointel/artifacts/detection-model-promotion/aoi512e80-positive-vs-hard-negative/detection_model_promotion_report.json` - - threshold `0.05`: rejected for `positive_mean_f1_below_gate` and `background_false_positive_pressure`, mean F1 `0.1335249717919908`, max background detections `278` - - threshold `0.15`: rejected for the same reasons, mean F1 `0.1335249717919908`, max background detections `100` - - threshold `0.25`: rejected for the same reasons, mean F1 `0.13511851520077328`, max background detections `56` - - recommended candidate `none` - -Open: -- Do not activate `geointel-building-yolov8s-aoi512e80-pt` as the V1 default. -- AOI-scale training improves the Ultralytics validation curve but does not improve persisted QA/QC enough for operational use. -- The recurring failure mode is overproduction near the 300-detection cap with low recall and too many false positives. -- Next recommended pass: add/export more diverse positive AOIs and improve label quality/geometry-to-box strategy before training another higher-capacity model. A pure scale or epoch change is not enough. - -## Sprint 146 Unique hard-negative YOLOv8s candidate gate (2026-07-09) - -Changed: -- Fixed the all-in-one Docker runtime so `/app/scripts/train_operator_yolo_detector.sh` is copied into the image and made executable. -- Added regression coverage in `backend/tests/test_docker_runtime_config.py` so the all-in-one image must include the operator YOLO training wrapper. -- Hardened `scripts/build_detection_model_promotion_report.py` with explicit `--default-positive-tile-size` and `--default-positive-tile-overlap` options for older positive evidence portfolios that record the model at portfolio level but omit per-run tile provenance. -- Added regression coverage in `backend/tests/test_sprint143_detection_model_promotion_report.py` for portfolio-level model fallback plus explicit positive tile defaults. - -Tested: -- Red step: `python -m pytest backend\tests\test_docker_runtime_config.py::test_all_in_one_dockerfile_copies_operator_scripts_for_runtime_use -q` failed because the all-in-one Dockerfile did not copy the training wrapper. -- `python -m pytest backend\tests\test_docker_runtime_config.py -q` (`22 passed`) -- `bash scripts/run_readiness_check.sh` (`423 passed`; frontend typecheck/build passed; Alembic head `202606120900`) -- Pushed commit `afd2cba` and redeployed Tower with `.\scripts\deploy_tower.ps1 -InstallAi true`; browser runtime verification and live migration smoke passed. -- Verified the wrapper in the live container: `/app/scripts/train_operator_yolo_detector.sh` exists and is executable. -- Trained `geointel-building-yolov8s-uniquehardneg160e50-pt` on Tower from `/app/storage/operator-data/yolo-building-tile-uniquehardneg160/dataset.yaml` using local `/app/models/yolov8s.pt`, 50 CPU epochs, image size `160`, batch `8`. -- Training completed with final validation precision `0.38`, recall `0.365`, mAP50 `0.278`, mAP50-95 `0.0803`. -- Live model asset: - - `/app/models/geointel-building-yolov8s-uniquehardneg160e50.pt` - - model asset id `geointel-building-yolov8s-uniquehardneg160e50-pt` - - SHA256 `c4e480273d3da5fc27532cd8bdc3fa7786582e06848ea11b56714ab8cb1750b3` -- Ran 7-AOI positive calibration sweeps for Geel, Mol, Turnhout, Herentals, Balen, Retie and Westerlo: - - output root `/mnt/user/appdata/geointel/artifacts/detection-calibration/uniquehardneg160e50-positive` - - best observed AOI result: Westerlo threshold `0.25`, F1 `0.384180790960452`, precision `0.5177664974619289`, recall `0.30538922155688625`, detections `197` - - other positive AOIs remained weak, with best F1 roughly `0.10` to `0.17`. -- Assembled positive evidence portfolio: - - output `/mnt/user/appdata/geointel/artifacts/detection-calibration-portfolio/uniquehardneg160e50-positive/calibration_evidence_portfolio.json` - - sample count `7` - - evidence features `17008` - - role counts `false_negative=9710`, `false_positive=4734`, `match_candidate=1282`, `match_reference=1282` -- Ran 9-sample hard-negative/background matrix: - - output `/mnt/user/appdata/geointel/artifacts/detection-hard-negatives/uniquehardneg160e50/hard_negative_matrix_summary.json` - - threshold `0.25`: total background detections `98`, max sample detections `58` - - threshold `0.15`: total background detections `137`, max sample detections `85` - - threshold `0.05`: total background detections `276`, max sample detections `172` -- Red step: `python -m pytest backend\tests\test_sprint143_detection_model_promotion_report.py -q` failed because the promotion report could not yet accept explicit positive tile defaults. -- `python -m pytest backend\tests\test_sprint143_detection_model_promotion_report.py -q` (`2 passed`) -- Rebuilt the promotion report using explicit positive tile defaults: - - output `/mnt/user/appdata/geointel/artifacts/detection-model-promotion/uniquehardneg160e50-positive-vs-hard-negative-v2/detection_model_promotion_report.json` - - threshold `0.05`: rejected for `positive_mean_f1_below_gate` and `background_false_positive_pressure`, mean F1 `0.15797188547918842`, max background detections `172` - - threshold `0.15`: rejected for the same reasons, mean F1 `0.1598974047548654`, max background detections `85` - - threshold `0.25`: rejected for the same reasons, mean F1 `0.15967766715169612`, max background detections `58` - - recommended candidate `none` - -Open: -- Do not activate `geointel-building-yolov8s-uniquehardneg160e50-pt` as the V1 default. -- The candidate improves some individual AOIs but still combines low mean positive F1 with unacceptable false-positive pressure on background samples. -- Next model work should focus on materially better training data/model strategy, not another default activation attempt with this artifact. - -## Sprint 145 YOLOv8s hardneg r8 e60 full candidate evaluation (2026-07-08) - -Changed: -- Verified that the Tower-local YOLOv8s hardneg r8 training run completed all 60 requested CPU epochs. -- Finalized the completed model artifact: - - `/app/models/geointel-building-yolov8s-hardneg160r8e60.pt` - - model asset id `geointel-building-yolov8s-hardneg160r8e60-pt` - - SHA256 `d7daea04bd51a54a06944f0d4bf1961fe453dceb1fb34ef51daa73f6901fca81` -- Wrote `/app/storage/training/operator-yolo/geointel-building-yolov8s-hardneg160r8e60/training_summary.json`. - -Tested: -- Training summary reports `status=ok`, requested epochs `60`, completed epochs `60`. -- Ran 7-AOI positive matrix: - - output `/mnt/user/appdata/geointel/artifacts/detection-quality-matrix/multi-sample/yolov8s-hardneg160r8e60-positive-20260708/multi_sample_quality_summary.json` - - sample count `7` - - run count `21` - - best result: Westerlo threshold `0.15`, F1/score `0.20588235294117646`, precision `0.26666666666666666`, recall `0.16766467065868262`, detections `210`, false positives `154`, false negatives `278`. -- Ran hard-negative matrix: - - output `/mnt/user/appdata/geointel/artifacts/detection-hard-negatives/yolov8s-hardneg160r8e60-live/hard_negative_matrix_summary.json` - - Postel-bos detections `0/0/0` at thresholds `0.05/0.15/0.25` - - Lommel-heide detections `0/0/0` - - Kasterlee-bos detections `30/11/9` -- Assembled evidence portfolio: - - output `/mnt/user/appdata/geointel/artifacts/detection-calibration-portfolio/yolov8s-hardneg160r8e60-positive-20260708/output/calibration_evidence_portfolio.json` - - sample count `7` - - evidence features `15714` - - role counts `false_negative=10468`, `false_positive=4198`, `match_candidate=524`, `match_reference=524` -- Ran promotion report: - - output `/mnt/user/appdata/geointel/artifacts/detection-model-promotion/yolov8s-hardneg160r8e60-20260708/detection_model_promotion_report.json` - - evaluated `3` candidate thresholds - - recommended candidate `none` - - threshold `0.05`: mean F1 `0.07825931710275633`, max background detections `30`, rejected for `positive_mean_f1_below_gate` and `background_false_positive_pressure` - - threshold `0.15`: mean F1 `0.07870592446136859`, max background detections `11`, rejected for the same reasons - - threshold `0.25`: mean F1 `0.06111741186503092`, max background detections `9`, rejected for the same reasons -- Comparison baseline: `geointel-building-yolov8n-expanded160e50-pt|640|64|0.15` had mean F1 `0.19718007234060198` and max background detections `46`. - -Open: -- The e60 YOLOv8s hardneg r8 candidate improves hard-negative behavior at threshold `0.15` compared with `expanded160e50`, but its positive-AOI mean F1 is too low for operational use. -- Do not activate this model as default. -- Next model pass should focus on improving positive recall/fit without losing the hard-negative gains, likely through better labels, more positive AOIs, or a different architecture/training strategy rather than simply extending this same run. - -## Sprint 144 YOLOv8s hardneg r8 partial candidate evaluation (2026-07-08) - -Changed: -- Started a Tower-local YOLOv8s training run using: - - dataset `/app/storage/operator-data/yolo-building-tile-hardneg160r8/dataset.yaml` - - base model `/app/models/yolov8s.pt` - - requested epochs `60` - - image size `640` - - batch `2` - - device `cpu` -- The Codex command reached its 1-hour timeout after 12 completed epochs; the run had produced `weights/best.pt` and `weights/last.pt`. -- Preserved the partial best artifact as `/app/models/geointel-building-yolov8s-hardneg160r8e12partial.pt`. -- Wrote `/app/storage/training/operator-yolo/geointel-building-yolov8s-hardneg160r8e60/training_summary_partial_e12.json`. -- Treated the artifact explicitly as a partial evaluation candidate, not as a completed 60-epoch model. - -Tested: -- Live model catalog listed `geointel-building-yolov8s-hardneg160r8e12partial-pt` with SHA256 `0246202cddc47eb994a0afc9ee10d56b72298bd1cdc0b72b75e12b28e2202330`. -- Ran 7-AOI positive matrix: - - output `/mnt/user/appdata/geointel/artifacts/detection-quality-matrix/multi-sample/yolov8s-hardneg160r8e12partial-positive-20260708/multi_sample_quality_summary.json` - - sample count `7` - - run count `21` - - best result: Westerlo threshold `0.05`, F1/score `0.14826498422712936`, precision `0.15666666666666668`, recall `0.1407185628742515`, detections `300`, false positives `253`, false negatives `287`. -- Ran hard-negative matrix: - - output `/mnt/user/appdata/geointel/artifacts/detection-hard-negatives/yolov8s-hardneg160r8e12partial-live/hard_negative_matrix_summary.json` - - Postel-bos detections `0/0/0` at thresholds `0.05/0.15/0.25` - - Lommel-heide detections `0/0/0` - - Kasterlee-bos detections `18/1/0` -- Assembled evidence portfolio: - - output `/mnt/user/appdata/geointel/artifacts/detection-calibration-portfolio/yolov8s-hardneg160r8e12partial-positive-20260708/output/calibration_evidence_portfolio.json` - - sample count `7` - - evidence features `12908` - - role counts `false_negative=10861`, `false_positive=1785`, `match_candidate=131`, `match_reference=131` -- Ran promotion report: - - output `/mnt/user/appdata/geointel/artifacts/detection-model-promotion/yolov8s-hardneg160r8e12partial-20260708/detection_model_promotion_report.json` - - evaluated `3` candidate thresholds - - recommended candidate `none` - - threshold `0.05` rejected for `positive_mean_f1_below_gate` and `background_false_positive_pressure`, with mean F1 `0.05026994383963278` and max background detections `18` - - threshold `0.15` rejected for the same reasons, with mean F1 `0.0022606965174129354` and max background detections `1` - - threshold `0.25` rejected for insufficient positive evidence and positive F1 below gate. - -Open: -- The partial YOLOv8s r8 candidate is materially worse than the existing `expanded160e50` positive-AOI baseline and must not be activated. -- CPU-only training is too slow for a complete 60-epoch YOLOv8s pass inside a 1-hour interactive command window. -- Next pass should either resume/finish long-running training outside the interactive timeout or use GPU/accelerated runtime; only then rerun the same positive, hard-negative, evidence portfolio and promotion gates. - -## Sprint 143 Detection model promotion decision report (2026-07-08) - -Changed: -- Added `scripts/build_detection_model_promotion_report.py` as operator-only evidence tooling. -- The script combines a positive-AOI `calibration_evidence_portfolio.json` with one or more `hard_negative_matrix_summary.json` files. -- Candidate rows are grouped by `model_asset_id`, `tile_size`, `tile_overlap` and `threshold`. -- Promotion gates are explicit: - - minimum positive sample count - - minimum background sample count - - minimum mean positive F1 - - maximum background detections per sample -- Added readiness `py_compile` coverage for the new script. -- Documented the Tower command in `scripts/README.md`. - -Tested: -- Red step: `python -m pytest backend\tests\test_sprint143_detection_model_promotion_report.py -q` failed because the report script did not exist. -- `python -m pytest backend\tests\test_sprint143_detection_model_promotion_report.py -q` (`1 passed`) -- `python -m pytest backend\tests\test_sprint143_detection_model_promotion_report.py backend\tests\test_sprint139_multi_aoi_calibration_evidence_portfolio.py -q` (`2 passed`) -- `python -m py_compile scripts\build_detection_model_promotion_report.py` -- `python scripts\smoke_docs.py` -- `bash scripts/run_readiness_check.sh` (`419 passed`; frontend typecheck/build passed; Alembic head `202606120900`) -- Tower pulled commit `c2fba67` and generated: - - `/mnt/user/appdata/geointel/artifacts/detection-model-promotion/positive-expanded-vs-hard-negative-20260708/detection_model_promotion_report.json` - - `/mnt/user/appdata/geointel/artifacts/detection-model-promotion/positive-expanded-vs-hard-negative-20260708/detection_model_promotion_report.md` -- Live promotion report evaluated 15 model/tile/threshold candidates and recommended `none`. -- Best current positive candidate `geointel-building-yolov8n-expanded160e50-pt|640|64|0.15` was rejected by gates: - - `positive_mean_f1_below_gate` - - `background_false_positive_pressure` - - positive samples `7` - - background samples `3` - - mean F1 `0.19718007234060198` - - max background detections `46` - - total background detections `46` -- Tower container remained healthy on `0.0.0.0:1202->80/tcp`. - -Open: -- No evaluated model/threshold is ready for default promotion. -- Next model work should improve positive recall/F1 while preserving a strict hard-negative false-positive gate. - -## Sprint 141 Expanded positive-AOI matrix and portfolio metadata hardening (2026-07-08) - -Changed: -- Ran a fresh Tower multi-sample quality matrix for additional positive AOIs `balen`, `herentals` and `westerlo` using: - - `geointel-building-yolov8n-expanded160e50-pt` - - `geointel-building-yolov8n-hardneg160r8e40-pt` - - tile size `640`, overlap `64`, thresholds `0.15` and `0.05`. -- Assembled a broader positive-AOI evidence portfolio across 7 AOIs: - - Geel, Mol, Turnhout and Retie from `expanded160e50-live`. - - Balen, Herentals and Westerlo from the fresh `balen-herentals-westerlo-live-20260708` run. -- Hardened `scripts/export_detection_calibration_evidence.sh` so evidence bundles preserve calibration provenance fields in run summaries and GeoJSON properties: - - `model_asset_id` - - `model_request` - - `tile_size` - - `tile_overlap` -- Extended `backend/tests/test_sprint139_multi_aoi_calibration_evidence_portfolio.py` to assert portfolio best-run model/tile provenance is retained. - -Tested: -- Red step: `python -m pytest backend\tests\test_sprint139_multi_aoi_calibration_evidence_portfolio.py -q` failed with `KeyError: 'model_asset_id'` while bundle summaries dropped model provenance. -- `python -m pytest backend\tests\test_sprint139_multi_aoi_calibration_evidence_portfolio.py -q` (`1 passed`) -- `python -m pytest backend\tests\test_sprint139_multi_aoi_calibration_evidence_portfolio.py backend\tests\test_sprint138_calibration_evidence_bundle_smoke.py backend\tests\test_sprint137_browser_calibration_summary_evidence_script.py backend\tests\test_sprint125_detection_calibration_evidence_bundle.py -q` (`4 passed`) -- `bash -n scripts/export_detection_calibration_evidence.sh` -- `bash -n scripts/assemble_detection_calibration_evidence_portfolio.sh` -- `python -m compileall backend/app` -- `bash scripts/run_readiness_check.sh` (`418 passed`; frontend typecheck/build passed; Alembic head `202606120900`; shell syntax gates passed) -- Tower fresh matrix completed for Balen, Herentals and Westerlo. -- Tower positive-AOI portfolio assembly completed for 7 AOIs. -- Tower runtime remained healthy on `0.0.0.0:1202->80/tcp`. - -Evidence: -- Fresh Balen/Herentals/Westerlo output: `/mnt/user/appdata/geointel/artifacts/detection-quality-matrix/multi-sample/balen-herentals-westerlo-live-20260708/multi_sample_quality_summary.json`. -- Expanded 7-AOI portfolio output: `/mnt/user/appdata/geointel/artifacts/detection-calibration-portfolio/positive-aoi-expanded-20260708/output/calibration_evidence_portfolio.json`. -- Expanded positive-AOI portfolio sample count: `7`. -- Expanded positive-AOI evidence features: `12438`. -- Expanded positive-AOI role counts: `false_negative=9200`, `false_positive=2270`, `match_candidate=484`, `match_reference=484`. -- Best fresh positive-AOI result: Westerlo with `geointel-building-yolov8n-expanded160e50-pt`, threshold `0.05`, F1/score `0.3659305993690852`, precision `0.38666666666666666`, recall `0.3473053892215569`. -- Fresh Balen best: expanded160e50 threshold `0.05`, F1/score `0.16091954022988506`, precision `0.16333333333333333`, recall `0.15857605177993528`. -- Fresh Herentals best: expanded160e50 threshold `0.05`, F1/score `0.14093264248704665`, precision `0.22666666666666666`, recall `0.10225563909774436`. -- Hard-negative context from existing matrices: - - expanded160e50 at `0.05`: Kasterlee-bos `76`, Lommel-heide `10`, Postel-bos `1` detections. - - hardneg160r8e40 at `0.05`: Kasterlee-bos `25`, Lommel-heide `0`, Postel-bos `0` detections. - -Open: -- expanded160e50 is stronger on positive AOIs, especially Westerlo, but still produces many false positives and misses many references. -- hardneg160r8e40 is cleaner on hard-negative AOIs but materially weaker on the fresh positive AOIs. -- No current candidate should be promoted blindly as V1 default without a combined positive/hard-negative decision rule. - -Limitations: -- This pass ran additional live inference/QA workflows and produced operator artifacts, but did not change backend APIs, migrations, frontend runtime behavior, model weights, provider fetching or Docker runtime configuration. -- The 7-AOI portfolio initially generated before the metadata fix lacked model/tile provenance in `best_run_by_score`; it should be regenerated after Tower pulls this commit. - -Next recommended pass: -- Add a model promotion decision report that combines positive-AOI F1/recall and hard-negative false-positive pressure into one explicit accept/reject table per model and threshold. - -## Sprint 140 Live multi-AOI calibration portfolio run (2026-07-08) - -Changed: -- Created a Tower-local `calibration-evidence-portfolio-manifest.json` for existing persisted multi-sample quality matrix summaries: - - Geel: `/mnt/user/appdata/geointel/artifacts/detection-quality-matrix/multi-sample/20260707T025932Z/geel/quality_matrix_summary.json` - - Mol: `/mnt/user/appdata/geointel/artifacts/detection-quality-matrix/multi-sample/20260707T025932Z/mol/quality_matrix_summary.json` - - Turnhout: `/mnt/user/appdata/geointel/artifacts/detection-quality-matrix/multi-sample/20260707T025932Z/turnhout/quality_matrix_summary.json` -- Ran `scripts/assemble_detection_calibration_evidence_portfolio.sh` against the live Tower app at `http://127.0.0.1:1202`. -- Produced the first real multi-AOI calibration evidence handoff: - - `/mnt/user/appdata/geointel/artifacts/detection-calibration-portfolio/live-20260708/output/calibration_evidence_portfolio.json` - - `/mnt/user/appdata/geointel/artifacts/detection-calibration-portfolio/live-20260708/output/calibration_evidence_portfolio.md` - - per-sample `calibration_evidence.geojson`, `calibration_evidence_summary.json` and `calibration_evidence_review.html` artifacts for Geel, Mol and Turnhout. - -Tested: -- Tower manifest validation passed with `python3 -m json.tool`. -- Live portfolio assembly passed against persisted QA evidence from the running app. -- Output validation passed: portfolio JSON/Markdown and all per-sample evidence GeoJSON/summary/review files exist and are non-empty. -- Tower runtime remained healthy on `0.0.0.0:1202->80/tcp`. - -Evidence: -- Portfolio sample count: `3`. -- Total evidence features: `5509`. -- Combined role counts: `false_negative=5239`, `false_positive=164`, `match_candidate=53`, `match_reference=53`. -- Best sample by score: `mol`. -- Best per-sample scores: - - Geel: threshold `0.15`, F1/score `0.0187207488299532`, precision `0.25`, recall `0.009724473257698542`, evidence features `1885`. - - Mol: threshold `0.15`, F1/score `0.04195804195804196`, precision `0.16363636363636364`, recall `0.02406417112299465`, evidence features `1223`. - - Turnhout: threshold `0.15`, F1/score `0.03597122302158273`, precision `0.2459016393442623`, recall `0.019404915912031046`, evidence features `2401`. - -Open: -- The live portfolio confirms the evidence pipeline works, but the evaluated model/threshold set is not yet operational-quality for building extraction due to very low recall and a dominant false-negative count. - -Limitations: -- This pass produced operator artifacts only. It did not rerun inference, mutate application data, change database state, add endpoints, change frontend runtime behavior, download models, train models or rebuild the Docker app. -- The portfolio input came from the existing `20260707T025932Z` quality matrix; the next model review should use fresh matrices when new AOIs or model candidates are added. - -Next recommended pass: -- Add more positive and hard-negative AOIs, then run a fresh multi-sample quality matrix and portfolio for the next model candidate. Do not promote the current evaluated model as a V1 default. - -## Sprint 139 Multi-AOI calibration evidence portfolio (2026-07-08) - -Changed: -- Added `scripts/assemble_detection_calibration_evidence_portfolio.sh` for packaging multiple AOI calibration summaries and their persisted QA evidence bundles into one model-review portfolio. -- The assembler reads `calibration-evidence-portfolio-manifest.json`, copies each AOI summary into a sample folder, runs the existing `scripts/export_detection_calibration_evidence.sh` exporter per sample and writes: - - `calibration_evidence_portfolio.json` - - `calibration_evidence_portfolio.md` -- Added optional `CURL_BIN` support to `scripts/export_detection_calibration_evidence.sh` so operator smokes/tests can inject a deterministic endpoint mock while defaulting to normal `curl`. -- Added readiness syntax coverage and operator docs for the manifest convention. -- Updated `scripts/README.md`, `CHANGELOG.md` and `docs/TODO.md`. -- Added regression coverage in `backend/tests/test_sprint139_multi_aoi_calibration_evidence_portfolio.py`. - -Tested: -- Red step: `python -m pytest backend\tests\test_sprint139_multi_aoi_calibration_evidence_portfolio.py -q` failed while `scripts/assemble_detection_calibration_evidence_portfolio.sh` was absent. -- `python -m pytest backend\tests\test_sprint139_multi_aoi_calibration_evidence_portfolio.py -q` (`1 passed`) -- `python -m pytest backend\tests\test_sprint139_multi_aoi_calibration_evidence_portfolio.py backend\tests\test_sprint138_calibration_evidence_bundle_smoke.py backend\tests\test_sprint137_browser_calibration_summary_evidence_script.py backend\tests\test_sprint125_detection_calibration_evidence_bundle.py -q` (`4 passed`) -- `bash -n scripts/assemble_detection_calibration_evidence_portfolio.sh` -- `bash scripts/assemble_detection_calibration_evidence_portfolio.sh --help` -- `bash -n scripts/export_detection_calibration_evidence.sh` -- `bash scripts/export_detection_calibration_evidence.sh --help` -- `python -m compileall backend/app` -- `bash scripts/run_readiness_check.sh` (`418 passed`; frontend typecheck/build passed; Alembic head `202606120900`; shell syntax gates passed) - -Open: -- None for this pass. - -Limitations: -- This is local/operator evidence packaging only. It does not run inference, call live production data by itself, mutate application data, add backend endpoints, change migrations, create QA metrics, promote thresholds, download models, add provider fetching or change frontend runtime behavior. -- The regression test uses mocked canonical QA evidence responses; real persisted QA evidence remains validated by running the portfolio assembler against live Detection Lab or calibration-sweep summaries. - -Next recommended pass: -- Run the portfolio assembler against the existing Tower calibration summaries for at least two real AOIs, then use the portfolio JSON/Markdown as the first model-review handoff artifact before any further training or threshold promotion. - -## Sprint 138 Browser calibration evidence bundle smoke (2026-07-08) - -Changed: -- Added `scripts/smoke_detection_calibration_evidence_bundle.sh` as a local operator smoke for the Detection Lab `detection-calibration-summary.json` to QA evidence bundle path. -- The smoke creates a temporary browser-style calibration summary, injects a temporary mock `curl` for canonical QA evidence endpoint responses, runs the real `scripts/export_detection_calibration_evidence.sh` exporter and validates the generated GeoJSON, summary JSON and HTML review artifacts. -- Added readiness syntax coverage for the smoke script. -- Updated `scripts/README.md`, `CHANGELOG.md` and `docs/TODO.md`. -- Added regression coverage in `backend/tests/test_sprint138_calibration_evidence_bundle_smoke.py`. - -Tested: -- Red step: `python -m pytest backend\tests\test_sprint138_calibration_evidence_bundle_smoke.py -q` failed while `scripts/smoke_detection_calibration_evidence_bundle.sh` was absent. -- `python -m pytest backend\tests\test_sprint138_calibration_evidence_bundle_smoke.py -q` (`1 passed`) -- `python -m pytest backend\tests\test_sprint138_calibration_evidence_bundle_smoke.py backend\tests\test_sprint137_browser_calibration_summary_evidence_script.py backend\tests\test_sprint125_detection_calibration_evidence_bundle.py -q` (`3 passed`) -- `bash -n scripts/smoke_detection_calibration_evidence_bundle.sh` -- `bash scripts/smoke_detection_calibration_evidence_bundle.sh --help` -- `python -m compileall backend/app` -- `bash scripts/run_readiness_check.sh` (`417 passed`; frontend typecheck/build passed; Alembic head `202606120900`; shell syntax gates passed) -- Pushed commit `47d3587` to `main`. -- Tower repo fast-forwarded to `47d3587`; `bash -n scripts/smoke_detection_calibration_evidence_bundle.sh` passed on Tower. -- Tower operator smoke passed: `bash scripts/smoke_detection_calibration_evidence_bundle.sh` wrote mocked evidence artifacts under `/mnt/user/appdata/geointel/artifacts/detection-calibration-smoke/20260708T115724Z/evidence` with 4 evidence features across matched candidate, matched reference, false positive and false negative roles. -- Tower runtime remained healthy on `0.0.0.0:1202->80/tcp`; no app rebuild was required because this pass changed operator scripts/docs/tests only. - -Open: -- None for this pass. - -Limitations: -- This is local/operator evidence tooling only. It does not call live production data, mutate application data, add backend endpoints, change migrations, rerun inference, create QA metrics, promote thresholds, download models, add provider fetching or change frontend runtime behavior. -- The smoke uses mocked canonical evidence responses by design; real persisted QA evidence is still validated by running `export_detection_calibration_evidence.sh` against a live browser or sweep summary. - -Next recommended pass: -- Add a real multi-AOI calibration evidence capture convention: one folder per AOI/model/threshold matrix with browser summary, evidence bundle and operator notes, so model promotion decisions are based on comparable persisted artifacts rather than isolated runs. - -## Sprint 137 Browser calibration summary evidence bundle handoff (2026-07-08) - -Changed: -- Extended `scripts/export_detection_calibration_evidence.sh` so it can consume Detection Lab `detection-calibration-summary.json` browser exports as well as the existing operator `calibration_summary.json` format. -- Added summary normalization for browser-exported `rows`, root `project_id`, persisted `quality_check_id` values and `CALIBRATION_EVIDENCE_MODE=best` fallback selection. -- Updated `scripts/README.md`, `CHANGELOG.md` and `docs/TODO.md`. -- Added regression coverage in `backend/tests/test_sprint137_browser_calibration_summary_evidence_script.py`. - -Tested: -- Red step: `python -m pytest backend\tests\test_sprint137_browser_calibration_summary_evidence_script.py -q` failed while browser summary support was absent. -- `python -m pytest backend\tests\test_sprint137_browser_calibration_summary_evidence_script.py backend\tests\test_sprint136_calibration_summary_export_ui.py backend\tests\test_sprint125_detection_calibration_evidence_bundle.py -q` (`3 passed`) -- `bash -n scripts/export_detection_calibration_evidence.sh` -- `python -m compileall backend/app` -- `bash scripts/run_readiness_check.sh` (`416 passed`; frontend typecheck/build passed; Alembic head `202606120900`; live smoke syntax passed) -- Tower deploy from commit `673f6c6` completed with `GEOINTEL_INSTALL_AI=true`; the all-in-one container is healthy and published on `0.0.0.0:1202->80/tcp`. -- Deploy-time live migration smoke passed after the database became ready on attempt 4; PostGIS reported `3.6 USE_GEOS=1 USE_PROJ=1 USE_STATS=1`, required runtime schema objects were present and Alembic head was `202606120900`. -- Deploy-time browser runtime verification passed for frontend, API proxy and icon after one readiness retry. -- Live container check passed: `docker ps --filter name=geointel` reported `geointel` as healthy on `0.0.0.0:1202->80/tcp`. -- Live YOLO preflight passed with local model configured, dependencies available, `torch_version=2.12.1`, `ultralytics_version=8.4.90`, `will_download_models=false`, `will_run_inference=false` and `status=manifest_unavailable` because no tile manifest was supplied. - -Open: -- None for this pass. - -Limitations: -- This is operator evidence tooling only. It does not add backend endpoints, change migrations, rerun inference, create new QA metrics, promote thresholds, mutate model configuration, download models, add provider fetching or change frontend runtime behavior. - -Next recommended pass: -- Add a tiny local fixture smoke for the evidence bundle script that uses a saved browser-style summary plus mocked canonical evidence responses, so the bundle renderer itself is tested beyond static contract checks. - -## Sprint 136 Guided calibration summary export (2026-07-08) - -Changed: -- Added a `Download calibration summary` action to the guided Detection Lab calibration progress table. -- The client-side JSON export includes calibration thresholds, persisted `analysis_run_id`, `job_id`, `quality_check_id`, metric values and QA evidence GeoJSON URLs. -- Added compact action-row styling and regression coverage in `backend/tests/test_sprint136_calibration_summary_export_ui.py`. -- Updated `CHANGELOG.md` and `docs/TODO.md`. - -Tested: -- Red step: `python -m pytest backend\tests\test_sprint136_calibration_summary_export_ui.py -q` failed while the summary export helpers and button were absent. -- `python -m pytest backend\tests\test_sprint136_calibration_summary_export_ui.py backend\tests\test_sprint135_calibration_evidence_handoff.py backend\tests\test_sprint134_guided_detection_calibration_runner.py -q` (`3 passed`) -- `python -m compileall backend/app` -- `cd frontend && npm run typecheck` -- `cd frontend && npm run build` -- `bash scripts/run_readiness_check.sh` (`415 passed`; frontend typecheck/build passed; Alembic head `202606120900`; live smoke syntax passed) -- Tower deploy from commit `8089df3` completed with `GEOINTEL_INSTALL_AI=true`; the all-in-one container is published on `0.0.0.0:1202->80/tcp`. -- Deploy-time live migration smoke passed after the database became ready on attempt 2; PostGIS reported `3.6 USE_GEOS=1 USE_PROJ=1 USE_STATS=1`, required runtime schema objects were present and Alembic head was `202606120900`. -- Deploy-time browser runtime verification passed for frontend, API proxy and icon. -- Live bundle check passed: `Download calibration summary` is present in `assets/index-5CClxMR_.js`. -- Live YOLO preflight passed with local model configured, dependencies available, `will_download_models=false`, `will_run_inference=false` and `status=manifest_unavailable` because no tile manifest was supplied. - -Open: -- None for this pass. - -Limitations: -- This is a browser-side summary export only. It does not create server-side export records, rerun inference, create new QA metrics, promote thresholds, mutate model configuration, download models, add provider fetching or change API/database contracts. - -Next recommended pass: -- Add a small import/consume path for downloaded calibration summaries in the existing operator evidence bundle script, so browser-exported summary JSON can be used directly from an operator workstation. - -## Sprint 135 Calibration evidence handoff (2026-07-08) - -Changed: -- Added an `Open evidence map` action to successful guided detection calibration rows. -- Wired the Detection Lab action to the existing `openQualityEvidenceOnMap` flow, which loads persisted QA/QC evidence GeoJSON and opens the Map workspace overlay. -- Added compact table action styling and regression coverage in `backend/tests/test_sprint135_calibration_evidence_handoff.py`. -- Updated `CHANGELOG.md` and `docs/TODO.md`. - -Tested: -- Red step: `python -m pytest backend\tests\test_sprint135_calibration_evidence_handoff.py -q` failed while the Detection Lab evidence handoff prop was absent. -- `python -m pytest backend\tests\test_sprint135_calibration_evidence_handoff.py backend\tests\test_sprint134_guided_detection_calibration_runner.py backend\tests\test_sprint133_detection_threshold_calibration_ux.py backend\tests\test_sprint112_qa_evidence_overlay.py -q` (`7 passed`) -- `python -m compileall backend/app` -- `cd frontend && npm run typecheck` -- `cd frontend && npm run build` -- `bash scripts/run_readiness_check.sh` (`414 passed`; frontend typecheck/build passed; Alembic head `202606120900`; live smoke syntax passed) -- Tower deploy from commit `0c826ef` completed with `GEOINTEL_INSTALL_AI=true`; the all-in-one container is published on `0.0.0.0:1202->80/tcp`. -- Deploy-time live migration smoke passed after the database became ready on attempt 2; PostGIS reported `3.6 USE_GEOS=1 USE_PROJ=1 USE_STATS=1`, required runtime schema objects were present and Alembic head was `202606120900`. -- Deploy-time browser runtime verification passed for frontend, API proxy and icon. - -Open: -- None for this pass. - -Limitations: -- This pass adds review handoff only. It does not create new QA metrics, promote thresholds, mutate model configuration, download models, add provider fetching or change API/database contracts. - -Next recommended pass: -- Add an operator-facing calibration evidence summary/export shortcut once the map handoff has been used on real AOI runs. - -## Sprint 134 External remote-sensing YOLO candidate benchmark (2026-07-07) - -Changed: -- Added no production code and no repository-stored model weights. -- Evaluated the Hugging Face `agademer/yolo-remote-sensing-photovoltaic` model card as a candidate because it explicitly targets remote-sensing imagery and includes `building` as a class. -- Downloaded the YOLOv8l detection checkpoint manually as an operator/runtime asset: - - source model: `agademer/yolo-remote-sensing-photovoltaic` - - source file: `yolo-remote-sensing-photovoltaic-v8l-solar-farms-and-cities-v20260331-detect-1000_epochs.pt` - - runtime file: `/app/models/yolo-remote-sensing-photovoltaic-v8l-detect-1000.pt` - - catalog asset: `yolo-remote-sensing-photovoltaic-v8l-detect-1000-pt` - - SHA256: `242ff4ab889569278f0eb9fcd22eb2c4bf2a52e48d05d89cc7cfa7941165d203` -- Updated `scripts/README.md`, `docs/TODO.md`, `docs/CODEX_EXECUTION_LOG.md` and `CHANGELOG.md` with benchmark evidence and the decision not to promote this model. - -Tested: -- Live API preflight passed for `yolo-remote-sensing-photovoltaic-v8l-detect-1000-pt` with `status=ready`, `model_load_ok=true`, `manifest_valid=true`, `tile_paths_exist=true`, `will_download_models=false` and `will_run_inference=false`. -- Live 45-run multi-sample QA matrix completed: - - output: `/mnt/user/appdata/geointel/artifacts/detection-quality-matrix/multi-sample/remote-sensing-v8l1000-live/multi_sample_quality_summary.json` - - command compared `yolo-remote-sensing-photovoltaic-v8l-detect-1000-pt`, `geointel-building-yolov8n-expanded160e50-pt` and `geointel-building-yolov8n-hardneg160r8e40-pt` over Geel, Mol, Turnhout, Retie and Kasterlee-bos with tile `640`, overlap `64`, thresholds `0.25`/`0.15`/`0.05`. - - dense-sample results for the external candidate: - - Geel: best F1 `0.0` - - Mol: best F1 `0.010582010582010581` - - Turnhout: best F1 `0.019070321811680575` - - Retie: best F1 `0.0` - - Kasterlee-bos sparse result: best F1 `0.25` with 1 detection, 1 match and 0 false positives at thresholds `0.25`/`0.15`. - - dense-sample winner remained `geointel-building-yolov8n-expanded160e50-pt`. -- Live 27-run hard-negative matrix completed: - - output: `/mnt/user/appdata/geointel/artifacts/detection-hard-negatives/remote-sensing-v8l1000-live/hard_negative_matrix_summary.json` - - Postel-bos: external candidate produced 0/1/3 detections at thresholds `0.25`/`0.15`/`0.05`. - - Lommel-heide: external candidate produced 0/0/0 detections. - - Kasterlee-bos: external candidate produced 1/2/5 detections, cleaner than expanded160e50 and hardneg160r8e40 on that sparse AOI. - -Open: -- None for this benchmark pass. - -Limitations: -- The external model is very conservative on the current Kempen orthophoto/GRB benchmark and misses most dense buildings. -- It may be useful as evidence for a high-precision/sparse-review mode, but it is not a viable V1 default extraction model. -- The runtime `.pt` remains outside Git and must be managed as an operator asset. - -Next recommended pass: -- Train a higher-capacity local detector from a stronger base model using the existing operator tile dataset, then gate it with both dense QA and hard-negative matrices before any model default changes. - -## Sprint 133 Hard-negative-balanced YOLO candidate (2026-07-07) - -Changed: -- Hardened `scripts/export_operator_yolo_tile_dataset.py` with deterministic train-only background-negative repetition through `--background-negative-repeat` and `OPERATOR_YOLO_BACKGROUND_NEGATIVE_REPEAT`. -- Background-negative repetition applies only when `is_negative=true`, `sample_role=background_candidate` and `split=train`; validation tiles, positive tiles and normal reference samples are not duplicated. -- Added tile-level provenance fields `sample_role`, `repeat_index` and `is_repeated_background_negative`. -- Added regression coverage in `backend/tests/test_sprint130_operator_yolo_tile_dataset.py`. -- Updated `scripts/README.md`, `docs/TODO.md`, `docs/CODEX_EXECUTION_LOG.md` and `CHANGELOG.md`. - -Tested: -- RED: `python -m pytest backend\tests\test_sprint130_operator_yolo_tile_dataset.py -q` failed before `--background-negative-repeat` and `background_negative_repeat_count` existed. -- `python -m pytest backend\tests\test_sprint130_operator_yolo_tile_dataset.py -q` passed. -- `python -m py_compile scripts\export_operator_yolo_tile_dataset.py` passed. -- `python scripts\export_operator_yolo_tile_dataset.py --help` passed. -- Live Tower hard-negative-balanced tile export passed: - - dataset: `/app/storage/operator-data/yolo-building-tile-hardneg160r8` - - source samples: 10 - - tile size: `160` - - stride: `80` - - negative keep ratio: `1.0` - - background negative repeat: `8` - - exported tiles: `864` - - positive tiles: `260` - - negative tiles: `604` - - labels: `11213` - - train tiles: `756` - - validation tiles: `108` -- Live Tower 40-epoch CPU training passed: - - output model: `/app/models/geointel-building-yolov8n-hardneg160r8e40.pt` - - catalog asset: `geointel-building-yolov8n-hardneg160r8e40-pt` - - SHA256: `7a77bd9f68e4c3927ffc8a8cd978a81067b02f42cffe77ada5334b5f8dbb6b50` - - final validation: precision `0.403`, recall `0.378`, mAP50 `0.301`, mAP50-95 `0.0944` -- Live API preflight passed for `geointel-building-yolov8n-hardneg160r8e40-pt` with `status=ready`, `model_load_ok=true`, `manifest_valid=true`, `tile_paths_exist=true`, `will_download_models=false` and `will_run_inference=false`. -- Live 60-run multi-sample QA matrix completed: - - output: `/mnt/user/appdata/geointel/artifacts/detection-quality-matrix/multi-sample/hardneg160r8e40-live/multi_sample_quality_summary.json` - - command compared `geointel-building-yolov8n-hardneg160r8e40-pt`, `geointel-building-yolov8n-expanded160e50-pt`, `geointel-building-yolov8n-tile30-pt` and `yolov8s-building-segmentation-pt` over Geel, Mol, Turnhout, Retie and Kasterlee-bos with tile `640`, overlap `64`, thresholds `0.25`/`0.15`/`0.05`. - - best overall score and recall remained Geel with `geointel-building-yolov8n-expanded160e50-pt`, precision `0.30333333333333334`, recall `0.14748784440842788`, F1 `0.1984732824427481`. - - hardneg160r8e40 dense F1 lagged expanded160e50 on Geel (`0.14394765539803708` vs `0.1984732824427481`), Mol (`0.11572700296735906` vs `0.1651651651651652`), Turnhout (`0.14911463187325258` vs `0.1938490214352283`) and Retie (`0.10538116591928251` vs `0.1569506726457399`). -- Live 36-run hard-negative matrix completed: - - output: `/mnt/user/appdata/geointel/artifacts/detection-hard-negatives/hardneg160r8e40-live/hard_negative_matrix_summary.json` - - Postel-bos: hardneg160r8e40 produced 0/0/0 detections at thresholds `0.25`/`0.15`/`0.05`; expanded160e50 produced 0/0/1. - - Lommel-heide: hardneg160r8e40 produced 0/0/0 detections; expanded160e50 produced 0/0/10. - - Kasterlee-bos: hardneg160r8e40 produced 5/9/25 detections; expanded160e50 produced 38/46/76. - -Open: -- None for the hard-negative-balanced tile export contract itself. - -Limitations: -- `geointel-building-yolov8n-hardneg160r8e40-pt` reduced false-positive pressure but regressed dense-AOI recall/F1. It should not become the V1 default. -- This remains operator tooling only. It does not add Training Studio, browser training controls, provider fetching, fake detections, model auto-provisioning or API contract changes. - -Next recommended pass: -- Train or import a materially stronger aerial/Kempen building model candidate, then benchmark it against the same dense QA and hard-negative matrices before changing default model selection. - -## Sprint 132 Operator hard-negative detection matrix (2026-07-07) - -Changed: -- Added `scripts/run_operator_hard_negative_detection_matrix.sh`. -- The script reads `operator_samples_manifest.json`, selects samples marked `background_candidate` or `allow_empty_reference`, uploads only the raster, generates a tile manifest, checks configured-YOLO preflight, runs `POST /api/v1/detection/run` and counts persisted detections. -- It intentionally does not upload reference vectors and does not call detection QA/QC endpoints, because background AOIs have no meaningful reference target. -- Added readiness shell-syntax coverage for the new script. -- Added regression coverage in `backend/tests/test_sprint132_operator_hard_negative_matrix.py`. -- Updated `scripts/README.md`, `docs/TODO.md` and `CHANGELOG.md`. - -Tested: -- RED: `python -m pytest backend\tests\test_sprint132_operator_hard_negative_matrix.py -q` failed while `scripts/run_operator_hard_negative_detection_matrix.sh` did not exist. -- `python -m pytest backend\tests\test_sprint132_operator_hard_negative_matrix.py -q` passed. -- `bash -n scripts/run_operator_hard_negative_detection_matrix.sh` passed. -- Live Tower 27-run hard-negative matrix completed: - - output: `/mnt/user/appdata/geointel/artifacts/detection-hard-negatives/expanded160e50-live/hard_negative_matrix_summary.json` - - samples: Postel-bos, Lommel-heide and Kasterlee-bos - - models: `geointel-building-yolov8n-expanded160e50-pt`, `geointel-building-yolov8n-tile30-pt`, `yolov8s-building-segmentation-pt` - - tile size: `640` - - overlap: `64` - - thresholds: `0.25`, `0.15`, `0.05` -- Live false-positive pressure results: - - Postel-bos: expanded160e50 produced 0 detections at `0.25`/`0.15`, 1 at `0.05`; tile30 produced 0/0/1; yolov8s produced 0/3/6. - - Lommel-heide: expanded160e50 produced 0 detections at `0.25`/`0.15`, 10 at `0.05`; tile30 produced 0/0/3; yolov8s produced 0/0/0. - - Kasterlee-bos: expanded160e50 produced 38/46/76 detections at `0.25`/`0.15`/`0.05`; tile30 produced 15/22/42; yolov8s produced 5/6/7. - -Open: -- None for the hard-negative matrix tooling itself. - -Limitations: -- Background matrix scores false-positive pressure from detection counts only. It does not calculate precision/recall/F1 because background candidates intentionally do not provide a full reference target. -- Kasterlee-bos still has 7 GRB features and is best interpreted as a sparse/hard-negative AOI, not a purely empty background tile. -- `geointel-building-yolov8n-expanded160e50-pt` should not be promoted to default model while Kasterlee-bos false-positive pressure remains high. - -Next recommended pass: -- Train a hard-negative-balanced candidate: oversample sparse/background tiles, lower the dense-AOI max-detection bias, and rerun both dense QA matrix and hard-negative matrix before changing any default model selection. - -## Sprint 131 Operator sample expansion and negative-tile YOLO candidate (2026-07-07) - -Changed: -- Extended `scripts/prepare_operator_real_data_samples.py` with `sample_role` and `allow_empty_reference`. -- Added reference AOIs for Herentals, Balen, Retie and Westerlo. -- Added background-candidate AOIs for Postel-bos, Lommel-heide and Kasterlee-bos. Background candidates can persist empty GRB FeatureCollections for negative-tile training, while normal reference samples still fail on empty GRB results. -- Added regression coverage in `backend/tests/test_sprint131_operator_sample_expansion.py`. -- Updated `scripts/README.md`, `backend/README.md`, `docs/AI_PIPELINES.md`, `docs/TODO.md` and `CHANGELOG.md`. - -Tested: -- RED: `python -m pytest backend\tests\test_sprint131_operator_sample_expansion.py -q` failed before the new sample metadata and background candidates existed. -- `python -m pytest backend\tests\test_sprint131_operator_sample_expansion.py -q` passed. -- `python -m py_compile scripts\prepare_operator_real_data_samples.py` passed. -- `python scripts\prepare_operator_real_data_samples.py --help` passed. -- Live Tower operator sample preparation passed: - - manifest: `/app/storage/operator-data/operator_samples_manifest.json` - - samples: Geel `617`, Mol `374`, Turnhout `773`, Herentals `665`, Balen `309`, Retie `592`, Westerlo `334`, Postel-bos `0`, Lommel-heide `0`, Kasterlee-bos `7` reference features. -- Live Tower expanded tile export passed: - - dataset: `/app/storage/operator-data/yolo-building-tile-expanded160` - - tile size: `160` - - stride: `80` - - exported tiles: `360` - - positive tiles: `260` - - negative tiles: `100` - - labels: `11213` - - train tiles: `252` - - validation tiles: `108` -- Live Tower 50-epoch CPU training passed: - - output model: `/app/models/geointel-building-yolov8n-expanded160e50.pt` - - catalog asset: `geointel-building-yolov8n-expanded160e50-pt` - - SHA256: `bf6a5e8d25a62d784ee53764ea11d7ce89c4e7aeeac7588010e497b8d7dafb2b` - - final validation: precision `0.428`, recall `0.389`, mAP50 `0.318`, mAP50-95 `0.106` -- Live API preflight passed for `geointel-building-yolov8n-expanded160e50-pt` with `status=ready`, `model_load_ok=true`, `manifest_valid=true`, `tile_paths_exist=true`, `will_download_models=false` and `will_run_inference=false`. -- Live 45-run multi-sample QA matrix completed: - - output: `/mnt/user/appdata/geointel/artifacts/detection-quality-matrix/multi-sample/expanded160e50-live/multi_sample_quality_summary.json` - - command compared `geointel-building-yolov8n-expanded160e50-pt`, `geointel-building-yolov8n-tile30-pt` and `yolov8s-building-segmentation-pt` over Geel, Mol, Turnhout, Retie and Kasterlee-bos with tile `640`, overlap `64`, thresholds `0.25`/`0.15`/`0.05`. - - best overall score and recall: Geel, `geointel-building-yolov8n-expanded160e50-pt`, tile `640`, threshold `0.05`, 300 detections, 91 matches, 209 false positives, 526 false negatives, precision `0.30333333333333334`, recall `0.14748784440842788`, F1 `0.1984732824427481`. - - dense-sample score winners: Geel, Mol, Turnhout and Retie all selected `geointel-building-yolov8n-expanded160e50-pt`. - - hard-negative/sparse-sample winner: Kasterlee-bos selected `yolov8s-building-segmentation-pt`, threshold `0.25`, F1 `0.16666666666666666`; the expanded local model produced too many false positives there. - -Open: -- None for the sample-preparation and expanded-training runtime proof itself. - -Limitations: -- This remains operator tooling only. It does not add Training Studio, browser training controls, provider fetching, fake detections, model auto-provisioning or API contract changes. -- `geointel-building-yolov8n-expanded160e50-pt` is the best tested candidate on dense operator AOIs, but it is still experimental and should not become the V1 default until hard-negative false positives improve. -- The next model pass should add more sparse/background AOIs, tune confidence/NMS/max-detection settings and compare a stronger architecture or longer run against the same persisted QA matrix. - -Next recommended pass: -- Build a hard-negative model-quality pass: expand sparse/background AOIs, export a balanced tile dataset, train a stronger candidate, and rerun the multi-sample QA matrix with dense and background samples scored separately. - -## Sprint 130 Operator YOLO tile-level dataset tooling (2026-07-07) - -Changed: -- Added `scripts/export_operator_yolo_tile_dataset.py`. -- The exporter reads `operator_samples_manifest.json`, opens each raster/reference pair, creates overlapping tile windows, clips GRB building bounding boxes into tile-local YOLO labels, writes `dataset.yaml`, and reports `yolo_tile_dataset_summary.json`. -- Added deterministic negative tile retention through `negative_keep_ratio`. -- Added readiness compile coverage for the tile exporter. -- Added regression coverage in `backend/tests/test_sprint130_operator_yolo_tile_dataset.py`. -- Updated `scripts/README.md`, `backend/README.md`, `docs/AI_PIPELINES.md`, `docs/TODO.md` and `CHANGELOG.md`. - -Tested: -- RED: `python -m pytest backend\tests\test_sprint130_operator_yolo_tile_dataset.py -q` failed while `scripts/export_operator_yolo_tile_dataset.py` did not exist. -- `python -m pytest backend\tests\test_sprint130_operator_yolo_tile_dataset.py -q` passed. -- `python scripts\export_operator_yolo_tile_dataset.py --help` passed without requiring local GIS dependencies. -- `python -m py_compile scripts\export_operator_yolo_tile_dataset.py` passed. -- Live Tower tile export passed: - - dataset: `/app/storage/operator-data/yolo-building-tile-dataset` - - samples: Geel, Mol and Turnhout - - tile size: `192` - - stride: `96` - - exported tiles: `75` - - positive tiles: `75` - - labels: `5321` - - validation split: Turnhout -- Live Tower 30-epoch CPU tile training passed: - - output model: `/app/models/geointel-building-yolov8n-tile30.pt` - - catalog asset: `geointel-building-yolov8n-tile30-pt` - - SHA256: `b9e228202500d7c85836d12a72e320f4f2f0cef24cbb1b5bf7fa78a6778390af` - - final validation: precision `0.208`, recall `0.271`, mAP50 `0.122`, mAP50-95 `0.0308` -- Live API preflight passed for `geointel-building-yolov8n-tile30-pt` with `status=ready`, `model_load_ok=true`, `manifest_valid=true`, `tile_paths_exist=true`, `will_download_models=false` and `will_run_inference=false`. -- Live 48-run multi-sample QA matrix completed: - - output: `/mnt/user/appdata/geointel/artifacts/detection-quality-matrix/multi-sample/20260707T190720Z/multi_sample_quality_summary.json` - - command compared `geointel-building-yolov8n-tile30-pt` with `yolov8s-building-segmentation-pt` over Geel, Mol and Turnhout, tile sizes `512`/`640`, overlap `64`, thresholds `0.50`/`0.25`/`0.15`/`0.05`. - - best overall score: Mol, `geointel-building-yolov8n-tile30-pt`, tile `640`, threshold `0.15`, 272 detections, 37 matches, 235 false positives, 337 false negatives, precision `0.13602941176470587`, recall `0.09893048128342247`, F1 `0.11455108359133127`. - - best overall recall: Mol, `geointel-building-yolov8n-tile30-pt`, tile `512`, threshold `0.05`, 544 detections, 44 matches, 500 false positives, 330 false negatives, precision `0.08088235294117647`, recall `0.11764705882352941`, F1 `0.09586056644880174`. - - best overall precision: Turnhout, `yolov8s-building-segmentation-pt`, tile `640`, threshold `0.25`, precision `0.4`, recall `0.01034928848641656`, F1 `0.0201765447667087`. - - per-sample score winners: Geel `geointel-building-yolov8n-tile30-pt` F1 `0.09671179883945842`; Mol `geointel-building-yolov8n-tile30-pt` F1 `0.11455108359133127`; Turnhout `yolov8s-building-segmentation-pt` F1 `0.09971777986829727`. - -Open: -- None for the tile exporter/training runtime proof itself. - -Limitations: -- This remains operator tooling only. It does not add Training Studio, browser training controls, provider fetching, fake detections, model auto-provisioning or API contract changes. -- `geointel-building-yolov8n-tile30-pt` is an experimental local candidate, not a V1 default. It improves the operator-trained baseline materially but still has low recall and many false positives on the current 3-sample corpus. -- The current corpus is too small and all exported tiles were positive; the next model pass needs more AOIs and deliberate negative/background tiles. - -Next recommended pass: -- Expand the operator sample corpus beyond Geel/Mol/Turnhout, include negative/background AOIs, regenerate the tile dataset, then train a longer/larger local model candidate and rerun the same persisted QA matrix. - -## Sprint 129 Operator YOLO training dataset tooling (2026-07-07) - -Changed: -- Added `scripts/export_operator_yolo_dataset.py` to export prepared operator samples into a local YOLO detection dataset: - - input manifest: `operator_samples_manifest.json` - - output: `dataset.yaml`, `images/train`, `labels/train`, `images/val`, `labels/val`, `yolo_dataset_summary.json` - - labels are derived from GRB building references with `source_name=grb` and `reference_layer_name=buildings`. -- Added `scripts/train_operator_yolo_detector.sh` as an explicit operator/runtime wrapper around a local Ultralytics training smoke: - - requires `OPERATOR_YOLO_DATASET_DIR` - - requires an existing `YOLO_BASE_MODEL_PATH` - - writes a local `TRAIN_MODEL_OUTPUT_PATH` - - uses `PYTHON_BIN=python3` by default for the all-in-one container - - writes `training_summary.json`. -- Added readiness coverage for exporter compile and train-wrapper shell syntax. -- Added regression coverage in `backend/tests/test_sprint129_operator_yolo_training_dataset.py`. -- Updated `scripts/README.md`, `backend/README.md`, `docs/AI_PIPELINES.md`, `docs/TODO.md` and `CHANGELOG.md`. - -Tested: -- RED: `python -m pytest backend\tests\test_sprint129_operator_yolo_training_dataset.py -q` failed while the exporter and training wrapper contracts were incomplete. -- `python -m pytest backend\tests\test_sprint129_operator_yolo_training_dataset.py -q` passed. -- `python scripts\export_operator_yolo_dataset.py --help` passed without requiring local GIS dependencies. -- `python -m py_compile scripts\export_operator_yolo_dataset.py` passed. -- `bash -n scripts/train_operator_yolo_detector.sh` passed. -- Live Tower export passed: `/app/storage/operator-data/yolo-building-dataset` contains 3 images and 1427 labels from the current Geel/Mol/Turnhout samples. -- Live Tower training smoke passed with the existing `/app/models/yolov8n.pt` base model and wrote `/app/models/geointel-building-yolov8n-smoke.pt`. -- The first live smoke showed Ultralytics fetching an auxiliary plot font. The wrapper now sets `plots=False` and seeds `Arial.ttf` from an existing local system font before importing Ultralytics so the operator smoke path does not invoke plot/font network behavior. -- Full local readiness passed after the final wrapper hardening: `bash scripts/run_readiness_check.sh` ran 396 backend tests, frontend typecheck/build, Alembic head and smoke syntax checks. -- Pushed commits through `3936768` to Gitea and reset Tower `/mnt/user/appdata/geointel` to the same commit. -- Live Tower no-font smoke passed after deleting `/app/storage/ultralytics/Ultralytics/Arial.ttf`; the wrapper seeded the font locally and the 1-epoch run completed without the previous font fetch line. -- Live Tower final 8-epoch training smoke passed: - - output model: `/app/models/geointel-building-yolov8n-operator8.pt` - - catalog asset: `geointel-building-yolov8n-operator8-pt` - - SHA256: `071d64c89a8fd28f915f7a5a553e2d164942721292693a1612c725284c6e2e1e` - - training summary: `/app/storage/training/operator-yolo/geointel-building-yolov8n-operator8/training_summary.json`. -- Live API preflight passed for `geointel-building-yolov8n-operator8-pt` with `status=ready`, `model_load_ok=true`, `manifest_valid=true`, `tile_paths_exist=true`, `will_download_models=false` and `will_run_inference=false`. -- Live 36-run multi-sample QA matrix completed: - - command compared `geointel-building-yolov8n-operator8-pt` with `yolov8s-building-segmentation-pt` over Geel, Mol and Turnhout, tile sizes `512`/`640`, thresholds `0.50`/`0.25`/`0.15`. - - output: `/mnt/user/appdata/geointel/artifacts/detection-quality-matrix/multi-sample/20260707T033048Z/multi_sample_quality_summary.json`. - - `geointel-building-yolov8n-operator8-pt` produced zero detections for every sample/tile combination at thresholds `0.15` through `0.50`. - - best overall remained `yolov8s-building-segmentation-pt` on Mol, tile `640`, threshold `0.15`: 55 detections, 9 matches, 46 false positives, 365 false negatives, precision `0.16363636363636364`, recall `0.02406417112299465`, F1 `0.04195804195804196`. -- Live low-threshold operator8 matrix completed: - - output: `/mnt/user/appdata/geointel/artifacts/detection-quality-matrix/multi-sample/20260707T033230Z/multi_sample_quality_summary.json`. - - at threshold `0.05`, operator8 still produced zero detections on all samples. - - at threshold `0.01`, operator8 produced many false positives and almost no matches; best case was Turnhout tile `512` with 280 detections, 2 matches, 278 false positives, precision `0.007142857142857143`, recall `0.00258732212160414`, F1 `0.003798670465337132`. - -Open: -- None for the operator training/export tooling itself. - -Limitations: -- This is operator tooling only. It does not add Training Studio, browser training controls, provider fetching, fake detections, model auto-provisioning or API contract changes. -- The 3-sample/8-epoch operator model is not production-useful and should not be activated as the default building detector. - -Next recommended pass: -- Improve the training dataset before more model work: generate tile-level YOLO labels with enough positive/negative tiles, add more AOIs, then train a longer local model and rerun the same persisted QA matrix. - -## Sprint 128 Stronger building model runtime benchmark (2026-07-07) - -Changed: -- Added `keremberke/yolov8s-building-segmentation` as an explicit runtime model asset on Tower: - - path: `/mnt/user/appdata/geointel/models/yolov8s-building-segmentation.pt` - - source: `https://huggingface.co/keremberke/yolov8s-building-segmentation/resolve/main/best.pt` - - SHA256: `a27af31654c6a4edbdc85581c33d93c13986b5919de7de410f8d85d801b3bb34` -- Did not commit model weights to Git and did not add app-side model download behavior. -- Ran a stronger-candidate multi-sample matrix comparing: - - `yolov8n-building-segmentation-pt` - - `yolov8s-building-segmentation-pt` - - samples: Geel, Mol, Turnhout - - tile sizes: `512`, `640` - - overlap: `64` - - thresholds: `0.50`, `0.25`, `0.15` - -Tested: -- Hugging Face API metadata check showed `keremberke/yolov8s-building-segmentation` is public, uses the Ultralytics library, exposes `best.pt`, and reports validation mAP@0.5 values for the `keremberke/satellite-building-segmentation` dataset. -- Live model asset catalog reported `yolov8s-building-segmentation-pt`, `size_bytes=23814274`, `will_download_models=false`, SHA256 `a27af31654c6a4edbdc85581c33d93c13986b5919de7de410f8d85d801b3bb34`. -- Live preflight passed with `model_asset_id=yolov8s-building-segmentation-pt`, `check_model_load=true`, `model_file_exists=true`, `model_load_ok=true`, `will_download_models=false` and `will_run_inference=false`. -- Tower 36-run matrix passed: - - command: `OPERATOR_SAMPLE_MANIFEST_PATH=storage/operator-data/operator_samples_manifest.json QUALITY_MODEL_ASSET_IDS="yolov8n-building-segmentation-pt yolov8s-building-segmentation-pt" QUALITY_TILE_SIZES="512 640" QUALITY_TILE_OVERLAPS="64" QUALITY_THRESHOLDS="0.50 0.25 0.15" bash scripts/run_multi_sample_detection_quality_matrix.sh http://192.0.2.10:1202` - - output: `/mnt/user/appdata/geointel/artifacts/detection-quality-matrix/multi-sample/20260707T025932Z/multi_sample_quality_summary.json` - - best overall score: Mol, `yolov8s-building-segmentation-pt`, tile `640`, threshold `0.15`, 55 detections, 9 matches, 46 false positives, 365 false negatives, precision `0.16363636363636364`, recall `0.02406417112299465`, F1 `0.04195804195804196`. - - best overall recall: Mol, `yolov8s-building-segmentation-pt`, tile `512`, threshold `0.15`, 77 detections, 9 matches, 68 false positives, 365 false negatives, precision `0.11688311688311688`, recall `0.02406417112299465`, F1 `0.03991130820399113`. - - best overall precision: Turnhout, `yolov8s-building-segmentation-pt`, tile `640`, threshold `0.25`, 20 detections, 8 matches, 12 false positives, 765 false negatives, precision `0.4`, recall `0.01034928848641656`, F1 `0.0201765447667087`. - - best Geel score: `yolov8s-building-segmentation-pt`, tile `640`, threshold `0.15`, F1 `0.0187207488299532`. - - best Mol score: `yolov8s-building-segmentation-pt`, tile `640`, threshold `0.15`, F1 `0.04195804195804196`. - - best Turnhout score remained `yolov8n-building-segmentation-pt`, tile `512`, threshold `0.15`, F1 `0.03934426229508197`. -- Best-score evidence export passed for every sample in the new matrix: - - Geel evidence: `/mnt/user/appdata/geointel/artifacts/detection-quality-matrix/multi-sample/20260707T025932Z/geel/calibration_evidence_review.html`, 641 features, 611 false negatives, 18 false positives, 6 matched detections and 6 matched references. - - Mol evidence: `/mnt/user/appdata/geointel/artifacts/detection-quality-matrix/multi-sample/20260707T025932Z/mol/calibration_evidence_review.html`, 429 features, 365 false negatives, 46 false positives, 9 matched detections and 9 matched references. - - Turnhout evidence: `/mnt/user/appdata/geointel/artifacts/detection-quality-matrix/multi-sample/20260707T025932Z/turnhout/calibration_evidence_review.html`, 915 features, 755 false negatives, 124 false positives, 18 matched detections and 18 matched references. - -Open: -- None for adding and benchmarking the `yolov8s` candidate. - -Limitations: -- `yolov8s` improves precision and F1 on Geel/Mol but still misses most reference buildings. Best recall is about 2.4%, which is not sufficient for a usable V1 building extraction default. -- The model is a runtime artifact and remains outside Git. - -Next recommended pass: -- Source or train a materially stronger aerial-building model. The GeoIntel pipeline is now good enough to benchmark candidates quickly, but the current public YOLO building-segmentation candidates are still too weak for the target Flemish orthophoto/GRB workflow. - -## Sprint 127 Multi-sample detection quality calibration tooling (2026-07-07) - -Changed: -- Added `scripts/prepare_operator_real_data_samples.py` as an explicit operator/runtime helper for documented Geel, Mol and Turnhout real-data samples. -- The helper downloads small Digitaal Vlaanderen OMWRGBMRVL WMS `Ortho` GeoTIFFs and GRB OGC API Features `GBG` building GeoJSON references for the documented AOIs only. -- The helper writes `operator_samples_manifest.json`, sample metadata, source URLs and attribution under the runtime operator-data directory and reuses existing files by default. -- Added `scripts/run_multi_sample_detection_quality_matrix.sh` to run `scripts/run_detection_quality_matrix.sh` once per manifest sample. -- The multi-sample wrapper combines per-sample `quality_matrix_summary.json` files into `multi_sample_quality_summary.json` with `best_overall_by_score`, `best_overall_by_recall`, `best_overall_by_precision` and `best_by_sample`. -- Added readiness checks for Python compile and shell syntax. -- Added regression coverage in `backend/tests/test_sprint127_operator_sample_quality_matrix.py`. -- Updated `scripts/README.md`, `backend/README.md`, `docs/AI_PIPELINES.md`, `docs/TODO.md` and `CHANGELOG.md`. - -Tested: -- RED: `python -m pytest backend\tests\test_sprint127_operator_sample_quality_matrix.py -q` failed because the sample-preparation and multi-sample scripts did not exist. -- RED: `python -m pytest backend\tests\test_sprint127_operator_sample_quality_matrix.py::test_prepare_operator_real_data_samples_help_does_not_require_gis_dependencies -q` failed because `--help` required missing GIS dependencies. -- `python -m pytest backend\tests\test_sprint127_operator_sample_quality_matrix.py -q` passed. -- `python scripts\prepare_operator_real_data_samples.py --help` passed without requiring local GIS dependencies. -- `python -m py_compile scripts\prepare_operator_real_data_samples.py` passed. -- `bash -n scripts/run_multi_sample_detection_quality_matrix.sh` passed. -- `python -m pytest backend\tests\test_sprint127_operator_sample_quality_matrix.py backend\tests\test_sprint126_detection_quality_matrix.py backend\tests\test_sprint125_detection_calibration_evidence_bundle.py backend\tests\test_sprint124_detection_calibration_sweep.py -q` passed. -- `python scripts\smoke_docs.py` passed. -- `git diff --check` passed. -- `bash scripts/run_readiness_check.sh` passed: 393 backend tests, frontend typecheck/build, Alembic head `202606120900`, live smoke syntax checks and the new sample/multi-sample checks. -- Pushed commit `06dfc5f` to Gitea and fast-forwarded Tower `/mnt/user/appdata/geointel` to the same commit. -- Tower sample preparation passed by running the new helper in the live `geointel` all-in-one container through stdin: - - Geel reused existing runtime files: 617 GRB GBG reference features. - - Mol was newly prepared: 374 GRB GBG reference features. - - Turnhout was newly prepared: 773 GRB GBG reference features. - - Manifest: `/mnt/user/appdata/geointel/storage/operator-data/operator_samples_manifest.json`. -- Tower multi-sample quality matrix passed: - - command: `OPERATOR_SAMPLE_MANIFEST_PATH=storage/operator-data/operator_samples_manifest.json QUALITY_MODEL_ASSET_IDS="yolov8n-building-segmentation-pt yolov8n-pt" QUALITY_TILE_SIZES="512 640" QUALITY_TILE_OVERLAPS="64" QUALITY_THRESHOLDS="0.50 0.15" bash scripts/run_multi_sample_detection_quality_matrix.sh http://192.0.2.10:1202` - - output: `/mnt/user/appdata/geointel/artifacts/detection-quality-matrix/multi-sample/20260707T025303Z/multi_sample_quality_summary.json` - - run count: 24 real persisted workflows across 3 samples. - - best overall score/recall: Turnhout, `yolov8n-building-segmentation-pt`, tile `512`, overlap `64`, threshold `0.15`, 142 detections, 18 matches, 124 false positives, 755 false negatives, precision `0.1267605633802817`, recall `0.02328589909443726`, F1 `0.03934426229508197`. - - best overall precision: Geel, `yolov8n-building-segmentation-pt`, tile `640`, overlap `64`, threshold `0.50`, 4 detections, 1 match, 3 false positives, 616 false negatives, precision `0.25`, recall `0.0016207455429497568`, F1 `0.0032206119162640897`. - - best Geel score: tile `512`, threshold `0.15`, 80 detections, 6 matches, 74 false positives, 611 false negatives, F1 `0.017216642754662843`. - - best Mol score: tile `640`, threshold `0.15`, 77 detections, 7 matches, 70 false positives, 367 false negatives, F1 `0.03104212860310421`. - - best Turnhout score: tile `512`, threshold `0.15`, 142 detections, 18 matches, 124 false positives, 755 false negatives, F1 `0.03934426229508197`. - - generic `yolov8n-pt` produced zero building detections across every sample, tile size and threshold. -- Tower best-score evidence export passed for every sample: - - Geel: `/mnt/user/appdata/geointel/artifacts/detection-quality-matrix/multi-sample/20260707T025303Z/geel/calibration_evidence_review.html`, 697 features, 611 false negatives, 74 false positives, 6 matched detections and 6 matched references. - - Mol: `/mnt/user/appdata/geointel/artifacts/detection-quality-matrix/multi-sample/20260707T025303Z/mol/calibration_evidence_review.html`, 451 features, 367 false negatives, 70 false positives, 7 matched detections and 7 matched references. - - Turnhout: `/mnt/user/appdata/geointel/artifacts/detection-quality-matrix/multi-sample/20260707T025303Z/turnhout/calibration_evidence_review.html`, 915 features, 755 false negatives, 124 false positives, 18 matched detections and 18 matched references. - -Open: -- None for multi-sample tooling. - -Limitations: -- This is operator tooling only. It does not add a live GRB provider, live orthophoto provider, application endpoint, migration, frontend feature, model download or fixture inference path. -- The prepared sample files are runtime artifacts under appdata/storage and remain excluded from Git. -- The three-sample benchmark confirms the current building-segmentation evaluation model is not extraction-quality for V1: best recall is only about 2.3% and false negatives dominate every sample. - -Next recommended pass: -- Replace or add a stronger aerial/building model candidate and rerun the same multi-sample matrix; optionally add IoU-threshold sweeps after a model produces materially better candidate detections. - -## Sprint 126 Detection quality matrix tooling (2026-07-07) - -Changed: -- Added `scripts/run_detection_quality_matrix.sh` as an operator-facing model/tile/threshold matrix for the configured-YOLO real-data path. -- The matrix reuses `scripts/verify_real_data_detection_qa_workflow.sh` for each row so every result is backed by persisted Project, Dataset, AnalysisRun, Detection, QualityCheck, Metric and Export records. -- The script accepts `QUALITY_MODEL_ASSET_IDS`, `QUALITY_TILE_SIZES`, `QUALITY_TILE_OVERLAPS` and `QUALITY_THRESHOLDS`, writes per-run logs and produces `quality_matrix_summary.json`. -- The summary reports model asset, tile size, overlap, confidence threshold, detection count, QA score, precision, recall, F1, mean IoU, matches, false positives and false negatives. -- Added `best_by_score`, `best_by_recall` and `best_by_precision` rankings for operator model-quality decisions. -- Added readiness syntax coverage and regression coverage in `backend/tests/test_sprint126_detection_quality_matrix.py`. -- Updated `scripts/README.md`, `backend/README.md`, `docs/AI_PIPELINES.md`, `docs/TODO.md` and `CHANGELOG.md`. - -Tested: -- RED: `python -m pytest backend\tests\test_sprint126_detection_quality_matrix.py -q` failed because `scripts/run_detection_quality_matrix.sh` did not exist. -- `python -m pytest backend\tests\test_sprint126_detection_quality_matrix.py -q` passed. -- `python -m pytest backend\tests\test_sprint126_detection_quality_matrix.py backend\tests\test_sprint124_detection_calibration_sweep.py backend\tests\test_sprint125_detection_calibration_evidence_bundle.py -q` passed. -- `bash -n scripts/run_detection_quality_matrix.sh` passed. -- `bash scripts/run_detection_quality_matrix.sh --help` passed. -- `python scripts\smoke_docs.py` passed. -- `git diff --check` passed. -- `bash scripts/run_readiness_check.sh` passed: 390 backend tests, frontend typecheck/build, Alembic head `202606120900`, live smoke syntax checks and the new matrix syntax check. -- Pushed commit `e728f70` to Gitea and fast-forwarded Tower `/mnt/user/appdata/geointel` to the same commit. -- Tower live matrix passed against the Geel operator sample: - - command: `QUALITY_MODEL_ASSET_IDS="yolov8n-building-segmentation-pt yolov8n-pt" QUALITY_TILE_SIZES="512 640" QUALITY_TILE_OVERLAPS="64" QUALITY_THRESHOLDS="0.50 0.15" bash scripts/run_detection_quality_matrix.sh http://192.0.2.10:1202` - - output: `/mnt/user/appdata/geointel/artifacts/detection-quality-matrix/20260707T023000Z/quality_matrix_summary.json` - - run count: 8 - - best by score and recall: `yolov8n-building-segmentation-pt`, tile `512`, overlap `64`, threshold `0.15`, 80 detections, 6 matches, 74 false positives, 611 false negatives, precision `0.075`, recall `0.009724473257698542`, F1 `0.017216642754662843`. - - best by precision: `yolov8n-building-segmentation-pt`, tile `640`, overlap `64`, threshold `0.50`, 4 detections, 1 match, 3 false positives, 616 false negatives, precision `0.25`, recall `0.0016207455429497568`, F1 `0.0032206119162640897`. - - generic `yolov8n-pt` produced zero building detections for all tested tile/threshold combinations. -- Tower best-run evidence export passed from the matrix summary: - - `/mnt/user/appdata/geointel/artifacts/detection-quality-matrix/20260707T023000Z/calibration_evidence.geojson` - - `/mnt/user/appdata/geointel/artifacts/detection-quality-matrix/20260707T023000Z/calibration_evidence_summary.json` - - `/mnt/user/appdata/geointel/artifacts/detection-quality-matrix/20260707T023000Z/calibration_evidence_review.html` - - evidence features: 697 total, 611 false negatives, 74 false positives, 6 matched detections and 6 matched references. - -Open: -- None for matrix tooling. - -Limitations: -- This is operator benchmarking tooling only. It does not change inference behavior, add model downloads, seed fixture detections, fetch providers, change API contracts or change migrations. -- A single Geel sample is not enough to declare a production V1 building-extraction baseline; additional orthophoto/reference samples are still needed before picking defaults. - -Next recommended pass: -- Add at least two more local orthophoto/reference samples and run the same quality matrix before choosing V1 defaults; the current Geel evidence says runtime plumbing works, but the active model is still not extraction-quality. - -## Sprint 125 Detection calibration evidence bundle (2026-07-07) - -Changed: -- Added `scripts/export_detection_calibration_evidence.sh` to turn a persisted detection calibration summary into visual QA evidence artifacts. -- The script reads `calibration_summary.json`, fetches the existing project quality-check evidence GeoJSON endpoint for each `quality_check_id`, enriches features with threshold/score/provenance and writes: - - `calibration_evidence.geojson` - - `calibration_evidence_summary.json` - - `calibration_evidence_review.html` -- The HTML review artifact renders a simple SVG overview with distinct roles for `match_candidate`, `match_reference`, `false_positive` and `false_negative`. -- Registered the script in `scripts/run_readiness_check.sh` as a syntax check. -- Added regression coverage in `backend/tests/test_sprint125_detection_calibration_evidence_bundle.py`. -- Updated `scripts/README.md`, `backend/README.md`, `docs/AI_PIPELINES.md`, `docs/TODO.md` and `CHANGELOG.md`. - -Validation: -- RED: `python -m pytest backend/tests/test_sprint125_detection_calibration_evidence_bundle.py -q` failed because `scripts/export_detection_calibration_evidence.sh` did not exist. -- `python -m pytest backend/tests/test_sprint125_detection_calibration_evidence_bundle.py -q` passed. -- `bash -n scripts/export_detection_calibration_evidence.sh` passed. -- `bash scripts/export_detection_calibration_evidence.sh --help` passed. -- Missing-input guard printed usage and did not fetch evidence. -- `bash scripts/run_readiness_check.sh` passed: 389 backend tests, Alembic head check, frontend typecheck/build and shell syntax checks. -- Tower pulled commit `ea8dcb2` with `git pull --ff-only origin main`. -- Tower evidence export passed against `/mnt/user/appdata/geointel/artifacts/detection-calibration/20260707T002103Z/calibration_summary.json`. -- Evidence artifacts written on Tower: - - `/mnt/user/appdata/geointel/artifacts/detection-calibration/20260707T002103Z/calibration_evidence.geojson` - - `/mnt/user/appdata/geointel/artifacts/detection-calibration/20260707T002103Z/calibration_evidence_summary.json` - - `/mnt/user/appdata/geointel/artifacts/detection-calibration/20260707T002103Z/calibration_evidence_review.html` -- Evidence counts from the Geel calibration export: - - total evidence features: 2555 - - false negatives: 2460 - - false positives: 79 - - matched detections: 8 - - matched references: 8 -- Copied `calibration_evidence_review.html` and `calibration_evidence_summary.json` to the local ignored `artifacts/detection-calibration/20260707T002103Z/` directory for inspection. -- Internal browser validation passed through a temporary local static server: the review page loaded with title `GeoIntel Detection Calibration Evidence`, 1 SVG, 2555 SVG paths, 4 calibration table rows and 0 console errors. - -Open: -- None for evidence export tooling. - -Limitations: -- This is operator tooling only. It does not rerun inference, change API behavior, add UI behavior, fetch providers, seed demo data or download models. -- The SVG review is a lightweight geometry overview, not a replacement for full MapLibre evidence review in the workbench. -- The evidence distribution confirms the current active model misses most reference buildings on this sample. This points to model suitability and/or tiling strategy as the next bottleneck, not runtime plumbing. - -Next recommended pass: -- Add a model-quality decision pass: compare the current evaluation model against another building/aerial model or adjusted tile/overlap settings on at least two additional local orthophoto/reference samples. - -## Sprint 124 Detection calibration sweep tooling (2026-07-07) - -Changed: -- Added `scripts/run_detection_calibration_sweep.sh` as an operator-facing confidence-threshold sweep for the configured-YOLO real-data path. -- The sweep reuses `scripts/verify_real_data_detection_qa_workflow.sh` once per threshold, so each row is backed by persisted Project, Dataset, AnalysisRun, Detection, QualityCheck, Metric and export records. -- The sweep fetches project `quality-checks` after each run and writes per-threshold summaries plus `calibration_summary.json` with detection count, QA score, precision, recall, F1, mean IoU, matches, false positives and false negatives. -- Registered the sweep in `scripts/run_readiness_check.sh` as a syntax check. -- Added regression coverage in `backend/tests/test_sprint124_detection_calibration_sweep.py`. -- Updated `scripts/README.md`, `backend/README.md`, `docs/AI_PIPELINES.md`, `docs/TODO.md` and `CHANGELOG.md`. - -Validation: -- RED: `python -m pytest backend/tests/test_sprint124_detection_calibration_sweep.py -q` failed because `scripts/run_detection_calibration_sweep.sh` did not exist. -- `python -m pytest backend/tests/test_sprint124_detection_calibration_sweep.py -q` passed. -- `bash -n scripts/run_detection_calibration_sweep.sh` passed. -- `bash scripts/run_detection_calibration_sweep.sh --help` passed. -- Missing-input guard printed usage and did not start a live workflow. -- `bash scripts/run_readiness_check.sh` passed: 388 backend tests, Alembic head check, frontend typecheck/build and shell syntax checks. -- Tower pulled commit `590e597` with `git pull --ff-only origin main` and ran the default Geel calibration sweep. -- The first Tower sweep exposed that the summary script looked for `f1_score` while persisted metrics use `f1`; the script was patched with a `metrics.get("f1")` fallback and regression coverage. -- RED: `python -m pytest backend/tests/test_sprint124_detection_calibration_sweep.py -q` failed while the script lacked the `f1` fallback. -- `python -m pytest backend/tests/test_sprint124_detection_calibration_sweep.py -q` passed after the fallback. -- Tower pulled commit `e8cd463` and reran the Geel calibration sweep successfully: - - output: `artifacts/detection-calibration/20260707T002103Z/calibration_summary.json` - - threshold `0.50`: 4 detections, score/F1 `0.0032206119162640897`, precision `0.25`, recall `0.0016207455429497568`, 1 match, 3 false positives, 616 false negatives - - threshold `0.35`: 9 detections, score/F1 `0.003194888178913738`, precision `0.1111111111111111`, recall `0.0016207455429497568`, 1 match, 8 false positives, 616 false negatives - - threshold `0.25`: 20 detections, score/F1 `0.0031397174254317113`, precision `0.05`, recall `0.0016207455429497568`, 1 match, 19 false positives, 616 false negatives - - threshold `0.15`: 54 detections, score/F1 `0.014903129657228018`, precision `0.09259259259259259`, recall `0.008103727714748784`, 5 matches, 49 false positives, 612 false negatives - - best by score for this sample: threshold `0.15` - -Open: -- None for calibration tooling. - -Limitations: -- The sweep is intentionally mutating and creates one real workflow run per threshold. -- It is calibration tooling only; it does not change inference, add model downloads, fetch providers, seed demo detections or change API/UI behavior. -- The current active building model still performs poorly on the Geel validation sample. Threshold `0.15` is best among the tested values, but recall remains under 1%; this is model/data-quality evidence, not a production-ready extraction baseline. - -Next recommended pass: -- Inspect false-positive/false-negative evidence for the Geel runs, then add at least two more local orthophoto/reference samples before choosing V1 default confidence/IoU guidance. - -## Sprint 123 YOLO class and tile CRS normalization (2026-07-07) - -Changed: -- Investigated the Geel real-data smoke that persisted zero detections despite the configured building model being available. -- Confirmed on Tower that `/app/models/yolov8n-building-segmentation.pt` reports model class `Building` and returns 4 raw detections at confidence `0.5` on the same real Geel tile manifest. -- Fixed configured-YOLO detection persistence so model class names are compared case-insensitively against `class_filter`, persisted as canonical lowercase domain classes, and preserve the original model class name in `properties_json.model_class_name`. -- Found a second live GIS correctness issue: generated tile manifests carried Lambert bounds/transforms but no CRS, so detection GeoJSON could expose EPSG:31370 coordinates as if they were EPSG:4326. -- Fixed raster tile manifest generation to include `crs`, `source_crs` and `dataset_crs` on the manifest and `crs` on each tile entry when the source raster CRS is known. -- Added regression coverage in `backend/tests/test_sprint8b_yolo_foundation.py` and `backend/tests/test_raster_operations_service.py`. - -Validation: -- RED: `python -m pytest backend/tests/test_sprint8b_yolo_foundation.py::test_yolo_class_filter_is_case_insensitive_and_persists_canonical_class -q` failed with `detection_count=0` because `Building` did not match `building`. -- `python -m pytest backend/tests/test_sprint8b_yolo_foundation.py::test_yolo_class_filter_is_case_insensitive_and_persists_canonical_class -q` passed. -- `python -m pytest backend/tests/test_sprint8b_yolo_foundation.py backend/tests/test_model_asset_catalog.py backend/tests/test_sprint121_real_data_detection_qa_smoke.py backend/tests/test_sprint122_raster_upload_metadata_mapping.py -q` passed: 20 tests. -- RED: `python -m pytest backend/tests/test_raster_operations_service.py::test_raster_tile_returns_manifest_payload -q` failed because the tile manifest had no `crs`. -- `python -m pytest backend/tests/test_raster_operations_service.py::test_raster_tile_returns_manifest_payload -q` passed. -- `python -m compileall backend/app` passed. -- `bash scripts/run_readiness_check.sh` passed: 387 backend tests, Alembic head check, frontend typecheck/build and shell syntax checks. -- Tower deploy from commit `71c2cd9` passed with `GEOINTEL_INSTALL_AI=true`. -- Deploy-time live migration smoke passed; PostGIS reported `3.6 USE_GEOS=1 USE_PROJ=1 USE_STATS=1` and Alembic head was `202606120900`. -- Deploy-time browser runtime verification passed for `http://192.0.2.10:1202`. -- Real-data smoke after the class-normalization deploy passed and persisted 4 detections: - - project: `cb80638d-dbef-48ac-b19c-cec7c3efc96e` - - raster dataset: `ae0ff76d-70c0-404f-b777-54d14517179a` - - reference dataset: `8ac01b4f-bd6a-4d6a-b625-a0950ae0f3eb` - - analysis run: `7ba34274-411d-45e3-8f54-c37baec598b1` - - quality check: `66907e6a-9ed7-4b0c-976f-5ad1ba9b8b7a` - - detection export: `516d37a3-2305-48a2-a3dd-b56f70eb055e` - - persisted detections used canonical `class_name=building` and preserved `model_class_name=Building`. -- Tower deploy from commit `bc87681` passed with `GEOINTEL_INSTALL_AI=true`. -- Deploy-time live migration smoke passed; PostGIS reported `3.6 USE_GEOS=1 USE_PROJ=1 USE_STATS=1` and Alembic head was `202606120900`. -- Deploy-time browser runtime verification passed for `http://192.0.2.10:1202`. -- Real-data smoke after the tile-CRS deploy passed and persisted 4 detections: - - project: `6ced26f3-4486-451e-a05e-26a8f859e361` - - raster dataset: `d54c3420-03d4-45a2-9501-bf1cce165a89` - - reference dataset: `319dad51-15e9-4ae6-815b-8e39023ed962` - - manifest: `/app/storage/tiles/6ced26f3-4486-451e-a05e-26a8f859e361/d54c3420-03d4-45a2-9501-bf1cce165a89/721c9557-5910-4994-b0ac-ba3418d12246/manifest.json` - - analysis run: `e99bcd07-ba48-4ebe-9ba9-24a94a8c1dcb` - - quality check: `32c8252b-fe60-4062-9639-125c62ca677f` - - detection export: `9d3a7f60-07a2-415c-9f75-a3c1988d0904` -- Verified the new tile manifest now carries `crs=EPSG:31370`, `source_crs=EPSG:31370`, `dataset_crs=EPSG:31370` and per-tile `crs=EPSG:31370`. -- Verified Detection GeoJSON now returns WGS84 coordinates around Geel instead of raw Belgian Lambert coordinates. -- Live detection QA persisted honest metrics for the Geel sample: 1 match, 3 false positives, 616 false negatives and score `0.0032206119162640897`. - -Open: -- None for availability, persistence and CRS propagation. - -Limitations: -- This fixes class routing, persistence and future tile manifest CRS propagation. Existing tile manifests generated before this fix remain missing CRS and should be regenerated before AI runs. -- The active building model is operational but not calibrated for production-quality local Belgian/Kempen orthophoto extraction. The Geel sample proves end-to-end persistence and QA, while the 1/617 reference match result shows that confidence thresholds, tiling strategy, class mapping and IoU defaults still need model-quality calibration. - -Next recommended pass: -- Run a detection calibration pass on several local orthophoto/reference samples: sweep confidence thresholds, inspect false positives/false negatives, tune tile size/overlap where needed and record a practical V1 baseline. - -## Sprint 122 Real operator data availability and raster metadata fix (2026-07-07) - -Changed: -- Created real operator validation files on Tower under `/mnt/user/appdata/geointel/storage/operator-data`. -- Generated `/mnt/user/appdata/geointel/storage/operator-data/geel_orthophoto_wms_512.tif` from the official Digitaal Vlaanderen OMWRGBMRVL WMS `Ortho` layer for a 500 m x 500 m AOI around Geel. -- Generated `/mnt/user/appdata/geointel/storage/operator-data/geel_grb_gbg_buildings.geojson` from the official Digitaal Vlaanderen GRB OGC API Features `GBG` building collection for the same AOI; it contained 617 features. -- Fixed `DatasetService` raster upload metadata mapping so extracted `bounds`, `resolution` and `dtype` populate persisted `bounds_json`, `resolution_json` and `bands_json`. -- Added `backend/tests/test_sprint122_raster_upload_metadata_mapping.py`. - -Validation: -- RED: `python -m pytest backend/tests/test_sprint122_raster_upload_metadata_mapping.py -q` failed because uploaded raster `bounds_json` was `None`. -- `python -m pytest backend/tests/test_sprint122_raster_upload_metadata_mapping.py -q` passed. -- `python -m compileall backend/app` passed. -- `bash scripts/run_readiness_check.sh` passed: 386 backend tests, Alembic head check, frontend typecheck/build and shell syntax checks. -- Tower deploy from commit `2468945` passed with `GEOINTEL_INSTALL_AI=true`. -- Deploy-time live migration smoke passed; PostGIS reported `3.6 USE_GEOS=1 USE_PROJ=1 USE_STATS=1` and Alembic head was `202606120900`. -- Deploy-time browser runtime verification passed for `http://192.0.2.10:1202`. -- Real-data smoke passed: - - command: `REAL_RASTER_PATH=/mnt/user/appdata/geointel/storage/operator-data/geel_orthophoto_wms_512.tif REAL_REFERENCE_VECTOR_PATH=/mnt/user/appdata/geointel/storage/operator-data/geel_grb_gbg_buildings.geojson bash scripts/verify_real_data_detection_qa_workflow.sh http://192.0.2.10:1202` - - project: `e1ec201b-bd83-4c95-be5a-f7225902d3c5` - - raster dataset: `fca14d23-bc0c-4b1f-8bfa-ba968f2e05d0` - - reference dataset: `5bb4a9b4-2a4e-4680-a729-777a75ecd51f` - - model asset: `yolov8n-building-segmentation-pt` - - manifest: `/app/storage/tiles/e1ec201b-bd83-4c95-be5a-f7225902d3c5/fca14d23-bc0c-4b1f-8bfa-ba968f2e05d0/0f29f110-951f-48eb-a2fb-636b587e31ee/manifest.json` - - analysis run: `c6798559-590c-42e3-a192-45a2409fa832` - - detections: `0` - - quality check: `cd0d13f9-f6ce-4acf-8859-7cb7aa666125` - - detection export: `0081c230-1766-4ff3-8df0-e47236f529d1` - -Limitations: -- The workflow is operational against real operator data. A follow-up class-normalization pass found that the active evaluation model returned `Building` while the workflow filtered on `building`; see Sprint 123. -- The prepared files are runtime artifacts on Tower, not repository fixtures. - -Next recommended pass: -- Redeploy the class-normalization fix, rerun the real-data smoke and calibrate confidence/IoU thresholds against persisted detection and QA metrics. - -## Sprint 121 Real data detection and QA workflow smoke (2026-07-07) - -Changed: -- Added `scripts/verify_real_data_detection_qa_workflow.sh` for live-runtime validation with operator-provided real GIS inputs. -- The smoke creates a project, uploads a real GeoTIFF-style raster as a source dataset, uploads a real reference-building GeoJSON/JSON as `dataset_role=reference`, validates CRS/bounds/features, tiles the raster, selects a mounted local model asset, runs read-only YOLO preflight, runs configured YOLO detection, runs detection QA against persisted `vector_features`, and exports the detection run GeoJSON. -- Registered the smoke in `scripts/run_readiness_check.sh` as a syntax check only, so normal readiness does not require real orthophotos, reference vectors, optional AI dependencies or model files. -- Documented Tower usage and limitations in `scripts/README.md`, `backend/README.md`, `docs/AI_PIPELINES.md`, `docs/TODO.md` and `CHANGELOG.md`. - -Validation: -- RED: `python -m pytest backend/tests/test_sprint121_real_data_detection_qa_smoke.py -q` failed while `scripts/verify_real_data_detection_qa_workflow.sh` did not exist. -- `python -m pytest backend/tests/test_sprint121_real_data_detection_qa_smoke.py -q` passed: 1 test. -- `bash -n scripts/verify_real_data_detection_qa_workflow.sh` passed. -- `bash scripts/verify_real_data_detection_qa_workflow.sh --help` passed and printed required `REAL_RASTER_PATH` and `REAL_REFERENCE_VECTOR_PATH` usage. -- `python -m compileall backend/app` passed. -- `python scripts/smoke_docs.py` passed. -- `bash scripts/run_readiness_check.sh` passed: 385 backend tests, Alembic head check, frontend typecheck, frontend production build and shell syntax checks. -- `cd backend && python -m alembic upgrade head --sql` passed. -- Missing-input guard passed: `bash scripts/verify_real_data_detection_qa_workflow.sh http://localhost:1202` returned exit code 2 and printed usage. -- Local `docker compose config` could not run in this Windows Codex environment because the `docker` command is not installed. - -Limitations: -- The full real-data smoke was not executed in this Codex workspace because no operator-provided real GeoTIFF and reference GeoJSON were found locally. -- The script enforces real inputs and never seeds demo data, enables fixture detections, fetches live GRB/OSM/Sentinel data or downloads model weights. - -Next recommended pass: -- Place a target orthophoto/GeoTIFF and matching reference-building GeoJSON under the Tower appdata path and run `REAL_RASTER_PATH=... REAL_REFERENCE_VECTOR_PATH=... bash scripts/verify_real_data_detection_qa_workflow.sh http://192.0.2.10:1202`. - -## Sprint 120 Model asset detection workflow smoke (2026-07-06) - -Changed: -- Added `scripts/verify_model_asset_detection_workflow.sh` to validate the configured-YOLO runtime path against a live Docker/Tower deployment. -- The smoke seeds the explicit offline demo workflow, creates a raster tile manifest, selects the active local model asset from `GET /api/v1/detection/model-assets`, verifies read-only YOLO preflight, submits the existing detection run endpoint and checks persisted AnalysisRun, Detection list and Detection GeoJSON outputs. -- Registered the script in `scripts/run_readiness_check.sh` as a syntax check only, so ordinary readiness runs remain valid on machines without optional AI dependencies or mounted model files. -- Documented the smoke in `scripts/README.md`, `backend/README.md`, `docs/AI_PIPELINES.md`, `docs/TODO.md` and `CHANGELOG.md`. - -Validation: -- RED: `python -m pytest backend/tests/test_sprint120_model_asset_detection_workflow_smoke.py -q` failed because `scripts/verify_model_asset_detection_workflow.sh` did not exist yet. -- `python -m pytest backend/tests/test_sprint120_model_asset_detection_workflow_smoke.py -q` passed: 1 test. -- `bash -n scripts/verify_model_asset_detection_workflow.sh` passed. -- Live Tower smoke passed: `bash scripts/verify_model_asset_detection_workflow.sh http://192.0.2.10:1202`. -- Live smoke selected `model_asset_id=yolov8n-building-segmentation-pt`, generated manifest `/app/storage/tiles/c0b00f1f-80bf-4992-be94-f5e5e6f6bf63/f9160f51-ee78-43b3-9353-d5390576fa1d/e9acd488-c376-45ed-b259-0dd79886f21e/manifest.json`, persisted analysis run `7f9e7ecb-c43d-4ed3-9f98-424bc0317805` and returned `detection_count=0`. -- `python -m compileall backend/app` passed. -- `cd backend && python -m pytest -q` passed: 384 tests with the existing Pydantic `model_*` namespace warnings. -- `cd frontend && npm run typecheck` passed. -- `cd frontend && npm run build` passed. -- `cd backend && python -m alembic heads` passed: `202606120900 (head)`. -- `cd backend && python -m alembic upgrade head --sql` passed. -- `bash scripts/run_readiness_check.sh` passed: 384 backend tests, frontend typecheck/build, API contract audit, Alembic head and shell syntax checks. -- Live browser/API smoke passed: `bash scripts/verify_browser_runtime.sh http://192.0.2.10:1202`. -- Live GIS capability smoke passed: `bash scripts/verify_gis_runtime.sh http://192.0.2.10:1202`. -- Live raster workflow smoke passed: `bash scripts/verify_demo_raster_workflow.sh http://192.0.2.10:1202`. -- Live workbench default-state smoke passed: `bash scripts/verify_workbench_default_state.sh http://192.0.2.10:1202`. -- Live workbench backing-state smoke passed: `bash scripts/verify_workbench_interactions.sh http://192.0.2.10:1202`. -- Live demo/export workflow smoke passed: `bash scripts/verify_demo_export_workflow.sh http://192.0.2.10:1202`. -- `bash scripts/verify_ai_handoff_interactions.sh http://192.0.2.10:1202` could not run in this local Codex shell because Node cannot import Playwright; the script remains syntax-checked in readiness and the internal browser was used for live visual verification instead. -- Internal browser validation passed on `http://192.0.2.10:1202`: AI Labs rendered Detection Lab and Segmentation Lab, selecting `yolo-configured` showed the Local model assets selector with `yolov8n-building-segmentation (active)` and `yolov8n`, no-download copy was visible and no console errors were emitted. -- `git push origin main` pushed commit `b2fe7fa`. -- Tower deploy from commit `b2fe7fa` completed with `GEOINTEL_INSTALL_AI=true`; the all-in-one container is published on `0.0.0.0:1202->80/tcp`. -- Deploy-time live migration smoke passed after the database became ready on attempt 3; PostGIS reported `3.6 USE_GEOS=1 USE_PROJ=1 USE_STATS=1` and Alembic head was `202606120900`. -- Deploy-time browser runtime verification passed for `http://192.0.2.10:1202`, API proxy and icon. -- Post-deploy live model asset detection workflow smoke passed: `bash scripts/verify_model_asset_detection_workflow.sh http://192.0.2.10:1202` selected `yolov8n-building-segmentation-pt`, persisted analysis run `f758c992-4fb8-4dca-ab29-5c216cb14078` and returned `detection_count=0`. - -Limitations: -- The smoke proves the configured-YOLO runtime path, provenance and persistence. It does not prove production model quality because it runs against the synthetic demo raster. -- Real operational validation still requires uploading a georeferenced Kempen orthophoto/GeoTIFF, running the configured building model on that raster and comparing persisted detections against reference building vectors through QA/QC. - -Next recommended pass: -- Create the real-data validation path for orthophoto upload, tile generation, configured building-model run and reference-vector QA/QC. - -## Sprint 118 Local model and reference catalog clarity (2026-07-06) - -Changed: -- Added a read-only backend model asset catalog through `GET /api/v1/detection/model-assets`. -- Added `YOLO_MODELS_DIR` to backend settings, Compose, Unraid env examples and all-in-one runtime startup so `/app/models` is the explicit model catalog directory. -- Extended configured YOLO preflight and detection runs with optional `model_asset_id`, resolved server-side against the model asset catalog. -- Detection jobs and analysis runs now persist selected model asset ID, path and SHA-256 in parameters for reproducibility. -- Detection Lab now loads local model assets, selects the active model by default and lets operators choose a cataloged local model file for `yolo-configured`. -- Provider Capabilities now distinguishes GRB/OSM/manual/fixture reference-data sources from AI model choices. -- Updated `docs/API_CONTRACTS.md`, `docs/AI_PIPELINES.md`, `backend/README.md`, `frontend/README.md`, `deploy/unraid/README.md`, `scripts/README.md`, `docs/TODO.md` and `CHANGELOG.md`. -- Added design/plan documents under `docs/superpowers/`. - -Validation: -- RED: `python -m pytest backend/tests/test_model_asset_catalog.py -q` failed before implementation because `app.services.model_asset_catalog_service` did not exist. -- `python -m pytest backend/tests/test_model_asset_catalog.py -q` passed: 5 tests. -- RED: `python -m pytest backend/tests/test_sprint118_yolo_preflight_ui.py -q` failed before frontend wiring because the model asset types/API/hook/UI were absent. -- `python -m pytest backend/tests/test_sprint118_yolo_preflight_ui.py -q` passed: 2 tests. -- RED: runtime config tests failed before `YOLO_MODELS_DIR` was added to env examples, Unraid runtime and `scripts/configure_yolo_model.py`. -- `python -m pytest backend/tests/test_docker_runtime_config.py::test_env_example_uses_runtime_env_names_read_by_backend_and_frontend backend/tests/test_docker_runtime_config.py::test_unraid_deploy_passes_ai_build_arg_and_yolo_runtime_env backend/tests/test_sprint119_yolo_model_configuration.py -q` passed: 6 tests. -- `python -m compileall backend/app` passed. -- `cd backend && python -m pytest -q` passed: 383 tests. -- `cd frontend && npm run typecheck` passed. -- `cd frontend && npm run build` passed. -- `python scripts/audit_api_contracts.py` passed: 81 implemented routes match docs; 2 explicit non-envelope endpoints tracked. -- `bash scripts/run_readiness_check.sh` passed: 383 backend tests plus frontend typecheck/build, API contract audit, Alembic head and shell syntax checks. -- `cd backend && python -m alembic upgrade head --sql` passed. -- `bash -n scripts/live_migration_smoke.sh; bash -n deploy/unraid/run-dockerman-container.sh; bash -n deploy/unraid/all-in-one-start.sh; bash -n scripts/deploy_tower.sh` passed. -- Local `docker compose config` could not run because Docker is not installed in this Windows Codex environment; Tower deploy validation remains required. -- `git push origin main` passed and pushed commits through `6e2a8cb`. -- `powershell -NoProfile -ExecutionPolicy Bypass -File scripts\deploy_tower.ps1` with `GEOINTEL_INSTALL_AI=true` passed and redeployed Tower from commit `6e2a8cb`. -- Deploy-time live migration smoke passed on Tower; PostGIS reported `3.6 USE_GEOS=1 USE_PROJ=1 USE_STATS=1` and Alembic head was `202606120900`. -- Deploy-time browser runtime verification passed for `http://192.0.2.10:1202`, API proxy and icon. -- Live `GET http://192.0.2.10:1202/api/v1/detection/model-assets` returned two cataloged local assets: `yolov8n-building-segmentation-pt` active with SHA-256 `152d6a9c5c76c9f2fd2fd5cc167efaed7c8c02e31002b15415899710f1d71f98`, and `yolov8n-pt`. -- Live `GET /api/v1/detection/yolo/preflight?model_asset_id=yolov8n-pt` resolved `/app/models/yolov8n.pt`, reported dependencies available, no downloads and no inference. -- Live `GET /api/v1/detection/yolo/preflight?model_asset_id=yolov8n-building-segmentation-pt&check_model_load=true` passed model load smoke with `model_load_ok=true`, `torch_version=2.12.1`, `ultralytics_version=8.4.89`, no downloads and no inference. -- Internal browser validation passed on `http://192.0.2.10:1202`: Detection Lab showed `Local model assets`, listed `yolov8n-building-segmentation (active)` and `yolov8n`, auto-selected the active asset, showed no-download copy, and emitted no console errors. -- Internal browser validation passed for System/Provider Capabilities: `Official reference sources`, GRB, OSM and `not AI model choices` copy were visible with no console errors. - -Limitations: -- The catalog is intentionally filesystem-backed and read-only. It does not download, validate semantic class metadata, train models or manage model lifecycle records in the database. -- GRB/OSM remain provider capabilities only; no live external fetching was added. - -Next recommended pass: -- Redeploy Tower, verify `/api/v1/detection/model-assets`, confirm Detection Lab shows the local model picker, then continue with real raster/model workflow validation on non-synthetic imagery. - -## Sprint 117 Reusable GIS run and AI runtime opt-in (2026-07-05) - -Changed: -- Added a Map workspace full-run mode selector with `Create new dataset/export` and `Reuse latest saved dataset for QA`. -- Reuse mode runs QA/QC against the latest saved derived map-selection dataset without creating another derived dataset/export pair. -- Added opt-in Docker and Unraid AI build support through `GEOINTEL_INSTALL_AI=true`; default builds still install only the GIS runtime. -- Passed YOLO runtime environment variables and a `/app/models` volume into the all-in-one Unraid container so local PyTorch/Ultralytics models can be mounted explicitly. -- Hardened the AI image path after Tower validation showed `torch` imported but `ultralytics` failed on a missing OpenCV native library. The Dockerfiles now include the required OpenCV runtime shared libraries and YOLO dependency detection performs real imports instead of `find_spec` checks. -- Added a writable `YOLO_CONFIG_DIR` default under application storage after Tower validation showed Ultralytics otherwise falls back to `/tmp` because root config is not writable in the container. -- Added YOLO preflight runtime diagnostics so operators can see dependency assumption state, model directory, `YOLO_CONFIG_DIR`, installed `torch`/`ultralytics` package versions and CUDA availability without loading a model, running inference or downloading weights. -- Added a read-only `GET /api/v1/detection/yolo/preflight` endpoint and Detection Lab YOLO runtime preflight panel so browser operators can inspect live AI runtime readiness without loading a model, running inference or downloading weights. -- Updated `.env.example`, `backend/README.md`, `frontend/README.md`, `scripts/README.md`, `docs/AI_PIPELINES.md`, `docs/TODO.md` and `CHANGELOG.md`. -- Added regression coverage in `backend/tests/test_sprint116_operational_gis_map_workflow.py`, `backend/tests/test_sprint8b_yolo_foundation.py` and `backend/tests/test_docker_runtime_config.py`. - -Validation: -- RED: `python -m pytest backend\tests\test_sprint116_operational_gis_map_workflow.py backend\tests\test_docker_runtime_config.py -q` failed before implementation because `fullWorkflowMode`, AI build args and YOLO runtime env wiring were absent. -- `python -m pytest backend\tests\test_sprint116_operational_gis_map_workflow.py backend\tests\test_docker_runtime_config.py -q` passed: 22 tests. -- `cd frontend && npm run typecheck` passed. -- `cd frontend && npm run build` passed. -- `python -m compileall backend/app` passed. -- `python -m py_compile scripts\yolo_preflight.py backend\scripts\yolo_preflight.py` passed. -- `python -m pytest backend\tests\test_sprint31_unraid_template.py backend\tests\test_docker_runtime_config.py -q` passed: 27 tests. -- RED: `python -m pytest backend\tests\test_sprint8b_yolo_foundation.py backend\tests\test_docker_runtime_config.py -q` failed before the runtime hardening because YOLO dependency detection still used `find_spec` and the Dockerfiles lacked OpenCV native runtime libraries. -- `python -m pytest backend\tests\test_sprint8b_yolo_foundation.py backend\tests\test_docker_runtime_config.py -q` passed: 30 tests. -- RED: `python -m pytest backend\tests\test_docker_runtime_config.py -q` failed before `YOLO_CONFIG_DIR` wiring because the Compose, Unraid and startup paths did not define a writable Ultralytics config directory. -- `python -m pytest backend\tests\test_docker_runtime_config.py -q` passed: 21 tests. -- `python -m compileall backend/app` passed after the AI runtime hardening. -- `cd backend && python -m pytest -q` passed: 367 tests. -- `cd frontend && npm run typecheck` passed. -- `cd frontend && npm run build` passed. -- `bash scripts/run_readiness_check.sh` passed: 367 backend tests plus frontend typecheck/build. -- `cd backend && python -m alembic heads` passed: `202606120900 (head)`. -- `cd backend && python -m alembic upgrade head --sql` passed. -- `bash -n scripts/live_migration_smoke.sh; bash -n scripts/deploy_tower.sh; bash -n deploy/unraid/run-dockerman-container.sh` passed. -- Local Codex host could not run `docker compose config` because Docker is not installed in this Windows environment; Tower Docker validation is required after push/deploy. -- `powershell -NoProfile -ExecutionPolicy Bypass -File scripts\deploy_tower.ps1` with `GEOINTEL_INSTALL_AI=true` passed after the AI runtime hardening and redeployed Tower from commit `9cad8d4`. -- Deploy-time live migration smoke passed on Tower; PostGIS reported `3.6 USE_GEOS=1 USE_PROJ=1 USE_STATS=1` and Alembic head was `202606120900`. -- Deploy-time browser runtime verification passed for `http://192.0.2.10:1202`, API proxy and icon. -- Tower container check passed: `torch` imported as `2.12.1+cu130`, `torch.cuda.is_available()` returned `False`, `ultralytics` imported as `8.4.87`, and `scripts/yolo_preflight.py --enabled --json` returned `dependencies_available=true`, `status=not_configured`, `will_download_models=false`, `will_run_inference=false` because no local model path is configured yet. -- Tower runtime `YOLO_CONFIG_DIR` is `/app/storage/ultralytics`; the directory exists, is writable and Ultralytics writes settings there instead of root config. -- Internal browser validation passed against `http://192.0.2.10:1202`: the live shell and Map workspace rendered without console errors, with database layer selection, Operational GIS controls, and both full-run modes visible. -- RED: `python -m pytest backend\tests\test_sprint13_yolo_preflight.py -q` failed before runtime diagnostics were implemented because `runtime` was absent from preflight output. -- `python -m pytest backend\tests\test_sprint13_yolo_preflight.py -q` passed: 8 tests. -- `python -m pytest backend\tests\test_sprint13_yolo_preflight.py backend\tests\test_sprint8b_yolo_foundation.py backend\tests\test_docker_runtime_config.py -q` passed: 39 tests. -- `python -m compileall backend/app` passed. -- `cd backend && python -m pytest -q` passed: 369 tests. -- `cd frontend && npm run typecheck` passed. -- `cd frontend && npm run build` passed. -- `bash scripts/run_readiness_check.sh` passed: 369 backend tests plus frontend typecheck/build and Alembic head. -- `cd backend && python -m alembic heads` passed: `202606120900 (head)`. -- `cd backend && python -m alembic upgrade head --sql` passed. -- `bash -n scripts/live_migration_smoke.sh`, `bash -n scripts/deploy_tower.sh`, `bash -n deploy/unraid/run-dockerman-container.sh` and `bash -n deploy/unraid/all-in-one-start.sh` passed. -- Local Codex host still cannot run `docker compose config` because Docker is not installed in this Windows environment; Tower Docker validation is required after push/deploy. -- `powershell -NoProfile -ExecutionPolicy Bypass -File scripts\deploy_tower.ps1` with `GEOINTEL_INSTALL_AI=true` passed and redeployed Tower from commit `7a29e78`. -- Deploy-time live migration smoke passed on Tower; PostGIS reported `3.6 USE_GEOS=1 USE_PROJ=1 USE_STATS=1` and Alembic head was `202606120900`. -- Deploy-time browser runtime verification passed for `http://192.0.2.10:1202`, API proxy and icon. -- Tower container check passed: remote checkout is `7a29e78`, `geointel` is healthy on `0.0.0.0:1202->80/tcp`, and `scripts/yolo_preflight.py --enabled --json` reports `dependencies_available=true`, `torch_version=2.12.1`, `ultralytics_version=8.4.88`, `cuda_available=false`, `yolo_config_dir=/app/storage/ultralytics`, `status=not_configured`, `will_download_models=false` and `will_run_inference=false`. -- RED: `python -m pytest backend\tests\test_sprint13_yolo_preflight.py::test_yolo_preflight_api_returns_canonical_envelope backend\tests\test_sprint118_yolo_preflight_ui.py -q` failed before implementation because `/api/v1/detection/yolo/preflight` returned 404 and the Detection Lab did not surface a YOLO runtime preflight panel. -- `python -m pytest backend\tests\test_sprint13_yolo_preflight.py::test_yolo_preflight_api_returns_canonical_envelope backend\tests\test_sprint118_yolo_preflight_ui.py -q` passed: 2 tests. -- `cd frontend && npm run typecheck` passed after adding the preflight API client and Detection Lab panel. -- `python -m pytest backend\tests\test_sprint13_yolo_preflight.py backend\tests\test_sprint118_yolo_preflight_ui.py backend\tests\test_sprint48_api_contract_audit.py -q` passed: 13 tests. -- `python -m compileall backend/app` passed. -- `cd backend && python -m pytest -q` passed: 371 tests. -- `cd frontend && npm run build` passed. -- `bash scripts/run_readiness_check.sh` passed: 371 backend tests plus frontend typecheck/build and API contract audit for 80 documented routes. -- `cd backend && python -m alembic heads` passed: `202606120900 (head)`. -- `cd backend && python -m alembic upgrade head --sql` passed. -- `bash -n scripts/live_migration_smoke.sh` and `bash -n scripts/deploy_tower.sh` passed. -- `git push` passed after Tower/Gitea became reachable again and pushed commit `7aa9382`. -- `powershell -NoProfile -ExecutionPolicy Bypass -File scripts\deploy_tower.ps1` with `GEOINTEL_INSTALL_AI=true` passed and redeployed Tower from commit `7aa9382`. -- Deploy-time live migration smoke passed on Tower; PostGIS reported `3.6 USE_GEOS=1 USE_PROJ=1 USE_STATS=1` and Alembic head was `202606120900`. -- Deploy-time browser runtime verification passed for `http://192.0.2.10:1202`, API proxy and icon. -- Live API check passed for `GET http://192.0.2.10:1202/api/v1/detection/yolo/preflight`: it returned the canonical `data` envelope, `status=not_configured`, `YOLO_ENABLED=false`, `torch_version=2.12.1`, `ultralytics_version=8.4.89`, `yolo_config_dir=/app/storage/ultralytics`, `will_download_models=false` and `will_run_inference=false`. -- Tower container check passed with explicit CLI `--enabled`: `dependencies_available=true`, `torch_version=2.12.1`, `ultralytics_version=8.4.89`, `cuda_available=false`, `status=not_configured`, `will_download_models=false` and `will_run_inference=false` because no local model path is configured yet. - -Limitations: -- `GEOINTEL_INSTALL_AI=true` installs optional PyTorch/Ultralytics dependencies but still requires a user-provided local model file; GeoIntel does not download weights. -- Reuse mode intentionally reuses only the latest saved map-selection dataset for QA/QC. It does not delete or mutate older derived datasets/exports. - -Next recommended pass: -- Run full readiness, deploy Tower, and browser-verify both Map run modes plus configured-YOLO preflight status in the live container. - -## Sprint 116 Operational GIS map workflow (2026-07-04) - -Changed: -- Switched the default MapLibre basemap to an OpenStreetMap road raster style with visible attribution while preserving `VITE_MAP_STYLE_URL` as the override for managed/production map styles. -- Added a persisted database layer selector to the Map workspace so ready vector datasets can be opened directly from stored project data. -- Added an Operational GIS run panel that reuses the selected AOI bbox or active layer bbox and calls the existing persisted `vector_features` bbox selection workflow. -- Added a visible basemap policy notice when the public OpenStreetMap fallback is active. -- Added a guided operational workflow that brings query, derived dataset save, GeoJSON export, reference selection, QA/QC run and evidence handoff into the Map workspace. -- Added a one-click full GIS workflow action that runs persisted selection, saves the derived dataset, saves a GeoJSON export and optionally runs QA/QC against the selected reference dataset. -- Updated `.env.example`, `CHANGELOG.md`, `docs/TODO.md`, `docs/ENVIRONMENT_SPEC.md` and `frontend/README.md`. -- Added regression coverage in `backend/tests/test_sprint116_operational_gis_map_workflow.py`. - -Validation: -- `cd frontend && npm run typecheck` passed. -- `python -m pytest backend\tests\test_sprint116_operational_gis_map_workflow.py backend\tests\test_sprint85_map_workspace_density.py backend\tests\test_sprint106_map_bbox_extract.py backend\tests\test_sprint107_map_selection_export.py backend\tests\test_sprint108_map_selection_derived_dataset.py -q` passed: 18 tests. -- `python -m pytest backend\tests\test_sprint116_operational_gis_map_workflow.py backend\tests\test_sprint109_map_selection_qa_shortcut.py backend\tests\test_sprint107_map_selection_export.py backend\tests\test_sprint108_map_selection_derived_dataset.py -q` passed: 11 tests. -- `python -m pytest backend\tests\test_sprint116_operational_gis_map_workflow.py -q` passed: 2 tests after aligning `.env.example` with the managed-style override policy. -- RED: `python -m pytest backend\tests\test_sprint116_operational_gis_map_workflow.py -q` failed before implementation because `Run full GIS workflow`, `runFullGisWorkflow` and `fullWorkflowStatus` were not present. -- `python -m pytest backend\tests\test_sprint116_operational_gis_map_workflow.py -q` passed: 2 tests after adding the full GIS workflow action. -- `python -m pytest backend\tests\test_sprint116_operational_gis_map_workflow.py backend\tests\test_sprint106_map_bbox_extract.py backend\tests\test_sprint107_map_selection_export.py backend\tests\test_sprint108_map_selection_derived_dataset.py backend\tests\test_sprint109_map_selection_qa_shortcut.py backend\tests\test_sprint110_map_qa_evidence_drilldown.py -q` passed: 18 tests. -- `cd frontend && npm run build` passed. -- `python -m compileall backend/app` passed. -- `cd backend && python -m pytest -q` passed: 364 tests. -- `bash scripts/run_readiness_check.sh` passed: 364 backend tests plus frontend typecheck/build. -- `cd backend && python -m alembic heads` passed: `202606120900 (head)`. -- `cd backend && python -m alembic upgrade head --sql` passed. -- `bash -n scripts/live_migration_smoke.sh` passed. -- `powershell -NoProfile -ExecutionPolicy Bypass -File scripts\deploy_tower.ps1` passed; rebuilt and redeployed the all-in-one container on `http://192.0.2.10:1202` from commit `350d50a`. -- Deploy-time live migration smoke passed after the database became ready on attempt 3; PostGIS reported `3.6 USE_GEOS=1 USE_PROJ=1 USE_STATS=1` and Alembic head was `202606120900`. -- Deploy-time browser runtime verification passed for frontend, API proxy and icon. -- Internal Codex browser validation passed against `http://192.0.2.10:1202`: the Map workspace rendered a nonblank road basemap, persisted vector layer selector, operational GIS run panel and bbox query action with no console errors. -- `powershell -NoProfile -ExecutionPolicy Bypass -File scripts\deploy_tower.ps1` passed again after the guided workflow update; rebuilt and redeployed the all-in-one container on `http://192.0.2.10:1202` from commit `14b66e6`. -- Deploy-time live migration smoke passed after the database became ready on attempt 2; PostGIS reported `3.6 USE_GEOS=1 USE_PROJ=1 USE_STATS=1` and Alembic head was `202606120900`. -- Internal Codex browser validation passed: the Map workspace showed the basemap policy notice, database layer selector, guided operational GIS steps/actions and nonblank map canvas with no console errors. -- `powershell -NoProfile -ExecutionPolicy Bypass -File scripts\deploy_tower.ps1` passed after aligning `.env.example`; rebuilt and redeployed the all-in-one container on `http://192.0.2.10:1202` from commit `fc88ceb`. -- Deploy-time live migration smoke passed after the database became ready on attempt 2; PostGIS reported `3.6 USE_GEOS=1 USE_PROJ=1 USE_STATS=1` and Alembic head was `202606120900`. -- Deploy-time browser runtime verification passed for frontend, API proxy and icon. -- Tower runtime check passed after the one-click GIS workflow update: remote checkout is commit `5331358`, the `geointel` all-in-one container is healthy and published on `0.0.0.0:1202->80/tcp`. -- `LIVE_SMOKE_CONTAINER=geointel bash scripts/live_migration_smoke.sh` passed on Tower; PostGIS reported `3.6 USE_GEOS=1 USE_PROJ=1 USE_STATS=1`, required runtime schema objects were present and Alembic head was `202606120900`. -- `bash scripts/verify_browser_runtime.sh http://192.0.2.10:1202` passed on Tower for frontend, API proxy and icon. -- Internal Codex browser validation passed against `http://192.0.2.10:1202`: the Map workspace rendered without console warnings/errors or horizontal overflow, the `Run full GIS workflow` action was present, and a live run produced the persisted query/save/export status `Dataset/export complete. Select a reference dataset to add QA/QC.` - -Limitations: -- The default OpenStreetMap tile service is appropriate for local V1 testing and demos, but production or heavier deployments should set `VITE_MAP_STYLE_URL` to a managed tile/style provider. -- This pass does not add live GRB/OSM fetching, new API routes, new migrations or fake data. -- The one-click workflow can still create a new derived dataset/export each time it is clicked; a future polish pass should add explicit reuse/replace behavior for repeated operator runs. - -Next recommended pass: -- Add reuse/replace behavior for repeated map workflow runs and make reference selection for QA/QC more guided in the Map workspace. - -## Sprint 115 QA/QC and Exports usability layout pass (2026-07-04) - -Changed: -- Added a QA/Exports usability layer to the frontend shell CSS to reduce evidence/history density without changing behavior. -- Rebalanced QA/QC and Exports workspace columns for review-first usage. -- Made QA/QC summary, handoff, drilldown, feature evidence, metric history and raw provenance surfaces more compact. -- Reduced raw QA provenance height so JSON evidence remains available but no longer dominates the page. -- Made export handoff cards, latest-artifact cards, action cards and export history controls denser and easier to scan. -- Updated `CHANGELOG.md`, `docs/TODO.md` and `frontend/README.md`. -- Added regression coverage in `backend/tests/test_sprint115_quality_export_usability_layout.py`. - -Validation: -- `cd frontend && npm run typecheck` passed. -- `cd frontend && npm run build` passed. -- `python -m pytest backend\tests\test_sprint115_quality_export_usability_layout.py backend\tests\test_sprint86_quality_workspace_density.py backend\tests\test_sprint89_export_system_density.py backend\tests\test_sprint70_quality_handoff_polish.py backend\tests\test_sprint78_export_preview_readability.py -q` passed: 15 tests. -- `python -m compileall backend/app` passed. -- `cd backend && python -m pytest -q` passed: 362 tests. -- `bash scripts/run_readiness_check.sh` passed: 362 backend tests plus frontend typecheck/build. -- `powershell -NoProfile -ExecutionPolicy Bypass -File scripts\deploy_tower.ps1` passed; rebuilt and redeployed the all-in-one container on `http://192.0.2.10:1202` from commit `915b34c`. -- Deploy-time live migration smoke passed after the database became ready on attempt 2; PostGIS reported `3.6 USE_GEOS=1 USE_PROJ=1 USE_STATS=1` and Alembic head was `202606120900`. -- Deploy-time browser runtime verification passed for frontend, API proxy and icon. - -Limitations: -- This pass is visual/layout only; it does not change API contracts, persistence, export generation, QA metrics or map behavior. -- Live Tower redeploy has been run; the QA/QC and Exports usability layout pass is available at `http://192.0.2.10:1202`. - -Next recommended pass: -- Run a live visual audit after redeploy, then refine AI Labs/System or address any remaining visual rough edges found in the browser. - -## Sprint 114 Data and Map usability layout pass (2026-07-04) - -Changed: -- Added a Data/Map usability layer to the frontend shell CSS to improve the core select-and-extract workflow without changing behavior. -- Rebalanced the Data workspace columns and made dataset upload, role summaries, catalog cards, metrics and actions more compact. -- Made the Map workspace more map-first by ordering the MapLibre frame before dense controls and increasing desktop map height. -- Compressed map context, provenance, layer controls, bbox selection, selected-feature extraction and inspector surfaces. -- Updated `CHANGELOG.md`, `docs/TODO.md` and `frontend/README.md`. -- Added regression coverage in `backend/tests/test_sprint114_data_map_usability_layout.py`. - -Validation: -- `cd frontend && npm run typecheck` passed. -- `cd frontend && npm run build` passed. -- `python -m pytest backend\tests\test_sprint113_calm_workbench_layout.py backend\tests\test_sprint114_data_map_usability_layout.py backend\tests\test_sprint74_data_map_mobile_polish.py backend\tests\test_sprint85_map_workspace_density.py -q` passed: 10 tests. -- `python -m compileall backend/app` passed. -- `cd backend && python -m pytest -q` passed: 360 tests. -- `bash scripts/run_readiness_check.sh` passed: 360 backend tests plus frontend typecheck/build. -- `powershell -NoProfile -ExecutionPolicy Bypass -File scripts\deploy_tower.ps1` passed; rebuilt and redeployed the all-in-one container on `http://192.0.2.10:1202` from commit `9721937`. -- Deploy-time live migration smoke passed after the database became ready on attempt 2; PostGIS reported `3.6 USE_GEOS=1 USE_PROJ=1 USE_STATS=1` and Alembic head was `202606120900`. -- Deploy-time browser runtime verification passed for frontend, API proxy and icon. - -Limitations: -- This pass is visual/layout only; it does not change API contracts, persistence, map query behavior, exports or QA logic. -- Live Tower redeploy has been run; the Data and Map usability layout pass is available at `http://192.0.2.10:1202`. - -Next recommended pass: -- Run a live visual audit after redeploy and then refine QA/QC and Exports in the same quieter style. - -## Sprint 113 calm workbench layout pass (2026-07-04) - -Changed: -- Added a calm-density layer to the frontend shell CSS to reduce visual pressure without changing workflows. -- Softened the base palette, borders and shadows. -- Made the top context bar, left workspace navigation, main heading, readiness tiles and inspector surfaces more compact. -- Hid the duplicated workspace command bar because the sidebar remains the primary persistent navigation. -- Updated `CHANGELOG.md`, `docs/TODO.md` and `frontend/README.md`. -- Added regression coverage in `backend/tests/test_sprint113_calm_workbench_layout.py`. - -Validation: -- `cd frontend && npm run typecheck` passed. -- `python -m pytest backend\tests\test_sprint49_workbench_shell_refactor.py backend\tests\test_sprint62_frontend_visual_polish.py backend\tests\test_sprint82_shell_density_polish.py backend\tests\test_sprint83_workspace_panel_hierarchy.py -q` passed: 10 tests. -- `cd frontend && npm run build` passed. -- `python -m pytest backend\tests\test_sprint113_calm_workbench_layout.py -q` passed: 2 tests. -- `python -m compileall backend/app` passed. -- `cd backend && python -m pytest -q` passed: 358 tests. -- `bash scripts/run_readiness_check.sh` passed: 358 backend tests plus frontend typecheck/build. -- `powershell -NoProfile -ExecutionPolicy Bypass -File scripts\deploy_tower.ps1` passed; rebuilt and redeployed the all-in-one container on `http://192.0.2.10:1202` from commit `0355a3d`. -- Deploy-time live migration smoke passed after the database became ready on attempt 3; PostGIS reported `3.6 USE_GEOS=1 USE_PROJ=1 USE_STATS=1` and Alembic head was `202606120900`. -- Deploy-time browser runtime verification passed for frontend, API proxy and icon. - -Limitations: -- This pass improves visual density and hierarchy only; no API, persistence, workflow or map behavior changed. -- Live Tower redeploy has been run; the calmer layout is available at `http://192.0.2.10:1202`. - -Next recommended pass: -- Do a live visual audit after redeploy and then tune individual workspaces, starting with Data and Map, based on actual screenshots. - -## Sprint 112 QA evidence map overlay (2026-06-25) - -Changed: -- Added `QualityEvidenceService` to resolve persisted QA/QC evidence ids back to stored geometries. -- Added `GET /api/v1/projects/{project_id}/quality-checks/{quality_check_id}/evidence/geojson`. -- The endpoint returns a canonical envelope with `quality_check_id`, dataset/run provenance, warnings and a GeoJSON FeatureCollection. -- Evidence resolution supports candidate dataset `vector_features`, candidate persisted `detections`/`segmentations` for analysis-run QA, and reference `vector_features`. -- Added QA/QC panel actions to show selected or latest evidence on the Map workspace. -- Added a MapLibre QA evidence source/layers with distinct match candidate, match reference, false-positive and false-negative styling. -- Added map overlay loading/error/clear state and a compact legend. -- Updated `docs/API_CONTRACTS.md`, `frontend/README.md`, `CHANGELOG.md` and `docs/TODO.md`. -- Added regression coverage in `backend/tests/test_sprint112_qa_evidence_overlay.py`. - -Validation: -- RED: `python -m pytest backend\tests\test_sprint112_qa_evidence_overlay.py -q` failed before implementation because `app.services.quality_evidence_service` did not exist. -- RED: after backend implementation, the same test failed until frontend `qaEvidenceData`/API wiring existed. -- `python -m pytest backend\tests\test_sprint112_qa_evidence_overlay.py -q` passed: 4 tests. -- `cd frontend && npm run typecheck` passed after making the MapLibre expression type explicit. -- `python -m pytest backend\tests\test_sprint112_qa_evidence_overlay.py backend\tests\test_qa_service.py backend\tests\test_sprint8c_detection_visualization_qa.py backend\tests\test_sprint9_segmentation_foundation.py -q` passed: 25 tests. -- `python -m compileall backend/app` passed. -- `cd backend && python -m pytest -q` passed: 356 tests. -- `cd frontend && npm run typecheck` passed. -- `cd frontend && npm run build` passed. -- `cd backend && python -m alembic heads` passed: `202606120900 (head)`. -- `cd backend && python -m alembic upgrade head --sql` passed. -- `bash -n scripts/live_migration_smoke.sh` passed. -- `bash scripts/run_readiness_check.sh` passed: 356 backend tests plus frontend typecheck/build. -- `powershell -NoProfile -ExecutionPolicy Bypass -File scripts\deploy_tower.ps1` passed; rebuilt and redeployed the all-in-one container on `http://192.0.2.10:1202` from commit `b9674a0`. -- Deploy-time live migration smoke passed against the container database after the database became ready on attempt 3; PostGIS reported `3.6 USE_GEOS=1 USE_PROJ=1 USE_STATS=1` and Alembic head was `202606120900`. -- Deploy-time browser runtime verification passed for frontend, API proxy and icon. -- Live QA evidence API smoke passed: `GET /api/v1/projects/c0b00f1f-80bf-4992-be94-f5e5e6f6bf63/quality-checks/2a291f88-5ed1-4110-ba6b-d200ec722098/evidence/geojson` returned a GeoJSON FeatureCollection with 4 persisted evidence features and 0 warnings. -- Internal Codex browser validation passed against `http://192.0.2.10:1202`: the QA/QC evidence drilldown rendered, `Show evidence overlay` opened the Map workspace, MapLibre canvas was present, the QA/QC evidence overlay reported 4 rendered features, and the mobile viewport had no horizontal overflow. - -Limitations: -- The overlay is generated read-only from existing persisted evidence and geometries; no new evidence table or migration was introduced. -- Missing evidence ids are reported as warnings and do not create fake geometries. -- No provider fetching, AI dependency, real model behavior or new product domain was added. - -Next recommended pass: -- Consider a small export/handoff action for the evidence overlay GeoJSON or a reusable browser smoke script that verifies the QA evidence overlay after deploy. - -## Sprint 111 QA feature evidence persistence (2026-06-25) - -Changed: -- Added feature-level evidence extraction to the shared QA IoU matcher. -- Dataset QA now returns and persists `match_evidence`, `false_positive_evidence` and `false_negative_evidence`. -- Detection QA and segmentation QA now use the same evidence-aware matcher and persist the same evidence keys in `quality_checks.findings_json`. -- Extended the QA/QC drilldown with compact matched, false-positive and false-negative feature id lists before the raw findings JSON. -- Updated `docs/API_CONTRACTS.md`, `frontend/README.md`, `CHANGELOG.md` and `docs/TODO.md`. -- Added/extended regression coverage in `backend/tests/test_qa_service.py`, `backend/tests/test_sprint7a_persistence_foundation.py` and `backend/tests/test_sprint111_qa_feature_evidence.py`. - -Validation: -- RED: `python -m pytest backend\tests\test_qa_service.py -q` failed before implementation because `QaProviderComparisonResult` had no `match_evidence`. -- RED: `python -m pytest backend\tests\test_sprint111_qa_feature_evidence.py -q` failed before docs were updated because `docs/API_CONTRACTS.md` did not document the evidence keys. -- `python -m pytest backend\tests\test_qa_service.py -q` passed: 3 tests. -- `python -m pytest backend\tests\test_sprint8c_detection_visualization_qa.py backend\tests\test_sprint9_segmentation_foundation.py -q` passed: 18 tests. -- `python -m pytest backend\tests\test_sprint111_qa_feature_evidence.py -q` passed: 2 tests. -- `python -m pytest backend\tests\test_qa_service.py backend\tests\test_sprint7a_persistence_foundation.py -q` passed: 10 tests. -- `python -m compileall backend/app` passed. -- `cd backend && python -m pytest -q` passed: 352 tests. -- `cd frontend && npm run typecheck` passed. -- `cd frontend && npm run build` passed. -- `cd backend && python -m alembic heads` passed: `202606120900 (head)`. -- `cd backend && python -m alembic upgrade head --sql` passed. -- `bash -n scripts/live_migration_smoke.sh` passed. -- `bash scripts/run_readiness_check.sh` passed. -- `powershell -NoProfile -ExecutionPolicy Bypass -File scripts\deploy_tower.ps1` passed; rebuilt and redeployed the all-in-one container on `http://192.0.2.10:1202`. -- Deploy-time live migration smoke passed against the container database, including PostGIS/version/schema checks. -- Deploy-time browser runtime verification passed for frontend, API proxy and icon. -- Live QA API smoke passed: `POST /api/v1/qa/detections-vs-reference` returned `match_evidence`, `false_positive_evidence` and `false_negative_evidence`. -- Live persisted quality-check smoke passed: `GET /api/v1/projects/c0b00f1f-80bf-4992-be94-f5e5e6f6bf63/quality-checks` returned the evidence arrays in `findings_json`. - -Limitations: -- Feature-level evidence is persisted as ids/IoU metadata in `quality_checks.findings_json`; no `quality_check_items` table or first-class evidence geometry table was introduced. -- Evidence map overlays can now be built from persisted ids, but overlay generation remains future work. -- No migration, provider fetching, AI dependency, real model behavior or new product domain was added. - -Next recommended pass: -- Add QA evidence overlay generation by resolving persisted evidence ids back to candidate/reference geometries and rendering false positives/false negatives as MapLibre layers. - -## Sprint 110 Map QA evidence drilldown (2026-06-25) - -Changed: -- Extended `QaComparisonResult` frontend typing with optional `quality_check_id`, matching the existing backend QA result payload. -- Updated `useMapSelectionQa` to keep the latest persisted map-selection quality-check id after a successful QA/QC comparison. -- Extended the Map workspace QA/QC result state with inline evidence: quality-check id, matches, false positives, false negatives, mean IoU and QA warnings. -- Added `Open QA/QC evidence` handoff from Map workspace to the existing QA/QC workspace drilldown, avoiding a parallel QA detail system. -- Added compact styling for the Map QA evidence and warning surface. -- Updated `frontend/README.md`, `CHANGELOG.md` and `docs/TODO.md`. -- Added regression coverage in `backend/tests/test_sprint110_map_qa_evidence_drilldown.py`. - -Validation: -- RED: `python -m pytest backend\tests\test_sprint110_map_qa_evidence_drilldown.py -q` failed before implementation because the hook/evidence wiring was absent. -- `python -m pytest backend\tests\test_sprint110_map_qa_evidence_drilldown.py -q` passed: 2 tests. -- `python -m compileall backend/app` passed. -- `cd backend && python -m pytest -q` passed: 349 tests. -- `cd frontend && npm run typecheck` passed. -- `cd frontend && npm run build` passed. -- `cd backend && python -m alembic heads` passed: `202606120900 (head)`. -- `cd backend && python -m alembic upgrade head --sql` passed. -- `bash -n scripts/live_migration_smoke.sh` passed. -- `bash scripts/run_readiness_check.sh` passed. -- `powershell -NoProfile -ExecutionPolicy Bypass -File scripts\deploy_tower.ps1` passed; rebuilt and redeployed the all-in-one container on `http://192.0.2.10:1202`. -- Deploy-time live migration smoke passed against the container database, including PostGIS/version/schema checks. -- Deploy-time browser runtime verification passed for frontend, API proxy and icon. -- Live API proxy smoke passed: `GET http://192.0.2.10:1202/api/v1/projects` returned the demo project envelope. - -Limitations: -- The Map evidence handoff opens the existing QA/QC workspace; selecting a specific historical check inside that workspace remains governed by the QA/QC panel's own latest-check behavior. -- False-positive and false-negative geometries are summarized by persisted metrics/findings; dedicated map overlays for unmatched evidence remain future work. -- No backend API contract, migration, provider fetching, AI dependency, real model behavior or new product domain was added. - -Next recommended pass: -- Add optional unmatched-evidence map overlays once the QA persistence model stores explicit matched/unmatched feature ids or geometries. - -## Sprint 109 Map selection QA shortcut (2026-06-25) - -Changed: -- Added `useMapSelectionQa` to keep Map workspace QA/QC orchestration out of `App.tsx`. -- Added a Map workspace QA/QC shortcut after `Save as dataset`, allowing the latest derived map selection dataset to be compared against a selected reference dataset. -- The shortcut reuses the existing `qaApi.runQa` flow and refreshes persisted quality checks/project data after completion. -- Added inline precision, recall, F1 and quality-check status feedback in the Map workspace. -- Added compact styling for the Map selection QA surface. -- Updated `frontend/README.md`, `CHANGELOG.md` and `docs/TODO.md`. -- Added regression coverage in `backend/tests/test_sprint109_map_selection_qa_shortcut.py`. - -Validation: -- RED: `python -m pytest backend\tests\test_sprint109_map_selection_qa_shortcut.py -q` failed before implementation because the hook and wiring were absent. -- `python -m pytest backend\tests\test_sprint109_map_selection_qa_shortcut.py -q` passed: 2 tests. -- `python -m compileall backend/app` passed. -- `cd backend && python -m pytest -q` passed: 347 tests. -- `cd frontend && npm run typecheck` passed. -- `cd frontend && npm run build` passed. -- `cd backend && python -m alembic heads` passed: `202606120900 (head)`. -- `cd backend && python -m alembic upgrade head --sql` passed. -- `bash -n scripts/live_migration_smoke.sh` passed. -- `bash scripts/run_readiness_check.sh` passed. -- `powershell -NoProfile -ExecutionPolicy Bypass -File scripts\deploy_tower.ps1` passed; rebuilt and redeployed the all-in-one container on `http://192.0.2.10:1202`. -- Deploy-time live migration smoke passed against the container database, including PostGIS/version/schema checks. -- Deploy-time browser runtime verification passed for frontend, API proxy and icon. -- Live API QA smoke passed: `POST /api/v1/qa/detections-vs-reference` compared derived map selection dataset `266aa1de-908e-4bc4-987e-996374ad747b` against reference dataset `21dd968a-2ba4-4798-89d4-f3af91f9d24c`, returned `precision=0.5`, `recall=0.5`, `f1_score=0.5`, `mean_iou=0.8339768339652592` and persisted quality check `1730c270-6dee-4000-8813-12aa91df6b33`. -- Live quality-check list smoke passed: `GET /api/v1/projects/c0b00f1f-80bf-4992-be94-f5e5e6f6bf63/quality-checks` returned the persisted map-selection QA check with precision, recall, F1, mean IoU, false-positive and false-negative metrics. - -Limitations: -- The Map shortcut currently uses the existing QA comparison defaults with IoU threshold `0.5`. -- QA results are summarized inline; detailed false-positive/false-negative evidence remains in the QA/QC workspace. -- No backend API contract, migration, provider fetching, AI dependency, real model behavior or new product domain was added. - -Next recommended pass: -- Add a QA result drilldown/handoff from the Map workspace so operators can inspect persisted false-positive and false-negative evidence directly after running selection QA/QC. - -## Sprint 108 Map selection derived datasets (2026-06-25) - -Changed: -- Added `POST /api/v1/projects/{project_id}/datasets/{dataset_id}/vector/select/derive`. -- Added `VectorSelectionDeriveRequest` for bbox selection-to-derived-dataset requests. -- Added `VectorOperationsService.derive_selection_dataset`, which selects persisted PostGIS `vector_features`, writes a derived GeoJSON dataset artifact, stores source provenance and re-indexes the derived features into `vector_features`. -- Added `Save as dataset` to the Map workspace selection result state with loading/error/latest-dataset feedback. -- Updated frontend dataset API typing and wiring for selection-derived datasets. -- Updated `docs/API_CONTRACTS.md`, `backend/README.md`, `frontend/README.md`, `CHANGELOG.md` and `docs/TODO.md`. -- Added regression coverage in `backend/tests/test_sprint108_map_selection_derived_dataset.py`. - -Validation: -- RED: `python -m pytest backend\tests\test_sprint108_map_selection_derived_dataset.py -q` failed before implementation because the service, route and frontend contracts were absent. -- `python -m pytest backend\tests\test_sprint108_map_selection_derived_dataset.py -q` passed: 4 tests. -- `python -m compileall backend/app` passed. -- `cd backend && python -m pytest -q` passed: 345 tests. -- `cd frontend && npm run typecheck` passed. -- `cd frontend && npm run build` passed. -- `cd backend && python -m alembic heads` passed: `202606120900 (head)`. -- `cd backend && python -m alembic upgrade head --sql` passed. -- `bash -n scripts/live_migration_smoke.sh` passed. -- `bash scripts/run_readiness_check.sh` passed. -- `powershell -NoProfile -ExecutionPolicy Bypass -File scripts\deploy_tower.ps1` passed; rebuilt and redeployed the all-in-one container on `http://192.0.2.10:1202`. -- Deploy-time live migration smoke passed against the container database, including PostGIS/version/schema checks. -- Deploy-time browser runtime verification passed for frontend, API proxy and icon. -- Live API smoke passed: `POST /api/v1/projects/c0b00f1f-80bf-4992-be94-f5e5e6f6bf63/datasets/6e5a3926-1a15-4136-b54f-ba5de9ec0e84/vector/select/derive` created derived dataset `266aa1de-908e-4bc4-987e-996374ad747b` with `dataset_role="derived"`, `source_name="map_selection"` and 2 features. -- Live API content smoke passed: `GET /api/v1/projects/c0b00f1f-80bf-4992-be94-f5e5e6f6bf63/datasets/266aa1de-908e-4bc4-987e-996374ad747b/content` returned a GeoJSON `FeatureCollection` with 2 features. -- Live PostGIS query smoke passed: `POST /api/v1/projects/c0b00f1f-80bf-4992-be94-f5e5e6f6bf63/datasets/266aa1de-908e-4bc4-987e-996374ad747b/vector/select` returned 2 features from the derived dataset's persisted `vector_features`. - -Limitations: -- Selection-derived datasets are bbox-only and use EPSG:4326 coordinates. -- Empty selections are rejected with `VECTOR_OPERATION_EMPTY_RESULT`. -- No migrations, live provider fetching, AI dependency, real model behavior or new product domain were added. - -Next recommended pass: -- Add an explicit QA/QC shortcut from a selected derived map dataset to compare it against a reference dataset without leaving the Map workspace. - -## Sprint 107 Map selection export handoff (2026-06-25) - -Changed: -- Added `vector_selection` to the GeoJSON export contract. -- Added `ExportService.export_vector_selection_geojson`, which queries persisted PostGIS `vector_features` through `VectorFeatureService.select_features_by_bbox`, writes the selected FeatureCollection and persists an `exports` row with `export_type="vector_selection_geojson"`. -- Extended `POST /api/v1/exports/geojson` to accept `export_kind="vector_selection"` with EPSG:4326 bbox and feature limit. -- Added frontend export API typing for bbox/limit and `useExportWorkflow.exportMapSelectionGeoJson`. -- Added `Save area export` to the Map workspace selection result state with loading/error/latest-path feedback. -- Updated `docs/API_CONTRACTS.md`, `backend/README.md`, `frontend/README.md`, `CHANGELOG.md` and `docs/TODO.md`. -- Added regression coverage in `backend/tests/test_sprint107_map_selection_export.py`. - -Validation: -- RED: `python -m pytest backend\tests\test_sprint107_map_selection_export.py -q` failed before implementation because the selection export service, route contract and frontend wiring were absent. -- `python -m pytest backend\tests\test_sprint107_map_selection_export.py -q` passed: 3 tests. -- `python -m compileall backend/app` passed. -- `cd backend && python -m pytest -q` passed: 341 tests. -- `cd frontend && npm run typecheck` passed. -- `cd frontend && npm run build` passed. -- `cd backend && python -m alembic heads` passed: `202606120900 (head)`. -- `cd backend && python -m alembic upgrade head --sql` passed. -- `bash -n scripts/live_migration_smoke.sh` passed. -- `bash scripts/run_readiness_check.sh` passed. -- `powershell -NoProfile -ExecutionPolicy Bypass -File scripts\deploy_tower.ps1` passed; rebuilt and redeployed the all-in-one container on `http://192.0.2.10:1202`. -- Deploy-time live migration smoke passed against the container database, including PostGIS/version/schema checks. -- Deploy-time browser runtime verification passed for frontend, API proxy and icon. -- Live API smoke passed: `POST /api/v1/exports/geojson` with `export_kind="vector_selection"` created export `1d16c78b-7e8c-4081-8edc-5be38811b50e` with `export_type="vector_selection_geojson"`, `feature_count=2` and `source_table="vector_features"`. -- Live API content smoke passed: `GET /api/v1/exports/1d16c78b-7e8c-4081-8edc-5be38811b50e/content` returned a GeoJSON `FeatureCollection` with 2 persisted vector features. - -Limitations: -- Selection exports are bbox-only and reuse the same EPSG:4326 constraints as the Map area selection endpoint. -- Saving a selection creates an export artifact, not a derived dataset. -- No migrations, live provider fetching, AI dependency, real model behavior or new product domain were added. - -Next recommended pass: -- Add a live browser smoke that exercises `Save area export`, confirms the export appears in Export Center history and previews/downloads the persisted `vector_selection_geojson` artifact. - -## Sprint 106 Map area selection extract (2026-06-25) - -Changed: -- Added `POST /api/v1/projects/{project_id}/datasets/{dataset_id}/vector/select` for read-only bbox selection over persisted PostGIS `vector_features`. -- Added `VectorSelectionBBox`, `VectorSelectionRequest` and `VectorSelectionResponse` schemas and exported them through the backend schema module. -- Added `VectorFeatureService.select_features_by_bbox`, including EPSG:4326 bbox validation, feature limit capping, PostGIS `ST_Intersects` query and GeoJSON FeatureCollection conversion from persisted geometries. -- Added frontend `selectVectorFeatures` API client support and `useMapSelectionExtract`. -- Extended the Map workspace with an `Area selection` panel, two-click map bbox selection, manual bbox inputs, selected-feature/AOI/active-layer bbox shortcuts, area GeoJSON download/copy actions and a compact selected-feature table. -- Extended `GeoMap` with `selection-bbox` and `selection-result` MapLibre GeoJSON overlays. -- Updated `docs/API_CONTRACTS.md`, `frontend/README.md`, `backend/README.md`, `CHANGELOG.md` and `docs/TODO.md`. -- Added regression coverage in `backend/tests/test_sprint106_map_bbox_extract.py`. - -Validation: -- RED: `python -m pytest backend\tests\test_sprint106_map_bbox_extract.py -q` failed before implementation because the vector selection service, route and frontend contracts were absent. -- `python -m pytest backend\tests\test_sprint106_map_bbox_extract.py -q` passed: 5 tests. -- `python -m compileall backend/app` passed. -- `cd backend && python -m pytest -q` passed: 338 tests. -- `cd frontend && npm run typecheck` passed. -- `cd frontend && npm run build` passed. -- `bash scripts/run_readiness_check.sh` passed. -- `cd backend && python -m alembic heads` passed: `202606120900 (head)`. -- `cd backend && python -m alembic upgrade head --sql` passed. -- `bash -n scripts/live_migration_smoke.sh` passed. -- `powershell -NoProfile -ExecutionPolicy Bypass -File scripts\deploy_tower.ps1` passed and redeployed commit `851d722` to Tower on port 1202. -- Deploy-time live migration smoke passed after database readiness attempt 3; PostGIS reported `3.6 USE_GEOS=1 USE_PROJ=1 USE_STATS=1`, required runtime schema objects were present and Alembic head was `202606120900`. -- Deploy-time browser runtime verification passed for frontend, API proxy and icon. -- `bash scripts/verify_workbench_default_state.sh http://192.0.2.10:1202` passed with demo project, AOI, 3/3 ready datasets and seeded QA/QC. -- Live API smoke passed against `POST /api/v1/projects/{project_id}/datasets/{dataset_id}/vector/select`: demo vector dataset returned 2 persisted features as a GeoJSON FeatureCollection. -- Internal browser validation passed against `http://192.0.2.10:1202`: Map workspace rendered `Area selection`, `Start map bbox` and `Run area extract`; `Use layer bbox` filled EPSG:4326 bbox values; `Run area extract` returned 2 features, showed `vector_features` source plus `Download area GeoJSON` and `Copy area GeoJSON`; console warnings/errors were empty. - -Limitations: -- Selection shape is bbox-only in EPSG:4326. Polygon/lasso selection remains future work. -- The endpoint is read-only and does not create exports or derived datasets; operators can download the selected GeoJSON client-side. -- No migrations, live provider fetching, AI dependency, real model behavior or new product domain were added. - -Next recommended pass: -- Add a browser/live smoke around the area selection panel after deploy, then consider export-center handoff for persisted selection artifacts if V1 needs server-side audit retention. - -## Sprint 105 Map feature extract (2026-06-25) - -Changed: -- Added a `Selection & extract` surface to `frontend/src/components/map/MapWorkspace.tsx`. -- Clicking a visible map feature now gives operators a focused extraction panel with geometry type, coordinate count, EPSG:4326 bbox, property count and property table. -- Added client-side `Download selected GeoJSON`, `Copy selected properties` and `Clear selection` actions for the clicked feature. -- Added a dedicated `selected-feature` MapLibre source with fill/line/circle highlight layers in `frontend/src/components/GeoMap.tsx`. -- Wired the selected feature highlight through `frontend/src/App.tsx`. -- Added responsive selection/extract CSS in `frontend/src/styles/app.css`. -- Updated `frontend/README.md`, `CHANGELOG.md` and `docs/TODO.md`. -- Added `backend/tests/test_sprint105_map_feature_extract.py`. - -Validation: -- RED: `python -m pytest backend\tests\test_sprint105_map_feature_extract.py -q` failed before implementation because the extract panel, selected-feature highlight layer and CSS contracts were absent. -- `python -m pytest backend\tests\test_sprint105_map_feature_extract.py backend\tests\test_sprint19_map_workbench.py backend\tests\test_sprint85_map_workspace_density.py -q` passed: 9 tests. -- `python -m compileall backend/app` passed. -- `cd backend && python -m pytest -q` passed: 333 tests. -- `cd frontend && npm run typecheck` passed. -- `cd frontend && npm run build` passed. -- `bash scripts/run_readiness_check.sh` passed. -- `cd backend && python -m alembic heads` passed: `202606120900 (head)`. -- `cd backend && python -m alembic upgrade head --sql` passed. -- `bash -n scripts/live_migration_smoke.sh` passed. -- `powershell -NoProfile -ExecutionPolicy Bypass -File scripts\deploy_tower.ps1` passed and redeployed commit `561304c` to Tower on port 1202. -- Deploy-time live migration smoke passed after database readiness attempt 3; PostGIS reported `3.6 USE_GEOS=1 USE_PROJ=1 USE_STATS=1`, required runtime schema objects were present and Alembic head was `202606120900`. -- Deploy-time browser runtime verification passed for frontend, API proxy and icon. -- Internal browser live check confirmed the Map workspace renders the `Selection & extract` panel and empty selection guidance at `http://192.0.2.10:1202`. -- Live frontend bundle check confirmed `Selection & extract`, `selected-feature` and `Download selected GeoJSON` markers in `/assets/index-DVYT-JPu.js`. - -Limitations: -- This pass extracts the single currently clicked and loaded map feature only. -- Rectangle, lasso or polygon selection over persisted PostGIS `vector_features` still requires a backend spatial query endpoint and drawing workflow. -- Internal browser canvas clicks did not reliably hit the small demo polygon features during validation; static regression tests, TypeScript build and live bundle markers verify the MapLibre selection wiring, and the live UI panel is present. -- No backend API contract, migration, provider fetching, AI dependency or persistence behavior changed. - -Next recommended pass: -- Add map area/rectangle selection backed by a PostGIS spatial-query endpoint for multi-feature extraction, then expose export handoff for the selected result set. - -## Sprint 100 raster tile Segmentation Lab handoff (2026-06-24) - -Changed: -- Added `segmentationTileManifestPath` state to `frontend/src/hooks/useSegmentationWorkflow.ts`. -- Sent `tile_manifest_path` in existing segmentation run requests when the field is populated. -- Added a `Tile manifest` input to `frontend/src/components/segmentation/SegmentationLab.tsx`. -- Added a `Use in Segmentation Lab` handoff beside the existing Detection Lab handoff in `frontend/src/components/datasets/RasterControls.tsx`. -- Wired the handoff through `frontend/src/components/datasets/DatasetDetailPanel.tsx` and `frontend/src/App.tsx`. -- Updated `frontend/README.md` and `CHANGELOG.md`. -- Added `backend/tests/test_sprint100_segmentation_manifest_handoff.py`. - -Validation: -- RED: `python -m pytest backend\tests\test_sprint100_segmentation_manifest_handoff.py -q` failed before implementation because segmentation manifest state and handoff wiring did not exist. -- `python -m pytest backend\tests\test_sprint100_segmentation_manifest_handoff.py -q` passed. -- `cd frontend && npm run typecheck` passed. -- `python -m pytest backend\tests\test_sprint100_segmentation_manifest_handoff.py backend\tests\test_sprint99_raster_ui_handoff.py backend\tests\test_sprint88_ai_lab_density.py backend\tests\test_sprint9_segmentation_foundation.py -q` passed: 17 tests. -- `cd frontend && npm run build` passed. -- `python -m compileall backend/app` passed. -- `python -m pytest -q` from `backend/` passed: 323 tests. -- `bash scripts/run_readiness_check.sh` passed. -- `cd backend && python -m alembic heads` passed: `202606120900 (head)`. -- `cd backend && python -m alembic upgrade head --sql` passed. -- `bash -n scripts/live_migration_smoke.sh` passed. -- `powershell -NoProfile -ExecutionPolicy Bypass -File scripts\deploy_tower.ps1` passed and redeployed `140314a` to Tower on port 1202. -- Deploy-time live migration smoke passed after the database became ready on attempt 3; PostGIS reported `3.6 USE_GEOS=1 USE_PROJ=1 USE_STATS=1`, required runtime schema objects were present and Alembic head was `202606120900`. -- Deploy-time browser runtime verification passed for frontend, API proxy and icon. -- `bash scripts/verify_demo_raster_workflow.sh http://192.0.2.10:1202` passed: inspect, preview, stats and `raster.tile`. -- `bash scripts/verify_workbench_default_state.sh http://192.0.2.10:1202` passed with `3/3 ready` datasets. -- `bash scripts/verify_workbench_interactions.sh http://192.0.2.10:1202` passed. -- Live frontend bundle check confirmed `Latest tile manifest`, `Use in Detection Lab`, `Use in Segmentation Lab` and `Raster tile manifest path` markers in `/assets/index-DygxAZpB.js`. - -Limitations: -- Frontend handoff only; no backend route, migration, provider fetching, AI dependency or model behavior changes. -- Segmentation remains governed by the existing model registry and explicit-run controls. - -Next recommended pass: -- Add a real browser interaction smoke for clicking both raster manifest handoff buttons into AI Labs, then continue with small usability polish around AI model readiness. - -## Sprint 99 raster tile Detection Lab handoff (2026-06-23) - -Changed: -- Added latest raster tile manifest tracking to `frontend/src/hooks/useDatasetWorkflow.ts` from persisted `raster.tile` job results and direct tile generation responses. -- Surfaced the latest manifest path in `frontend/src/components/datasets/RasterControls.tsx`. -- Added a `Use in Detection Lab` handoff that fills the selected raster dataset and tile manifest path in the existing Detection Lab state. -- Updated `frontend/src/components/datasets/DatasetDetailPanel.tsx`, `frontend/src/App.tsx`, `frontend/README.md` and `CHANGELOG.md`. -- Added `backend/tests/test_sprint99_raster_ui_handoff.py`. - -Validation: -- RED: `python -m pytest backend\tests\test_sprint99_raster_ui_handoff.py -q` failed before implementation because the raster tile manifest state and handoff wiring did not exist. -- `python -m pytest backend\tests\test_sprint99_raster_ui_handoff.py -q` passed. -- `cd frontend && npm run typecheck` passed. -- `python -m pytest backend\tests\test_sprint99_raster_ui_handoff.py backend\tests\test_sprint95_raster_pipeline_hardening.py backend\tests\test_sprint28_dataset_workflow_hook.py -q` passed: 6 tests. -- `cd frontend && npm run build` passed. -- `python -m compileall backend/app` passed. -- `python -m pytest -q` from `backend/` passed: 322 tests. -- `bash scripts/run_readiness_check.sh` passed. -- `cd backend && python -m alembic heads` passed: `202606120900 (head)`. -- `cd backend && python -m alembic upgrade head --sql` passed. -- `bash -n scripts/live_migration_smoke.sh` passed. -- `powershell -NoProfile -ExecutionPolicy Bypass -File scripts\deploy_tower.ps1` passed and redeployed `aa41dfa` to Tower on port 1202. -- Deploy-time live migration smoke passed after the database became ready on attempt 2; PostGIS reported `3.6 USE_GEOS=1 USE_PROJ=1 USE_STATS=1`, required runtime schema objects were present and Alembic head was `202606120900`. -- Deploy-time browser runtime verification passed for frontend, API proxy and icon. -- `bash scripts/verify_demo_raster_workflow.sh http://192.0.2.10:1202` passed: inspect, preview, stats and `raster.tile`. -- `bash scripts/verify_workbench_default_state.sh http://192.0.2.10:1202` passed with `3/3 ready` datasets. -- `bash scripts/verify_workbench_interactions.sh http://192.0.2.10:1202` passed. -- Live frontend bundle check confirmed `Latest tile manifest` and `Use in Detection Lab` markers in `/assets/index-gJWV1CAi.js`. - -Limitations: -- Frontend handoff only; no API contract, migration, provider fetching, AI inference or model behavior changes. -- The Detection Lab still follows the existing model availability and explicit-run constraints. - -Next recommended pass: -- Add a browser interaction smoke for clicking the raster manifest handoff into Detection Lab, or continue with segmentation tile-manifest prefill parity. - -## Sprint 98 demo raster workflow smoke (2026-06-23) - -Changed: -- Added `scripts/verify_demo_raster_workflow.sh`, a browser-facing runtime smoke for the seeded `demo_context_raster.tif` fixture. -- Added the new smoke to readiness syntax checks. -- Hardened `RasterOperationsService.tile` so tile manifest bounds accept both Rasterio tuple bounds and object bounds. -- Updated `backend/tests/test_raster_operations_service.py` to cover tuple-based window bounds. -- Added `backend/tests/test_sprint98_raster_workflow_smoke.py`. -- Updated `scripts/README.md` and `CHANGELOG.md`. - -Validation: -- RED: `python -m pytest backend\tests\test_sprint98_raster_workflow_smoke.py -q` failed before implementation because `scripts/verify_demo_raster_workflow.sh` did not exist. -- `python -m pytest backend\tests\test_sprint98_raster_workflow_smoke.py backend\tests\test_readiness_gate.py -q` passed: 14 tests. -- `bash -n scripts/verify_demo_raster_workflow.sh` passed. -- Live diagnostic run of `bash scripts/verify_demo_raster_workflow.sh http://192.0.2.10:1202` showed inspect, preview and stats passed, then raster tile failed with HTTP 500. -- Tower backend logs identified the root cause: `rasterio.windows.bounds(...)` returned a tuple, while tile manifest generation expected `.left/.bottom/.right/.top` attributes. -- RED: `python -m pytest backend\tests\test_raster_operations_service.py::test_raster_tile_returns_manifest_payload -q` reproduced the live `AttributeError` after updating the fixture to tuple bounds. -- `python -m pytest backend\tests\test_raster_operations_service.py::test_raster_tile_returns_manifest_payload backend\tests\test_sprint98_raster_workflow_smoke.py -q` passed: 2 tests. -- `python -m compileall backend/app` passed. -- `python -m pytest -q` from `backend/` passed: 321 tests. -- `cd frontend && npm run typecheck` passed. -- `cd frontend && npm run build` passed. -- `bash scripts/run_readiness_check.sh` passed. -- `cd backend && python -m alembic heads` passed: `202606120900 (head)`. -- `cd backend && python -m alembic upgrade head --sql` passed. -- `bash -n scripts/live_migration_smoke.sh` passed. -- `powershell -NoProfile -ExecutionPolicy Bypass -File scripts\deploy_tower.ps1` passed and redeployed `7b093c0` to Tower on port 1202. -- `bash scripts/verify_demo_raster_workflow.sh http://192.0.2.10:1202` initially proved the tile fix but exposed the existing job terminal status convention as `success` rather than `completed`; the smoke now accepts `success` and `completed`. -- `bash scripts/verify_demo_raster_workflow.sh http://192.0.2.10:1202` passed after the smoke status fix: inspect, preview, stats and raster tile manifest all succeeded. -- `bash scripts/verify_workbench_default_state.sh http://192.0.2.10:1202` passed after redeploy. -- `bash scripts/verify_workbench_interactions.sh http://192.0.2.10:1202` passed after redeploy. -- `bash scripts/verify_demo_export_workflow.sh http://192.0.2.10:1202` passed after redeploy. -- `bash scripts/run_readiness_check.sh` passed again after the smoke status update. - -Limitations: -- The raster smoke creates a small tile set each run. It is appropriate for local/runtime validation, not high-volume benchmarking. -- The smoke intentionally does not run AI inference or external imagery/provider fetching. - -Next recommended pass: -- Run full readiness, redeploy, then verify the raster smoke live against `http://192.0.2.10:1202`. - -## Sprint 97 demo raster fixture workflow (2026-06-23) - -Changed: -- Added `raster_dataset_id` to the demo workflow response contract. -- Extended `DemoWorkflowService` with a deterministic in-memory `demo_context_raster.tif` GeoTIFF fixture persisted through `StorageService` and the existing `datasets` table as a ready `raster`/`fixture` source dataset. -- Updated the frontend demo workflow hook so Detection and Segmentation Labs receive the seeded raster dataset while the candidate vector remains selected for Data, Map and Export review. -- Updated default-state and interaction smokes to require candidate vector, reference vector and raster fixture datasets as `3/3 ready`. -- Updated `scripts/README.md`, `frontend/README.md` and `CHANGELOG.md`. - -Validation: -- RED: `python -m pytest backend\tests\test_sprint97_demo_raster_fixture.py -q` failed before implementation because the demo schema/service and frontend hook did not expose or select a raster fixture. -- `python -m pytest backend\tests\test_sprint97_demo_raster_fixture.py -q` passed: 2 tests. -- `python -m compileall backend/app` passed. -- `python -m pytest backend\tests\test_sprint97_demo_raster_fixture.py backend\tests\test_sprint15_demo_workflow.py backend\tests\test_sprint21_demo_workflow_smoke.py backend\tests\test_readiness_gate.py -q` passed: 21 tests. -- `bash -n scripts/verify_workbench_default_state.sh` passed. -- `bash -n scripts/verify_workbench_interactions.sh` passed. -- `cd frontend && npm run typecheck` passed. -- `python -m pytest backend\tests\test_sprint96_useful_default_context.py backend\tests\test_sprint39_frontend_orchestration_hooks.py -q` passed: 11 tests. -- `python -m pytest -q` from `backend/` passed: 320 tests. -- `bash scripts/run_readiness_check.sh` passed. -- `cd frontend && npm run build` passed. -- `cd backend && python -m alembic heads` passed: `202606120900 (head)`. -- `cd backend && python -m alembic upgrade head --sql` passed. -- `bash -n scripts/live_migration_smoke.sh` passed. -- `powershell -NoProfile -ExecutionPolicy Bypass -File scripts\deploy_tower.ps1` passed and redeployed `ca730ed` to Tower on port 1202. -- `bash scripts/verify_workbench_default_state.sh http://192.0.2.10:1202` passed and reported `Datasets: 3/3 ready`. -- `bash scripts/verify_workbench_interactions.sh http://192.0.2.10:1202` passed and verified candidate, reference and raster fixture datasets. -- `bash scripts/verify_demo_export_workflow.sh http://192.0.2.10:1202` passed. -- `bash scripts/verify_gis_runtime.sh http://192.0.2.10:1202` passed. -- `bash scripts/verify_browser_runtime.sh http://192.0.2.10:1202` passed. -- Live API check confirmed `demo_context_raster.tif` as `raster`/`fixture`/`ready` with `EPSG:4326`. -- Chrome headless screenshot of `http://192.0.2.10:1202` showed the populated Overview workspace, selected demo context and no obvious desktop horizontal overflow. - -Limitations: -- The raster fixture is a tiny generated local GeoTIFF for V1 workflow validation only. It does not represent external imagery and does not enable real AI inference. -- No migrations, provider fetching, real YOLO/SAM behavior or product scope beyond the existing offline demo workflow changed. -- Optional `scripts/capture_workbench_screenshots.sh` could not run in this Windows runner because Playwright is not installed; Chrome headless was used for the live visual check instead. - -Next recommended pass: -- Continue with a focused raster operation happy-path smoke against the seeded raster fixture: inspect, preview, stats and tiling through the browser-facing API. - -## Sprint 48 Backend API contract audit (2026-06-17) - -Changed: -- Added `scripts/audit_api_contracts.py` to import the FastAPI app, enumerate the implemented `GET`/`POST`/`PATCH`/`DELETE` route surface and compare it with active `### METHOD route` headings in `docs/API_CONTRACTS.md`. -- Added the API contract audit to `scripts/run_readiness_check.sh`. -- Corrected contract drift in `docs/API_CONTRACTS.md`: - - documented `GET/PATCH /api/v1/projects/{project_id}/areas/{area_id}`; - - corrected vector stats from `POST` to implemented `GET`; - - documented `GET /api/v1/projects/{project_id}/datasets/{dataset_id}/content`; - - changed non-implemented building-stats, legacy analysis object-detection/segmentation and YOLO export entries from active route headings to future-route notes. -- Added `backend/tests/test_sprint48_api_contract_audit.py`. -- Updated `scripts/README.md`, `docs/TODO.md` and `CHANGELOG.md`. - -Validation: -- RED: `cd backend && python -m pytest tests/test_sprint48_api_contract_audit.py -q` failed before implementation because the audit script, readiness integration and route docs were missing. -- RED: `python scripts/audit_api_contracts.py` reported missing docs for 4 implemented routes and 5 stale documented routes. -- `python scripts/audit_api_contracts.py` passed: 76 implemented routes matched docs and 2 explicit non-envelope endpoints were tracked. -- `cd backend && python -m pytest tests/test_sprint48_api_contract_audit.py tests/test_readiness_gate.py -q` passed: 12 tests. -- `python -m py_compile scripts/audit_api_contracts.py` passed. -- `python -m compileall backend/app` passed. -- `cd backend && python -m pytest -W error::DeprecationWarning` passed: 201 tests. -- `bash scripts/run_readiness_check.sh` passed and included `API contract audit OK`. -- `cd frontend && npm run typecheck` passed. -- `cd frontend && npm run build` passed. -- `cd backend && python -m alembic heads` passed: `202606120900 (head)`. -- `cd backend && python -m alembic upgrade head --sql` passed. -- `bash -n scripts/live_migration_smoke.sh` passed. -- `powershell -NoProfile -ExecutionPolicy Bypass -File scripts\deploy_tower.ps1` passed and redeployed the all-in-one container to Tower on port 1202. -- `bash scripts/verify_gis_runtime.sh http://192.0.2.10:1202` passed after redeploy. -- `bash scripts/verify_workbench_default_state.sh http://192.0.2.10:1202` passed after redeploy. -- `bash scripts/verify_workbench_interactions.sh http://192.0.2.10:1202` passed after redeploy. - -Limitations: -- This pass audits route documentation presence, implemented/stale route drift and explicit non-envelope exceptions. It does not yet exercise every error path response body at runtime. -- No API behavior, migrations, provider fetching, AI behavior or product capabilities changed. - -Next recommended pass: -- Add an error-envelope runtime audit for representative invalid/missing-resource paths across projects, datasets, providers, detection, segmentation, QA and exports. - -## Sprint 47 Workbench interaction smoke (2026-06-17) - -Changed: -- Added stable `data-testid` anchors to the existing project, area, map, dataset, QA/QC and export controls so browser checks can target real controls instead of brittle text/layout selectors. -- Added `scripts/verify_workbench_interactions.sh`, a dependency-light runtime smoke that verifies the backing state for project switching, AOI/map selection, dataset selection, QA refresh and export refresh through the browser-facing API proxy. -- Added the script syntax check to `scripts/run_readiness_check.sh`. -- Added `backend/tests/test_sprint47_workbench_interaction_smoke.py` to keep the UI anchors, readiness gate and interaction smoke contract in place. -- Updated `scripts/README.md`, `docs/TODO.md` and `CHANGELOG.md`. - -Validation: -- RED: `cd backend && python -m pytest tests/test_sprint47_workbench_interaction_smoke.py -q` failed before implementation because the UI anchors, readiness script reference and interaction smoke script were missing. -- `cd backend && python -m pytest tests/test_sprint47_workbench_interaction_smoke.py -q` passed: 3 tests. -- `cd frontend && npm run typecheck` passed. -- `bash -n scripts/verify_workbench_interactions.sh` passed. -- `bash scripts/verify_workbench_interactions.sh http://192.0.2.10:1202` passed against the pre-deploy runtime API surface. -- `python -m compileall backend/app` passed. -- `cd backend && python -m pytest -W error::DeprecationWarning` passed: 198 tests. -- `bash scripts/run_readiness_check.sh` passed. -- `cd frontend && npm run build` passed. -- `cd backend && python -m alembic heads` passed: `202606120900 (head)`. -- `cd backend && python -m alembic upgrade head --sql` passed. -- `bash -n scripts/live_migration_smoke.sh` passed. -- `powershell -NoProfile -ExecutionPolicy Bypass -File scripts\deploy_tower.ps1` passed and redeployed the all-in-one container to Tower on port 1202. -- `bash scripts/verify_workbench_interactions.sh http://192.0.2.10:1202` passed after redeploy. -- `bash scripts/verify_workbench_default_state.sh http://192.0.2.10:1202` passed after redeploy. -- `bash scripts/verify_gis_runtime.sh http://192.0.2.10:1202` passed after redeploy. -- Live browser check against `http://192.0.2.10:1202` passed using the new anchors: project, map, dataset, QA/QC and export panels were present; QA refresh and export metadata actions worked; latest export updated; no horizontal overflow was detected. - -Limitations: -- The shell smoke validates the state behind the controls but does not click rendered controls by itself. The added `data-testid` anchors are intended for Codex/browser click checks and future browser artifact automation. -- No API contracts, migrations, provider fetching, AI behavior or product capabilities changed. - -Next recommended pass: -- Add persisted screenshot artifact automation for the anchored browser pass, or move to a backend service contract audit if UI stabilization is sufficient. - -## Sprint 46 Workbench default-state smoke (2026-06-17) - -Changed: -- Added `scripts/verify_workbench_default_state.sh`, a dependency-light runtime smoke for the browser-facing workbench default demo state. -- The smoke calls the offline demo workflow, then verifies `GeoIntel Demo - Building QA`, `Demo AOI - Geel buildings`, `2/2 ready` datasets and a persisted QA/QC result through canonical `data.items` envelopes. -- Added the script syntax check to `scripts/run_readiness_check.sh`. -- Extended `backend/tests/test_readiness_gate.py` so the readiness gate and script keep covering the default-state smoke contract. -- Updated `scripts/README.md` and `CHANGELOG.md`. - -Validation: -- RED: `cd backend && python -m pytest tests/test_readiness_gate.py -q` failed before implementation because `verify_workbench_default_state.sh` was missing and readiness did not reference it. -- `cd backend && python -m pytest tests/test_readiness_gate.py -q` passed: 9 tests. -- `bash -n scripts/verify_workbench_default_state.sh` passed. -- `bash scripts/verify_workbench_default_state.sh http://192.0.2.10:1202` passed. -- `python -m compileall backend/app` passed. -- `cd backend && python -m pytest -W error::DeprecationWarning` passed: 195 tests. -- `bash scripts/run_readiness_check.sh` passed. -- `cd frontend && npm run typecheck` passed. -- `cd frontend && npm run build` passed. -- `cd backend && python -m alembic heads` passed: `202606120900 (head)`. -- `cd backend && python -m alembic upgrade head --sql` passed. -- `bash -n scripts/live_migration_smoke.sh` passed. -- `powershell -NoProfile -ExecutionPolicy Bypass -File scripts\deploy_tower.ps1` passed and redeployed the all-in-one container to Tower on port 1202. -- `bash scripts/verify_workbench_default_state.sh http://192.0.2.10:1202` passed after redeploy. -- `bash scripts/verify_gis_runtime.sh http://192.0.2.10:1202` passed after redeploy. -- `bash scripts/verify_demo_export_workflow.sh http://192.0.2.10:1202` passed after redeploy. -- Live browser check against `http://192.0.2.10:1202` passed at 1280x720: selected project `GeoIntel Demo - Building QA`, status showed `1 area`, `2/2 ready` datasets and `2 checks`, map workspace rendered and no horizontal overflow was detected. - -Limitations: -- The committed smoke validates the connected default workbench state through HTTP/API contracts, not pixel layout. Browser screenshot and overflow validation remain a Codex/browser verification step. -- No API contracts, migrations, provider fetching, AI behavior or product capabilities changed. - -Next recommended pass: -- Add a deeper browser interaction smoke for core controls, starting with project switching, area selection and map layer opacity. - -## Sprint 45 Default demo selection polish (2026-06-17) - -Changed: -- Updated `frontend/src/hooks/useProjectWorkspace.ts` so cold-start project selection preserves an existing selected project, honors an explicit preferred project and otherwise prefers a populated demo/workbench project over an empty first project. -- New project creation now selects the newly created project immediately after creation. -- Updated `frontend/src/hooks/useDemoWorkflow.ts` so demo seed refresh passes the seeded project id to `loadProjects`. -- Extended orchestration tests to cover preferred demo selection and project creation selection behavior. - -Validation: -- `cd backend && python -m pytest tests/test_sprint39_frontend_orchestration_hooks.py tests/test_sprint21_demo_workflow_smoke.py -q` passed: 11 tests. -- `python -m compileall backend/app` passed. -- `cd backend && python -m pytest -W error::DeprecationWarning` passed: 194 tests. -- `bash scripts/run_readiness_check.sh` passed. -- `cd frontend && npm run typecheck` passed. -- `cd frontend && npm run build` passed. -- `cd backend && python -m alembic heads` passed: `202606120900 (head)`. -- `cd backend && python -m alembic upgrade head --sql` passed. -- `bash -n scripts/live_migration_smoke.sh` passed. -- Browser check against local Vite preview with live backend passed after async settle: selected project `GeoIntel Demo - Building QA`, status showed `1 area`, `2/2 ready` datasets and `2 checks`. -- `powershell -NoProfile -ExecutionPolicy Bypass -File scripts\deploy_tower.ps1` passed and redeployed the all-in-one container to Tower on port 1202. -- `bash scripts/verify_gis_runtime.sh http://192.0.2.10:1202` passed. -- `bash scripts/verify_demo_export_workflow.sh http://192.0.2.10:1202` passed. -- Live browser check against `http://192.0.2.10:1202` passed after async settle: selected project `GeoIntel Demo - Building QA`, status showed `1 area`, `2/2 ready` datasets and `2 checks`, with no horizontal overflow. - -Limitations: -- No API contracts, migrations, provider fetching, AI behavior or product capabilities changed. -- The heuristic probes up to eight project candidates on cold start; a future backend list endpoint with area/dataset counts would make this cleaner. - -Next recommended pass: -- Add a lightweight browser regression script for the demo start page once the UI state is stable enough to automate end to end. - -## Sprint 44 Workbench UI polish pass (2026-06-17) - -Changed: -- Reworked `frontend/src/styles/app.css` from a minimal browser-default stylesheet into a compact GIS workbench skin with modern controls, restrained neutral/green accents, scroll-contained long panels and responsive layout rules. -- Promoted `MapWorkspace` above the dense workflow grid in `frontend/src/App.tsx` so GIS context is visible before lower-detail provider, AI, QA and export panels. -- Moved `DatasetPanel` into the first workflow row beside project/area/provider setup. -- Added a static layout regression test in `backend/tests/test_sprint30_workbench_components.py` for map-first ordering and scroll-contained workflow panels. -- Updated frontend README and changelog. - -Validation: -- Browser visual check against local Vite preview passed at desktop width: map-first layout visible, workflow panels scroll-contained, page height reduced from roughly 14.9k px to roughly 3.2k px. -- Browser responsive check at 390px width passed with no horizontal overflow. -- `python -m compileall backend/app` passed. -- `cd backend && python -m pytest -W error::DeprecationWarning` passed: 194 tests. -- `bash scripts/run_readiness_check.sh` passed. -- `cd frontend && npm run typecheck` passed. -- `cd frontend && npm run build` passed. -- `cd backend && python -m alembic heads` passed: `202606120900 (head)`. -- `cd backend && python -m alembic upgrade head --sql` passed. -- `bash -n scripts/live_migration_smoke.sh` passed. -- `powershell -NoProfile -ExecutionPolicy Bypass -File scripts\deploy_tower.ps1` passed and redeployed `geointel-all-in-one:latest` to Tower on port 1202. -- `bash scripts/verify_gis_runtime.sh http://192.0.2.10:1202` passed. -- `bash scripts/verify_demo_export_workflow.sh http://192.0.2.10:1202` passed. -- Live browser check against `http://192.0.2.10:1202` passed: map-first layout rendered, scroll height roughly 3.2k px and no desktop horizontal overflow detected. - -Limitations: -- No API contracts, migrations, provider fetching, AI behavior or product capabilities changed. -- This is still a dense operational workbench rather than a designed product shell with navigation or tabs. -- The live default selected project can still be an empty project with the demo name; project selection polish remains a separate follow-up. - -Next recommended pass: -- Add UI browser regression coverage for the map-first demo workflow and polish the default project/demo selection state. - -## Sprint 43 Workbench bootstrap hook decomposition (2026-06-17) - -Changed: -- Moved frontend bootstrap, project-change reload/reset and detection/segmentation result reload effects from `frontend/src/App.tsx` into `frontend/src/hooks/useWorkbenchBootstrap.ts`. -- Kept `App.tsx` as a composition root that wires hook outputs into panels; it no longer imports `useEffect`. -- Extended orchestration tests so lifecycle side effects stay in the bootstrap hook. -- Updated frontend README, changelog and TODO status. - -Validation: -- `cd backend && python -m pytest tests/test_sprint39_frontend_orchestration_hooks.py -q` passed: 9 tests. -- `python -m compileall backend/app` passed. -- `cd backend && python -m pytest -W error::DeprecationWarning` passed: 193 tests. -- `bash scripts/run_readiness_check.sh` passed. -- `cd frontend && npm run typecheck` passed. -- `cd frontend && npm run build` passed. -- `cd backend && python -m alembic heads` passed: `202606120900 (head)`. -- `cd backend && python -m alembic upgrade head --sql` passed. -- `bash -n scripts/live_migration_smoke.sh` passed. -- `powershell -NoProfile -ExecutionPolicy Bypass -File scripts\deploy_tower.ps1` passed and redeployed `geointel-all-in-one:latest` to Tower on port 1202. -- `bash scripts/verify_gis_runtime.sh http://192.0.2.10:1202` passed. -- `bash scripts/verify_demo_export_workflow.sh http://192.0.2.10:1202` passed. -- `App.tsx` size audit after extraction: 621 lines; `useWorkbenchBootstrap.ts`: 81 lines. - -Limitations: -- No UX behavior, API contracts, migrations, provider fetching or AI behavior changed. -- `App.tsx` line count remains high because it explicitly wires many panel props; the remaining size is primarily composition. - -Next recommended pass: -- Pick the next V1 stabilization focus: UI browser regression coverage, backend service contract audit, or golden dataset expansion. - -## Sprint 42 App entrypoint cleanup (2026-06-17) - -Changed: -- Removed the stale `FormEvent`/`useState` React imports from `frontend/src/App.tsx`. -- Removed the UTF-8 BOM from `App.tsx` so patches and static checks use normal UTF-8 text. -- Added a regression test that verifies the clean entrypoint encoding and React import set. -- Recorded the current `App.tsx` size audit: 622 lines after the orchestration hook decomposition passes. - -Validation: -- `cd backend && python -m pytest tests/test_sprint39_frontend_orchestration_hooks.py -q` passed: 8 tests. -- `python -m compileall backend/app` passed. -- `cd backend && python -m pytest -W error::DeprecationWarning` passed: 192 tests. -- `bash scripts/run_readiness_check.sh` passed. -- `cd frontend && npm run typecheck` passed. -- `cd frontend && npm run build` passed. -- `cd backend && python -m alembic heads` passed: `202606120900 (head)`. -- `cd backend && python -m alembic upgrade head --sql` passed. -- `bash -n scripts/live_migration_smoke.sh` passed. -- `powershell -NoProfile -ExecutionPolicy Bypass -File scripts\deploy_tower.ps1` passed and redeployed `geointel-all-in-one:latest` to Tower on port 1202. -- `bash scripts/verify_gis_runtime.sh http://192.0.2.10:1202` passed. -- `bash scripts/verify_demo_export_workflow.sh http://192.0.2.10:1202` passed. - -Limitations: -- No UX behavior, API contracts, migrations, provider fetching or AI behavior changed. -- `App.tsx` remains a large composition root; the remaining size is primarily panel wiring and hook outputs. - -Next recommended pass: -- Optional bootstrap-effect extraction if another no-behavior size reduction is useful. - -## Sprint 41 Demo workflow hook decomposition (2026-06-17) - -Changed: -- Moved offline demo workflow orchestration from `frontend/src/App.tsx` into `frontend/src/hooks/useDemoWorkflow.ts`. -- Preserved the existing backend fixture seed flow and all cross-module selection updates for project, candidate/reference datasets, map AOI, QA/QC, detection, segmentation and exports. -- Extended static frontend orchestration tests so `demoApi.seedWorkflow` is owned by the new hook and not `App.tsx`. -- Updated frontend README, changelog and TODO status. - -Validation: -- `cd backend && python -m pytest tests/test_sprint21_demo_workflow_smoke.py tests/test_sprint39_frontend_orchestration_hooks.py -q` passed: 9 tests. -- `python -m compileall backend/app` passed. -- `cd backend && python -m pytest -W error::DeprecationWarning` passed: 191 tests. -- `bash scripts/run_readiness_check.sh` passed. -- `cd frontend && npm run typecheck` passed. -- `cd frontend && npm run build` passed. -- `cd backend && python -m alembic heads` passed: `202606120900 (head)`. -- `cd backend && python -m alembic upgrade head --sql` passed. -- `bash -n scripts/live_migration_smoke.sh` passed. -- `powershell -NoProfile -ExecutionPolicy Bypass -File scripts\deploy_tower.ps1` passed and redeployed `geointel-all-in-one:latest` to Tower on port 1202. -- `bash scripts/verify_gis_runtime.sh http://192.0.2.10:1202` passed. -- `bash scripts/verify_demo_export_workflow.sh http://192.0.2.10:1202` passed. - -Limitations: -- No UX behavior, API contracts, migrations, provider fetching or AI behavior changed. -- `App.tsx` still has a UTF-8 BOM and a stale React import cleanup opportunity; TypeScript build is unaffected. - -Next recommended pass: -- Do a final `App.tsx` size/import cleanup pass. - -## Sprint 40 Project workspace hook decomposition (2026-06-17) - -Changed: -- Moved project list/create state, area create state and project-scoped area/dataset loading into `frontend/src/hooks/useProjectWorkspace.ts`. -- Kept demo workflow orchestration in `App.tsx` because it coordinates project, dataset, QA/QC, detection, segmentation and export selections across multiple hooks. -- Moved default clip-area fallback selection into `frontend/src/hooks/useDatasetWorkflow.ts`. -- Moved default map-area fallback selection into `frontend/src/hooks/useMapWorkspaceState.ts`. -- Extended static frontend orchestration tests to lock these ownership boundaries. -- Updated frontend README, changelog and TODO status. - -Validation: -- `cd backend && python -m pytest tests/test_sprint39_frontend_orchestration_hooks.py -q` passed: 6 tests. -- `python -m compileall backend/app` passed. -- `cd backend && python -m pytest -W error::DeprecationWarning` passed: 190 tests. -- `cd frontend && npm run typecheck` passed. -- `cd frontend && npm run build` passed. -- `bash scripts/run_readiness_check.sh` passed. -- `cd backend && python -m alembic heads && python -m alembic upgrade head --sql` passed. -- `bash -n scripts/live_migration_smoke.sh` passed. -- `powershell -NoProfile -ExecutionPolicy Bypass -File scripts/deploy_tower.ps1` rebuilt and redeployed the all-in-one Tower container at `http://192.0.2.10:1202`. -- Tower live migration smoke passed and reported `Database collation version: ok`. -- Tower browser runtime verification passed. -- `bash scripts/verify_gis_runtime.sh http://192.0.2.10:1202` passed. -- `bash scripts/verify_demo_export_workflow.sh http://192.0.2.10:1202` passed. - -Open: -- None for this pass. - -Limitations: -- No UX behavior, API contracts, migrations, provider fetching or AI behavior changed. -- Demo workflow orchestration remains in `App.tsx` until it can be safely split without obscuring cross-module state updates. - -Next recommended pass: -- Run full readiness and Tower deploy verification, then consider extracting the demo workflow coordinator into a dedicated hook. - -## Sprint 39 Frontend orchestration decomposition (2026-06-17) - -Changed: -- Moved provider capability loading state and `externalApi.listProviders` calls into `frontend/src/hooks/useProviderCapabilities.ts`. -- Moved change-detection state, validation and `analysisApi.runChangeDetection` calls into `frontend/src/hooks/useChangeDetectionWorkflow.ts`. -- Moved map-layer derived state, area GeoJSON feature construction and selected-feature reset behavior into `frontend/src/hooks/useMapWorkspaceState.ts`. -- Kept `App.tsx` as the cross-module composition layer without changing panel props, API contracts, migrations or product behavior. -- Added static regression tests for the extracted orchestration hooks. -- Updated frontend README, changelog and TODO status. - -Validation: -- `cd backend && python -m pytest tests/test_sprint39_frontend_orchestration_hooks.py -q` passed: 4 tests. -- `python -m compileall backend/app` passed. -- `cd backend && python -m pytest -W error::DeprecationWarning` passed: 188 tests. -- `cd frontend && npm run typecheck` passed. -- `cd frontend && npm run build` passed. -- `bash scripts/run_readiness_check.sh` passed. -- `cd backend && python -m alembic heads && python -m alembic upgrade head --sql` passed. -- `bash -n scripts/live_migration_smoke.sh` passed. -- `powershell -NoProfile -ExecutionPolicy Bypass -File scripts/deploy_tower.ps1` rebuilt and redeployed the all-in-one Tower container at `http://192.0.2.10:1202`. -- Tower live migration smoke passed and reported `Database collation version: ok`. -- Tower browser runtime verification passed. -- `bash scripts/verify_gis_runtime.sh http://192.0.2.10:1202` passed. -- `bash scripts/verify_demo_export_workflow.sh http://192.0.2.10:1202` passed. - -Open: -- None for this pass. - -Limitations: -- Project/area/dataset cross-load orchestration still lives in `App.tsx`; it is a good next low-risk decomposition target. - -Next recommended pass: -- Run full readiness and Tower deploy verification, then extract project/area loading into a dedicated hook if behavior remains stable. - -## Sprint 38 Export Center preview hardening (2026-06-17) - -Changed: -- Hardened the export content preview path so HTML report artifacts return `EXPORT_CONTENT_UNSUPPORTED` instead of a generic JSON parse failure. -- Updated the frontend Export Center to offer JSON preview only for JSON/GeoJSON artifacts. -- HTML project report artifacts now display as download-only in the export list. -- Extracted export preview rendering from `frontend/src/App.tsx` into `frontend/src/components/exports/ExportPreview.tsx`. -- Updated API/frontend docs, changelog and TODO status. - -Validation: -- `cd backend && python -m pytest tests/test_sprint17_export_foundation.py -q` passed: 10 tests. -- `cd frontend && npm run typecheck` passed. -- `python -m compileall backend/app` passed. -- `cd backend && python -m pytest -W error::DeprecationWarning` passed: 184 tests. -- `cd frontend && npm run build` passed. -- `bash scripts/run_readiness_check.sh` passed. -- `cd backend && python -m alembic heads && python -m alembic upgrade head --sql` passed. -- `powershell -NoProfile -ExecutionPolicy Bypass -File scripts/deploy_tower.ps1` rebuilt and redeployed the all-in-one Tower container at `http://192.0.2.10:1202`. -- Tower live migration smoke passed and reported `Database collation version: ok`. -- `bash scripts/verify_gis_runtime.sh http://192.0.2.10:1202` passed. -- `bash scripts/verify_demo_export_workflow.sh http://192.0.2.10:1202` passed. - -Open: -- None for this pass. - -Limitations: -- This pass does not add new export formats, PDF reports, provider fetching, AI inference or migrations. - -Next recommended pass: -- Run the full readiness gate, frontend build and Tower deploy smoke; then continue with shared workbench orchestration decomposition or export cleanup/history filtering. - -## Sprint 37 Tower PostgreSQL collation maintenance (2026-06-17) - -Changed: -- Performed the manual PostgreSQL collation maintenance action reported by the live migration smoke on the Tower all-in-one runtime. -- Created a pre-maintenance custom-format database backup at `backups/geointel-before-collation-refresh-20260617-065707.dump`. -- Ran `REINDEX DATABASE geointel;` followed by `ALTER DATABASE "geointel" REFRESH COLLATION VERSION;`. -- Confirmed the database collation metadata now matches the runtime collation version: `geointel stored=2.36 actual=2.36`. - -Validation: -- `LIVE_SMOKE_CONTAINER=geointel bash scripts/live_migration_smoke.sh` passed on Tower and reported `Database collation version: ok`. -- `bash scripts/verify_browser_runtime.sh http://192.0.2.10:1202` passed. -- `bash scripts/verify_gis_runtime.sh http://192.0.2.10:1202` passed. -- `bash scripts/verify_demo_export_workflow.sh http://192.0.2.10:1202` passed. - -Notes: -- An initial SSH script attempt was interrupted by PowerShell BOM/stdin handling before reindex or refresh executed; the subsequent base64-delivered script ran without `docker exec -i` stdin interference. -- Earlier backup attempts were left in `backups/` alongside the final validated backup. -- No code, API contracts, migrations, product features, provider fetching or AI behavior changed. - -Next recommended pass: -- Continue with export/download polish or frontend export center hardening, using the now-clean Tower runtime as the validation target. - -## Sprint 32 Unraid all-in-one runtime (2026-06-17) - -Changed: -- Added `docker-compose.unraid.yml` for a single editable `geointel` container on Unraid. -- Added `deploy/unraid/Dockerfile.all-in-one` to build one image containing embedded PostGIS, backend GIS runtime, nginx and frontend static assets. -- Added `deploy/unraid/all-in-one-start.sh` to start embedded PostGIS, apply Alembic migrations, start FastAPI on internal localhost and serve nginx on container port 80. -- Added `deploy/unraid/nginx-all-in-one.conf` so `/api` and `/health` proxy to `127.0.0.1:8000` inside the same container. -- Updated `deploy/unraid/geointel.env.example`, Unraid XML template and README for one-container operation and editable web/storage/database paths. -- Updated Tower deploy scripts to stop the old multi-container stack without deleting volumes and start `docker-compose.unraid.yml`. -- Updated `scripts/live_migration_smoke.sh` to support both all-in-one `geointel` and legacy `backend` Compose services. -- Added root `.dockerignore` for all-in-one builds. -- Updated Sprint 31 tests to cover the all-in-one Dockerfile, startscript, nginx config, deploy scripts and template metadata. - -Validation: -- `python -m pytest backend/tests/test_sprint31_unraid_template.py backend/tests/test_live_migration_smoke_script.py backend/tests/test_docker_runtime_config.py` passed: 26 tests. -- `cd frontend && npm run typecheck` passed. -- `cd frontend && npm run build` passed. -- `python -m compileall backend/app` passed. -- `cd backend && python -m pytest` passed: 179 tests. -- `bash scripts/run_readiness_check.sh` passed: 179 backend tests, frontend typecheck/build, Alembic head check and script syntax checks. -- `cd backend && python -m alembic heads` passed: single head `202606120900`. -- `cd backend && python -m alembic upgrade head --sql` passed. -- `bash -n scripts/live_migration_smoke.sh` passed. -- `bash -n deploy/unraid/all-in-one-start.sh` passed. - -Notes: -- No API contracts, migrations, product features, provider fetching or AI behavior changed. -- Local Windows environment does not have `docker` in PATH; Tower deployment should provide the live all-in-one Docker validation. - -## Sprint 31 Unraid deployment template (2026-06-17) - -Changed: -- Made `docker-compose.yml` configurable through `.env` defaults for frontend port, backend port, storage path, PostGIS database/user/password, CORS origins and upload limit. -- Added `deploy/unraid/geointel.env.example` for Unraid/Tower runtime configuration. -- Added `deploy/unraid/geointel-unraid-template.xml` as Unraid/DockerMan-style metadata for the editable Compose stack settings. -- Added `deploy/unraid/geointel-icon.svg` and `deploy/unraid/geointel-icon.png`, served through matching `frontend/public` assets. -- Added the frontend favicon link for the GeoIntel icon. -- Added Sprint 31 tests for Unraid template coverage, compose variable coverage, docs and icon availability. -- Updated root README, TODO and changelog docs. - -Validation: -- `python -m pytest backend/tests/test_sprint31_unraid_template.py backend/tests/test_docker_runtime_config.py` passed: 22 tests. -- `cd frontend && npm run typecheck` passed. -- `cd frontend && npm run build` passed. -- `python -m compileall backend/app` passed. -- `cd backend && python -m pytest` passed: 177 tests. -- `bash scripts/run_readiness_check.sh` passed: 177 backend tests, frontend typecheck/build, Alembic head check and script syntax checks. -- `cd backend && python -m alembic heads` passed: single head `202606120900`. -- `cd backend && python -m alembic upgrade head --sql` passed. -- `bash -n scripts/live_migration_smoke.sh` passed. -- Tower deploy via `scripts/deploy_tower.ps1` passed after commit `3a8b82f`. -- Tower Docker Compose config/build/up passed with the env-default compose file. -- Tower live migration smoke passed with PostGIS 3.4 and Alembic head `202606120900`. -- Tower browser runtime verification passed on `http://192.0.2.10:1202`. -- Additional HTTP smoke passed for frontend HTML, `GET /api/v1/projects`, `/geointel-icon.svg` and `/geointel-icon.png`. - -Notes: -- Local Windows environment does not have `docker` in PATH, so local `docker compose config` could not be run from this machine. -- Tower deployment validated Docker Compose config and live runtime after commit. -- No API contracts, backend behavior, migrations, product features, provider fetching or AI behavior changed. - -## Sprint 30 workbench component decomposition (2026-06-17) - -Changed: -- Moved persisted QA/QC result rendering from `frontend/src/App.tsx` into `frontend/src/components/quality/QualityResultsPanel.tsx`. -- Moved map layer controls, MapLibre composition and feature inspector rendering into `frontend/src/components/map/MapWorkspace.tsx`. -- Updated map/workbench and QA regression tests for the new component boundaries. -- Added Sprint 30 component wiring tests to keep QA and map markup out of `App.tsx`. -- Updated frontend README, TODO and changelog docs. - -Validation: -- `python -m pytest backend/tests/test_sprint30_workbench_components.py backend/tests/test_sprint27_frontend_workflow_hooks.py backend/tests/test_sprint19_map_workbench.py` passed: 9 tests. -- `python -m compileall backend/app` passed. -- `cd backend && python -m pytest` passed: 173 tests. -- `cd frontend && npm run typecheck` passed. -- `cd frontend && npm run build` passed. -- `bash scripts/run_readiness_check.sh` passed: 173 backend tests, frontend typecheck/build, Alembic head check and script syntax checks. -- `cd backend && python -m alembic heads` passed: single head `202606120900`. -- `cd backend && python -m alembic upgrade head --sql` passed. -- `bash -n scripts/live_migration_smoke.sh` passed. -- Tower deploy via `scripts/deploy_tower.ps1` passed after commit `acf9590`. -- Tower live migration smoke passed with PostGIS 3.4 and Alembic head `202606120900`. -- Tower browser runtime verification passed on `http://192.0.2.10:1202`. -- Additional HTTP smoke passed for frontend HTML and `GET /api/v1/projects` through the frontend proxy. - -Notes: -- No API contracts, backend behavior, migrations, product features, provider fetching, AI behavior or UI redesign changed. -- Next maintainability pass should split export preview and remaining shared workbench orchestration into focused components/hooks. - -## Sprint 29 dataset component decomposition (2026-06-17) - -Changed: -- Moved dataset upload/list rendering from `frontend/src/App.tsx` into `frontend/src/components/datasets/DatasetPanel.tsx`. -- Moved dataset detail and job-list rendering into `frontend/src/components/datasets/DatasetDetailPanel.tsx`. -- Split raster controls and vector controls into `frontend/src/components/datasets/RasterControls.tsx` and `frontend/src/components/datasets/VectorControls.tsx`. -- Updated Sprint 28 regression tests for the new component boundary and added Sprint 29 component wiring tests. -- Updated frontend README, TODO and changelog docs. - -Validation: -- `python -m pytest backend/tests/test_sprint29_dataset_components.py backend/tests/test_sprint28_dataset_workflow_hook.py backend/tests/test_sprint27_frontend_workflow_hooks.py` passed: 10 tests. -- `python -m compileall backend/app` passed. -- `cd backend && python -m pytest` passed: 170 tests. -- `cd frontend && npm run typecheck` passed. -- `cd frontend && npm run build` passed. -- `bash scripts/run_readiness_check.sh` passed: 170 backend tests, frontend typecheck/build, Alembic head check and script syntax checks. -- `cd backend && python -m alembic heads` passed: single head `202606120900`. -- `cd backend && python -m alembic upgrade head --sql` passed. -- `bash -n scripts/live_migration_smoke.sh` passed. -- Tower deploy via `scripts/deploy_tower.ps1` passed after commit `1cbb356`. -- Tower live migration smoke passed with PostGIS 3.4 and Alembic head `202606120900`. -- Tower browser runtime verification passed on `http://192.0.2.10:1202`. -- Additional HTTP smoke passed for frontend HTML and `GET /api/v1/projects` through the frontend proxy. - -Notes: -- No API contracts, backend behavior, migrations, product features, provider fetching, AI behavior or UI redesign changed. -- Next maintainability pass should split change detection, QA/QC results and map workspace controls into focused presentational components. - -## Sprint 28 dataset workflow hook hardening (2026-06-17) - -Changed: -- Moved dataset selection, upload form state, dataset detail loading, dataset jobs and raster/vector operation orchestration from `frontend/src/App.tsx` into `frontend/src/hooks/useDatasetWorkflow.ts`. -- Kept project dataset listing in `App.tsx` so project/area loading remains the shared workbench boundary. -- Added regression tests to verify App uses the dataset workflow hook and still wires dataset, raster and vector callbacks. -- Updated frontend README, TODO and changelog docs. - -Validation: -- `python -m pytest backend/tests/test_sprint28_dataset_workflow_hook.py backend/tests/test_sprint27_frontend_workflow_hooks.py backend/tests/test_sprint26_frontend_workflow_hooks.py` passed: 11 tests. -- `python -m compileall backend/app` passed. -- `cd backend && python -m pytest` passed: 167 tests. -- `cd frontend && npm run typecheck` passed. -- `cd frontend && npm run build` passed. -- `bash scripts/run_readiness_check.sh` passed: 167 backend tests, frontend typecheck/build, Alembic head check and script syntax checks. -- `cd backend && python -m alembic heads` passed: single head `202606120900`. -- `cd backend && python -m alembic upgrade head --sql` passed. -- `bash -n scripts/live_migration_smoke.sh` passed. -- Initial Tower rebuild hit Docker btrfs storage exhaustion; safely reclaimed build cache only with `docker builder prune -af` without pruning volumes. -- Tower Docker storage recovered from `/var/lib/docker` 94% used to 58% used after cleanup and rebuild. -- Tower deploy via `scripts/deploy_tower.ps1` passed after commit `361776c`. -- Tower live migration smoke passed with PostGIS 3.4 and Alembic head `202606120900`. -- Tower browser runtime verification passed on `http://192.0.2.10:1202`. -- Additional HTTP smoke passed for frontend HTML and `GET /api/v1/projects` through the frontend proxy. - -Notes: -- No API contracts, backend behavior, migrations, product features, provider fetching, AI behavior or UI redesign changed. -- Next maintainability pass should split dataset detail, raster controls and vector controls into presentational components fed by the hook state. - -## Sprint 27 export and QA workflow hook hardening (2026-06-17) - -Changed: -- Moved Export Center orchestration state and API calls from `frontend/src/App.tsx` into `frontend/src/hooks/useExportWorkflow.ts`. -- Moved QA/QC comparison state and persisted quality-check listing from `frontend/src/App.tsx` into `frontend/src/hooks/useQualityWorkflow.ts`. -- Added regression tests to verify App uses export/quality hooks and still wires QA/QC results plus ExportCenter callbacks. -- Updated frontend README, TODO and changelog docs. - -Validation: -- `python -m pytest backend/tests/test_sprint27_frontend_workflow_hooks.py backend/tests/test_sprint26_frontend_workflow_hooks.py` passed: 8 tests. -- `python -m compileall backend/app` passed. -- `cd backend && python -m pytest` passed: 164 tests. -- `cd frontend && npm run typecheck` passed. -- `cd frontend && npm run build` passed. -- `bash scripts/run_readiness_check.sh` passed: 164 backend tests, frontend typecheck/build, Alembic head check and script syntax checks. -- `cd backend && python -m alembic heads` passed: single head `202606120900`. -- `cd backend && python -m alembic upgrade head --sql` passed. -- `bash -n scripts/live_migration_smoke.sh` passed. -- Tower deploy via `scripts/deploy_tower.ps1` passed after commit `fd0000f`. -- Tower live migration smoke passed with PostGIS 3.4 and Alembic head `202606120900`. -- Tower browser runtime verification passed on `http://192.0.2.10:1202`. -- Additional HTTP smoke passed for frontend HTML and `GET /api/v1/projects` through the frontend proxy. - -Notes: -- No API contracts, backend behavior, migrations, product features, provider fetching, AI behavior or UI redesign changed. -- Local Windows Docker CLI was unavailable (`docker` command not found); Tower deployment remains handled through `scripts/deploy_tower.ps1`. -- Next maintainability pass should extract dataset/raster/vector operation workflows from `App.tsx`. - -## Sprint 26 frontend workflow hook hardening (2026-06-17) - -Changed: -- Moved Detection Lab orchestration state and API calls from `frontend/src/App.tsx` into `frontend/src/hooks/useDetectionWorkflow.ts`. -- Moved Segmentation Lab orchestration state and API calls from `frontend/src/App.tsx` into `frontend/src/hooks/useSegmentationWorkflow.ts`. -- Added shared frontend `formatError` helper under `frontend/src/lib/formatError.ts`. -- Added regression tests to verify App uses workflow hooks and still wires DetectionLab/SegmentationLab callbacks. -- Updated frontend README, TODO and changelog docs. - -Validation: -- `python -m pytest backend/tests/test_sprint26_frontend_workflow_hooks.py backend/tests/test_sprint22_workbench_status_strip.py` passed: 6 tests. -- `cd frontend && npm run typecheck` passed. -- `cd frontend && npm run build` passed. -- `bash scripts/run_readiness_check.sh` passed: 160 backend tests, frontend typecheck/build, Alembic head check and script syntax checks. -- `python -m compileall backend/app` passed. -- `cd backend && python -m alembic upgrade head --sql` passed. -- `bash -n scripts/live_migration_smoke.sh` passed. -- Tower deploy/live migration/browser runtime passed after commit `6c32f29`. -- In-app browser check passed on `http://192.0.2.10:1202`: workbench, status strip, Detection Lab, Segmentation Lab and Export Center visible with no console error logs. - -Notes: -- No API contracts, backend behavior, migrations, product features, provider fetching, AI behavior or UI redesign changed. -## Sprint 25 YOLO compatibility smoke hardening (2026-06-17) - -Changed: -- Added explicit `--check-model-load` support to `scripts/yolo_preflight.py`, `backend/scripts/yolo_preflight.py` and `YoloPreflightService`. -- The model-load smoke requires real optional AI dependencies, loads only an existing local model file, runs no inference and does not download weights. -- The CLI rejects `--check-model-load` with `--assume-dependencies` to avoid false-positive AI readiness. -- Added regression tests for mocked successful load, load failure reporting and CLI guard behavior. -- Added Python compile validation for both YOLO preflight entrypoints to the readiness gate. -- Updated AI pipeline, scripts, backend, TODO and changelog docs, including Docker runtime usage. - -Validation: -- `python -m py_compile scripts/yolo_preflight.py` passed. -- `python -m pytest backend/tests/test_sprint13_yolo_preflight.py backend/tests/test_readiness_gate.py` passed: 14 tests. -- `bash scripts/run_readiness_check.sh` passed: 156 backend tests, frontend typecheck/build, Alembic head check and script syntax checks. -- `python -m compileall backend/app` passed. -- `cd backend && python -m alembic upgrade head --sql` passed. -- `bash -n scripts/live_migration_smoke.sh` passed. -- Tower deploy/live migration/browser runtime passed after commit `6c32f29`. -- In-app browser check passed on `http://192.0.2.10:1202`: workbench, status strip, Detection Lab, Segmentation Lab and Export Center visible with no console error logs. -- Tower deploy/live migration/browser runtime passed after commit `382dcad`. -- Backend-container YOLO preflight sanity passed: default status `not_configured`, `will_download_models=false`, `will_run_inference=false`. -- Backend-container CLI guard passed: `--check-model-load` with `--assume-dependencies` is rejected. - -Notes: -- No base dependencies, API contracts, migrations, product features, provider fetching or detection persistence behavior changed. -## Sprint 24 demo/export artifact cleanup tooling (2026-06-17) - -Changed: -- Added `scripts/cleanup_demo_artifacts.py` for dry-run-first cleanup of old offline demo export artifacts. -- Added `backend/scripts/cleanup_demo_artifacts.py` so the same cleanup can run inside the backend Docker container. -- Cleanup is constrained to an exact demo project name by default, keeps the newest exports per project and refuses file deletion outside `STORAGE_ROOT`. -- Added regression tests for cleanup selection, path safety, dry-run candidate reporting and readiness gate coverage. -- Added Python compile validation for the cleanup script to `scripts/run_readiness_check.sh`. -- Documented cleanup usage in `scripts/README.md`, `docs/STORAGE_ARCHITECTURE.md`, `backend/README.md`, `docs/TODO.md` and `CHANGELOG.md`. - -Validation: -- `python -m py_compile scripts/cleanup_demo_artifacts.py` passed. -- `python -m pytest backend/tests/test_sprint24_cleanup_demo_artifacts.py backend/tests/test_readiness_gate.py` passed: 10 tests. -- `bash scripts/run_readiness_check.sh` passed twice after adding the backend container entrypoint: 152 backend tests, frontend typecheck/build, Alembic head check and script syntax checks. -- `python -m compileall backend/app` passed. -- `cd backend && python -m alembic upgrade head --sql` passed. -- `bash -n scripts/live_migration_smoke.sh` and `bash -n scripts/verify_demo_export_workflow.sh` passed. -- Local `docker compose config` could not run because the Windows Docker CLI is not installed in this Codex environment. -- Tower deploy/live migration/browser runtime passed after final commit `2d4e6bd`. -- Live backend-container cleanup dry-run exposed and then fixed confusing dry-run labeling so candidates are reported as `candidate_files`, not `deleted_files`; final dry-run reported 2 candidate files, 0 deleted files and 0 deleted export rows. - -Notes: -- No API contracts, migrations, product features, provider fetching, AI inference or source dataset cleanup behavior changed. -## Sprint 23 V1 report handoff summary (2026-06-17) - -Changed: -- Added V1 readiness summary data to project metadata exports. -- Added V1 Readiness Summary and Known Limitations sections to lightweight HTML project report exports. -- Included persisted AOI, dataset readiness, QA/QC and export-history counts in the handoff summary. -- Updated export tests, API contract docs, frontend README, TODO and changelog. - -Tested: -- Passed: backend compile, export tests through full readiness, full backend pytest, frontend typecheck/build, Alembic heads, Alembic SQL upgrade, live smoke syntax check, Tower deploy, live migration smoke and live project report smoke. - -Known limitations: -- Report export remains a lightweight HTML artifact, not a PDF designer or custom report builder. - -Next recommended pass: -- Add optional cleanup tooling for stale demo/export artifacts if repeated smoke runs keep accumulating local artifacts. -## Sprint 22 V1 workbench status strip (2026-06-17) - -Changed: -- Added `frontend/src/components/WorkbenchStatusStrip.tsx` to summarize existing V1 state for project, AOI, datasets, active map layer, QA/QC and exports. -- Wired the status strip into `frontend/src/App.tsx` using existing orchestration state only. -- Added compact status-strip styling and regression tests for the frontend wiring contract.`n- Hardened `frontend/src/components/GeoMap.tsx` so MapLibre source/layer updates wait for style readiness before adding sources.`n- Hardened demo project lookup so duplicate historical demo projects prefer complete fixture state before repairing incomplete state. -- Updated frontend README, TODO and changelog. - -Tested: -- Passed: backend compile, focused pytest, full backend pytest with DeprecationWarning as error, frontend typecheck/build, Alembic heads, Alembic SQL upgrade, readiness via Git Bash and live smoke syntax check via Git Bash. - -Known limitations: -- The strip is a read-only operator summary; it intentionally does not add new backend status APIs or product workflows. - -Next recommended pass: -- Add a compact project handoff summary in exports/report output if the browser-facing V1 workflow remains green. - -## Sprint 21 V1 demo workflow smoke hardening (2026-06-17) - -Changed: -- Hardened `scripts/verify_demo_export_workflow.sh` so the explicit offline demo smoke validates area GeoJSON, fixture datasets, vector FeatureCollection content, vector feature summaries, persisted QA/QC metrics and export downloads through the frontend proxy. -- Updated the frontend demo workflow action to open the candidate vector fixture dataset after seeding/loading the demo, so the Map Workbench is populated without a manual dataset click. -- Added regression tests for the strengthened smoke script and frontend demo loading contract. -- Updated scripts/frontend documentation, changelog and TODO status. - -Tested: -- Passed: backend compile, backend pytest with DeprecationWarning as error, readiness, frontend typecheck/build, Alembic heads, Alembic SQL upgrade, Tower deploy, live migration smoke, browser-runtime smoke and expanded demo/export workflow smoke. - -Known limitations: -- The demo smoke intentionally seeds fixture demo data when run; it should be used as an explicit verification command, not as an implicit healthcheck. - -Next recommended pass: -- Add a compact V1 dashboard/status strip for project, AOI, datasets, QA and exports so operators can see readiness at a glance after opening a project. -## Sprint 20 V1 selected area map overlay (2026-06-17) - -Changed: -- Added GeoJSON geometry serialization for project areas so persisted AOIs can be displayed by the map workbench. -- Added a dedicated MapLibre area overlay layer with separate visibility and opacity controls. -- Added area list actions and map workspace controls to select the active AOI. -- Updated API/frontend docs, changelog and TODO status for selected area display. - -Tested: -- Passed: backend compile, backend pytest with DeprecationWarning as error, readiness, frontend typecheck/build, Alembic heads, Alembic SQL upgrade, Tower deploy, live migration smoke, browser-runtime smoke and browser UI audit. - -Known limitations: -- Area geometry is displayed as a simple filled/outlined GeoJSON overlay; no drawing/editing workflow is introduced in this pass. - -Next recommended pass: -- Add a small V1 workflow polish pass for richer dataset/area empty states and a fixture-driven end-to-end browser smoke once the new build is deployed. -## Sprint 19 V1 map workbench controls (2026-06-17) - -Changed: -- Added active MapLibre layer visibility and opacity controls. -- Added click-to-inspect feature property display for the active GeoJSON workbench layer. -- Added active layer label and feature count to the Map workspace panel. -- Updated the app header from the stale Sprint 9 label to the GeoIntel Kempen V1 Workbench identity. -- Added regression tests for the frontend map control and feature inspection wiring. - -Limitations: -- The current workbench still shows one active GeoJSON overlay at a time; multi-layer stack ordering remains a later UI enhancement. -- Raster preview display still remains metadata/path-oriented unless the backend exposes a browser-safe raster image/tile URL. -- No API contracts, migrations, backend behavior, provider fetching, AI inference or new dependencies were introduced. - -Validation planned: -- `python -m compileall backend/app` -- `cd backend && python -m pytest -W error::DeprecationWarning` -- `cd frontend && npm run typecheck` -- `cd frontend && npm run build` -- `bash scripts/run_readiness_check.sh` via Git Bash on Windows -- Tower redeploy through `scripts/deploy_tower.ps1` -## Sprint 18 vector change detection foundation (2026-06-16) - -Changed: -- Added `POST /api/v1/analysis/change-detection` for comparing two vector datasets in the same project through the existing synchronous job envelope. -- Added `ChangeDetectionService` with persisted `vector_features` as the primary source of comparable geometries and explicit stored-GeoJSON fallback warnings for older datasets. -- Added frontend Change Detection controls, summary counts and MapLibre overlay styling for `added`, `removed` and `unchanged` feature properties. -- Added nginx no-cache headers for frontend HTML/assets after browser verification exposed stale cached modules on the LAN deployment. -- Added backend tests for persisted-vector comparison and canonical API envelope behavior. - -Limitations: -- The foundation classifies `added`, `removed` and `unchanged` only. It does not emit fake `changed` objects without durable object ids/versioning. -- No migrations, live GRB/OSM/Sentinel fetching, AI inference, new dependencies, LiDAR, Copilot, Training Studio or separate Reports module were introduced. - -Validation: -- `python -m compileall backend/app` -- `cd backend && python -m pytest -W error::DeprecationWarning` -- `cd frontend && npm run typecheck` -- `cd frontend && npm run build` -- `bash scripts/run_readiness_check.sh` via Git Bash on Windows -- `cd backend && python -m alembic heads && python -m alembic upgrade head --sql` -# Codex Execution Log - -## 2026-07-30 - Fail-closed SAM roof-refinement gate hardening - -### What changed - -- Reproduced the V64 Flemish calibration-candidate export for Aarschot, Beveren and Oostkamp from the immutable temporal-cutoff manifest. -- Ran the checksummed `/app/sam2_t.pt` model on the server RTX 4080 SUPER and rendered deterministic before/after label contact sheets. -- Rejected both the legacy refinement settings and a stricter trial because dense or temporally absent footprint prompts still produced visually invalid roof boxes; neither result was promoted into a training corpus. -- Hardened `scripts/refine_yolo_labels_with_sam.py` with configurable centre-shift and per-dimension ratio gates. The selected values and model checksum are persisted in `sam-refinement.json`. -- Added an optional provider-native source-class allowlist to Belgian label normalization. A V65 diagnostic retained only GRB `TYPE=1` main buildings and auditable rejection counts, reducing the three candidate AOIs from 427 to 283 source features without claiming semantic parity with PICC or UrbIS. -- Added explicit SAM fallback policies. `retain` preserves historical behavior; `drop` creates a fail-closed visible-roof-only shard and records every removed fallback. -- Tested global image-edge translation at narrow and broad radii. The broad optima jumped to unrelated repeated urban edges, so this experiment was rejected and was not added to the production corpus. - -### What was tested - -- `python -m pytest backend/tests/test_sam_roof_label_refinement.py -q` passed (`2 passed`). -- `python -m py_compile scripts/refine_yolo_labels_with_sam.py` passed. -- `python -m pytest backend/tests/test_sam_roof_label_refinement.py backend/tests/test_building_label_normalization.py -q` passed (`10 passed`). -- CUDA refinement completed on 706 candidate labels; the strictest trial refined 659 and retained 47 explicit fallbacks. Visual QA still failed, so the run remains evidence only. -- The V65 main-building-only/drop-fallback CUDA trial retained 134 of 466 tiled labels and dropped 332 fallbacks. Its contact sheet still contained wrong tree, ground and compound masks, so it also remains rejected evidence only. - -### What remains open - -- Replace or align the rejected Flemish calibration labels with image-visible, independently validated roof boxes. -- Rebuild and retrain only after that label gate passes; protected test and pure-background evaluation remain closed. - -### Known limitations - -- Geometry plausibility alone cannot prove that a SAM mask represents the intended roof in dense scenes. - -### Next recommended pass - -- Add an auditable image/footprint alignment stage or select lower-parallax independent Flemish AOIs, then repeat visual QA before corpus composition. - -## 2026-07-30 - V66 independent Flemish low-rise replacement audit - -### What changed - -- Added and provisioned three spatially independent Flemish low-rise calibration candidates: Zutendaal, Zoersel and Landen. -- Materialized immutable temporal corpus `building-be-v66-lowrise-temporal-r1` with manifest SHA-256 `d861da48aca40121e158e6ab243a6ccbe53e14d500a186af64b620f612935b07`. -- Applied the provider-native GRB main-building allowlist, retaining 73, 66 and 110 source instances respectively while preserving every excluded annex in label-audit evidence. -- Tested per-instance image-edge alignment, V31 detector-consensus translation, strict SAM refinement/drop and an independent YOLO-World roof vocabulary. Every generated contact sheet remained fail-closed rejected; none entered training. - -### What was tested - -- `python -m pytest tests/test_provision_belgium_building_training_portfolio.py -q` passed (`3 passed`). -- The server confirmed CUDA execution on the RTX 4080 SUPER. -- YOLO-World model SHA-256: `9b2c17ab6124a913e9b3a5c170617920d91b0f01111a8479da69f00e2cf27792`; it returned 65 low-confidence detections across 12 tiles and failed visual precision. -- The V31 consensus route accepted only Zoersel with nine agreeing pairs and failed the other two AOIs; visual review rejected the accepted shift as well. - -### What remains open - -- An independently reviewed image-visible Flemish roof-label set is still required before the national retraining loop can honestly resume. -- Protected test/background evaluation, promotion and production redeployment remain closed. - -### Known limitations - -- Orthophoto ground displacement means current GRB ground-footprint boxes are not detector-grade roof truth at IoU 0.5. Automatic proposal models tested here do not reach the required visual precision. - -### Next recommended pass - -- Obtain or annotate image-visible roof boxes independently of the release candidate, freeze their checksums and human acceptance evidence, then rebuild and retrain the national corpus. - -## Post-V1 national coverage completion: Wallonia (2026-07-22) - -- Located and live-validated the stable official WALOUS 2018 GeoTIFF - distribution. The retained raster SHA-256 is - `a788cf4619363664d1e80def79b32176b4703317d123c8cd703f2eb10e8d56b2`; - the full source is EPSG:3812 at 1 m and the merged live provisioning report - now covers 2018, 2020 and 2023. -- Added the official 2018 stacked-class to view-class crosswalk. Greenhouse - code `62` enters the construction class and unmarked source value `0` is - normalized to internal nodata `255`; both behaviors have regression tests - so background pixels cannot inflate hectare metrics. -- Selected the official SPW MNT 2021-2022 1 m GeoTIFF as the governed Walloon - terrain source after a live storage audit showed sufficient capacity. Added - fail-closed operator provisioning, bounded `bbox intersect Area` - persistence, raster validation and terrain analysis with explicit - DNG/EPSG:5710 vertical-reference provenance. -- Replaced the frontend-only AI geography warning with a machine-readable - runtime contract. Detection capabilities now expose training/validation - scope, validated regions, national status and the review requirement; the - configured local weights remain bound to Mol/Kempen evidence and fail closed - as not nationally validated. -- Deployed immutable AI image - `geointel-all-in-one:f5431387128d193e6e638818f5641d3410227fd6-ai`; - live health, PostGIS 3.6, Alembic `202607160001`, browser proxy and packaged - SPW terrain provisioner checks passed. The configured YOLO capability now - returns `nationally_validated=false`, `validated_regions=[flanders_mol_kempen]` - and `operator_review_required=true` from the runtime API. -- Live WALOUS 2018 acquisition created Dataset - `572dd6d0-c829-41d4-bf4a-19b6563c3ff0` for the 130.28 km² Wallonia golden - area. All 1,302,769 derived 10 m cells were valid; measured cover included - 3,615.39 ha forest/tree cover, 209.84 ha water and 2,315.33 ha artificial - cover. Same-scope 2020/2023 acquisition then produced a three-observation, - seven-metric 2018-2023 comparison without inventing object changes. -- Live comparison exposed that only the later WALOUS limitation was returned. - Temporal responses now retain both edition warnings, ensuring the 2018 - crosswalk/methodology caveat survives comparison with 2023. -- Live Tower provisioning exposed an incorrect assumption that 11 WALOUS - classes implied numeric codes 1 through 11. The official SPW legend and the - downloaded 2020 raster confirm codes `1,2,3,4,5,6,7,8,9,80,90`. Corrected - validation, class semantics, colours and all hectare aggregations; added a - provisioner regression containing codes 80/90 and retained exact source - observation ranges. -- Validated the official WALOUS 2020 and 2023 archives, their EPSG:3812 1 m - raster contract, 11 classes, CC BY 4.0 attribution and published edition - accuracy. Added a fail-closed operator provisioner with archive-size, - extraction, CRS, resolution, class and checksum gates. -- Added bounded WALOUS persistence through `DatasetService`, semantic hectare - metrics, a governed PNG overlay and automatic 2020/2023 temporal-series - materialization. The existing temporal API now compares persisted WALOUS - raster metrics while keeping object-level change unavailable. -- Added the queryable legal SPW flood-hazard polygon product and class-aware - metrics through the existing official-vector engine. -- Wired both integrations through Compose, the all-in-one Unraid runner, - editable DockerMan template and readiness gate. Added canonical API, - persistence, rendering, temporal and runtime-parity regression tests. -- Revalidated both official Walloon DTM distributions. The 1 m archive is - operator-provisioned once on persistent storage and selections read bounded - windows from it; the approximately 213 GB 0.5 m distribution remains - deliberately unprovisioned because it is not required for the V1 analysis - contract. -- Reprobed the documented MDK WCS endpoints. Strict TLS still fails hostname - validation; acquisition remains disabled and no insecure fallback was added. -- A live Tower deploy exposed PostGIS crash recovery exceeding the former - startup/deploy waits. Raised both bounded waits to 15/16 minutes and added a - release regression so recovery can finish without a premature rollback. -- The same live restart exposed an unconditional recursive `chown` over the - persistent database. Replaced it with root-directory ownership only to avoid - rewriting relation metadata and delaying every all-in-one startup. - -This file must be updated by Codex after each implementation pass. - -## Format - -```md -## Pass X — Title -Date: - -### Completed -- ... - -### Files changed -- ... - -### Tests run -- ... - -### Known limitations -- ... - -### Next recommended pass -- ... -``` - -## Initial status -Specification phase completed through M0. No code foundation has been implemented yet. - -## M2 Engineering Package - -- [x] Add ADR decision records. -- [x] Add RFC placeholders for future modules. -- [x] Add API/database/event contracts. -- [x] Add model registry and class catalogs. -- [x] Add queue architecture. -- [x] Add acceptance matrix and test catalog. -- [x] Add Codex M2 build prompts. -- [ ] Start Codex Pass 01 backend foundation. - -## M8 preparation - -Added the tomorrow execution layer for Codex autonomy: Day 1 master prompt, pass prompts, failure recovery, quality gates, operator checklist and smoke script scaffold. - -## Sprint 1 readiness hardening (2026-06-11) - -Date: 2026-06-11 - -### Completed -- Hardened backend dependency declarations for Sprint 1 runtime modules in `backend/pyproject.toml`. -- Normalized helper scripts for backend/frontend install/test/dev/readiness across `python`/`python3` interpreter availability. -- Fixed PostGIS/geospatial stack compatibility issues (`geojson_service` import path, package config). -- Updated backend/frontend/docs/readme commands for import smoke, setup, and readiness verification. -- Fixed frontend shell script line-ending parsing failures and added `npm` availability checks. -- Added missing frontend type path fixes and TypeScript typing corrections. -- Added/verified minimal Sprint 1 tests for health and GeoJSON parsing/rejection behaviors. - -### Files changed -- `backend/pyproject.toml` -- `backend/app/core/config.py` -- `backend/app/services/geojson_service.py` -- `backend/tests/test_health.py` -- `backend/tests/test_geojson_dataset_service.py` -- `backend/README.md` -- `frontend/package.json` -- `frontend/tsconfig.json` -- `frontend/src/components/GeoMap.tsx` -- `frontend/src/services/api/areas.ts` -- `frontend/src/services/api/projects.ts` -- `frontend/src/services/api/datasets.ts` -- `frontend/src/App.tsx` -- `frontend/README.md` -- `scripts/run_readiness_check.sh` -- `scripts/backend_install.sh` -- `scripts/backend_test.sh` -- `scripts/backend_dev.sh` -- `scripts/codex_pass_end_check.sh` -- `scripts/smoke_backend_import.sh` -- `scripts/frontend_install.sh` -- `scripts/frontend_typecheck.sh` -- `scripts/frontend_build.sh` -- `scripts/frontend_dev.sh` -- `README.md` -- `.env.example` -- `CHANGELOG.md` -- `Makefile` - -### Tests run -- `python -m compileall backend/app` (pass) -- `cd backend; python -m pytest` (pass, 5 tests) -- `cd backend; python -c "from app.main import app; print(app.title)"` (pass) -- `bash scripts/run_readiness_check.sh` (pass) -- `bash scripts/smoke_backend_import.sh` (pass) -- `bash scripts/frontend_install.sh` (pass) -- `bash scripts/frontend_typecheck.sh` (pass) -- `bash scripts/frontend_build.sh` (pass) -- `make`-based targets not runnable in this environment (`make` command missing) -- `docker compose config` not runnable in this environment (`docker` command missing) -- `python3` commands fail in this environment because `python3` maps to Microsoft Store stub; use `python` instead. - -### Known limitations -- `docker` and `make` are not installed in the current local shell environment. -- `python3` is not a usable interpreter in this environment; `python` must be used for all backend runtime/tests. - -### Next recommended pass -- Run `docker compose` validation and DB-backed migration checks in an environment with Docker + PostGIS service available. - -## Pass 12 — Sprint 2 Foundation -Date: 2026-06-11 - -### Completed -- Added vector/raster dataset typing and lifecycle states (`uploaded`, `validating`, `ready`, `failed`) in dataset service. -- Added vector metadata extraction details (feature counts, geometry types, bounds, area, CRS assumptions). -- Added raster metadata service with dependency-aware unavailable behavior and explicit `RASTER_PROCESSING_UNAVAILABLE` handling. -- Added dataset vector inspect/summary and raster metadata endpoints for project-scoped datasets. -- Persisted deterministic storage metadata for uploads (original/stored filename, MIME, size, checksum). -- Extended frontend dataset manager details panel with type/status/file metadata/feature counts and raster summary readiness. -- Added minimal Sprint 2 tests for vector metadata, legacy `geojson` compatibility, storage metadata persistence, and raster dependency fallback. - -### Files changed -- `backend/app/services/dataset_service.py` -- `backend/app/services/raster_service.py` -- `backend/app/services/geojson_service.py` -- `backend/app/schemas/dataset.py` -- `backend/app/api/routes/datasets.py` -- `backend/app/services/storage_service.py` -- `backend/tests/test_geojson_dataset_service.py` -- `backend/tests/test_raster_service.py` -- `backend/tests/test_storage_service.py` -- `backend/README.md` -- `frontend/src/App.tsx` -- `frontend/src/services/api/datasets.ts` -- `frontend/src/types.ts` -- `docs/API_CONTRACTS.md` -- `docs/CODEX_EXECUTION_LOG.md` -- `.env.example` -- `backend/README.md` -- `frontend/README.md` -- `CHANGELOG.md` -- `README.md` - -### Tests run -- Sprint 2 tests to be executed via readiness commands (see below). - -### Known limitations -- `rasterio` is not required by default; raster metadata extraction is unavailable until installed in the environment. -- Docker and PostGIS validation still depends on local availability of Docker/DB runtime. - -### Next recommended pass -- Keep Sprint 1/2 architecture; implement raster clipping/tiling APIs and status jobs before Detection/Segmentation modules. - -## Pass 13 — Sprint 2 validation and legacy compatibility hardening -Date: 2026-06-11 - -### Completed -- Verified Sprint 2 readiness commands in current environment (where tools are available). -- Revalidated backend tests and frontend typecheck/build after a Sprint 2 compatibility patch. -- Added frontend vector-detail compatibility for legacy `geojson` dataset rows in Sprint 1 records. -- Confirmed backend import smoke and dataset/raster/vector service behavior remain intact. - -### Files changed -- `frontend/src/App.tsx` -- `docs/CODEX_EXECUTION_LOG.md` - -### Tests run -- `python -m compileall backend/app` (pass) -- `cd backend && python -m pytest` (pass, 11 tests) -- `bash scripts/run_readiness_check.sh` (pass) -- `bash scripts/smoke_backend_import.sh` (pass) -- `cd frontend && npm run typecheck` (pass) -- `cd frontend && npm run build` (pass) -- `cd backend; python3 -m compileall backend/app` (fails: python3 shim unavailable in this shell) -- `cd backend; python3 -c "from app.main import app; print(app.title)"` (fails: python3 shim unavailable in this shell) -- `docker compose config` (fails: docker command unavailable in this shell) - -### Known limitations -- `python3` is not available in the current environment; use `python` commands for verification. -- `docker` is not available in the current environment. - -### Next recommended pass -- Run the same sprint verification commands in an environment with `python3` and `docker` installed. - -## Pass 14 — Sprint 3 operations + job foundation -Date: 2026-06-11 - -### Completed -- Added lightweight job model/migration and service layer with statuses `queued`, `running`, `success`, `failed`. -- Added job API endpoints for create/list/read/status under project scope. -- Added vector operation service foundation: - - inspect - - bbox - - stats - - clip by area - - buffer - - intersect -- Added raster operation foundation: - - inspect - - metadata - - preview readiness - - clip placeholder (dependency-aware) - - tile placeholder (dependency-aware) -- Added job-based execution wrappers for vector/raster operation endpoints. -- Updated dataset detail UI with available operations, job list/status, and derived output navigation. -- Added/updated Sprint 3 API contract and backend/frontend documentation updates. - -### Files changed -- `backend/app/schemas/operations.py` -- `backend/app/schemas/__init__.py` -- `backend/app/services/vector_operations_service.py` -- `backend/app/services/raster_operations_service.py` -- `backend/app/services/job_service.py` -- `backend/app/api/routes/jobs.py` -- `backend/app/models/entities.py` -- `backend/app/models/__init__.py` -- `backend/alembic/versions/20260611212435_add_jobs_table.py` -- `backend/tests/test_vector_operations_service.py` -- `backend/tests/test_raster_operations_service.py` -- `backend/tests/test_storage_service.py` -- `frontend/src/App.tsx` -- `frontend/src/services/api/datasets.ts` -- `frontend/src/services/api/jobs.ts` -- `frontend/src/types.ts` -- `backend/README.md` -- `frontend/README.md` -- `docs/API_CONTRACTS.md` -- `docs/CODEX_EXECUTION_LOG.md` -- `CHANGELOG.md` - -### Tests run -- `python -m compileall backend/app` (pass) -- `cd backend && python -m pytest` (pass) -- `bash scripts/run_readiness_check.sh` (pass) -- `bash scripts/smoke_backend_import.sh` (pass) -- `cd frontend && npm run typecheck` (pass) -- `cd frontend && npm run build` (pass) - -### Known limitations -- Raster processing beyond readiness/metadata is intentionally dependency-aware placeholder in Sprint 3. -- `docker` remains unavailable in this environment. -- `python3` still resolves to Windows Store stub; use `python` for verification. - -### Next recommended pass -- Install rasterio/GDAL for real raster clipping/tile implementations. -- Add queue-backed worker (Redis/RQ) behind existing synchronous job facade. -- Add deeper operation acceptance tests for output dataset geometry correctness and persisted metadata. - -## Pass 15 — Sprint 4 raster foundation -Date: 2026-06-11 - -### Completed -- Finalized dependency-aware raster processing behavior for clip/tile/preview and improved metadata enrichment. -- Ensured raster metadata and preview responses include deterministic file metadata (`size_bytes`, `checksum_sha256`, `path`) where available. -- Added raster tile manifest generation with deterministic storage paths and returned manifest payload. -- Updated API contracts and execution documentation from placeholder wording to actual raster-op foundations. -- Added targeted Sprint 4 tests for missing-area clip behavior and tile manifest payload shape. - -### Files changed -- `backend/app/services/raster_operations_service.py` -- `backend/app/api/routes/health.py` -- `backend/tests/test_raster_operations_service.py` -- `docs/API_CONTRACTS.md` -- `docs/CODEX_EXECUTION_LOG.md` -- `backend/README.md` -- `frontend/README.md` -- `README.md` -- `CHANGELOG.md` - -### Tests run -- `python -m compileall backend/app` -- `cd backend && python -m pytest` -- `bash scripts/run_readiness_check.sh` -- `bash scripts/smoke_backend_import.sh` -- `cd frontend && npm run typecheck` -- `cd frontend && npm run build` - -### Known limitations -- Raster dependency packages remain optional and will report `RASTER_PROCESSING_UNAVAILABLE` if absent. -- Raster clip/tile remain synchronous under the current in-process job wrapper. - -### Next recommended pass -- Run full raster end-to-end tests with real GeoTIFF fixtures and validate output dataset metadata persistence. -## Pass 16 � Sprint 4 raster operations foundation hardening -Date: 2026-06-11 - -### Completed -- Realized the Sprint 4 raster foundation readiness in implementation and docs alignment: - - metadata extraction now returns real raster profile fields when rasterio is available - - preview generation writes deterministic PNG artifacts and reuses cached previews - - clip and tile operations persist deterministic outputs and manifest structure - - all raster processing paths now use explicit dependency-aware errors when rasterio/numpy/pillow are missing -- Fixed remaining frontend render/type issues introduced during raster path handling. -- Strengthened raster tests for tile manifest minimum size and dependency-aware behavior. -- Updated sprint milestone docs to reflect Sprint 4 status: - - `backend/README.md` - - `frontend/README.md` - -### Files changed -- `backend/app/services/raster_operations_service.py` -- `backend/tests/test_raster_operations_service.py` -- `backend/app/api/routes/datasets.py` -- `backend/app/schemas/operations.py` -- `frontend/src/App.tsx` -- `backend/README.md` -- `frontend/README.md` -- `docs/CODEX_EXECUTION_LOG.md` - -### Tests run -- `python -m compileall backend/app` (pass) -- `cd backend && python -m pytest` (pass, 26 tests) -- `bash scripts/run_readiness_check.sh` (pass) -- `bash scripts/smoke_backend_import.sh` (pass) -- `cd frontend && npm run typecheck` (pass) -- `cd frontend && npm run build` (pass) - -### Known limitations -- `docker` command is unavailable in this environment, so `docker compose config` could not be executed. -- `python3` command is unavailable as an alias in this environment; use `python` instead. -- Full raster dependency stack may be unavailable in some dev environments; those cases intentionally return structured `RASTER_PROCESSING_UNAVAILABLE` responses. - -### Next recommended pass -- Sprint 5: add end-to-end RasterOps coverage for CRS-preserving re-projection, export-quality metadata policy, and tile set artifact cleanup lifecycle. -## Pass 17 — Sprint 5 raster analytics hardening - -Date: 2026-06-11 - -### Completed -- Implemented Sprint 5 raster analytics foundation: - - band statistics endpoint and service with dependency-aware unavailable mode. - - reproject operation with CRS validation and reprojection metadata persistence. - - clip/tile hardening for missing/invalid geometry and empty clip output handling. - - enriched tile manifest fields (`tile_set_id`, `tile_size`, `overlap`, `source_dataset_id`, `source_raster_id`, `bounds`, `count`, `tile_paths`, `ai_inference`, `tile_server`, `created_at`, parameters). -- Updated raster stats/job error tests: - - dependency-aware stats failure coverage. - - invalid CRS request validation for reproject. - - persisted derived dataset assertions for reproject and clip. - - failure persistence test for failed raster jobs (`_run_job_sync`). -- Strengthened raster frontend detail panel rendering: - - job result JSON is visible for raster/vector operations. - - clearer raster metadata/status visibility retained for CRS/bounds/resolution display. -- Updated docs: - - backend/README Sprint 5 section. - - frontend/README Sprint 5 section. - - CHANGELOG entry for Sprint 5. - -### Files changed -- `backend/app/services/raster_operations_service.py` (final reproject and manifest hardening alignment) -- `backend/tests/test_raster_operations_service.py` -- `frontend/src/App.tsx` -- `backend/README.md` -- `frontend/README.md` -- `docs/API_CONTRACTS.md` -- `docs/RASTER_OPERATIONS_SPEC.md` -- `docs/CODEX_EXECUTION_LOG.md` -- `CHANGELOG.md` - -### Tests run -- `python -m compileall backend/app` (pass) -- `cd backend && python -m pytest` (pass) -- `bash scripts/run_readiness_check.sh` (pass) -- `bash scripts/smoke_backend_import.sh` (pass) -- `cd frontend && npm run typecheck` (pass) -- `cd frontend && npm run build` (pass) - -### Known limitations -- Raster statistics and reproject operations still depend on environment availability of `rasterio`/`numpy`. -- Raster dependency checks and operation errors remain dependency-aware when libraries are unavailable. - -### Next recommended pass -- Sprint 6: add raster index/mask workflows (NDVI/NDWI/NDBI), tile serving or export packaging, and AI-ready dataset linking. -## Pass 18 - Sprint 6 spectral indices - -### Completed -- Added local raster index operations (`ndvi`, `ndwi`, `ndbi`) under the existing raster operation architecture. -- Added typed band payload validation and explicit `INVALID_PARAMETERS` handling for missing/invalid band indexes. -- Implemented dependency-aware failure behavior for index execution (`RASTER_PROCESSING_UNAVAILABLE`) when `rasterio` or `numpy` are unavailable. -- Implemented local index output generation with float32 raster derivation and persisted provenance metadata on derived datasets. -- Extended dataset detail UI with spectral index controls (NDVI/NDWI/NDBI), run actions, and output dataset navigation from jobs. -- Updated API contracts, raster operation spec, and project documentation for Sprint 6 behavior. - -### Files changed -- `backend/app/schemas/operations.py` -- `backend/app/services/raster_operations_service.py` -- `backend/app/api/routes/datasets.py` -- `backend/tests/test_raster_operations_service.py` -- `frontend/src/services/api/datasets.ts` -- `frontend/src/App.tsx` -- `frontend/src/types.ts` -- `docs/API_CONTRACTS.md` -- `docs/RASTER_OPERATIONS_SPEC.md` -- `backend/README.md` -- `frontend/README.md` -- `CHANGELOG.md` -- `docs/CODEX_EXECUTION_LOG.md` - -### Tests run -- `python -m compileall backend/app` -- `cd backend && python -m pytest` -- `bash scripts/run_readiness_check.sh` -- `bash scripts/smoke_backend_import.sh` -- `cd frontend && npm run typecheck` -- `cd frontend && npm run build` - -### Known limitations -- Raster dependency checks remain optional; missing raster packages return explicit `RASTER_PROCESSING_UNAVAILABLE` results. -- Job execution remains synchronous under current Sprint 3 job facade. -- `docker` and `python3` availability still depend on developer environment. - -### Next recommended pass -- Keep operation architecture stable, then add threshold/mask workflows and output export packaging in a follow-up pass. - - -## Pass 19 - RC-2 stabilization -Date: 2026-06-12 - -### Completed -- Fixed backend compile/import blockers identified in RC-1: - - corrected dataset upload parameter ordering. - - corrected schema package re-exports for area schemas. -- Fixed frontend typecheck/build blockers in `App.tsx`. -- Added Alembic migration for dataset reference/provenance metadata columns required by current ORM models. -- Fixed QA comparison runtime crash and added focused QA service coverage. -- Corrected envelope response-model mismatches for vector inspect and raster stats endpoints. -- Strengthened `scripts/run_readiness_check.sh` so readiness runs backend compile, backend tests, frontend typecheck and frontend build. -- Improved readiness Python interpreter selection so it chooses an interpreter capable of running pytest. - -### Files changed -- `backend/app/services/dataset_service.py` -- `backend/app/schemas/__init__.py` -- `backend/app/api/routes/datasets.py` -- `backend/app/services/qa_service.py` -- `backend/alembic/versions/202606120001_add_dataset_reference_metadata.py` -- `backend/tests/test_qa_service.py` -- `frontend/src/App.tsx` -- `scripts/run_readiness_check.sh` -- `docs/CODEX_EXECUTION_LOG.md` - -### Tests run -- `python -m compileall backend\\app` (pass) -- `cd backend && python -m pytest` (pass, 40 tests) -- `cd frontend && npm run typecheck` (pass) -- `cd frontend && npm run build` (pass; bundle-size warning only) -- `bash scripts/run_readiness_check.sh` (pass) -- `cd backend && python -m alembic heads` (pass, single head `202606120001`) -- `cd backend && python -m alembic upgrade head --sql` (pass, generated SQL includes required dataset metadata columns) -- `docker compose config` not runnable in this environment because `docker` is not installed. - -### Known limitations -- Fresh online database migration was validated only as generated Alembic SQL in this environment; run `cd backend && python -m alembic upgrade head` against a live PostgreSQL/PostGIS database on a machine with Docker or Postgres available. -- Existing non-RC architecture limitations from RC-1 remain intentionally unfixed: synchronous job facade, file-first vector outputs, monolithic frontend component, and incomplete future AI/storage architecture. - -### Next recommended pass -- Do not start Sprint 7 until RC-2 verification is repeated against a live Docker/PostGIS environment. - -## Pass 20 - Sprint 7A persistence and QA foundation -Date: 2026-06-12 - -### Completed -- Added first-class `vector_features` ORM model and Alembic migration with dataset and GiST geometry indexes. -- Persisted uploaded vector GeoJSON features into PostGIS-backed `vector_features` while keeping original file storage intact. -- Added first-class `quality_checks` and `metrics` ORM models and Alembic migration indexes. -- Added `QualityService` for persisted QA/QC domain records and metric rows. -- Updated QA candidate-vs-reference route so successful QA jobs also persist a `QualityCheck` and metrics, and return `quality_check_id` in `result_json`. -- Hardened provider capability contracts for GRB and OSM as `not_configured` stubs with supported layers, geometry types and query modes. -- Added Sprint 7A tests for vector feature persistence, quality check persistence, metrics persistence, dataset role validation, provider contracts, migration integrity and QA route persistence. -- Updated database/API documentation for Vector Features Architecture, Quality Check Architecture, Metrics Architecture and Provider Architecture. - -### Files changed -- `backend/app/models/entities.py` -- `backend/app/models/__init__.py` -- `backend/app/services/dataset_service.py` -- `backend/app/services/vector_feature_service.py` -- `backend/app/services/quality_service.py` -- `backend/app/api/routes/qa.py` -- `backend/app/providers/base.py` -- `backend/app/providers/grb.py` -- `backend/app/providers/osm.py` -- `backend/app/schemas/health.py` -- `backend/alembic/versions/202606120700_sprint7a_persistence_foundation.py` -- `backend/tests/test_sprint7a_persistence_foundation.py` -- `docs/DATABASE_IMPLEMENTATION_PLAN.md` -- `docs/API_CONTRACTS.md` -- `docs/CODEX_EXECUTION_LOG.md` -- `CHANGELOG.md` - -### Tests run -- `python -m compileall backend/app` (pass) -- `python -m pytest backend -q` (pass, 47 tests) - -### Known limitations -- Sprint 7A intentionally does not implement GRB downloads, OSM downloads, Detection Lab, Segmentation Lab, LiDAR, AI Copilot, Training Studio or Reports. -- Job execution remains the existing synchronous facade. -- Live database migration still needs validation against a running PostgreSQL/PostGIS service in an environment with Docker or Postgres available. - -### Next recommended pass -- Complete full release validation commands, including Alembic heads/SQL generation, readiness script, frontend typecheck/build and Docker config if Docker is available. - -### Validation addendum -Date: 2026-06-12 - -Additional Sprint 7A validation completed after migration index cleanup: - -- `python -m compileall backend/app` (pass) -- `cd backend && python -m pytest` (pass, 47 tests) -- `bash scripts/run_readiness_check.sh` (pass) -- `cd frontend && npm run typecheck` (pass) -- `cd frontend && npm run build` (pass; Vite chunk-size warning only) -- `cd backend && python -m alembic heads` (pass, single head `202606120700`) -- `cd backend && python -m alembic upgrade head --sql` (pass; generated SQL includes `vector_features`, `quality_checks`, `metrics` and the named GiST index `ix_vector_features_geometry`) -- `docker compose config` could not run because Docker is not installed in this shell. - -## Pass 21 - Sprint 7B provider integration skeleton (2026-06-12) - -- Implemented central provider registry for `grb`, `osm`, `manual` and `fixture`. -- Added provider capability, layer, status and future import-contract endpoints using the existing response envelope style. -- Preserved GRB and OSM as explicit `not_configured` providers; no live WFS, Overpass, download or fake provider data was introduced. -- Documented and tested provider-to-dataset mapping rules; future provider output must flow through `DatasetService` / `VectorFeatureService` rather than direct `vector_features` writes. -- Added frontend Provider Capabilities panel without live import buttons for GRB/OSM. -- Added opt-in `scripts/live_migration_smoke.sh` for real PostGIS migration smoke checks. -- Added Sprint 7B tests for provider registry, API envelopes, invalid provider handling, import contract and smoke script presence. - -## Pass 22 - Sprint 8 Detection Lab foundation (2026-06-12) - -### Completed -- Added first-class `detections` ORM model and Alembic migration with project, dataset, analysis run, class and GiST geometry indexes. -- Hardened `analysis_runs` with dataset, job, model, result and created-at fields while keeping jobs conceptually separate from analysis lifecycle. -- Added model registry capability service for `yolo-placeholder` (`not_configured`) and `manual-fixture-detector` (explicit fixture/demo only). -- Added `DetectionService` boundary for model listing, request validation, analysis run creation, job creation, unavailable model responses and explicit fixture persistence. -- Added Detection Lab API endpoints under `/api/v1/detection` using the existing response envelope style. -- Added minimal frontend Detection Lab panel for model capability status, raster dataset selection, confidence threshold and run result/error display. -- Updated database, API, AI pipeline, backend/frontend README, TODO and changelog docs. - -### Known limitations -- Real YOLO/PyTorch inference is not enabled and no model downloads are performed. -- Fixture detector requires `fixture_mode=true` and explicit fixture detections; it is not production inference. -- Segmentation, LiDAR, AI Copilot, Training Studio and Reports remain out of scope. - -### Next recommended pass -- Verify Sprint 8 with full backend/frontend/readiness/Alembic gates, then perform a Sprint 8 verification audit before Sprint 8B real YOLO integration. - -## Pass 23 - Sprint 8B configured YOLO foundation (2026-06-12) - -### Completed -- Added optional backend `ai` dependency group for `ultralytics` and `torch`; normal backend startup remains import-safe without those packages. -- Added YOLO configuration settings: - - `YOLO_ENABLED` - - `YOLO_MODEL_PATH` - - `YOLO_MODEL_ID` - - `YOLO_MODEL_DISPLAY_NAME` - - `YOLO_MODEL_VERSION` - - `YOLO_DEVICE` - - `YOLO_IMAGE_SIZE` - - `YOLO_MAX_TILES` - - `YOLO_BATCH_SIZE` -- Added `yolo-configured` model registry capability with honest `not_configured`, `dependency_unavailable` and `configured` states. -- Added `YoloDetectionAdapter` that imports Ultralytics only in the load path and refuses missing local model files before model construction. -- Added raster tile manifest validation and configured tile-limit enforcement for real YOLO runs. -- Added pixel bbox to EPSG:4326 polygon georeferencing from tile transform or bounds metadata. -- Routed configured YOLO outputs through existing `DetectionService`, `Job`, `AnalysisRun` and first-class `Detection` persistence. -- Added Detection Lab tile manifest path input for the configured YOLO model. -- Added mocked Sprint 8B tests for model registry status, dependency-unavailable behavior, tile manifest validation, georeferencing and persisted detections. -- Updated API, AI pipeline, backend/frontend README and changelog documentation. - -### Known limitations -- Sprint 8B does not add workers/queues; configured YOLO runs remain synchronous behind the existing job abstraction. -- Real model loading is validated at execution time. The registry reports configured when dependencies and local model path are present. -- No model weights are downloaded by GeoIntel. -- Detection visualization/map overlays are deferred. -- Segmentation, LiDAR, AI Copilot, Training Studio and Reports remain out of scope. - -### Next recommended pass -- Run full Sprint 8B validation and then perform a Sprint 8B verification audit before advancing to detection visualization/QA or segmentation planning. - -## Pass 24 - Sprint 8C detection visualization and QA integration (2026-06-12) - -### Completed -- Added detection result review endpoints for listing runs, listing detections by run/dataset, retrieving detection detail and returning persisted detections as GeoJSON FeatureCollections. -- Added lightweight detection filters for class name and minimum confidence. -- Added detection QA against persisted reference `vector_features` using the existing `QualityService`, `quality_checks` and `metrics` persistence path. -- Added frontend Detection Lab run selection, detection table, class/confidence filters and MapLibre detection GeoJSON overlay via the existing map component. -- Added frontend detection QA controls and metric summary display. -- Added Sprint 8C tests for GeoJSON output, list/filter behavior, detection detail, API envelope shape, QA persistence and no-match QA behavior. -- Added direct Sprint 8B tests for missing and invalid tile manifest files. -- Updated API, AI pipeline, backend/frontend README and changelog documentation. - -### Known limitations -- Detection QA requires reference datasets to have persisted `vector_features`; unsupported references return a clear error instead of fake metrics. -- Detection overlays reuse the existing single GeoJSON map layer styling; complex class-based map styling is deferred. -- Segmentation, LiDAR, AI Copilot, Training Studio and Reports remain out of scope. - -### Next recommended pass -- Run full Sprint 8C validation and perform a Sprint 8C verification audit before starting Sprint 9 Segmentation Lab. - -## Pass 25 - Sprint 9 Segmentation Lab foundation (2026-06-12) - -### Completed -- Added first-class `segmentations` ORM model and Alembic migration with project, dataset, job, analysis run, class and GiST geometry indexes. -- Added segmentation model registry capabilities for `segmentation-placeholder`, `fixture-segmenter`, `yolo-seg-configured` and `sam-configured`. -- Added `SegmentationService` boundary for raster validation, job/analysis-run lifecycle, unavailable model responses and explicit fixture-only persistence. -- Added segmentation adapter placeholder module with no SAM, YOLO-seg, torch or ultralytics imports. -- Added persisted segmentation GeoJSON output generated from PostGIS geometry and provenance properties. -- Added segmentation QA against persisted reference `vector_features` using existing `quality_checks` and `metrics`. -- Added minimal frontend Segmentation Lab panel for model states, raster selection, runs/results, GeoJSON map overlay and QA metric display. -- Updated API, AI pipeline, storage, database, backend/frontend README and changelog documentation. - -### Files changed -- `backend/app/models/entities.py` -- `backend/app/models/__init__.py` -- `backend/alembic/versions/202606120900_sprint9_segmentation_foundation.py` -- `backend/app/schemas/segmentation.py` -- `backend/app/schemas/__init__.py` -- `backend/app/services/model_registry_service.py` -- `backend/app/services/segmentation_adapter.py` -- `backend/app/services/segmentation_service.py` -- `backend/app/api/routes/segmentation.py` -- `backend/app/main.py` -- `backend/tests/test_sprint9_segmentation_foundation.py` -- `frontend/src/types.ts` -- `frontend/src/services/api/segmentation.ts` -- `frontend/src/services/api/index.ts` -- `frontend/src/App.tsx` -- `docs/API_CONTRACTS.md` -- `docs/AI_PIPELINES.md` -- `docs/STORAGE_ARCHITECTURE.md` -- `docs/DATABASE_IMPLEMENTATION_PLAN.md` -- `backend/README.md` -- `frontend/README.md` -- `CHANGELOG.md` -- `docs/CODEX_EXECUTION_LOG.md` - -### Tests run -- `python -m pytest backend/tests/test_sprint9_segmentation_foundation.py -q` (red first: missing `Segmentation` import, then pass) -- `cd backend && python -m pytest` (pass, 88 tests) -- `cd frontend && npm run typecheck` (pass) - -### Known limitations -- Sprint 9 intentionally does not implement real SAM, real YOLO-seg, model downloads, new AI dependencies or production-scale async inference. -- Fixture segmenter requires explicit `fixture_mode=true` and explicit fixture segmentations; it is not production inference. -- Metric area is only persisted when provided by the fixture/output payload; Sprint 9 does not compute authoritative area from masks. - -### Next recommended pass -- Run full Sprint 9 validation and then perform Sprint 9 Verification Audit before considering future real SAM/YOLO-seg integration. - -### Validation addendum -- `python -m compileall backend/app` (pass) -- `cd backend && python -m pytest` (pass, 88 tests) -- `bash scripts/run_readiness_check.sh` (pass) -- `cd frontend && npm run typecheck` (pass) -- `cd frontend && npm run build` (pass; existing Vite chunk-size warning only) -- `cd backend && python -m alembic heads` (pass, single head `202606120900`) -- `cd backend && python -m alembic upgrade head --sql` (pass; generated SQL includes `segmentations` and GiST index) -- `bash -n scripts/live_migration_smoke.sh` (pass) -- `docker compose config` could not run because Docker is not installed in this shell. - -## Pass 26 - Sprint 10 release hardening and frontend modularization (2026-06-13) - -### Completed -- Extracted Provider Capabilities, Detection Lab and Segmentation Lab sections from `frontend/src/App.tsx` into focused frontend components. -- Preserved existing workbench state ownership, API client calls, map overlay behavior and UI copy. -- Hardened `scripts/run_readiness_check.sh` with Alembic head verification and live migration smoke script syntax validation. -- Updated frontend README and changelog documentation for Sprint 10 maintainability work. - -### Files changed -- `frontend/src/App.tsx` -- `frontend/src/components/providers/ProviderPanel.tsx` -- `frontend/src/components/detection/DetectionLab.tsx` -- `frontend/src/components/segmentation/SegmentationLab.tsx` -- `scripts/run_readiness_check.sh` -- `frontend/README.md` -- `CHANGELOG.md` -- `docs/CODEX_EXECUTION_LOG.md` - -### Known limitations -- Sprint 10 intentionally does not add new backend capabilities, migrations, product features, AI dependencies or live provider fetching. -- `App.tsx` still owns shared workbench state orchestration; further extraction can be considered in a later maintainability pass if needed. - -### Sprint 10 addendum - additional frontend extraction -- Extracted `frontend/src/components/project/ProjectPanel.tsx` and `frontend/src/components/project/AreaPanel.tsx` from `frontend/src/App.tsx`. -- Kept project and area form state owned by `App.tsx`; extracted components receive state and callbacks only. -- `cd frontend && npm run typecheck` passed after the additional extraction. - -## Pass 27 - Sprint 11 Live Docker/PostGIS Runtime Validation (2026-06-13) - -### Completed -- Hardened `scripts/live_migration_smoke.sh` so it runs `SELECT 1`, applies `alembic upgrade head`, then checks `PostGIS_Version()`. -- Added migrated schema-object checks for core tables and geometry indexes after the live migration step. -- Added `backend/tests/test_live_migration_smoke_script.py` to lock the smoke-script ordering and schema-check contract. -- Documented the Docker/PostGIS validation command sequence, expected local `DATABASE_URL` and cleanup commands in `backend/README.md`. - -### Files changed -- `scripts/live_migration_smoke.sh` -- `backend/tests/test_live_migration_smoke_script.py` -- `backend/README.md` -- `CHANGELOG.md` -- `docs/CODEX_EXECUTION_LOG.md` - -### Runtime status -- Docker is not installed or not available in this shell, so `docker compose config`, `docker compose up -d db` and the live container-backed smoke could not be completed here. -- On a Docker-enabled machine, run: - - `docker compose config` - - `docker compose up -d db` - - `DATABASE_URL=postgresql+psycopg://geointel:geointel@localhost:5432/geointel bash scripts/live_migration_smoke.sh` - -### Known limitations -- Sprint 11 did not add product behavior, API contracts, migrations, AI dependencies or provider fetching. -- Live runtime validation is partially blocked until Docker/PostGIS is available in the execution environment. - -## Pass 28 - Sprint 12 QA/QC golden dataset and benchmarking (2026-06-15) - -### Completed -- Added deterministic golden QA/QC fixtures for reference and predicted building polygons. -- Added `fixtures/golden/expected_qa_metrics.json` with the expected partial-match baseline. -- Added `scripts/run_golden_qa_benchmark.py` to run existing `QaService` logic and verify `QualityService` persistence output. -- Added backend tests for expected golden metrics, benchmark command output and persisted metric keys. -- Updated QA/QC specification, backend README and changelog documentation. - -### Files changed -- `fixtures/golden/reference_buildings.geojson` -- `fixtures/golden/predicted_buildings.geojson` -- `fixtures/golden/expected_qa_metrics.json` -- `scripts/run_golden_qa_benchmark.py` -- `backend/tests/test_sprint12_golden_qa_benchmark.py` -- `docs/QA_QC_SPECIFICATION.md` -- `backend/README.md` -- `CHANGELOG.md` -- `docs/CODEX_EXECUTION_LOG.md` - -### Expected benchmark metrics -- precision: `0.5` -- recall: `0.5` -- F1: `0.5` -- mean IoU: `0.8339768339761133` -- false positives: `1` -- false negatives: `1` - -### Known limitations -- The benchmark uses explicit fixture/demo data and an in-memory persistence session; it does not replace the pending Docker/PostGIS live smoke. -- Sprint 12 does not add product features, API contracts, migrations, live providers, AI model execution or new dependencies. - -## Pass 29 - Sprint 13 Real YOLO operational hardening (2026-06-15) - -### Completed -- Added `YoloPreflightService` for local configured-YOLO readiness checks without model loading, inference or downloads. -- Added `scripts/yolo_preflight.py` for CLI checks of enabled state, dependencies, local model file, tile manifest validity, tile limit and tile paths. -- Added Sprint 13 backend tests for disabled, dependency-unavailable and ready preflight states plus CLI JSON output. -- Updated AI pipeline, backend README and changelog documentation. - -### Files changed -- `backend/app/services/yolo_preflight_service.py` -- `scripts/yolo_preflight.py` -- `backend/tests/test_sprint13_yolo_preflight.py` -- `docs/AI_PIPELINES.md` -- `backend/README.md` -- `CHANGELOG.md` -- `docs/CODEX_EXECUTION_LOG.md` - -### Known limitations -- Preflight does not prove model compatibility or inference correctness; it intentionally avoids loading YOLO models. -- Optional AI dependencies are still not installed by default. -- Docker/PostGIS live validation remains pending until Docker is available. - -## Pass 30 - Release hardening audit pass (2026-06-15) - -### Completed -- Audited release-readiness signals after Sprint 13, including timestamp warnings, frontend bundle output, migration SQL rendering and readiness coverage. -- Replaced backend `datetime.utcnow()` calls with timezone-aware UTC timestamps in service paths. -- Verified the affected backend tests with `DeprecationWarning` promoted to errors. -- Split frontend production output into app, React vendor and MapLibre vendor chunks, with an explicit chunk warning threshold for the known MapLibre GIS runtime. -- Updated backend/frontend README, TODO and changelog documentation. - -### Files changed -- `backend/app/services/dataset_service.py` -- `backend/app/services/geojson_service.py` -- `backend/app/services/job_service.py` -- `backend/app/services/qa_service.py` -- `backend/app/services/quality_service.py` -- `frontend/vite.config.ts` -- `backend/README.md` -- `frontend/README.md` -- `docs/TODO.md` -- `CHANGELOG.md` -- `docs/CODEX_EXECUTION_LOG.md` - -### Known limitations -- This pass does not add product features, migrations, API contracts, AI dependencies, provider fetching or model execution. -- Docker/PostGIS live validation still requires a Docker-enabled machine. -- Larger frontend architectural decomposition remains a separate low-risk planning item; this pass only hardened build output. - -## Pass 31 - Extended release hardening sweep (2026-06-15) - -### Completed -- Promoted the backend readiness gate to run `pytest` with `-W error::DeprecationWarning`. -- Added backend tests that verify readiness and pass-end scripts keep the stricter release checks in place. -- Hardened `scripts/codex_pass_end_check.sh` so placeholder scans skip `node_modules`, `dist` and `__pycache__` folders. -- Updated `docs/TODO.md` with a current implementation status layer while preserving older planning context. -- Re-ran pass-end checks and strict backend warning checks. - -### Files changed -- `scripts/run_readiness_check.sh` -- `scripts/codex_pass_end_check.sh` -- `backend/tests/test_readiness_gate.py` -- `backend/README.md` -- `docs/TODO.md` -- `CHANGELOG.md` -- `docs/CODEX_EXECUTION_LOG.md` - -### Known limitations -- This pass still does not add API contracts, migrations, product features, provider fetching, AI dependencies or model execution. -- Docker/PostGIS live validation remains blocked in this local environment because Docker is unavailable. - -## Pass 32 - Readiness contract gate hardening (2026-06-15) - -### Completed -- Added API contract smoke validation to `scripts/run_readiness_check.sh`. -- Added a regression test that requires the readiness gate to keep running `scripts/smoke_contracts.py`. -- Re-ran the full readiness gate after the change. - -### Files changed -- `scripts/run_readiness_check.sh` -- `backend/tests/test_readiness_gate.py` -- `backend/README.md` -- `CHANGELOG.md` -- `docs/CODEX_EXECUTION_LOG.md` - -### Known limitations -- Docker/PostGIS live validation remains blocked in this local environment because Docker is unavailable. - -## Pass 33 - Docker runtime build hardening (2026-06-15) - -### Completed -- Investigated Unraid/Tower Docker build failure from pasted server output. -- Fixed backend Docker build ordering so `README.md` and `app/` exist before `pip install .`. -- Removed mandatory root `.env` references from Compose; default local runtime now uses checked-in environment values. -- Added PostGIS healthcheck and backend `depends_on` health condition. -- Made the backend container run `python -m alembic upgrade head` before starting Uvicorn. -- Added backend and frontend `.dockerignore` files to reduce Docker build context and exclude dependency/build/cache outputs. -- Added regression tests for Dockerfile package-source ordering, Compose env behavior, DB health/migration startup and Docker ignore coverage. - -### Files changed -- `backend/Dockerfile` -- `docker-compose.yml` -- `backend/.dockerignore` -- `frontend/.dockerignore` -- `backend/tests/test_docker_runtime_config.py` -- `README.md` -- `backend/README.md` -- `docs/TODO.md` -- `CHANGELOG.md` -- `docs/CODEX_EXECUTION_LOG.md` - -### Known limitations -- Docker commands still cannot be executed in this local Codex environment because Docker is unavailable here. -- The server should rerun `docker compose build --no-cache && docker compose up -d` to verify the real Docker runtime. - -## Pass 34 - Docker browser port 1202 (2026-06-15) - -### Completed -- Changed Docker Compose frontend host publishing from `5173:5173` to `1202:5173`. -- Added backend Docker CORS defaults for `http://localhost:1202` and `http://127.0.0.1:1202`. -- Updated `.env.example` and local/Docker documentation to point browser users to `http://localhost:1202` for Docker Compose. -- Added a regression assertion to Docker runtime config tests. - -### Files changed -- `docker-compose.yml` -- `.env.example` -- `backend/tests/test_docker_runtime_config.py` -- `README.md` -- `backend/README.md` -- `frontend/README.md` -- `docs/LOCAL_DEVELOPMENT_RUNBOOK.md` -- `CHANGELOG.md` -- `docs/CODEX_EXECUTION_LOG.md` - -### Known limitations -- Docker commands still cannot be executed in this local Codex environment because Docker is unavailable here. - -## Pass 35 - Docker backend database startup retry (2026-06-16) - -### Completed -- Investigated Tower runtime logs showing backend Alembic startup failed with `connection refused` even after the db container reported healthy. -- Added `backend/docker_start.sh` to retry a real SQLAlchemy `SELECT 1` connection before migrations. -- Updated Compose to run `sh /app/docker_start.sh` for backend startup. -- Added regression tests that require the Docker start script and SQL readiness retry before migrations. - -### Files changed -- `backend/docker_start.sh` -- `docker-compose.yml` -- `backend/tests/test_docker_runtime_config.py` -- `backend/README.md` -- `CHANGELOG.md` -- `docs/CODEX_EXECUTION_LOG.md` - -### Known limitations -- Docker commands still cannot be executed in this local Codex environment because Docker is unavailable here. - -## Pass 36 - Alembic Docker log formatting fix (2026-06-16) - -### Completed -- Investigated backend Docker logs showing repeated literal `%(levelname)-5.5s [%(name)s] %(message)s` lines during migrations. -- Fixed `backend/alembic.ini` logging formatter from escaped `%%(...)` tokens to runtime interpolation `%(...)` tokens. -- Added a regression test for Alembic logging formatter correctness. -- Verified Alembic SQL rendering no longer emits literal formatter spam. - -### Files changed -- `backend/alembic.ini` -- `backend/tests/test_alembic_logging_config.py` -- `CHANGELOG.md` -- `docs/CODEX_EXECUTION_LOG.md` - -## Pass 37 - Frontend same-origin API proxy for Docker LAN access (2026-06-16) - -### Completed -- Audited the running app at `http://192.0.2.10:1202` from Codex: frontend HTML and backend `/health` were reachable, but `/api/v1/projects` on the frontend origin returned the frontend HTML fallback. -- Changed the frontend API client default from `http://localhost:8000` to same-origin requests. -- Added Vite proxy routes for `/api` and `/health`. -- Added Docker Compose `VITE_API_PROXY_TARGET=http://backend:8000` so LAN browsers use `http://192.0.2.10:1202` only and the frontend container proxies API calls internally. -- Added regression tests for same-origin API/proxy behavior. - -### Files changed -- `frontend/src/services/api/client.ts` -- `frontend/vite.config.ts` -- `docker-compose.yml` -- `backend/tests/test_docker_runtime_config.py` -- `README.md` -- `frontend/README.md` -- `CHANGELOG.md` -- `docs/CODEX_EXECUTION_LOG.md` - -### Known limitations -- The running Tower deployment needs a rebuild/restart before this fix is active. - -## Pass 38 - Browser runtime proxy guard (2026-06-16) - -### Completed -- Added `scripts/verify_browser_runtime.sh` to verify the browser-facing frontend URL, `/api/v1/projects` proxy behavior and optional backend health endpoint. -- Added readiness syntax validation for the browser runtime verification script. -- Updated environment and local development documentation to prefer same-origin frontend API calls with Vite proxying in Docker/LAN deployments. - -### Files changed -- `scripts/verify_browser_runtime.sh` -- `scripts/run_readiness_check.sh` -- `backend/tests/test_docker_runtime_config.py` -- `README.md` -- `docs/ENVIRONMENT_SPEC.md` -- `docs/LOCAL_DEVELOPMENT_RUNBOOK.md` -- `CHANGELOG.md` -- `docs/CODEX_EXECUTION_LOG.md` - -### Known limitations -- The currently running Tower deployment at `http://192.0.2.10:1202` still returns frontend HTML for `/api/v1/projects` until the frontend image is rebuilt and restarted. - -## Pass 39 - Environment contract cleanup (2026-06-16) - -### Completed -- Corrected `.env.example` and `docs/ENVIRONMENT_SPEC.md` to use the YOLO environment variable names read by backend settings: `YOLO_ENABLED`, `YOLO_MODEL_PATH`, `YOLO_MODEL_VERSION` and `YOLO_MAX_TILES`. -- Updated frontend example settings to keep `VITE_API_BASE_URL` empty by default and expose `VITE_API_PROXY_TARGET` for Vite proxy routing. -- Added regression coverage for example environment names and browser runtime proxy verification. - -### Files changed -- `.env.example` -- `docs/ENVIRONMENT_SPEC.md` -- `backend/tests/test_docker_runtime_config.py` -- `CHANGELOG.md` -- `docs/CODEX_EXECUTION_LOG.md` - -### Known limitations -- Docker cannot be executed in this local Codex environment; Tower still needs an image rebuild/restart to activate the frontend proxy fix. - -## Pass 40 - Frontend Docker nginx reverse proxy (2026-06-16) - -### Completed -- Replaced the Docker frontend runtime with a production Vite build served by nginx. -- Added `frontend/nginx.conf` with explicit reverse proxy rules for `/api/` and `/health` to `backend:8000`. -- Changed Docker Compose frontend publishing from `1202:5173` to `1202:80`. -- Updated Docker runtime regression tests and documentation so the browser-facing API path is no longer dependent on Vite dev-server proxy behavior. - -### Files changed -- `frontend/Dockerfile` -- `frontend/nginx.conf` -- `docker-compose.yml` -- `backend/tests/test_docker_runtime_config.py` -- `README.md` -- `frontend/README.md` -- `docs/ENVIRONMENT_SPEC.md` -- `docs/LOCAL_DEVELOPMENT_RUNBOOK.md` -- `CHANGELOG.md` -- `docs/CODEX_EXECUTION_LOG.md` - -### Known limitations -- Docker still cannot be executed in this local Codex environment. Tower must rebuild the frontend image to activate the nginx runtime. - -## Sprint 14 - Docker GIS runtime enablement (2026-06-16) - -- Added backend `gis` optional dependency group for the approved Rasterio/GeoPandas runtime stack. -- Updated backend Docker image to install `.[gis]` and GDAL/GEOS/PROJ system packages. -- Added `scripts/verify_gis_runtime.sh` to verify PostGIS, Rasterio and GeoPandas capabilities through the browser-facing frontend proxy. -- Added readiness syntax coverage for the GIS runtime verification script. -- Added regression tests for Docker GIS dependency installation and capability verification coverage. -- Updated backend, environment, root README and changelog documentation with local/LAN verification commands. -- No API contracts, migrations, AI dependencies, provider fetching or product features were changed. -- Added `scripts/gis_import_smoke.py` and wired it into the backend Docker build so broken Rasterio/GeoPandas/pyogrio imports fail during image build. -- Added Docker Compose healthchecks for backend and frontend; frontend now waits for backend service health before starting. -- Corrected the GIS import smoke placement so the backend Docker build can access it inside the `./backend` build context; the root script now wraps the backend script. - -## Sprint 15 - Explicit demo workflow seed (2026-06-16) - -- Added `POST /api/v1/demo/workflow` for an explicit offline demo workflow seed. -- Added `DemoWorkflowService` to create or return a demo project, AOI, fixture reference dataset, fixture candidate dataset and persisted QA/QC metrics. -- Added `scripts/seed_demo_workflow.py` for terminal-based demo seeding. -- Added frontend `Load demo workflow` action in the Projects panel. -- Added endpoint/fixture-contract tests and readiness compile coverage for the demo seed script. -- No live GRB/OSM fetching, AI inference, migrations or new dependencies were introduced. - -## Sprint 16 - QA/QC result visibility (2026-06-16) - -- Added `GET /api/v1/projects/{project_id}/quality-checks` for read-only project QA/QC result listing. -- Added `QualityCheckService` to return persisted `quality_checks` with metric rows. -- Added frontend QA/QC Results panel and API client support. -- Demo workflow loading and QA actions now refresh persisted QA/QC results in the UI. -- Added backend tests for quality check listing and canonical envelopes. -- No migrations, live provider fetching, AI inference or new dependencies were introduced. - -## Sprint 17 export foundation (2026-06-16) - -Changed: -- Hardened GeoJSON exports so vector dataset, detection run and segmentation run exports persist `exports` rows and write JSON artifacts. -- Added project metadata JSON export plus export list/read/content endpoints. -- Added a frontend Export Center panel for creating exports, listing export records and previewing JSON content. -- Added backend tests for export persistence, artifact writing, raster rejection and canonical envelope behavior. - -Tested: -- `python -m compileall backend/app` -- `cd backend && python -m pytest -W error::DeprecationWarning` -- `cd frontend && npm run typecheck` -- `cd frontend && npm run build` -- `bash scripts/run_readiness_check.sh` -- `cd backend && python -m alembic heads && python -m alembic upgrade head --sql` -- `bash -n scripts/live_migration_smoke.sh && bash -n scripts/verify_browser_runtime.sh && bash -n scripts/verify_gis_runtime.sh` - -Open: -- Docker/live browser validation must be rerun on the deployment host after rebuild. -- YOLO-format export and report export remain documented future work; this pass only implements JSON/GeoJSON export foundation. - -Limitations: -- Export artifacts are returned through API JSON content preview; browser file-download UX is not implemented yet. -- Detection and segmentation exports require existing persisted runs; no inference or fake output generation is introduced. - -Next recommended pass: -- Rebuild/redeploy the Docker stack and verify `/api/v1/exports/*` through the LAN frontend proxy, then consider a lightweight file-download endpoint or report artifact pass. - -## Sprint 17 export download hardening (2026-06-16) - -Changed: -- Added `GET /api/v1/exports/{export_id}/download` as a raw file response for stored JSON/GeoJSON export artifacts. -- Reused the same export artifact existence validation for content preview and downloads. -- Added frontend Export Center download buttons using the configured/same-origin API base URL. -- Added backend tests for missing artifacts and file download response headers/content. - -Tested: -- `python -m compileall backend/app` -- `cd backend && python -m pytest -W error::DeprecationWarning` -- `cd frontend && npm run typecheck` -- `cd frontend && npm run build` -- `bash scripts/run_readiness_check.sh` -- `cd backend && python -m alembic heads && python -m alembic upgrade head --sql` -- `bash -n scripts/live_migration_smoke.sh && bash -n scripts/verify_browser_runtime.sh && bash -n scripts/verify_gis_runtime.sh` - -Open: -- Docker/LAN validation should be rerun after redeploy on the Tower host. - -Limitations: -- Download endpoint is intentionally a raw file response, not a canonical JSON envelope, because it is a browser/file artifact path. - -Next recommended pass: -- Rebuild Docker and verify Export Center create/preview/download against `http://192.0.2.10:1202`. - -## Sprint 17 lightweight report artifact export (2026-06-16) - -Changed: -- Added `POST /api/v1/exports/report` to create a lightweight HTML project report artifact from persisted project, dataset and QA/QC summary state. -- Added HTML escaping for report-rendered project and dataset values. -- Updated export downloads to return `text/html` for HTML report artifacts and `application/json` for JSON/GeoJSON artifacts. -- Added a frontend Export Center action for project report HTML export. -- Added backend tests for HTML report artifact creation and HTML download response behavior. - -Tested: -- `python -m compileall backend/app` -- `cd backend && python -m pytest -W error::DeprecationWarning` -- `cd frontend && npm run typecheck` -- `cd frontend && npm run build` -- `bash scripts/run_readiness_check.sh` -- `cd backend && python -m alembic heads && python -m alembic upgrade head --sql` -- `bash -n scripts/live_migration_smoke.sh && bash -n scripts/verify_browser_runtime.sh && bash -n scripts/verify_gis_runtime.sh` - -Open: -- Docker/LAN verification should be rerun after deployment rebuild. - -Limitations: -- Report export is intentionally a simple HTML artifact, not a PDF designer or standalone Reports module. -- Report content is summary-only and uses existing persisted project, dataset and QA/QC rows. - -Next recommended pass: -- Rebuild Docker and verify Export Center metadata, GeoJSON, report HTML and download flows through the LAN URL. - -## Sprint 17 export audit trail and LAN demo/export smoke (2026-06-16) - -Changed: -- Added export history to project metadata JSON and lightweight HTML report artifacts. -- Added `scripts/verify_demo_export_workflow.sh` to verify the browser-facing demo workflow, persisted QA/QC listing, metadata export, report export, vector GeoJSON export, export listing and artifact downloads. -- Included the demo/export workflow script in the main readiness syntax gate. -- Added backend tests to lock export-history content and demo/export script coverage. - -Tested: -- `python -m compileall backend/app` -- `cd backend && python -m pytest -W error::DeprecationWarning` -- `cd frontend && npm run typecheck` -- `cd frontend && npm run build` -- `bash scripts/run_readiness_check.sh` -- `cd backend && python -m alembic heads && python -m alembic upgrade head --sql` -- `bash -n scripts/live_migration_smoke.sh && bash -n scripts/verify_browser_runtime.sh && bash -n scripts/verify_gis_runtime.sh && bash -n scripts/verify_demo_export_workflow.sh` - -Open: -- `scripts/verify_demo_export_workflow.sh` still needs to be run against the rebuilt Tower deployment URL. - -Limitations: -- The smoke script intentionally uses explicit fixture demo data and does not fetch live GRB/OSM or run AI inference. - -Next recommended pass: -- Rebuild Docker on the Tower host and run `bash scripts/verify_demo_export_workflow.sh http://192.0.2.10:1202`. - -## Sprint 32 Unraid all-in-one runtime verification (2026-06-17) - -Changed: -- Converted the Unraid/Tower runtime to a single editable `geointel` Docker container via `docker-compose.unraid.yml`. -- Built the all-in-one image from `postgres:16-bookworm` with PostgreSQL 16/PostGIS packages, the FastAPI backend, nginx and the React frontend. -- Removed the default nginx site from the image so `/api/v1/*` is proxied to the embedded backend instead of returning nginx 404s. -- Hardened live migration smoke and browser runtime verification with startup retries. -- Browser runtime verification now checks the frontend, `/api/v1/projects` canonical JSON envelope and `/geointel-icon.png`. - -Tested: -- `python -m pytest backend\tests\test_sprint31_unraid_template.py` -- `bash -n deploy/unraid/all-in-one-start.sh` -- `bash -n scripts/live_migration_smoke.sh` -- `bash -n scripts/verify_browser_runtime.sh` -- `powershell -NoProfile -ExecutionPolicy Bypass -File scripts\deploy_tower.ps1` -- `docker compose -f docker-compose.unraid.yml ps` on Tower -- `bash scripts/verify_browser_runtime.sh http://192.0.2.10:1202` - -Verified runtime: -- Tower runs one GeoIntel app container: `geointel`. -- Published browser port is `0.0.0.0:1202->80/tcp`. -- Container health is `healthy`. -- Live migration smoke passed with PostGIS available and one Alembic head. -- Frontend, API proxy and icon are reachable at `http://192.0.2.10:1202`. - -Open: -- Existing reused PostgreSQL volume logs a collation version mismatch because the old database was created on Debian glibc 2.31 and the all-in-one runtime uses glibc 2.36. Runtime and migrations pass; a future maintenance pass can rebuild/refresh collation metadata if needed. - -## Sprint 32 DockerMan template/icon follow-up (2026-06-17) - -Changed: -- Added a PNG icon for Unraid/DockerMan because DockerMan may not reliably render app-served SVG icons. -- Changed the Unraid template `` to `geointel` so it matches the running all-in-one container name. -- Changed the template icon URL to the absolute PNG URL `http://192.0.2.10:1202/geointel-icon.png`. -- Added DockerMan labels to `docker-compose.unraid.yml` so the running Compose container exposes Unraid managed/webui/icon metadata. -- Updated Tower deploy scripts to copy the editable template to `/boot/config/plugins/dockerMan/templates-user/my-geointel.xml`. -- Updated Tower deploy scripts to copy the PNG icon to `/boot/config/plugins/dockerMan/images/geointel-icon.png`. - -Expected Unraid behavior: -- Refresh the Unraid Docker page after deploy so DockerMan reloads the user template metadata. -- The running `geointel` container should have template-backed editable fields and a PNG icon. - -## Sprint 32 automatic DockerMan-native deploy follow-up (2026-06-17) - -Changed: -- Added `deploy/unraid/run-dockerman-container.sh` as the single source of truth for the final Unraid container launch. -- Updated Tower deploy scripts so repository deploys validate the Compose reference, build the image with plain `docker build` and start the final container with `docker run` plus DockerMan labels. -- The launch script installs the DockerMan template/icon, removes old `geointel` containers, preserves/migrates the old Compose PostGIS volume when needed and starts the final `geointel` container as DockerMan-managed. -- Updated live migration smoke to support direct container execution through `LIVE_SMOKE_CONTAINER=geointel`. - -Expected Unraid behavior: -- A deploy from the repo should no longer leave the final app as a plain Compose-owned container. -- The final image/container should avoid Compose metadata labels that can confuse Unraid's Docker page. -- The running `geointel` container should expose `net.unraid.docker.managed=dockerman`, web UI metadata and icon metadata immediately after deploy. - -## Sprint 33 QA/QC benchmark readiness hardening (2026-06-17) - -Changed: -- Added `scripts/verify_golden_qa_benchmark.sh` as a shell wrapper for the deterministic QA/QC golden benchmark. -- Made `scripts/run_readiness_check.sh` run `scripts/run_golden_qa_benchmark.py --json` so QA/QC metric drift fails the main release gate. -- Added a readiness syntax check for the golden benchmark wrapper. -- Hardened `scripts/validate_fixtures.py` so `fixtures/golden` GeoJSON files and expected fixture paths are validated alongside the general GeoJSON fixtures. -- Added backend regression tests that keep the golden benchmark wired into readiness. -- Updated script/backend docs, TODO and changelog. - -Tested: -- `python scripts/validate_fixtures.py` -- `python scripts/run_golden_qa_benchmark.py --json` -- `bash -n scripts/verify_golden_qa_benchmark.sh` -- `bash scripts/verify_golden_qa_benchmark.sh` -- `python -m compileall backend/app` -- `cd backend && python -m pytest -W error::DeprecationWarning` -- `cd frontend && npm run typecheck` -- `cd frontend && npm run build` -- `bash scripts/run_readiness_check.sh` -- `cd backend && python -m alembic heads && python -m alembic upgrade head --sql` -- `bash -n scripts/live_migration_smoke.sh` - -Open: -- None for this pass. - -Limitations: -- The benchmark intentionally uses explicit local fixtures only. It does not fetch live GRB/OSM data and does not run AI inference. - -Next recommended pass: -- Continue with broader QA/QC golden demo coverage or frontend export preview decomposition. - -## Sprint 34 browser-facing golden QA demo hardening (2026-06-17) - -Changed: -- Hardened `scripts/verify_demo_export_workflow.sh` so the browser-facing demo/export smoke loads `fixtures/golden/expected_qa_metrics.json`. -- The smoke now verifies persisted QA/QC status, F1 score, precision, recall, mean IoU, false positives, false negatives and match counts against the golden baseline. -- Corrected the offline demo AOI to cover the golden fixture geometries instead of an older broad Kempen placeholder outside the fixture coordinates. -- Made existing demo workflows self-heal stale/unsupported QA checks by syncing the demo AOI and persisting a fresh golden QA/QC result. -- Added regression checks in backend tests so the demo/export smoke cannot regress back to key-existence-only QA/QC validation. -- Updated script documentation, TODO and changelog. - -Tested: -- `python -m compileall backend/app` -- `cd backend && python -m pytest tests/test_sprint15_demo_workflow.py tests/test_sprint21_demo_workflow_smoke.py tests/test_readiness_gate.py -q` -- `cd backend && python -m pytest -W error::DeprecationWarning` -- `cd frontend && npm run typecheck` -- `cd frontend && npm run build` -- `bash scripts/run_readiness_check.sh` -- `powershell -NoProfile -ExecutionPolicy Bypass -File scripts/deploy_tower.ps1` -- `bash scripts/verify_browser_runtime.sh http://192.0.2.10:1202` -- `bash scripts/verify_gis_runtime.sh http://192.0.2.10:1202` -- `bash scripts/verify_demo_export_workflow.sh http://192.0.2.10:1202` - -Open: -- Docker build still emits a warning about `GEOINTEL_POSTGRES_PASSWORD` being present as an image `ENV`; runtime behavior is green, but a future secret-hygiene pass should move that default out of the Dockerfile. - -Limitations: -- The demo/export smoke remains intentionally fixture-based and idempotent. It does not fetch live providers and does not run AI inference. - -Next recommended pass: -- Run the full release-readiness gate and then rebuild/deploy to Tower for browser-facing verification. - -## Sprint 35 Docker runtime secret hygiene (2026-06-17) - -Changed: -- Removed embedded PostGIS database name/user/password defaults from `deploy/unraid/Dockerfile.all-in-one` image metadata. -- Kept database credentials as runtime configuration supplied by `.env`, the Unraid template, Compose or `docker run -e`. -- Added regression coverage so `GEOINTEL_POSTGRES_PASSWORD` is not baked into the all-in-one Dockerfile again. -- Updated Unraid runtime documentation and changelog. - -Tested: -- `cd backend && python -m pytest tests/test_sprint31_unraid_template.py tests/test_docker_runtime_config.py -q` -- `bash -n deploy/unraid/all-in-one-start.sh` -- `bash -n deploy/unraid/run-dockerman-container.sh` -- `python -m compileall backend/app` -- `cd backend && python -m pytest -W error::DeprecationWarning` -- `cd frontend && npm run typecheck` -- `cd frontend && npm run build` -- `bash scripts/run_readiness_check.sh` -- `cd backend && python -m alembic heads && python -m alembic upgrade head --sql` -- `powershell -NoProfile -ExecutionPolicy Bypass -File scripts/deploy_tower.ps1` -- `bash scripts/verify_browser_runtime.sh http://192.0.2.10:1202` -- `bash scripts/verify_gis_runtime.sh http://192.0.2.10:1202` -- `bash scripts/verify_demo_export_workflow.sh http://192.0.2.10:1202` - -Open: -- Local Windows shell has no `docker` command in PATH, so Docker build/config verification must run on Tower during deploy. -- Tower rebuild completed and the previous Docker BuildKit `SecretsUsedInArgOrEnv` warning no longer appears. - -Limitations: -- The start script still has safe local defaults for standalone/dev startup. Shared deployments should set `GEOINTEL_POSTGRES_PASSWORD` via runtime configuration. - -Next recommended pass: -- Run release readiness, rebuild/deploy Tower and verify browser/GIS/demo smoke again. - -## Sprint 36 PostgreSQL collation maintenance visibility (2026-06-17) - -Changed: -- Added PostgreSQL database collation version reporting to `scripts/live_migration_smoke.sh`. -- The live smoke now prints `COLLATION_VERSION_MISMATCH` with stored and actual versions when a reused PostGIS volume was created under an older libc/collation runtime. -- The smoke also prints the exact `ALTER DATABASE "... " REFRESH COLLATION VERSION;` acknowledgement command, but does not run it automatically. -- Documented the Unraid maintenance procedure and backup/index review guidance. -- Added regression coverage for the collation reporting path. - -Tested: -- `cd backend && python -m pytest tests/test_live_migration_smoke_script.py -q` -- `bash -n scripts/live_migration_smoke.sh` -- `python -m compileall backend/app` -- `cd backend && python -m pytest -W error::DeprecationWarning` -- `cd frontend && npm run typecheck` -- `cd frontend && npm run build` -- `bash scripts/run_readiness_check.sh` -- `powershell -NoProfile -ExecutionPolicy Bypass -File scripts/deploy_tower.ps1` -- `bash scripts/verify_browser_runtime.sh http://192.0.2.10:1202` -- `bash scripts/verify_gis_runtime.sh http://192.0.2.10:1202` -- `bash scripts/verify_demo_export_workflow.sh http://192.0.2.10:1202` - -Open: -- Tower live smoke reports `COLLATION_VERSION_MISMATCH: database=geointel stored=2.31 actual=2.36`. -- Runtime remains green. The next maintenance action is optional/manual acknowledgement after backup/index review: `ALTER DATABASE "geointel" REFRESH COLLATION VERSION;`. - -Limitations: -- The smoke reports and documents the maintenance action. It intentionally does not mutate collation metadata automatically. - -Next recommended pass: -- Run release readiness, deploy Tower and decide whether to manually acknowledge the current collation version. - -## Sprint 49 Workbench shell UI refactor (2026-06-17) - -Changed: -- Audited the live workbench UI and confirmed the main usability issue was information architecture: all V1 workflows were mounted as one long vertical panel stack. -- Refactored the frontend into a task-based workbench shell with Overview, Data, Map, QA/QC, AI Labs, Exports and System workspaces. -- Added a persistent top context bar for active project, AOI, dataset and layer state. -- Moved selected dataset details into a persistent right-side inspector while keeping the same dataset/raster/vector operation callbacks. -- Added stable primary navigation test anchors. -- Documented the new frontend shell structure and updated the changelog. - -Tested: -- `cd frontend && npm run typecheck` -- `cd frontend && npm run build` -- Local Vite visual audit on `http://127.0.0.1:5175` - -Open: -- Local Vite visual audit shows `Request failed (404)` when no local backend/proxy target is available. Docker/nginx same-origin proxy behavior remains the production path. -- The next pass should run full release readiness and deploy to Tower for browser-facing verification on `http://192.0.2.10:1202`. - -Limitations: -- This pass intentionally changes UI structure only. It does not add product capabilities, alter API contracts, change migrations, fetch live providers or enable new AI models. - -Next recommended pass: -- Run full readiness, rebuild/deploy Tower, then perform a live browser smoke through the new workbench navigation. - -## Sprint 50 Workspace usability polish (2026-06-17) - -Changed: -- Refined the task-based shell workspaces after the first UI refactor. -- Converted Project, AOI and Dataset panels into compact forms and card-based lists for faster scanning. -- Converted the Map workspace controls into a toolbar with dedicated AOI/layer controls and status. -- Converted Detection Lab and Segmentation Lab into model, run, result and QA blocks. -- Added CSS utilities for entity cards, dataset cards, model cards, lab blocks, primary/secondary actions and responsive nested forms. -- Added regression coverage for the polished workspace structure. - -Tested: -- `cd frontend && npm run typecheck` -- `cd frontend && npm run build` -- `cd backend && python -m pytest tests/test_sprint47_workbench_interaction_smoke.py tests/test_sprint49_workbench_shell_refactor.py -q` - -Open: -- Run full release readiness and deploy the polish to Tower. - -Limitations: -- This pass remains frontend-only. It does not add features, change API contracts, alter migrations, fetch live providers or enable new AI models. - -Next recommended pass: -- Deploy to Tower and verify the Data, Map and AI Labs workspaces on `http://192.0.2.10:1202`. - -## Sprint 51 QA/QC and export workspace polish (2026-06-17) - -Changed: -- Refined the QA/QC workspace so persisted checks are shown as summary tiles, quality-check cards and metric chips instead of a raw nested list. -- Refined the Exports workspace with grouped export actions, latest-export status, artifact history cards and a framed JSON/GeoJSON preview panel. -- Kept the existing `useQualityWorkflow` and `useExportWorkflow` dataflow intact; no API client calls or backend contracts changed. -- Added regression coverage for the polished QA/QC and Exports workspace structure. - -Tested: -- `cd frontend && npm run typecheck` -- `cd backend && python -m pytest tests/test_sprint27_frontend_workflow_hooks.py tests/test_sprint30_workbench_components.py tests/test_sprint47_workbench_interaction_smoke.py -q` -- `cd backend && python -m pytest tests/test_sprint51_quality_export_polish.py -q` -- `cd frontend && npm run build` -- `bash scripts/run_readiness_check.sh` (`207 passed`) -- `powershell -NoProfile -ExecutionPolicy Bypass -File scripts/deploy_tower.ps1` -- Tower live migration smoke passed. -- Tower browser runtime verification passed on `http://192.0.2.10:1202`. - -Open: -- Manual visual review of populated QA/QC and Exports states with real project artifacts remains useful after the next demo workflow run. - -Limitations: -- This pass remains UI polish only. It does not add product capabilities, change API contracts, alter migrations, fetch live providers or enable new AI models. - -Next recommended pass: -- Verify QA/QC and Exports on the deployed Tower workbench, then continue with selected-object inspector detail tabs. - -## Sprint 52 selected context inspector tabs (2026-06-17) - -Changed: -- Replaced the dataset-only right inspector with a tabbed `WorkbenchInspector`. -- Added Context, Dataset, QA/Exports and AI Runs tabs using existing project, AOI, dataset, QA, export and AI-run state. -- Kept the existing `DatasetDetailPanel` as the Dataset tab so raster/vector operations and callbacks remain behavior-compatible. -- Added inspector cards for selected map feature properties, latest QA/QC, latest export and selected detection/segmentation run summaries. -- Added regression coverage for inspector wiring and tab structure. - -Tested: -- `cd frontend && npm run typecheck` -- `cd backend && python -m pytest tests/test_sprint49_workbench_shell_refactor.py tests/test_sprint50_workspace_usability_polish.py tests/test_sprint51_quality_export_polish.py -q` -- `cd backend && python -m pytest tests/test_sprint28_dataset_workflow_hook.py tests/test_sprint29_dataset_components.py tests/test_sprint52_workbench_inspector_tabs.py -q` -- `cd backend && python -m pytest tests/test_sprint52_workbench_inspector_tabs.py -q` -- `cd frontend && npm run build` -- `bash scripts/run_readiness_check.sh` (`210 passed`) -- `powershell -NoProfile -ExecutionPolicy Bypass -File scripts/deploy_tower.ps1` -- Tower live migration smoke passed. -- Tower browser runtime verification passed on `http://192.0.2.10:1202`. - -Open: -- Manual click-through of each inspector tab with populated demo data remains useful for visual fine-tuning. - -Limitations: -- This pass remains UI orchestration only. It does not add features, change API contracts, alter migrations, fetch live providers or enable new AI models. - -Next recommended pass: -- Verify the tabbed inspector live on Tower, then continue with map/dataset selection ergonomics. - -## Sprint 53 map/dataset selection ergonomics (2026-06-17) - -Changed: -- Added active-state styling to dataset cards so the selected dataset is visibly anchored in the catalog. -- Added dataset quick actions to open a dataset directly in the Map workspace or Exports workspace after loading details. -- Added inspector navigation actions to jump to Data, Map, QA/QC, Exports and AI Labs without hunting through the left navigation. -- Kept the existing dataset loading, map layer state, export flow and API clients unchanged. -- Added regression coverage for selection quick actions and inspector navigation wiring. - -Tested: -- `cd frontend && npm run typecheck` -- `cd backend && python -m pytest tests/test_sprint28_dataset_workflow_hook.py tests/test_sprint29_dataset_components.py tests/test_sprint52_workbench_inspector_tabs.py -q` -- `cd backend && python -m pytest tests/test_sprint53_selection_ergonomics.py -q` -- `cd frontend && npm run build` -- `bash scripts/run_readiness_check.sh` (`213 passed`) -- `powershell -NoProfile -ExecutionPolicy Bypass -File scripts/deploy_tower.ps1` -- Tower live migration smoke passed. -- Tower browser runtime verification passed on `http://192.0.2.10:1202`. - -Open: -- Manual demo-data click-through can still tune copy/density after real populated cards are visible. - -Limitations: -- This pass remains UI orchestration only. It does not add features, change API contracts, alter migrations, fetch live providers or enable new AI models. - -Next recommended pass: -- Verify dataset quick actions with demo data on Tower, then improve populated map/detail readability if needed. - -## Sprint 54 populated-state UI polish (2026-06-17) - -Changed: -- Ran the live demo/export workflow against the Tower deployment to inspect real populated workbench states. -- Adjusted the Data workspace so Project and AOI remain side by side while the Dataset catalog spans the full row for readable populated dataset cards. -- Made dataset-card action rows responsive so Map/Exports/detail actions do not crowd or clip on populated cards. -- Limited the Exports artifact history to the latest 10 entries by default with an explicit show-all toggle. -- Kept the Export Preview panel visible even before an artifact is selected, avoiding a blank middle column in the Exports workspace. -- Shortened displayed export storage paths while keeping the full path available in the title attribute. -- Added regression coverage for the populated Data layout and Exports populated-state behavior. - -Tested: -- `bash scripts/verify_demo_export_workflow.sh http://192.0.2.10:1202` -- Local Vite visual audit using the live Tower API proxy on `http://127.0.0.1:5176` -- `cd frontend && npm run typecheck` -- `cd backend && python -m pytest tests/test_sprint51_quality_export_polish.py tests/test_sprint53_selection_ergonomics.py -q` -- `cd frontend && npm run build` -- `bash scripts/run_readiness_check.sh` (`214 passed`) -- `powershell -NoProfile -ExecutionPolicy Bypass -File scripts/deploy_tower.ps1` -- Tower live migration smoke passed. -- Tower browser runtime verification passed on `http://192.0.2.10:1202`. -- Direct HTTP check passed for `http://192.0.2.10:1202` and `http://192.0.2.10:1202/api/v1/projects`. - -Open: -- Continue monitoring export history growth during repeated demo workflow runs. - -Limitations: -- This pass remains UI polish only. It does not add features, change API contracts, alter migrations, fetch live providers or enable new AI models. - -Next recommended pass: -- Add export history filtering or retention controls if artifact history continues to grow during demo runs. - -## Sprint 55 live visual shell polish (2026-06-17) - -Changed: -- Performed a Browser-based visual audit of the live Tower workbench at `http://192.0.2.10:1202`. -- Confirmed the main visual defect was the cramped three-column desktop shell: left navigation, central workspace and inspector competed for width at 1280px. -- Compacted the sticky top context bar and left navigation. -- Changed the standard desktop breakpoint so the inspector moves below the workspace up to 1360px, while remaining a side panel on wider displays. -- Made the Map toolbar wrap responsively instead of forcing four controls into a narrow row. -- Added a workspace-change scroll reset so switching pages starts at the workspace heading instead of inheriting stale scroll position. -- Added regression coverage for the standard desktop shell width and scroll-reset behavior. - -Tested: -- Local Browser visual audit against `http://127.0.0.1:5177` using the live Tower API proxy. -- Verified Overview, Data, Map and Exports workspaces visually after the shell changes. -- Browser console error/warning check returned no entries. -- `cd frontend && npm run typecheck` -- `cd backend && python -m pytest tests/test_sprint53_selection_ergonomics.py tests/test_sprint50_workspace_usability_polish.py -q` -- `cd frontend && npm run build` -- `bash scripts/run_readiness_check.sh` (`215 passed`) -- `powershell -NoProfile -ExecutionPolicy Bypass -File scripts/deploy_tower.ps1` -- Tower live migration smoke passed. -- Tower browser runtime verification passed on `http://192.0.2.10:1202`. -- Live Browser visual verification passed for Overview and Map on `http://192.0.2.10:1202`. - -Open: -- Export history still grows during repeated demo runs and should get filtering or retention controls. - -Limitations: -- This pass remains UI shell polish only. It does not add features, change API contracts, alter migrations, fetch live providers or enable new AI models. - -Next recommended pass: -- Continue with export history filtering or retention controls if repeated demo runs keep growing artifact history. - -## Sprint 56 export history controls (2026-06-17) - -Changed: -- Added frontend-only search for export type, status, id and storage path in the Exports workspace. -- Added export type and status filters generated from the loaded export records. -- Made the latest-10 limiter apply after filtering so large histories stay manageable without hiding matching records unexpectedly. -- Added a clear no-match empty state and reset view action. -- Slightly compacted export action buttons so the history controls are visible earlier on standard desktop viewports. -- Added regression coverage for the export history controls, filtered list limiting and no-match state. - -Tested: -- `cd frontend && npm run typecheck` -- `cd backend && python -m pytest tests/test_sprint51_quality_export_polish.py -q` -- `cd frontend && npm run build` -- Local Browser visual audit against `http://127.0.0.1:5178` using the live Tower API proxy. -- Verified Exports history controls render with 50 live artifacts and a `report` search narrows the list to 17 matching artifacts. -- Browser console error/warning check returned no entries. - -Open: -- Run full readiness, deploy Tower and verify the live Exports filters on `http://192.0.2.10:1202`. - -Limitations: -- This pass remains frontend UI hardening only. It does not add backend filtering, retention deletion, API changes, migrations, live provider fetching or AI model behavior. - -Next recommended pass: -- Consider a safe export retention/cleanup command if the artifact table keeps growing beyond demo needs. - -## Sprint 57 safer demo export cleanup (2026-06-17) - -Changed: -- Hardened the existing dry-run-first demo export cleanup command instead of creating a parallel cleanup path. -- Added `--max-delete` with a default cap of 25 so large `--apply` runs are blocked until explicitly reviewed and raised. -- Added repeatable `--export-type` filters for targeted cleanup, e.g. reports only. -- Extended the cleanup summary with `keep_latest`, `max_delete`, `export_types`, `type_filtered_export_count`, `candidate_exports` and `blocked_reason`. -- Updated the root wrapper to expose the new filter helper. -- Updated `scripts/README.md`, `docs/STORAGE_ARCHITECTURE.md`, `backend/README.md`, `docs/TODO.md` and `CHANGELOG.md`. -- Added regression coverage for export-type filtering, parser defaults and max-delete options. - -Tested: -- `python -m py_compile scripts/cleanup_demo_artifacts.py backend/scripts/cleanup_demo_artifacts.py` -- `cd backend && python -m pytest tests/test_sprint24_cleanup_demo_artifacts.py tests/test_readiness_gate.py -q` (`16 passed`) -- Tower dry-run command passed without deleting data: - `docker exec geointel /opt/geointel/venv/bin/python /app/scripts/cleanup_demo_artifacts.py --keep-latest 10 --max-delete 100 --export-type project_report_html` -- Tower dry-run reported `matched_export_count=51`, `type_filtered_export_count=17`, `selected_export_count=7`, `deleted_export_count=0`. - -Open: -- Run full readiness and redeploy Tower with the clearer `candidate_exports` dry-run output. - -Limitations: -- Cleanup still targets demo export records/files only. It does not delete source uploads, vector features, projects, AOIs, QA/QC records, rasters, tiles, masks or production data. - -Next recommended pass: -- Add a small live maintenance smoke that runs cleanup in dry-run mode through the deployed all-in-one container. - -## Sprint 58 demo cleanup dry-run smoke (2026-06-18) - -Changed: -- Added `scripts/verify_demo_cleanup_dry_run.sh` as a live maintenance smoke for the demo export cleanup path. -- The smoke auto-detects a running compose backend or all-in-one `geointel` container, with explicit `CLEANUP_MODE=local|compose|container` overrides. -- The smoke runs cleanup without `--apply`, then verifies `dry_run=true`, `deleted_export_count=0`, `deleted_files=[]`, expected filter settings and candidate dry-run fields. -- Added the smoke syntax check to `scripts/run_readiness_check.sh`. -- Added regression coverage that the readiness gate checks the smoke and that the smoke contract remains non-mutating. -- Updated `scripts/README.md`, `docs/STORAGE_ARCHITECTURE.md`, `backend/README.md`, `docs/TODO.md` and `CHANGELOG.md`. - -Tested: -- `bash -n scripts/verify_demo_cleanup_dry_run.sh` -- `python -m py_compile scripts/cleanup_demo_artifacts.py backend/scripts/cleanup_demo_artifacts.py` -- `cd backend && python -m pytest tests/test_readiness_gate.py tests/test_sprint24_cleanup_demo_artifacts.py -q` (`18 passed`) -- `bash scripts/run_readiness_check.sh` (`219 passed`) -- `powershell -NoProfile -ExecutionPolicy Bypass -File scripts/deploy_tower.ps1` -- Tower live migration smoke passed. -- Tower browser runtime verification passed on `http://192.0.2.10:1202`. -- Tower cleanup dry-run smoke passed with `matched=51`, `type_filtered=17`, `selected=7`, `deleted=0`. - -Open: -- None for this pass. - -Limitations: -- The readiness gate checks this live smoke's syntax only. The actual cleanup dry-run still requires a running backend/PostGIS runtime. - -Next recommended pass: -- Add browser screenshot artifact automation for visual regression handoff. - -## Sprint 59 workbench screenshot artifacts (2026-06-18) - -Changed: -- Added `scripts/capture_workbench_screenshots.sh` for optional visual regression handoff screenshots. -- The script seeds the explicit offline demo workflow, opens Overview, Data, Map, QA/QC, AI Labs, Exports and System, then writes viewport screenshots plus `manifest.json`. -- Desktop capture is always enabled; mobile capture is enabled by default and can be disabled with `CAPTURE_MOBILE=0`. -- Added `/artifacts/` to `.gitignore` so screenshot outputs stay local. -- Added readiness syntax coverage and regression checks for the screenshot capture contract. -- Updated `scripts/README.md`, `docs/TODO.md` and `CHANGELOG.md`. - -Tested: -- `bash -n scripts/capture_workbench_screenshots.sh` -- `cd backend && python -m pytest tests/test_readiness_gate.py -q` (`13 passed`) -- `bash scripts/run_readiness_check.sh` (`221 passed`) -- Local script execution without Playwright fails cleanly with setup instructions instead of producing partial artifacts. -- Browser-plugin visual capture against `http://192.0.2.10:1202` created viewport screenshots for all seven workspaces with no console errors or warnings. - -Open: -- Commit, deploy Tower and keep the visual artifact script available for future Playwright-enabled runners. - -Limitations: -- Playwright/Chromium is intentionally optional and not added to the frontend dependency set. The readiness gate checks script syntax only. - -Next recommended pass: -- Run a backend error-envelope audit for expected user-error paths. - -## Sprint 60 API error-envelope contract hardening (2026-06-18) - -Changed: -- Audited the backend error payload shape against `docs/API_CONTRACTS.md`. -- Changed central FastAPI error serialization to return top-level `error`, `message`, `details` and `request_id` fields. -- Preserved HTTPException detail dict support for future explicit error codes. -- Updated the frontend API client to parse the canonical top-level error contract while remaining tolerant of the older nested `error.code/message/details` shape. -- Added regression tests for AppError, HTTPException and validation-error envelopes. -- Updated provider-registry error assertions to the canonical top-level schema. -- Added static frontend parser coverage for canonical and legacy error payloads. -- Updated `docs/TODO.md` and `CHANGELOG.md`. - -Tested: -- `cd backend && python -m pytest tests/test_error_envelope_contract.py tests/test_sprint7b_provider_registry.py::test_provider_api_envelopes_and_invalid_provider -q` (`4 passed`) -- `python -m compileall backend/app` -- `cd frontend && npm run typecheck` -- `cd backend && python -m pytest -q` (`224 passed`) -- `cd frontend && npm run build` -- `cd backend && python -m pytest tests/test_error_envelope_contract.py tests/test_frontend_api_client_error_parser.py tests/test_sprint7b_provider_registry.py::test_provider_api_envelopes_and_invalid_provider -q` (`6 passed`) -- `bash scripts/run_readiness_check.sh` (`226 passed`) -- `powershell -NoProfile -ExecutionPolicy Bypass -File scripts/deploy_tower.ps1` -- Tower live migration smoke passed. -- Tower browser runtime verification passed on `http://192.0.2.10:1202`. -- Live `GET /api/v1/external/providers/unknown` returned `{"error":"PROVIDER_NOT_FOUND","message":"Provider not found","details":{},"request_id":null}`. -- Live `GET /api/v1/projects/not-a-uuid` returned top-level `VALIDATION_ERROR`. - -Open: -- None for this pass. - -Limitations: -- This pass changes only the centralized response envelope and frontend parser. It does not rename route-level error codes or change product behavior. - -Next recommended pass: -- Expand golden datasets beyond the current building QA fixtures. - -## Sprint 61 Golden QA scenario expansion (2026-06-18) - -Changed: -- Added `fixtures/golden/golden_qa_benchmarks.json` as the explicit scenario manifest for deterministic QA/QC regression coverage. -- Added local golden fixture pairs for perfect-match, no-overlap and MultiPolygon building comparisons. -- Updated `scripts/run_golden_qa_benchmark.py` to execute all manifest scenarios, assert expected metric drift, persist simulated `QualityCheck`/`Metric` rows for each scenario and report aggregate persistence totals. -- Preserved backward-compatible top-level benchmark fields for scripts that still read the original single-scenario output shape. -- Updated `scripts/README.md`, `docs/TODO.md` and `CHANGELOG.md`. - -Tested: -- Red step: `cd backend && python -m pytest tests/test_sprint12_golden_qa_benchmark.py -q` failed on missing multi-scenario manifest/output. -- `cd backend && python -m pytest tests/test_sprint12_golden_qa_benchmark.py -q` (`4 passed`) -- `python scripts/run_golden_qa_benchmark.py --json` - -Open: -- Run full readiness and deploy Tower after the expanded golden benchmark passes the release gate. - -Limitations: -- These are deterministic local QA/QC fixtures only. They do not introduce new production QA metrics or provider data. - -Next recommended pass: -- Continue with frontend visual polish backlog or add a live golden benchmark smoke only if a running PostGIS environment needs that extra release signal. - -## Sprint 62 Workbench visual polish (2026-06-18) - -Changed: -- Added a compact workspace command bar under the active workspace heading for quick movement between the main workbench surfaces. -- Polished the shared frontend visual system with raised/sunken surface tokens, softer shadows, tighter topbar spacing and consistent workspace panel styling. -- Replaced raw project/dataset empty-state text with structured empty-state blocks. -- Wrapped Detection Lab and Segmentation Lab result summaries in scan-friendly result cards and long result tables in scroll-safe containers. -- Improved mobile navigation density by making the primary nav and command chips horizontal rails on narrow screens. -- Added `backend/tests/test_sprint62_frontend_visual_polish.py` to guard the visual polish contracts. -- Updated `frontend/README.md`, `docs/TODO.md` and `CHANGELOG.md`. - -Tested: -- Red step: `cd backend && python -m pytest tests/test_sprint62_frontend_visual_polish.py -q` failed on missing command bar, panel polish and empty/result wrappers. -- `cd backend && python -m pytest tests/test_sprint62_frontend_visual_polish.py tests/test_sprint49_workbench_shell_refactor.py tests/test_sprint50_workspace_usability_polish.py -q` (`6 passed`) -- `cd frontend && npm run typecheck` -- `cd frontend && npm run build` -- Local Chrome/Playwright visual check against `http://127.0.0.1:5175` with live API proxy: desktop and mobile screenshots captured, no console warnings/errors, no horizontal page overflow. - -Open: -- Run full readiness and deploy Tower after this visual polish pass. - -Limitations: -- This is a frontend usability polish pass only. It does not add new API behavior, data processing, provider fetching or AI model functionality. - -Next recommended pass: -- Continue with map/result overlay ergonomics, especially making selected dataset/result provenance easier to see beside the map. - -## Sprint 63 Map overlay ergonomics (2026-06-18) - -Changed: -- Added active map layer source/provenance/draw-state context in the Map workspace using existing selected dataset, detection, segmentation and change-detection frontend state. -- Added a clear map empty-state when no vector/result layer is active. -- Added selected-feature property chips before the raw JSON feature inspector so common properties are scan-friendly. -- Tightened panel-title alignment with a scoped CSS override after the broader visual polish exposed a specificity issue in the existing `section > div:not(...)` rule. -- Added `backend/tests/test_sprint63_map_overlay_ergonomics.py`. -- Updated `frontend/README.md`, `docs/TODO.md` and `CHANGELOG.md`. - -Tested: -- Red step: `cd backend && python -m pytest tests/test_sprint63_map_overlay_ergonomics.py -q` failed on missing map provenance/feature-summary UI. -- `cd backend && python -m pytest tests/test_sprint63_map_overlay_ergonomics.py tests/test_sprint30_workbench_components.py tests/test_sprint53_selection_ergonomics.py -q` (`11 passed`) -- `cd frontend && npm run typecheck` -- `cd frontend && npm run build` -- Local Chrome/Playwright check against `http://127.0.0.1:5175` with live API proxy: Map workspace opened, provenance rail present, no console warnings/errors, no horizontal page overflow. - -Open: -- Run full readiness and deploy Tower after this pass. - -Limitations: -- This is a frontend ergonomics pass only. It does not add new map layers, backend endpoints, provider fetching or geospatial processing. - -Next recommended pass: -- Continue with export/report handoff polish or add a live browser smoke that explicitly visits every workspace after deployment. - -## Sprint 64 Export/report handoff polish (2026-06-18) - -Changed: -- Added a handoff readiness card to the Export Center using existing project, selected dataset, selected detection run, selected segmentation run and latest export state. -- Reworked existing export actions into artifact cards for refresh, project report, project metadata, selected vector GeoJSON, detection GeoJSON and segmentation GeoJSON. -- Added formatted export-type badges and extra export-card provenance for analysis-run ids and created timestamps when those fields are available. -- Added responsive styling for handoff summary/action cards. -- Added `backend/tests/test_sprint64_export_handoff_polish.py`. -- Updated `frontend/README.md`, `docs/TODO.md` and `CHANGELOG.md`. - -Tested: -- Red step: `python -m pytest backend/tests/test_sprint64_export_handoff_polish.py -q` failed on missing handoff summary/action structure and styles. -- `python -m pytest backend/tests/test_sprint64_export_handoff_polish.py backend/tests/test_sprint51_quality_export_polish.py -q` (`4 passed`) -- `cd frontend && npm run typecheck` -- `cd frontend && npm run build` -- Local Chrome/Playwright check against `http://127.0.0.1:5175` with live API proxy: Exports workspace opened, handoff summary/actions present, no console warnings/errors, no horizontal page overflow on desktop or mobile. -- `bash scripts/run_readiness_check.sh` (`233 passed`) -- `powershell -NoProfile -ExecutionPolicy Bypass -File scripts/deploy_tower.ps1` rebuilt and redeployed the all-in-one container on Tower, with live migration smoke and browser runtime verification passing. -- Live Chrome/Playwright check against `http://192.0.2.10:1202`: Exports workspace opened, 6 handoff action cards present, no console warnings/errors, no horizontal page overflow on desktop or mobile. - -Open: -- None for this pass. - -Limitations: -- This is a frontend handoff usability pass only. It does not add export endpoints, change export persistence, introduce provider fetching or add AI/model behavior. - -Next recommended pass: -- Run a live browser smoke across Exports and Overview after deployment, then continue with report artifact readability if the exported HTML itself needs visual polish. - -## Sprint 65 Project report readability polish (2026-06-18) - -Changed: -- Reworked the lightweight `project_report_html` renderer into a self-contained handoff layout with hero, readiness pill, scorecards and sectioned report content. -- Added print-friendly CSS and scroll-safe table wrappers to the HTML artifact. -- Added source and CRS columns to the dataset inventory section. -- Preserved existing export type, endpoint behavior, download behavior and storage flow. -- Added `backend/tests/test_sprint65_project_report_polish.py`. -- Updated `backend/README.md`, `docs/TODO.md` and `CHANGELOG.md`. - -Tested: -- Red step: `python -m pytest backend/tests/test_sprint65_project_report_polish.py -q` failed on missing report shell, scorecards, print styles and readiness pill classes. -- `python -m pytest backend/tests/test_sprint65_project_report_polish.py backend/tests/test_sprint17_export_foundation.py -q` (`12 passed`) -- `python -m compileall backend/app` -- `cd frontend && npm run typecheck` -- `cd frontend && npm run build` -- `bash scripts/run_readiness_check.sh` (`235 passed`) -- `powershell -NoProfile -ExecutionPolicy Bypass -File scripts/deploy_tower.ps1` rebuilt and redeployed the Tower all-in-one container, with live migration smoke and browser runtime verification passing. -- Live report smoke through `http://192.0.2.10:1202`: seeded explicit demo workflow, created `project_report_html`, downloaded the HTML artifact and verified it in Chrome with 5 scorecards, 5 report sections, no console warnings/errors and no horizontal overflow on desktop or mobile. - -Open: -- None for this pass. - -Limitations: -- This remains a lightweight HTML handoff artifact. It does not add PDF generation, a report designer, new endpoints, live provider fetching or AI/model behavior. - -Next recommended pass: -- Continue with a full-workspace browser smoke and then refine any remaining dense panels found during populated-state review. - -## Sprint 66 Live workspace smoke polish (2026-06-19) - -Changed: -- Ran a live browser smoke against `http://192.0.2.10:1202` across Overview, Data, Map, QA/QC, AI Labs, Exports and System. -- Captured desktop and mobile screenshots under `artifacts/sprint66-live-workspace-smoke/`. -- Confirmed all primary workspaces load with no console warnings/errors and no page-level horizontal overflow. -- Tightened Export Center handoff card CSS so action cards and readiness cells wrap by available width instead of forcing cramped three/four-column layouts in the populated Exports workspace. -- Added `backend/tests/test_sprint66_live_workspace_smoke_polish.py`. - -Tested: -- Red step: `python -m pytest backend/tests/test_sprint66_live_workspace_smoke_polish.py -q` failed on missing width-aware export grid CSS and Sprint 66 log entry. -- Live desktop browser smoke: all seven primary workspaces opened, screenshots captured, no console warnings/errors, no horizontal page overflow. -- Live mobile browser smoke: all seven primary workspaces opened, screenshots captured, no console warnings/errors, no page-level horizontal overflow. The mobile primary nav intentionally remains a horizontal rail. -- Local post-fix browser check against `http://127.0.0.1:5175` with live API proxy: Exports handoff action cards wrap to 2 desktop columns and 1 mobile column, no console warnings/errors and no horizontal page overflow. -- `bash scripts/run_readiness_check.sh` (`237 passed`) -- `powershell -NoProfile -ExecutionPolicy Bypass -File scripts/deploy_tower.ps1` rebuilt and redeployed the Tower all-in-one container, with live migration smoke and browser runtime verification passing. -- Live post-deploy Exports check on `http://192.0.2.10:1202`: handoff action cards render as 2 usable columns at desktop width, no console warnings/errors and no horizontal overflow. - -Open: -- None for this pass. - -Limitations: -- This is a visual ergonomics hardening pass only. It does not add endpoints, migrations, provider fetching, AI/model behavior or new product capabilities. - -Next recommended pass: -- Continue with populated Map/Data interaction polish, especially making it easier to activate the demo vector layer from the map empty state. - -## Sprint 67 Map empty-state quick actions (2026-06-19) - -Changed: -- Added ready vector/GeoJSON dataset quick actions to the Map workspace empty state. -- Reused the existing `openDatasetInMap` frontend flow so quick actions load the same persisted dataset layer as the Data workspace button. -- Added width-aware `.map-empty-action-grid` styling for desktop and mobile. -- Added `backend/tests/test_sprint67_map_empty_state_quick_actions.py`. -- Updated `frontend/README.md`, `docs/TODO.md` and `CHANGELOG.md`. - -Tested: -- Red step: `python -m pytest backend/tests/test_sprint67_map_empty_state_quick_actions.py -q` failed on missing Map quick-action props, App wiring and CSS. -- `python -m pytest backend/tests/test_sprint67_map_empty_state_quick_actions.py backend/tests/test_sprint63_map_overlay_ergonomics.py backend/tests/test_sprint30_workbench_components.py -q` (`9 passed`) -- `cd frontend && npm run typecheck` -- `cd frontend && npm run build` -- Local Chrome/Playwright check against `http://127.0.0.1:5175` with live API proxy: Map empty state showed 2 ready dataset actions, clicking the first loaded `demo_predicted_buildings.geojson` as a 2-feature active layer, no console warnings/errors and no horizontal overflow. -- `bash scripts/run_readiness_check.sh` (`240 passed`) -- `powershell -NoProfile -ExecutionPolicy Bypass -File scripts/deploy_tower.ps1` rebuilt and redeployed the Tower all-in-one container, with live migration smoke and browser runtime verification passing. -- Live post-deploy Map quick-action check on `http://192.0.2.10:1202`: Map empty state showed 2 ready dataset actions, clicking the first loaded `demo_predicted_buildings.geojson` as a 2-feature active layer, no console warnings/errors and no horizontal overflow. - -Open: -- None for this pass. - -Limitations: -- This is a frontend interaction polish pass only. It does not add map layers, backend endpoints, migrations, provider fetching or geospatial processing. - -Next recommended pass: -- Continue with Data catalog density polish, especially making selected/reference/candidate dataset roles easier to scan in populated demo projects. - -## Sprint 68 Data catalog density polish (2026-06-19) - -Changed: -- Added a compact role summary to the Data catalog for Selected, Reference, Candidate and Source datasets. -- Added scan-friendly dataset card badges plus source, reference layer and CRS context. -- Treated non-reference vector/GeoJSON datasets as QA Candidate display roles in the frontend only, preserving persisted `dataset_role` values and API contracts. -- Added responsive role-summary and role-badge CSS. -- Added `backend/tests/test_sprint68_dataset_catalog_density.py`. -- Updated `frontend/README.md`, `docs/TODO.md` and `CHANGELOG.md`. - -Tested: -- Red step: `python -m pytest backend/tests/test_sprint68_dataset_catalog_density.py -q` failed on missing role summary, role badges and responsive CSS. -- `python -m pytest backend/tests/test_sprint68_dataset_catalog_density.py backend/tests/test_sprint67_map_empty_state_quick_actions.py backend/tests/test_sprint30_workbench_components.py -q` (`10 passed`) -- `cd frontend && npm run typecheck` -- `cd frontend && npm run build` -- Local browser check against `http://127.0.0.1:5175` with live API proxy: Data workspace showed Selected, Reference, Candidate and Source summary cards, with 1 Reference, 1 Candidate and 0 Source in the demo catalog; dataset badges rendered correctly on desktop and mobile, no console warnings/errors and no horizontal overflow. -- Screenshots captured under `artifacts/sprint68-dataset-catalog-density/`. -- `bash scripts/run_readiness_check.sh` (`243 passed`) -- `powershell -NoProfile -ExecutionPolicy Bypass -File scripts/deploy_tower.ps1` rebuilt and redeployed the Tower all-in-one container, with live migration smoke and browser runtime verification passing. -- Live post-deploy Data catalog check on `http://192.0.2.10:1202`: Data workspace showed Selected, Reference, Candidate and Source summary cards, candidate/reference badges rendered, no console warnings/errors and no horizontal overflow on desktop or mobile. - -Open: -- None for this pass. - -Limitations: -- This is a frontend density/readability pass only. It does not change dataset persistence, backend role validation, API contracts, migrations, provider fetching or AI/model behavior. - -Next recommended pass: -- Continue with Data workspace action polish, especially making QA/export affordances clearer once candidate and reference layers are present. - -## Sprint 69 Data catalog action polish (2026-06-19) - -Changed: -- Added role-aware recommended action hints to dataset cards. -- Reworked dataset card actions into compact two-line buttons for Inspect, Map, Export / QA and Metadata. -- Kept all existing Data workspace handlers and API calls unchanged. -- Added disabled-action explanation copy for unsupported export/QA and raster metadata refresh cases. -- Added responsive `.dataset-action-grid` and `.dataset-action-button` CSS. -- Added `backend/tests/test_sprint69_dataset_action_polish.py`. -- Updated `frontend/README.md`, `docs/TODO.md` and `CHANGELOG.md`. - -Tested: -- Red step: `python -m pytest backend/tests/test_sprint69_dataset_action_polish.py -q` failed on missing action hints, action grid and responsive styles. -- `python -m pytest backend/tests/test_sprint69_dataset_action_polish.py backend/tests/test_sprint68_dataset_catalog_density.py backend/tests/test_sprint29_dataset_components.py -q` (`9 passed`) -- `cd frontend && npm run typecheck` -- `cd frontend && npm run build` -- Local browser check against `http://127.0.0.1:5175` with live API proxy: Data workspace rendered 2 role-aware hints and 8 compact dataset actions across the demo candidate/reference datasets, no console warnings/errors and no horizontal overflow on desktop or mobile. -- Screenshots captured under `artifacts/sprint69-dataset-action-polish/`. -- `bash scripts/run_readiness_check.sh` (`246 passed`) -- `powershell -NoProfile -ExecutionPolicy Bypass -File scripts/deploy_tower.ps1` rebuilt and redeployed the Tower all-in-one container, with live migration smoke and browser runtime verification passing. -- Live post-deploy Data action check on `http://192.0.2.10:1202`: Data workspace rendered 2 role-aware hints and 8 compact dataset actions across the demo candidate/reference datasets, no console warnings/errors and no horizontal overflow on desktop or mobile. - -Open: -- None for this pass. - -Limitations: -- This is a frontend affordance/readability pass only. It does not add new workflows, change dataset persistence, change API contracts, add migrations, fetch providers or alter AI/model behavior. - -Next recommended pass: -- Continue with QA/QC workspace handoff polish, especially linking the existing candidate/reference dataset context more clearly to persisted QA results. - -## Sprint 70 QA/QC handoff polish (2026-06-19) - -Changed: -- Added candidate/reference handoff cards to the QA/QC results panel. -- Resolved persisted quality-check candidate/reference dataset IDs to loaded dataset names when available. -- Passed `candidateDatasets` and `referenceDatasets` from `App.tsx` into `QualityResultsPanel`. -- Tightened QA candidate context to non-reference vector/GeoJSON datasets while preserving persisted `dataset_role` values. -- Added responsive `.quality-handoff-grid`, `.quality-dataset-name` and `.quality-check-dataset-link` CSS. -- Added `backend/tests/test_sprint70_quality_handoff_polish.py`. -- Updated `frontend/README.md`, `docs/TODO.md` and `CHANGELOG.md`. - -Tested: -- Red step: `python -m pytest backend/tests/test_sprint70_quality_handoff_polish.py -q` failed on missing dataset context props, handoff markup, App wiring and styles. -- `python -m pytest backend/tests/test_sprint70_quality_handoff_polish.py backend/tests/test_sprint39_frontend_orchestration_hooks.py backend/tests/test_sprint51_quality_export_polish.py -q` (`15 passed`) -- `python -m pytest backend/tests/test_sprint70_quality_handoff_polish.py backend/tests/test_sprint51_quality_export_polish.py backend/tests/test_sprint30_workbench_components.py backend/tests/test_sprint27_frontend_workflow_hooks.py -q` (`14 passed`) -- `cd frontend && npm run typecheck` -- `cd frontend && npm run build` -- Local browser check against `http://127.0.0.1:5175` with live API proxy: QA/QC workspace showed 1 candidate layer, 1 reference layer, latest comparison names and named dataset links inside persisted quality-check cards, with no console warnings/errors and no horizontal overflow. -- Screenshots captured under `artifacts/sprint70-quality-handoff-polish/`. -- `bash scripts/run_readiness_check.sh` (`250 passed`) -- `powershell -NoProfile -ExecutionPolicy Bypass -File scripts/deploy_tower.ps1` rebuilt and redeployed the Tower all-in-one container, with live migration smoke and browser runtime verification passing. -- Live post-deploy QA/QC handoff check on `http://192.0.2.10:1202`: QA/QC workspace showed 1 candidate layer, 1 reference layer, latest comparison names and named dataset links inside persisted quality-check cards, with no console warnings/errors and no horizontal overflow on desktop or mobile. - -Open: -- None for this pass. - -Limitations: -- This is a frontend handoff/readability pass only. It does not change QA persistence, metric calculations, API contracts, migrations, provider fetching or AI/model behavior. - -Next recommended pass: -- Continue with QA/QC result card polish, especially making metric groups easier to scan in long-lived demo projects. - -## Sprint 71 QA/QC metric card polish (2026-06-19) - -Changed: -- Added core metric evidence cards to QA/QC result cards for precision, recall, F1, mean IoU, false positives and false negatives. -- Kept the raw persisted metric list visible below the promoted evidence cards. -- Added compact metric label/value formatting in `QualityResultsPanel`. -- Added responsive `.quality-metric-grid`, `.quality-metric-card` and `.quality-metric-card-critical` CSS. -- Added `backend/tests/test_sprint71_quality_metric_polish.py`. -- Updated `frontend/README.md`, `docs/TODO.md` and `CHANGELOG.md`. - -Tested: -- Red step: `python -m pytest backend/tests/test_sprint71_quality_metric_polish.py -q` failed on missing metric promotion helpers, markup and styles. -- `python -m pytest backend/tests/test_sprint71_quality_metric_polish.py backend/tests/test_sprint70_quality_handoff_polish.py backend/tests/test_sprint51_quality_export_polish.py backend/tests/test_sprint30_workbench_components.py -q` (`13 passed`) -- `cd frontend && npm run typecheck` -- `cd frontend && npm run build` -- Local browser check against `http://127.0.0.1:5175` with live API proxy: QA/QC workspace rendered 12 promoted metric cards across 2 persisted quality checks, retained 2 raw metric sections, no console warnings/errors and no horizontal overflow on desktop or mobile. -- Screenshots captured under `artifacts/sprint71-quality-metric-polish/`. -- `bash scripts/run_readiness_check.sh` (`253 passed`) -- `powershell -NoProfile -ExecutionPolicy Bypass -File scripts/deploy_tower.ps1` rebuilt and redeployed the Tower all-in-one container, with live migration smoke and browser runtime verification passing. -- Live post-deploy QA/QC metric check on `http://192.0.2.10:1202`: QA/QC workspace rendered 12 promoted metric cards across 2 persisted quality checks, retained 2 raw metric sections, no console warnings/errors and no body-level horizontal overflow on desktop or mobile. -- Live mobile screenshot captured at `artifacts/sprint71-quality-metric-polish/live-qa-metrics-mobile.png`. - -Open: -- None for this pass. - -Limitations: -- Frontend readability pass only; no QA calculation, persistence, API, migrations, provider or AI/model changes. - -Next recommended pass: -- Continue with QA/QC metric/result filtering or result-card density for long-lived demo projects. - -## Sprint 72 Mobile overflow hardening (2026-06-20) - -Changed: -- Clamped page-level horizontal overflow for `html`, `body` and the workbench shell. -- Kept mobile sidebar navigation and workspace shortcut chips as contained horizontal scroll regions with overscroll containment. -- Added min-width/max-width containment for the workbench layout, main area, inspector panel and card surfaces. -- Allowed long QA check IDs, dataset links and inspector values to wrap instead of widening result cards. -- Switched inspector tabs to a two-column layout on narrow screens. -- Added `backend/tests/test_sprint72_mobile_overflow_hardening.py`. -- Updated `frontend/README.md`, `docs/TODO.md` and `CHANGELOG.md`. - -Tested: -- Red step: `python -m pytest backend/tests/test_sprint72_mobile_overflow_hardening.py -q` failed on missing mobile overflow and identifier wrapping contracts. -- `python -m pytest backend/tests/test_sprint72_mobile_overflow_hardening.py backend/tests/test_sprint71_quality_metric_polish.py backend/tests/test_sprint62_frontend_visual_polish.py backend/tests/test_sprint30_workbench_components.py -q` (`11 passed`) -- `cd frontend && npm run typecheck` -- `cd frontend && npm run build` -- Local browser check against `http://127.0.0.1:5176` with live API proxy at a 390px viewport: QA/QC workspace rendered 2 quality cards and 12 metric cards; body, shell, inspector, inspector panel and inspector tabs stayed within viewport width; sidebar/workspace nav retained contained horizontal scrolling; no console warnings/errors. -- Screenshot captured under `artifacts/sprint72-mobile-overflow-hardening/`. -- `bash scripts/run_readiness_check.sh` (`255 passed`) -- `powershell -NoProfile -ExecutionPolicy Bypass -File scripts/deploy_tower.ps1` rebuilt and redeployed the Tower all-in-one container, with live migration smoke and browser runtime verification passing. -- Live post-deploy mobile check on `http://192.0.2.10:1202` at a 390px viewport: QA/QC workspace rendered 2 quality cards and 12 metric cards; body, shell, inspector, inspector panel and inspector tabs stayed within viewport width; sidebar/workspace nav retained contained horizontal scrolling; no console warnings/errors. -- Live screenshot captured at `artifacts/sprint72-mobile-overflow-hardening/live-mobile-qa.png`. - -Open: -- None for this pass. - -Limitations: -- Frontend CSS hardening only; no UI flow, API, persistence, migration, provider or AI/model changes. - -Next recommended pass: -- Continue with QA/QC result filtering/density for long-lived demo projects, or a broader mobile visual pass across Data and Map once the overflow baseline is stable. - -## Sprint 73 QA/QC result filtering (2026-06-20) - -Changed: -- Added client-side QA/QC result search across check id, type, status, candidate/reference dataset ids, analysis/job ids and resolved dataset names. -- Added status and check-type filters derived from the loaded quality-check list. -- Added latest-eight result density control with a show-all toggle. -- Added a no-match empty state and reset action for filtered result views. -- Reused the dense history control styling pattern while allowing the QA/QC controls to wrap inside narrower workspace columns. -- Added `backend/tests/test_sprint73_quality_result_filtering.py`. -- Updated `frontend/README.md`, `docs/TODO.md` and `CHANGELOG.md`. - -Tested: -- Red step: `python -m pytest backend/tests/test_sprint73_quality_result_filtering.py -q` failed on missing filter state, filtered list logic and styles. -- `python -m pytest backend/tests/test_sprint73_quality_result_filtering.py backend/tests/test_sprint72_mobile_overflow_hardening.py backend/tests/test_sprint71_quality_metric_polish.py backend/tests/test_sprint70_quality_handoff_polish.py backend/tests/test_sprint51_quality_export_polish.py -q` (`13 passed`) -- `cd frontend && npm run typecheck` -- `cd frontend && npm run build` -- Local browser check against `http://127.0.0.1:5177` with live API proxy: QA/QC filters rendered against 2 persisted demo checks; search/status conflict showed the no-match state; reset restored 2 checks and 12 metric cards; no console warnings/errors and no body-level overflow. -- Local mobile browser check at a 390px viewport: filter controls stayed within viewport width, with 2 checks and 12 metric cards visible. -- Screenshots captured under `artifacts/sprint73-quality-result-filtering/`. -- `bash scripts/run_readiness_check.sh` (`257 passed`) -- `powershell -NoProfile -ExecutionPolicy Bypass -File scripts/deploy_tower.ps1` rebuilt and redeployed the Tower all-in-one container, with live migration smoke and browser runtime verification passing. -- Live post-deploy QA/QC filtering check on `http://192.0.2.10:1202`: search/status conflict showed the no-match state; reset restored 2 checks and 12 metric cards; no console warnings/errors and no body-level overflow. -- Live mobile check at a 390px viewport: QA/QC filter controls stayed within viewport width, with 2 checks and 12 metric cards visible. -- Live screenshots captured at `artifacts/sprint73-quality-result-filtering/live-qa-filtering.png` and `artifacts/sprint73-quality-result-filtering/live-qa-filtering-mobile.png`. - -Open: -- None for this pass. - -Limitations: -- Frontend filtering/density pass only; filtering is client-side over already-loaded persisted checks and does not change API pagination, persistence, QA calculations, migrations, provider behavior or AI/model behavior. - -Next recommended pass: -- Continue with Data/Map mobile visual polish, especially dataset upload/action forms and map toolbar density on narrow screens. - -## Sprint 74 Data/Map mobile visual polish (2026-06-20) - -Changed: -- Added mobile-density CSS for Data workspace upload forms, file input sizing and dataset action grids. -- Kept the desktop dataset action grid width contract intact while adding compact mobile tracks. -- Added touch/width containment for map toolbar controls, range sliders and empty-map quick actions. -- Reduced mobile map container height to keep controls and map visible together on narrow screens. -- Added `backend/tests/test_sprint74_data_map_mobile_polish.py`. -- Updated `frontend/README.md`, `docs/TODO.md` and `CHANGELOG.md`. - -Tested: -- Red step: `python -m pytest backend/tests/test_sprint74_data_map_mobile_polish.py -q` failed on missing mobile Data/Map CSS contracts. -- `python -m pytest backend/tests/test_sprint74_data_map_mobile_polish.py backend/tests/test_sprint72_mobile_overflow_hardening.py backend/tests/test_sprint69_dataset_action_polish.py backend/tests/test_sprint68_dataset_catalog_density.py backend/tests/test_sprint67_map_empty_state_quick_actions.py backend/tests/test_sprint63_map_overlay_ergonomics.py backend/tests/test_sprint50_workspace_usability_polish.py backend/tests/test_sprint30_workbench_components.py -q` (`21 passed`) -- `cd frontend && npm run typecheck` -- `cd frontend && npm run build` -- Local browser check against `http://127.0.0.1:5178` with live API proxy at a 390px viewport: Data upload form, file input and 8 dataset action buttons stayed within the viewport with no body-level horizontal overflow; Map toolbar, 2 layer controls, range sliders and empty-map quick actions also stayed within the viewport. -- Screenshots captured under `artifacts/sprint74-data-map-mobile-polish/`. -- `bash scripts/run_readiness_check.sh` (`259 passed`) -- `powershell -NoProfile -ExecutionPolicy Bypass -File scripts/deploy_tower.ps1` rebuilt and redeployed the Tower all-in-one container on port 1202, with live migration smoke and browser runtime verification passing. -- Live post-deploy browser check on `http://192.0.2.10:1202` at a 390px viewport: Data upload form, file input and 8 dataset action buttons stayed within the viewport; Map toolbar, 2 layer controls, range sliders and empty-map quick actions stayed within the viewport; no body-level horizontal overflow was detected. -- Live screenshots captured at `artifacts/sprint74-data-map-mobile-polish/live-data-mobile.png` and `artifacts/sprint74-data-map-mobile-polish/live-map-mobile.png`. - -Open: -- None for this pass. - -Limitations: -- Frontend CSS polish only; no Data/Map workflow, API, persistence, migration, provider or AI/model changes. - -Next recommended pass: -- Continue with AI Labs mobile/density polish, especially detection and segmentation forms/tables. - -## Sprint 75 AI Labs mobile visual polish (2026-06-20) - -Changed: -- Added mobile-density CSS for Detection and Segmentation Lab model cards, run forms and result summaries. -- Added overflow wrapping for long model ids, source tile paths, mask paths and QA summary values. -- Kept AI result tables scroll-contained while reducing their mobile minimum width. -- Added `backend/tests/test_sprint75_ai_labs_mobile_polish.py`. -- Updated `frontend/README.md`, `docs/TODO.md` and `CHANGELOG.md`. - -Tested: -- Red step: `python -m pytest backend/tests/test_sprint75_ai_labs_mobile_polish.py -q` failed on missing AI Labs mobile CSS contracts. -- `python -m pytest backend/tests/test_sprint75_ai_labs_mobile_polish.py backend/tests/test_sprint74_data_map_mobile_polish.py backend/tests/test_sprint72_mobile_overflow_hardening.py backend/tests/test_sprint62_frontend_visual_polish.py backend/tests/test_sprint30_workbench_components.py backend/tests/test_sprint8c_detection_visualization_qa.py backend/tests/test_sprint9_segmentation_foundation.py -q` (`30 passed`) -- `cd frontend && npm run typecheck` -- `cd frontend && npm run build` -- Local browser check against `http://127.0.0.1:5179` with live API proxy at a 390px viewport: AI Labs rendered 2 panels, 7 model cards, 6 lab blocks and 4 lab forms with no body-level horizontal overflow. -- Screenshot captured under `artifacts/sprint75-ai-labs-mobile-polish/`. -- `bash scripts/run_readiness_check.sh` (`261 passed`) -- `powershell -NoProfile -ExecutionPolicy Bypass -File scripts/deploy_tower.ps1` rebuilt and redeployed the Tower all-in-one container on port 1202, with live migration smoke and browser runtime verification passing. -- Live post-deploy browser check on `http://192.0.2.10:1202` at a 390px viewport: AI Labs rendered 2 panels, 7 model cards, 6 lab blocks and 4 lab forms with no body-level horizontal overflow. -- Live screenshot captured at `artifacts/sprint75-ai-labs-mobile-polish/live-ai-labs-mobile.png`. - -Open: -- None for this pass. - -Limitations: -- Frontend CSS polish only; no Detection/Segmentation workflow, API, persistence, migration, provider or AI/model changes. - -Next recommended pass: -- Continue with Export/System mobile-density polish, especially export action cards and provider capability lists. - -## Sprint 76 Export/System mobile visual polish (2026-06-20) - -Changed: -- Added scan-friendly Provider Capabilities cards with structured provider header, status badge, authority/configuration/geometry/query mode fields and layer chips. -- Added mobile-density CSS for provider cards, export action cards, export history controls and export card headers. -- Added overflow wrapping for long provider limitations, attribution/license notes, export ids and artifact paths. -- Added `backend/tests/test_sprint76_export_system_mobile_polish.py`. -- Updated `frontend/README.md`, `docs/TODO.md` and `CHANGELOG.md`. - -Tested: -- Red step: `python -m pytest backend/tests/test_sprint76_export_system_mobile_polish.py -q` failed on missing Export/System mobile CSS and provider markup contracts. -- `python -m pytest backend/tests/test_sprint76_export_system_mobile_polish.py backend/tests/test_sprint75_ai_labs_mobile_polish.py backend/tests/test_sprint74_data_map_mobile_polish.py backend/tests/test_sprint31_unraid_template.py backend/tests/test_sprint64_export_handoff_polish.py backend/tests/test_sprint7b_provider_registry.py backend/tests/test_sprint30_workbench_components.py -q` (`27 passed`) -- `cd frontend && npm run typecheck` -- `cd frontend && npm run build` -- `bash scripts/run_readiness_check.sh` (`263 passed`) -- `powershell -NoProfile -ExecutionPolicy Bypass -File scripts/deploy_tower.ps1` rebuilt and redeployed the Tower all-in-one container on port 1202, with live migration smoke and browser runtime verification passing. - -Open: -- None for this pass. - -Limitations: -- Frontend presentation polish only; no export workflow, provider API, persistence, migration, provider fetching or AI/model changes. - -Next recommended pass: -- Continue with right-side inspector mobile polish, especially long dataset/vector/raster metadata and action groups. - -## Sprint 77 Inspector mobile visual polish (2026-06-20) - -Changed: -- Added compact inspector action button grids and mobile-safe wrapping for long inspector values. -- Added scroll/wrap containment for dataset detail text, job JSON and loaded feature metadata. -- Added `dataset-tool-panel` and `dataset-tool-group` classes to raster/vector operation controls. -- Added CSS containment for raster/vector tool labels, inputs, selects and buttons inside the inspector. -- Added `backend/tests/test_sprint77_inspector_mobile_polish.py`. -- Updated `frontend/README.md`, `docs/TODO.md` and `CHANGELOG.md`. - -Tested: -- Red step: `python -m pytest backend/tests/test_sprint77_inspector_mobile_polish.py -q` failed on missing inspector mobile CSS and dataset tool markup contracts. -- `python -m pytest backend/tests/test_sprint77_inspector_mobile_polish.py backend/tests/test_sprint76_export_system_mobile_polish.py backend/tests/test_sprint75_ai_labs_mobile_polish.py backend/tests/test_sprint72_mobile_overflow_hardening.py backend/tests/test_sprint52_workbench_inspector_tabs.py backend/tests/test_sprint30_workbench_components.py backend/tests/test_sprint29_dataset_components.py -q` (`18 passed`) -- `cd frontend && npm run typecheck` -- `cd frontend && npm run build` -- `bash scripts/run_readiness_check.sh` (`265 passed`) -- `powershell -NoProfile -ExecutionPolicy Bypass -File scripts/deploy_tower.ps1` rebuilt and redeployed the Tower all-in-one container on port 1202, with live migration smoke and browser runtime verification passing. - -Open: -- None for this pass. - -Limitations: -- Frontend presentation polish only; no dataset workflow, raster/vector operation behavior, API, persistence, migration, provider fetching or AI/model changes. - -Next recommended pass: -- Continue with report/export preview readability polish, especially large JSON/HTML handoff artifacts. - -## Sprint 78 Export preview readability polish (2026-06-20) - -Changed: -- Added preview summary cards for JSON/GeoJSON export payload root type, root key count and rendered preview size. -- Added a scroll-contained export preview JSON shell and toolbar around the existing stored payload preview. -- Added wrapping for long JSON keys/values inside the preview body. -- Added `backend/tests/test_sprint78_export_preview_readability.py`. -- Updated `frontend/README.md`, `docs/TODO.md` and `CHANGELOG.md`. - -Tested: -- Red step: `python -m pytest backend/tests/test_sprint78_export_preview_readability.py -q` failed on missing preview summary/shell CSS and markup contracts. -- `python -m pytest backend/tests/test_sprint78_export_preview_readability.py backend/tests/test_sprint77_inspector_mobile_polish.py backend/tests/test_sprint76_export_system_mobile_polish.py backend/tests/test_sprint51_quality_export_polish.py backend/tests/test_sprint64_export_handoff_polish.py backend/tests/test_sprint17_export_foundation.py -q` (`20 passed`) -- `cd frontend && npm run typecheck` -- `cd frontend && npm run build` -- `bash scripts/run_readiness_check.sh` (`267 passed`; frontend typecheck/build passed; Alembic single head `202606120900`) -- `powershell -NoProfile -ExecutionPolicy Bypass -File scripts/deploy_tower.ps1` rebuilt and redeployed the Tower all-in-one container on port 1202, then passed live migration smoke and browser runtime verification. - -Open: -- None for this pass. - -Limitations: -- Frontend presentation polish only; no export content, export API, artifact storage, migration, provider fetching or AI/model changes. - -Next recommended pass: -- Continue with accessibility/keyboard focus polish across primary workbench controls. - -## Sprint 79 Accessibility focus polish (2026-06-20) - -Changed: -- Added a shared visible keyboard focus contract for primary buttons, workspace navigation, command chips, inspector tabs and dataset action buttons. -- Added explicit ARIA labels for workspace sidebar navigation, workspace command chips and overview quick actions. -- Bound inspector tabs to active tab panels with `aria-controls`, tab ids, `tabpanel` role and `aria-labelledby`. -- Added `backend/tests/test_sprint79_accessibility_focus_polish.py`. -- Updated `frontend/README.md`, `docs/TODO.md` and `CHANGELOG.md`. - -Tested: -- Red step: `python -m pytest backend/tests/test_sprint79_accessibility_focus_polish.py -q` failed on missing focus-visible CSS, navigation labels and inspector tab/panel bindings. -- `python -m pytest backend/tests/test_sprint79_accessibility_focus_polish.py backend/tests/test_sprint77_inspector_mobile_polish.py backend/tests/test_sprint53_selection_ergonomics.py backend/tests/test_sprint49_workbench_shell_refactor.py backend/tests/test_sprint47_workbench_interaction_smoke.py -q` (`15 passed`) -- `cd frontend && npm run typecheck` -- `cd frontend && npm run build` -- `bash scripts/run_readiness_check.sh` (`270 passed`; frontend typecheck/build passed; Alembic single head `202606120900`) -- `powershell -NoProfile -ExecutionPolicy Bypass -File scripts/deploy_tower.ps1` rebuilt and redeployed the Tower all-in-one container on port 1202, then passed live migration smoke and browser runtime verification. - -Open: -- None for this pass. - -Limitations: -- Frontend accessibility/presentation polish only; no workflow behavior, API contract, persistence, migration, provider fetching or AI/model changes. - -Next recommended pass: -- Continue with form-level validation/readability polish for dense raster/vector operation panels. - -## Sprint 80 Operation form readability polish (2026-06-20) - -Changed: -- Added structured headings, helper text, field wrappers, responsive field grids and action rows to raster operation controls. -- Added equivalent readability structure to vector clip, buffer and intersect controls. -- Added inline dataset tool error styling for raster clip/tile validation messages. -- Added `backend/tests/test_sprint80_operation_form_readability.py`. -- Updated `frontend/README.md`, `docs/TODO.md` and `CHANGELOG.md`. - -Tested: -- Red step: `python -m pytest backend/tests/test_sprint80_operation_form_readability.py -q` failed on missing form readability CSS and markup contracts. -- `python -m pytest backend/tests/test_sprint80_operation_form_readability.py -q` (`3 passed`) -- `python -m pytest backend/tests/test_sprint80_operation_form_readability.py backend/tests/test_sprint77_inspector_mobile_polish.py backend/tests/test_sprint29_dataset_components.py backend/tests/test_sprint28_dataset_workflow_hook.py backend/tests/test_vector_operations_service.py backend/tests/test_raster_operations_service.py -q` (`37 passed`) -- `cd frontend && npm run typecheck` -- `cd frontend && npm run build` -- `bash scripts/run_readiness_check.sh` (`273 passed`; frontend typecheck/build passed; Alembic single head `202606120900`) -- `powershell -NoProfile -ExecutionPolicy Bypass -File scripts/deploy_tower.ps1` rebuilt and redeployed the Tower all-in-one container on port 1202, then passed live migration smoke and browser runtime verification. - -Open: -- None for this pass. - -Limitations: -- Frontend readability/presentation polish only; no raster/vector operation behavior, API contract, persistence, migration, provider fetching or AI/model changes. - -Next recommended pass: -- Continue with compact empty/error-state polish across QA, exports and AI lab result panels. - -## Sprint 81 Result state consistency polish (2026-06-20) - -Changed: -- Added shared `result-state` CSS variants for loading, error, empty and ready states. -- Applied result-state blocks to QA/QC error/empty/filter-empty states. -- Applied result-state blocks to export loading, error and empty/filter-empty states. -- Applied result-state blocks to Detection and Segmentation model loading/errors, empty registries, result counts and QA/run errors. -- Added `backend/tests/test_sprint81_result_state_polish.py`. -- Updated `frontend/README.md`, `docs/TODO.md` and `CHANGELOG.md`. - -Tested: -- Red step: `python -m pytest backend/tests/test_sprint81_result_state_polish.py -q` failed on missing result-state CSS and panel markup contracts. -- `python -m pytest backend/tests/test_sprint81_result_state_polish.py -q` (`3 passed`) -- `python -m pytest backend/tests/test_sprint81_result_state_polish.py backend/tests/test_sprint80_operation_form_readability.py backend/tests/test_sprint75_ai_labs_mobile_polish.py backend/tests/test_sprint76_export_system_mobile_polish.py backend/tests/test_sprint73_quality_result_filtering.py backend/tests/test_sprint70_quality_handoff_polish.py backend/tests/test_sprint8c_detection_visualization_qa.py backend/tests/test_sprint9_segmentation_foundation.py -q` (`34 passed`) -- `cd frontend && npm run typecheck` -- `cd frontend && npm run build` -- `bash scripts/run_readiness_check.sh` (`276 passed`; frontend typecheck/build passed; Alembic single head `202606120900`) -- `powershell -NoProfile -ExecutionPolicy Bypass -File scripts/deploy_tower.ps1` rebuilt and redeployed the Tower all-in-one container on port 1202, then passed live migration smoke and browser runtime verification. - -Open: -- None for this pass. - -Limitations: -- Frontend presentation/state polish only; no workflow behavior, API contract, persistence, migration, provider fetching or AI/model changes. - -Next recommended pass: -- Continue with visual density review for topbar/sidebar/responsive shell after another live browser pass. - -## Sprint 82 Shell density polish (2026-06-20) - -Changed: -- Added a keyboard skip link that targets the active workspace main region. -- Added an explicit `Primary workspaces` label to the sidebar navigation and a focusable `workspace-main` target. -- Tightened narrow-screen topbar, context chip, sidebar nav and workspace shortcut density while keeping intentional horizontal rails scroll-safe. -- Added `backend/tests/test_sprint82_shell_density_polish.py`. -- Updated `frontend/README.md`, `docs/TODO.md` and `CHANGELOG.md`. - -Tested: -- Live browser pre-check against `http://192.0.2.10:1202` showed no console errors, no horizontal document overflow and a too-tall narrow viewport topbar/context stack. -- Red step: `python -m pytest backend/tests/test_sprint82_shell_density_polish.py -q` failed on missing skip-link, main focus target and compact mobile shell CSS contracts. -- `python -m pytest backend/tests/test_sprint82_shell_density_polish.py -q` (`3 passed`) -- `python -m pytest backend/tests/test_sprint82_shell_density_polish.py backend/tests/test_sprint79_accessibility_focus_polish.py backend/tests/test_sprint72_mobile_overflow_hardening.py backend/tests/test_sprint49_workbench_shell_refactor.py backend/tests/test_sprint47_workbench_interaction_smoke.py -q` (`13 passed`) -- `cd frontend && npm run typecheck` -- `cd frontend && npm run build` -- `bash scripts/run_readiness_check.sh` (`279 passed`; frontend typecheck/build passed; Alembic single head `202606120900`) -- Live post-deploy browser check found a narrow-screen cascade override that made `.context-bar` one-column again; tightened the regression test and kept the context rail scrollable through the smallest breakpoint. -- Re-ran `python -m pytest backend/tests/test_sprint82_shell_density_polish.py -q`, `cd frontend && npm run typecheck`, `cd frontend && npm run build` and `bash scripts/run_readiness_check.sh` (`279 passed`) after that fix. -- `powershell -NoProfile -ExecutionPolicy Bypass -File scripts/deploy_tower.ps1` rebuilt and redeployed the Tower all-in-one container on port 1202, then passed live migration smoke and browser runtime verification. -- Final live browser check against `http://192.0.2.10:1202` passed on desktop and mobile viewports: no console warnings/errors, no horizontal document overflow, skip link/main target present, `Primary workspaces` nav label present and mobile context bar stayed compact at 64px tall. - -Open: -- None for this pass. - -Limitations: -- Frontend shell presentation/accessibility polish only; no workflow behavior, API contract, persistence, migration, provider fetching or AI/model changes. - -Next recommended pass: -- Continue with a live visual review of dense workspace panel hierarchy after the shell density changes are deployed. - -## Sprint 83 Workspace panel hierarchy polish (2026-06-20) - -Changed: -- Made the Overview readiness strip visually calmer with a compact section surface and tighter status tiles. -- Added explicit `overview-action-copy`, `overview-quick-actions` and `quick-action-button` regions to the recommended-action block. -- Restyled the recommended flow block as a lighter accent callout so it no longer competes visually with the readiness strip. -- Added `backend/tests/test_sprint83_workspace_panel_hierarchy.py`. -- Updated `frontend/README.md`, `docs/TODO.md` and `CHANGELOG.md`. - -Tested: -- Live browser pre-check against `http://192.0.2.10:1202` showed no console errors or horizontal overflow, but the first workspace viewport still had several equally weighted white cards. -- Red step: `python -m pytest backend/tests/test_sprint83_workspace_panel_hierarchy.py -q` failed on missing Overview hierarchy regions and compact section-surface CSS contracts. -- `python -m pytest backend/tests/test_sprint83_workspace_panel_hierarchy.py -q` (`3 passed`) -- `python -m pytest backend/tests/test_sprint83_workspace_panel_hierarchy.py backend/tests/test_sprint82_shell_density_polish.py backend/tests/test_sprint62_frontend_visual_polish.py backend/tests/test_sprint50_workspace_usability_polish.py backend/tests/test_sprint22_workbench_status_strip.py backend/tests/test_sprint47_workbench_interaction_smoke.py -q` (`15 passed`) -- `cd frontend && npm run typecheck` -- `cd frontend && npm run build` -- `bash scripts/run_readiness_check.sh` (`282 passed`; frontend typecheck/build passed; Alembic single head `202606120900`) -- `powershell -NoProfile -ExecutionPolicy Bypass -File scripts/deploy_tower.ps1` rebuilt and redeployed the Tower all-in-one container on port 1202, then passed live migration smoke and browser runtime verification. -- Final live browser check against `http://192.0.2.10:1202` passed on desktop and mobile viewports: no console warnings/errors, no horizontal document overflow, Overview hierarchy regions present and four recommended-action buttons rendered. - -Open: -- None for this pass. - -Limitations: -- Frontend Overview presentation hierarchy only; no workflow behavior, API contract, persistence, migration, provider fetching or AI/model changes. - -Next recommended pass: -- Continue with Data workspace panel hierarchy and selected-item density after this pass is deployed and visually checked. - -## Sprint 84 Data workspace density polish (2026-06-20) - -Changed: -- Added selected-summary regions to Project, AOI and Dataset panels so the active data context appears before creation/upload forms. -- Split Project and AOI panels into `data-panel-form-block` and `data-panel-list-block` regions. -- Split Dataset catalog into selected dataset, upload source data and available dataset regions. -- Restyled dataset upload as an embedded source-data block while preserving the existing upload flow. -- Added `backend/tests/test_sprint84_data_workspace_density.py`. -- Updated `frontend/README.md`, `docs/TODO.md` and `CHANGELOG.md`. - -Tested: -- Live browser pre-check against `http://192.0.2.10:1202` showed Data workspace had no console errors or horizontal overflow, but the first Data viewport was still form-first and visually heavy. -- Red step: `python -m pytest backend/tests/test_sprint84_data_workspace_density.py -q` failed on missing selected-summary and named form/list/catalog regions. -- `python -m pytest backend/tests/test_sprint84_data_workspace_density.py -q` (`3 passed`) -- `python -m pytest backend/tests/test_sprint84_data_workspace_density.py backend/tests/test_sprint83_workspace_panel_hierarchy.py backend/tests/test_sprint50_workspace_usability_polish.py backend/tests/test_sprint29_dataset_components.py backend/tests/test_sprint68_dataset_catalog_density.py backend/tests/test_sprint69_dataset_action_polish.py backend/tests/test_sprint47_workbench_interaction_smoke.py -q` (`20 passed`) -- `cd frontend && npm run typecheck` -- `cd frontend && npm run build` -- `bash scripts/run_readiness_check.sh` (`285 passed`; frontend typecheck/build passed; Alembic single head `202606120900`) -- `powershell -NoProfile -ExecutionPolicy Bypass -File scripts/deploy_tower.ps1` rebuilt and redeployed the Tower all-in-one container on port 1202, then passed live migration smoke and browser runtime verification. -- Final live browser DOM/console check against `http://192.0.2.10:1202` passed on desktop and mobile viewports: Data workspace active, no console warnings/errors, no horizontal document overflow, three selected-summary regions, three form blocks and three list/catalog blocks rendered. - -Open: -- None for this pass. - -Limitations: -- Frontend Data workspace presentation hierarchy only; no upload behavior, API contract, persistence, migration, provider fetching or AI/model changes. - -Next recommended pass: -- Continue with Map workspace panel hierarchy and layer-control density after this pass is deployed and visually checked. - -## Sprint 85 Map workspace density polish (2026-06-20) - -Changed: -- Added a compact Map workspace context summary for selected AOI, active layer and rendered feature state. -- Wrapped existing layer controls and provenance in a dedicated `map-control-surface`. -- Wrapped the existing MapLibre component in a `map-frame-surface` and the selected-feature inspector in a `map-inspection-surface`. -- Added `backend/tests/test_sprint85_map_workspace_density.py`. -- Updated `frontend/README.md`, `docs/TODO.md` and `CHANGELOG.md`. - -Tested: -- Live browser pre-check against `http://192.0.2.10:1202` showed Map workspace had no console errors or horizontal overflow, but controls, provenance, map frame and inspector still read as a loose vertical stack. -- Red step: `python -m pytest backend/tests/test_sprint85_map_workspace_density.py -q` failed on missing Map workspace surface and context-summary contracts. -- `python -m pytest backend/tests/test_sprint85_map_workspace_density.py -q` (`3 passed`) -- `python -m pytest backend/tests/test_sprint85_map_workspace_density.py backend/tests/test_sprint63_map_overlay_ergonomics.py backend/tests/test_sprint67_map_empty_state_quick_actions.py backend/tests/test_sprint74_data_map_mobile_polish.py backend/tests/test_sprint47_workbench_interaction_smoke.py -q` (`13 passed`) -- `cd frontend && npm run typecheck` -- `cd frontend && npm run build` -- Live browser post-deploy check showed desktop Map workspace was structured and overflow-free, but the mobile breakpoint still stacked controls too tall above the map. -- Red step: `python -m pytest backend/tests/test_sprint85_map_workspace_density.py -q` then failed on missing compact mobile Map workspace breakpoint contracts. -- `python -m pytest backend/tests/test_sprint85_map_workspace_density.py -q` (`4 passed`) -- `cd frontend && npm run typecheck` -- `cd frontend && npm run build` -- `bash scripts/run_readiness_check.sh` (`289 passed`; frontend typecheck/build passed; Alembic single head `202606120900`) -- `powershell -NoProfile -ExecutionPolicy Bypass -File scripts/deploy_tower.ps1` rebuilt and redeployed the Tower all-in-one container on port 1202, then passed live migration smoke and browser runtime verification. -- Final live browser check against `http://192.0.2.10:1202` passed on desktop and mobile viewports: no console warnings/errors, no horizontal document overflow, three Map context summary cards, two layer control cards, separated control/map/inspector surfaces and mobile control preamble reduced after the compact breakpoint correction. - -Open: -- None for this pass. - -Limitations: -- Frontend Map workspace presentation hierarchy only; no overlay behavior, API contract, persistence, migration, provider fetching or AI/model changes. - -Next recommended pass: -- Continue with QA/QC workspace result hierarchy and filter density after this pass is deployed and visually checked. - -## Sprint 86 QA/QC workspace density polish (2026-06-20) - -Changed: -- Wrapped QA/QC summary metrics in `quality-summary-surface`. -- Wrapped candidate/reference/latest comparison context in `quality-evidence-surface`. -- Wrapped refresh, result states, filters and list limit controls in `quality-control-surface`. -- Wrapped persisted quality check cards in `quality-history-surface`. -- Added compact mobile CSS contracts for QA/QC summary, handoff, filter, score, metric and raw metric grids. -- Added `backend/tests/test_sprint86_quality_workspace_density.py`. -- Updated `frontend/README.md`, `docs/TODO.md` and `CHANGELOG.md`. - -Tested: -- Live browser pre-check against `http://192.0.2.10:1202` showed QA/QC workspace had no console errors or horizontal overflow, but summary, handoff, filters and history were still visually stacked at equal weight. Mobile measured summary at 210px, handoff at 295px and filters at 278px before the result history. -- Red step: `python -m pytest backend/tests/test_sprint86_quality_workspace_density.py -q` failed on missing QA/QC surface and density CSS contracts. -- `python -m pytest backend/tests/test_sprint86_quality_workspace_density.py -q` (`3 passed`) -- `python -m pytest backend/tests/test_sprint86_quality_workspace_density.py backend/tests/test_sprint70_quality_handoff_polish.py backend/tests/test_sprint71_quality_metric_polish.py backend/tests/test_sprint73_quality_result_filtering.py backend/tests/test_sprint81_result_state_polish.py backend/tests/test_sprint47_workbench_interaction_smoke.py -q` (`18 passed`) -- `cd frontend && npm run typecheck` -- `cd frontend && npm run build` -- First full readiness run caught a compatibility regression in `backend/tests/test_sprint51_quality_export_polish.py`: the root `quality-results-panel` class was no longer exact. Kept the old root class and moved the new shell into a wrapper. -- `python -m pytest backend/tests/test_sprint51_quality_export_polish.py backend/tests/test_sprint86_quality_workspace_density.py backend/tests/test_sprint70_quality_handoff_polish.py backend/tests/test_sprint73_quality_result_filtering.py -q` (`11 passed`) -- `cd frontend && npm run typecheck` -- `cd frontend && npm run build` -- `bash scripts/run_readiness_check.sh` (`292 passed`; frontend typecheck/build passed; Alembic single head `202606120900`) -- `powershell -NoProfile -ExecutionPolicy Bypass -File scripts/deploy_tower.ps1` rebuilt and redeployed the Tower all-in-one container on port 1202, then passed live migration smoke and browser runtime verification. -- Final live browser check against `http://192.0.2.10:1202` passed on desktop and mobile viewports: no console warnings/errors, no horizontal document overflow, QA/QC shell/surfaces present and two persisted quality check cards rendered. - -Open: -- None for this pass. - -Limitations: -- Frontend QA/QC workspace presentation hierarchy only; no quality-check behavior, API contract, persistence, migration, provider fetching or AI/model changes. - -Next recommended pass: -- Continue with Change Detection panel hierarchy and analysis workspace balance after this pass is deployed and visually checked. - -## Sprint 87 Change Detection density polish (2026-06-20) - -Changed: -- Wrapped Change Detection input controls in `change-detection-input-surface`. -- Replaced loose error/empty text with shared `result-state` cards inside `change-detection-state-stack`. -- Wrapped result metrics in `change-detection-result-surface`. -- Wrapped warning output in `change-detection-warning-surface`. -- Added compact responsive CSS contracts for Change Detection form and summary grids. -- Added `backend/tests/test_sprint87_change_detection_density.py`. -- Updated `frontend/README.md`, `docs/TODO.md` and `CHANGELOG.md`. - -Tested: -- Live browser pre-check attempt against `http://192.0.2.10:1202` hit a transient browser automation click timeout on the QA/QC workspace nav; source review showed Change Detection was still the older header/form/summary stack. -- Red step: `python -m pytest backend/tests/test_sprint87_change_detection_density.py -q` failed on missing Change Detection surface and density CSS contracts. -- `python -m pytest backend/tests/test_sprint87_change_detection_density.py backend/tests/test_sprint18_change_detection.py backend/tests/test_sprint39_frontend_orchestration_hooks.py backend/tests/test_sprint86_quality_workspace_density.py backend/tests/test_sprint47_workbench_interaction_smoke.py -q` (`20 passed`) -- `cd frontend && npm run typecheck` -- `cd frontend && npm run build` -- `bash scripts/run_readiness_check.sh` (`295 passed`; frontend typecheck/build passed; Alembic head `202606120900`; live smoke syntax passed) -- Tower deploy via `scripts/deploy_tower.ps1` rebuilt and restarted the all-in-one container on `http://192.0.2.10:1202`. -- Tower deploy live migration smoke passed with PostGIS `3.6 USE_GEOS=1 USE_PROJ=1 USE_STATS=1` and required runtime schema objects present. -- Browser runtime verification passed for frontend, proxied API and icon. -- Direct Chrome live UI check passed on desktop `1440x1000` and mobile `390x844`: Change Detection shell/input surface rendered, no horizontal overflow and no console warnings/errors. - -Open: -- None known after full readiness, Tower deploy and live browser validation. - -Limitations: -- Frontend Change Detection presentation hierarchy only; no change-detection behavior, API contract, persistence, migration, provider fetching or AI/model changes. - -Next recommended pass: -- Continue with AI Labs run-form hierarchy and detection/segmentation result density after this pass is deployed and visually checked. - -## Sprint 88 AI Labs density polish (2026-06-20) - -Changed: -- Wrapped Detection Lab and Segmentation Lab in shared `ai-lab-shell` workspace shells. -- Grouped model registry states into `ai-lab-model-surface` with a shared `ai-lab-state-stack`. -- Grouped run controls into `ai-lab-run-surface`. -- Grouped persisted detection/segmentation result loading and tables into `ai-lab-results-surface`. -- Grouped QA controls and metric summaries into `ai-lab-qa-surface`. -- Added shared AI Lab CSS contracts for compact model grids, form grids and summary grids. -- Added `backend/tests/test_sprint88_ai_lab_density.py`. -- Updated `frontend/README.md`, `docs/TODO.md` and `CHANGELOG.md`. - -Tested: -- Red step: `python -m pytest backend/tests/test_sprint88_ai_lab_density.py -q` failed on missing AI Lab shells/surfaces and CSS contracts. -- `python -m pytest backend/tests/test_sprint88_ai_lab_density.py backend/tests/test_sprint8c_detection_visualization_qa.py backend/tests/test_sprint9_segmentation_foundation.py backend/tests/test_sprint39_frontend_orchestration_hooks.py backend/tests/test_sprint47_workbench_interaction_smoke.py -q` (`34 passed`) -- `cd frontend && npm run typecheck` -- `cd frontend && npm run build` -- Local browser UI check against `http://127.0.0.1:5174` passed on desktop and mobile: Detection/Segmentation shells and model/run/result/QA surfaces rendered, no horizontal overflow and no console warnings/errors. The local-only screenshot showed expected API 500 states because only the frontend Vite server was running. -- First full readiness run caught legacy AI Lab static contract expectations for exact `lab-block` and `result-summary-card` class names. Kept those compatibility anchors while preserving the new AI Lab surfaces. -- `python -m pytest backend/tests/test_sprint50_workspace_usability_polish.py backend/tests/test_sprint75_ai_labs_mobile_polish.py backend/tests/test_sprint88_ai_lab_density.py -q` (`8 passed`) -- `bash scripts/run_readiness_check.sh` (`299 passed`; frontend typecheck/build passed; Alembic head `202606120900`; live smoke syntax passed) -- Tower deploy via `scripts/deploy_tower.ps1` rebuilt and restarted the all-in-one container on `http://192.0.2.10:1202`. -- Tower deploy live migration smoke passed with PostGIS `3.6 USE_GEOS=1 USE_PROJ=1 USE_STATS=1` and required runtime schema objects present. -- Browser runtime verification passed for frontend, proxied API and icon. -- Live browser AI Labs check against `http://192.0.2.10:1202` passed on desktop and mobile: Detection/Segmentation shells and model/run/result/QA surfaces rendered, no horizontal overflow and no console warnings/errors. - -Open: -- None known after full readiness, Tower deploy and live browser validation. - -Limitations: -- Frontend AI Labs presentation hierarchy only; no detection/segmentation behavior, API contract, persistence, migration, provider fetching or AI/model changes. - -Next recommended pass: -- Continue with export/system final visual consistency or live workflow guidance once this pass is deployed and visually checked. - -## Sprint 89 Export/System density polish (2026-06-20) - -Changed: -- Wrapped Export Center content in `export-center-shell`. -- Grouped export summary, handoff readiness, artifact actions, current state cards and history into focused `export-*` surfaces. -- Wrapped Provider Capabilities content in `system-provider-shell`. -- Replaced loose provider loading/error/empty text with shared `result-state` cards. -- Grouped provider registry content into `system-provider-capability-surface`. -- Split provider limitation/reason text and attribution/license data into `provider-detail-stack` and provenance cards. -- Added shared Export/System density CSS for compact summary, handoff, action, history and provider provenance grids. -- Added `backend/tests/test_sprint89_export_system_density.py`. -- Updated `frontend/README.md`, `docs/TODO.md` and `CHANGELOG.md`. - -Tested: -- Red step: `python -m pytest backend/tests/test_sprint89_export_system_density.py -q` failed on missing Export/System shells, surfaces and CSS contracts. -- `python -m pytest backend/tests/test_sprint89_export_system_density.py backend/tests/test_sprint51_quality_export_polish.py backend/tests/test_sprint64_export_handoff_polish.py backend/tests/test_sprint76_export_system_mobile_polish.py backend/tests/test_sprint78_export_preview_readability.py -q` (`12 passed`) -- `cd frontend && npm run typecheck` -- `cd frontend && npm run build` -- In-app browser fallback note: the Browser click path timed out on the local workspace navigation CDP command, so rendered validation used local Chrome via Playwright. -- Local Chrome UI check against `http://127.0.0.1:5174` passed on desktop and mobile: Export/System shells and surfaces rendered with no horizontal overflow. Local console showed expected Vite proxy 500s because only the frontend server was running. -- `bash scripts/run_readiness_check.sh` (`303 passed`; frontend typecheck/build passed; Alembic head `202606120900`; live smoke syntax passed) -- Tower deploy via `scripts/deploy_tower.ps1` rebuilt and restarted the all-in-one container on `http://192.0.2.10:1202`. -- Tower deploy live migration smoke passed with PostGIS `3.6 USE_GEOS=1 USE_PROJ=1 USE_STATS=1` and required runtime schema objects present. -- Browser runtime verification passed for frontend, proxied API and icon. -- Live Chrome UI check against `http://192.0.2.10:1202` passed on desktop and mobile: Export/System shells and surfaces rendered, four provider cards and eight provider provenance cards were visible, no horizontal overflow and no console warnings/errors. - -Open: -- None known after full readiness, Tower deploy and live browser validation. - -Limitations: -- Frontend Export/System presentation hierarchy only; no export behavior, API contract, persistence, migration, provider fetching or AI/model changes. - -Next recommended pass: -- Continue with end-to-end workflow guidance after this pass is deployed and visually checked. - -## Sprint 90 workflow guidance polish (2026-06-20) - -Changed: -- Added an Overview `workflow-guidance-panel` that shows the V1 flow from Project & AOI through Data, Map, QA / AI and Export. -- Added ready/waiting/next state labels from existing loaded project, dataset, map, QA/AI and export state. -- Routed the guidance cards through the existing `setActiveWorkspace` navigation only. -- Added compact responsive CSS for the guidance rail. -- Added `backend/tests/test_sprint90_workflow_guidance.py`. -- Updated `frontend/README.md`, `docs/TODO.md` and `CHANGELOG.md`. - -Tested: -- Red step: `python -m pytest backend/tests/test_sprint90_workflow_guidance.py -q` failed on missing workflow guidance App and CSS contracts. -- `python -m pytest backend/tests/test_sprint90_workflow_guidance.py backend/tests/test_sprint83_workspace_panel_hierarchy.py backend/tests/test_sprint49_workbench_shell_refactor.py backend/tests/test_sprint62_frontend_visual_polish.py backend/tests/test_sprint82_shell_density_polish.py -q` (`13 passed`) -- `cd frontend && npm run typecheck` -- `cd frontend && npm run build` -- `bash scripts/run_readiness_check.sh` (`306 passed`; frontend typecheck/build passed; Alembic head `202606120900`; live smoke syntax passed) -- Local browser UI check against `http://127.0.0.1:5174` passed on desktop and mobile: workflow guidance panel rendered with five steps and no horizontal overflow. Local console showed expected Vite proxy 500s because only the frontend server was running. -- Tower deploy via `scripts/deploy_tower.ps1` rebuilt and restarted the all-in-one container on `http://192.0.2.10:1202` from commit `2a0e7e7`. -- Tower deploy live migration smoke passed with PostGIS `3.6 USE_GEOS=1 USE_PROJ=1 USE_STATS=1` and required runtime schema objects present. -- Browser runtime verification passed for frontend, proxied API and icon. -- Live browser UI check against `http://192.0.2.10:1202` passed on desktop and mobile: workflow guidance panel rendered with five steps, no horizontal overflow and no console warnings/errors. - -Open: -- None known after full readiness, Tower deploy and live browser validation. - -Limitations: -- Frontend Overview workflow guidance only; no API contract, persistence, migration, provider fetching or AI/model behavior changes. - -Next recommended pass: -- After deploy and visual validation, continue with any remaining end-to-end workflow handoff polish surfaced by the live audit. - -## Sprint 91 populated workflow audit polish (2026-06-21) - -Changed: -- Audited the live populated demo state on `http://192.0.2.10:1202` across Overview, Data, Map, QA/QC, AI Labs and Exports. -- Changed the Overview workflow guidance badge to show `Ready for handoff` when project, dataset, map, QA/AI and export state are all present. -- Clarified the Map workflow step so it reports layer feature count separately from AOI context and shows `AOI loaded` for AOI-only map context. -- Extended `backend/tests/test_sprint90_workflow_guidance.py` with complete-state and Map-copy regression coverage. -- Updated `frontend/README.md`, `docs/TODO.md` and `CHANGELOG.md`. - -Tested: -- Live pre-change browser audit passed for the populated demo workflow: Data had 2 ready datasets, Map rendered `demo_predicted_buildings.geojson` with 2 layer features, QA/QC showed 2 checks, AI Labs showed model/result/QA surfaces, Exports showed 50 artifacts, and no checked workspace had console warnings/errors or horizontal overflow. -- Red step: `python -m pytest backend/tests/test_sprint90_workflow_guidance.py -q` failed on missing `workflowGuidanceComplete` / `Ready for handoff` / precise Map copy contracts. -- Post-deploy live check found the AOI-only reload state rendered `0 layer features + AOI`; a second red step failed on missing `AOI loaded` copy before the fix. -- `python -m pytest backend/tests/test_sprint90_workflow_guidance.py -q` (`4 passed`) -- `python -m pytest backend/tests/test_sprint90_workflow_guidance.py backend/tests/test_sprint83_workspace_panel_hierarchy.py backend/tests/test_sprint82_shell_density_polish.py -q` (`10 passed`) -- `cd frontend && npm run typecheck` -- `cd frontend && npm run build` -- Local browser UI check against `http://127.0.0.1:5174` passed for the Overview guidance panel with no horizontal overflow. Local console showed expected Vite proxy 500s because only the frontend server was running. -- `bash scripts/run_readiness_check.sh` (`307 passed`; frontend typecheck/build passed; Alembic head `202606120900`; live smoke syntax passed) -- Tower deploy via `scripts/deploy_tower.ps1` rebuilt and restarted the all-in-one container on `http://192.0.2.10:1202` from commit `97b943d`. -- Tower deploy live migration smoke passed with PostGIS `3.6 USE_GEOS=1 USE_PROJ=1 USE_STATS=1` and required runtime schema objects present. -- Browser runtime verification passed for frontend, proxied API and icon. -- Live post-change browser check passed: AOI-only Overview state showed `Map AOI loaded`; after opening `demo_predicted_buildings.geojson` on the map, Overview showed `Map 2 layer features + AOI`; both states showed `Ready for handoff`, no horizontal overflow and no console warnings/errors. - -Open: -- None known after full readiness, Tower deploy and live browser validation. - -Limitations: -- Frontend Overview copy/state polish only; no API contract, persistence, migration, provider fetching or AI/model behavior changes. - -Next recommended pass: -- After deploy and live validation, continue with any remaining populated-state visual issues found in the next audit. - -## Sprint 92 workflow rail interaction polish (2026-06-21) - -Changed: -- Audited the live Overview workflow rail click path on `http://192.0.2.10:1202`. -- Added `openWorkflowGuidanceStep` so Map and Export rail clicks can reuse existing dataset context flows. -- Map rail click now opens the first ready vector/GeoJSON dataset through `openDatasetInMap` when no layer is active. -- Export rail click now opens the first ready vector/GeoJSON dataset through `openDatasetExport` when no dataset is selected. -- Extended `backend/tests/test_sprint90_workflow_guidance.py` with regression coverage for the context-aware rail handler. -- Updated `frontend/README.md`, `docs/TODO.md` and `CHANGELOG.md`. - -Tested: -- Live pre-change browser audit showed the rail navigated correctly but Map landed with no active layer and Exports landed with `Selected dataset: none`. -- Red step: `python -m pytest backend/tests/test_sprint90_workflow_guidance.py -q` failed on missing `openWorkflowGuidanceStep` / dataset-context handler contracts. -- `python -m pytest backend/tests/test_sprint90_workflow_guidance.py backend/tests/test_sprint53_selection_ergonomics.py backend/tests/test_sprint67_map_empty_state_quick_actions.py backend/tests/test_sprint64_export_handoff_polish.py -q` (`15 passed`) -- `cd frontend && npm run typecheck` -- `cd frontend && npm run build` -- Local browser UI check against `http://127.0.0.1:5174` passed for rail rendering with no horizontal overflow. Local console showed expected Vite proxy 500s because only the frontend server was running. -- `bash scripts/run_readiness_check.sh` (`308 passed`; frontend typecheck/build passed; Alembic head `202606120900`; live smoke syntax passed) -- Tower deploy from commit `1872c60` completed; all-in-one container published on `0.0.0.0:1202->80/tcp`. -- Deploy-time live migration smoke passed after the database became ready on attempt 3; PostGIS reported `3.6 USE_GEOS=1 USE_PROJ=1 USE_STATS=1`, required runtime schema objects were present and Alembic head was `202606120900`. -- Deploy-time browser runtime verification passed for frontend, API proxy and icon. -- Live targeted browser validation against `http://192.0.2.10:1202` passed for `Open Map step`: `demo_predicted_buildings.geojson` became active, `2 features` rendered, no horizontal overflow and no console/page errors. -- Live targeted browser validation against `http://192.0.2.10:1202` passed for `Open Export step`: `demo_predicted_buildings.geojson` became the selected export dataset, no horizontal overflow and no console/page errors. - -Open: -- None for this pass. - -Limitations: -- Frontend workflow navigation polish only; no API contract, persistence, migration, provider fetching or AI/model behavior changes. - -Next recommended pass: -- After deploy and live validation, continue with export artifact action ergonomics or QA result drill-down, depending on the next live friction point. - -## Sprint 93 export handoff artifact polish (2026-06-21) - -Changed: -- Added a `Latest handoff artifacts` section to `frontend/src/components/exports/ExportCenter.tsx`. -- Grouped newest persisted artifacts for project report, project metadata, dataset GeoJSON, detection GeoJSON and segmentation GeoJSON. -- Reused existing JSON preview and artifact download callbacks from latest artifact cards. -- Added responsive latest artifact card styling in `frontend/src/styles/app.css`. -- Added `backend/tests/test_sprint93_export_handoff_completion.py` to lock the grouped handoff surface, actions and responsive CSS. -- Updated `CHANGELOG.md`, `docs/TODO.md` and `frontend/README.md`. - -Tested: -- Red step: `python -m pytest backend\tests\test_sprint93_export_handoff_completion.py -q` failed on missing latest artifact grouping/actions/styles. -- `python -m pytest backend\tests\test_sprint93_export_handoff_completion.py -q` (`3 passed`) -- `python -m pytest backend\tests\test_sprint93_export_handoff_completion.py backend\tests\test_sprint64_export_handoff_polish.py backend\tests\test_sprint89_export_system_density.py backend\tests\test_sprint51_quality_export_polish.py backend\tests\test_sprint78_export_preview_readability.py -q` (`13 passed`) -- `cd frontend && npm run typecheck` -- `cd frontend && npm run build` -- `bash scripts/run_readiness_check.sh` (`311 passed`; frontend typecheck/build passed; Alembic head `202606120900`; live smoke syntax passed) -- Tower deploy from commit `0a9054c` completed; all-in-one container published on `0.0.0.0:1202->80/tcp`. -- Deploy-time live migration smoke passed after the database became ready on attempt 2; PostGIS reported `3.6 USE_GEOS=1 USE_PROJ=1 USE_STATS=1`, required runtime schema objects were present and Alembic head was `202606120900`. -- Deploy-time browser runtime verification passed for frontend, API proxy and icon. -- Live browser validation against `http://192.0.2.10:1202` passed for `Open Export step`: selected dataset stayed `demo_predicted_buildings.geojson`, `Latest handoff artifacts` rendered, project report/project metadata/dataset GeoJSON cards were present, detection/segmentation cards showed `No artifact yet`, preview opened from the latest artifact card, no horizontal overflow and no console/page errors. - -Open: -- None for this pass. - -Limitations: -- Export Center frontend handoff polish only; no API contract, persistence, migration, provider fetching or AI/model behavior changes. - -Next recommended pass: -- After deploy and live validation, continue with QA/QC drilldown and map evidence layers. - -## Sprint 94 QA/QC evidence drilldown (2026-06-22) - -Changed: -- Added selected-check drilldown state to `frontend/src/components/quality/QualityResultsPanel.tsx`. -- Added a `QA/QC evidence drilldown` surface with selected check, candidate/reference layer, analysis run, job, status, score and timestamp provenance. -- Added false-positive evidence, false-negative evidence and map evidence handoff cards using persisted metric rows and dataset names. -- Added parameter and findings JSON panes for persisted QA/QC provenance. -- Added `Inspect latest check` and per-result `Inspect check` controls. -- Added responsive QA drilldown styles to `frontend/src/styles/app.css`. -- Added `backend/tests/test_sprint94_quality_drilldown.py`. -- Updated `CHANGELOG.md`, `docs/TODO.md` and `frontend/README.md`. - -Tested: -- Red step: `python -m pytest backend\tests\test_sprint94_quality_drilldown.py -q` failed on missing drilldown state/surfaces/styles. -- `python -m pytest backend\tests\test_sprint94_quality_drilldown.py backend\tests\test_sprint70_quality_handoff_polish.py backend\tests\test_sprint71_quality_metric_polish.py backend\tests\test_sprint73_quality_result_filtering.py backend\tests\test_sprint86_quality_workspace_density.py -q` (`15 passed`) -- `cd frontend && npm run typecheck` -- `cd frontend && npm run build` -- `bash scripts/run_readiness_check.sh` (`314 passed`; frontend typecheck/build passed; Alembic head `202606120900`; live smoke syntax passed) -- Tower deploy from commit `f3ad9c3` completed; all-in-one container published on `0.0.0.0:1202->80/tcp`. -- Deploy-time live migration smoke passed after the database became ready on attempt 2; PostGIS reported `3.6 USE_GEOS=1 USE_PROJ=1 USE_STATS=1`, required runtime schema objects were present and Alembic head was `202606120900`. -- Deploy-time browser runtime verification passed for frontend, API proxy and icon. -- Live browser validation against `http://192.0.2.10:1202` passed for `Open QA / AI step`: QA/QC evidence drilldown rendered, candidate/reference names resolved, false-positive/negative evidence rendered, parameters/findings JSON rendered, per-result `Inspect check` controls were available, no horizontal overflow and no console/page errors. - -Open: -- None for this pass. - -Limitations: -- QA/QC frontend drilldown only; no API contract, persistence, migration, provider fetching or AI/model behavior changes. -- Map evidence handoff points reviewers to candidate/reference datasets already persisted in the workbench; it does not create a new matched/unmatched geometry export. - -Next recommended pass: -- After deploy and live validation, continue with QA map overlay affordances or raster pipeline hardening. - -## Sprint 95 raster pipeline hardening (2026-06-22) - -Changed: -- Added a `Raster pipeline readiness` surface to `frontend/src/components/datasets/RasterControls.tsx`. -- Surfaced metadata profile, CRS readiness, preview artifact, tile manifest handoff and clip AOI state before raster operations. -- Added `Processing guardrails` for missing selected dataset, unavailable raster processing, missing metadata, missing CRS, missing preview, invalid tile parameters and missing clip areas. -- Added responsive raster readiness, guardrail and manifest-handoff styles to `frontend/src/styles/app.css`. -- Added `backend/tests/test_sprint95_raster_pipeline_hardening.py`. -- Updated `CHANGELOG.md`, `docs/TODO.md` and `frontend/README.md`. - -Tested: -- Red step: `python -m pytest backend\tests\test_sprint95_raster_pipeline_hardening.py -q` failed on missing readiness/handoff component structure and CSS. -- `python -m pytest backend\tests\test_sprint95_raster_pipeline_hardening.py -q` (`2 passed`) -- `python -m pytest backend\tests\test_sprint80_operation_form_readability.py backend\tests\test_sprint77_inspector_mobile_polish.py -q` (`5 passed`) -- `python -m compileall backend/app` -- `cd backend && python -m pytest -q` (`316 passed`) -- `cd frontend && npm run typecheck` -- `cd frontend && npm run build` -- `bash scripts/run_readiness_check.sh` (`316 passed`; frontend typecheck/build passed; Alembic head `202606120900`; live smoke syntax passed) -- `cd backend && python -m alembic heads` (`202606120900 (head)`) -- `cd backend && python -m alembic upgrade head --sql` -- `bash -n scripts/live_migration_smoke.sh` -- Tower deploy from commit `330b677` completed; all-in-one container published on `0.0.0.0:1202->80/tcp`. -- Deploy-time live migration smoke passed after the database became ready on attempt 2; PostGIS reported `3.6 USE_GEOS=1 USE_PROJ=1 USE_STATS=1`, required runtime schema objects were present and Alembic head was `202606120900`. -- Deploy-time browser runtime verification passed for frontend, API proxy and icon. -- Live browser validation against `http://192.0.2.10:1202` passed for the workbench shell: Overview/Data/Map/QA/QC/AI Labs/Exports markers were present, no horizontal overflow and no console/page errors. -- Live dataset API validation confirmed the default demo currently contains vector fixtures only, so the raster-specific panel is not visible in the default live state without a raster upload. - -Open: -- None for this pass. - -Limitations: -- Frontend raster inspector hardening only; no API contract, persistence, migration, provider fetching or AI/model behavior changes. -- The panel explains the existing tile manifest handoff but does not create a new manifest picker or new detection/segmentation behavior. -- Raster-specific live visual validation requires a raster dataset in the live project; the current offline demo seed contains vector fixtures only. - -Next recommended pass: -- After deploy and live validation, add a raster fixture/demo upload smoke or continue with map evidence overlay affordances for QA/QC. - -## Sprint 96 useful default context (2026-06-22) - -Changed: -- Added a guarded default dataset effect in `frontend/src/hooks/useDatasetWorkflow.ts`. -- When project data loads and no dataset is selected, the workbench now auto-opens the first ready vector dataset, falling back to any ready dataset and then the first dataset. -- This gives Data, Map and Exports an immediately useful selected dataset/map layer context for the populated demo flow. -- Added explicit no-raster guidance cards to Detection Lab and Segmentation Lab run controls. -- Added `backend/tests/test_sprint96_useful_default_context.py`. -- Updated `CHANGELOG.md`, `docs/TODO.md` and `frontend/README.md`. - -Tested: -- Red step: `python -m pytest backend\tests\test_sprint96_useful_default_context.py -q` failed on missing default dataset selection and no-raster AI Lab guidance. -- `python -m pytest backend\tests\test_sprint96_useful_default_context.py -q` (`2 passed`) -- `python -m pytest backend\tests\test_sprint39_frontend_orchestration_hooks.py backend\tests\test_sprint29_dataset_components.py backend\tests\test_sprint88_ai_lab_density.py -q` (`16 passed`) -- `python -m compileall backend/app` -- `cd backend && python -m pytest -q` (`318 passed`) -- `cd frontend && npm run typecheck` -- `cd frontend && npm run build` -- `bash scripts/run_readiness_check.sh` (`318 passed`; frontend typecheck/build passed; Alembic head `202606120900`; live smoke syntax passed) -- `cd backend && python -m alembic heads` (`202606120900 (head)`) -- `cd backend && python -m alembic upgrade head --sql` -- `bash -n scripts/live_migration_smoke.sh` -- Tower deploy from commit `aaf1299` completed; all-in-one container published on `0.0.0.0:1202->80/tcp`. -- Deploy-time live migration smoke passed after the database became ready on attempt 3; PostGIS reported `3.6 USE_GEOS=1 USE_PROJ=1 USE_STATS=1`, required runtime schema objects were present and Alembic head was `202606120900`. -- Deploy-time browser runtime verification passed for frontend, API proxy and icon. -- Live browser validation against `http://192.0.2.10:1202` passed: Data auto-selected `demo_predicted_buildings.geojson`, Map rendered `2 features`, Exports showed the same selected dataset, AI Labs showed no-raster guidance for detection and segmentation, desktop/mobile had no horizontal overflow and no console/page errors. - -Open: -- None for this pass. - -Limitations: -- Frontend usability/default-context hardening only; no API contract, persistence, migration, provider fetching or AI/model behavior changes. -- Detection and segmentation remain correctly blocked without a raster dataset. - -Next recommended pass: -- After deploy and live validation, add a raster fixture/demo upload smoke so AI Labs and raster controls can be validated with a connected raster state. - -## Sprint 101 AI Lab handoff browser smoke (2026-06-24) - -Changed: -- Added `scripts/verify_ai_handoff_interactions.sh`. -- The script seeds the explicit offline demo workflow through the frontend-facing API, creates a small raster tile manifest, opens the browser workbench with Playwright/Chromium, clicks `Use in Detection Lab` and `Use in Segmentation Lab`, and verifies both AI Lab forms receive the selected raster dataset plus `Raster tile manifest path`. -- Added syntax coverage for the new script to `scripts/run_readiness_check.sh`. -- Added `backend/tests/test_sprint101_ai_handoff_interaction_smoke.py`. -- Updated `scripts/README.md` and `CHANGELOG.md`. - -Tested: -- Red step: `python -m pytest backend\tests\test_sprint101_ai_handoff_interaction_smoke.py -q` failed while `scripts/verify_ai_handoff_interactions.sh` was absent. -- `python -m pytest backend\tests\test_sprint101_ai_handoff_interaction_smoke.py -q` (`1 passed`) -- `bash -n scripts/verify_ai_handoff_interactions.sh` -- Local Node Playwright availability check failed with `ERR_MODULE_NOT_FOUND`, so live browser-click execution requires Playwright to be installed or exposed in the runner environment. -- `python -m compileall backend/app` -- `cd backend && python -m pytest -q` (`324 passed`) -- `cd frontend && npm run typecheck` -- `cd frontend && npm run build` -- `bash scripts/run_readiness_check.sh` (`324 passed`; frontend typecheck/build passed; Alembic head `202606120900`; live smoke syntax passed) -- `cd backend && python -m alembic heads` (`202606120900 (head)`) -- `cd backend && python -m alembic upgrade head --sql` -- `bash -n scripts/live_migration_smoke.sh` -- Tower deploy from commit `aab51ed` completed; all-in-one container published on `0.0.0.0:1202->80/tcp`. -- Deploy-time live migration smoke passed after the database became ready on attempt 3; PostGIS reported `3.6 USE_GEOS=1 USE_PROJ=1 USE_STATS=1`, required runtime schema objects were present and Alembic head was `202606120900`. -- Deploy-time browser runtime verification passed for frontend, API proxy and icon. -- Live smoke passed: `bash scripts/verify_demo_raster_workflow.sh http://192.0.2.10:1202`. -- Live smoke passed: `bash scripts/verify_workbench_default_state.sh http://192.0.2.10:1202`. -- Live smoke passed: `bash scripts/verify_workbench_interactions.sh http://192.0.2.10:1202`. -- Live smoke passed: `bash scripts/verify_browser_runtime.sh http://192.0.2.10:1202`. -- Live browser-click validation with Codex Playwright plus installed Chrome passed against `http://192.0.2.10:1202`: the smoke seeded the demo workflow, generated a raster tile manifest, selected the raster in Data, opened the Dataset inspector tab, clicked `Use in Detection Lab`, selected `yolo-configured`, verified Detection Lab dataset and manifest values, clicked `Use in Segmentation Lab`, verified Segmentation Lab dataset and manifest values, and observed no console/page errors. - -Open: -- None for this pass. - -Limitations: -- Test/smoke tooling only; no product behavior, API contract, migration, AI dependency, provider fetching or model behavior changes. -- `scripts/verify_ai_handoff_interactions.sh` requires a runner with Playwright plus a browser. This Codex environment had Playwright available through the Node REPL and used installed Chrome; plain local `node` still reports `ERR_MODULE_NOT_FOUND` for `playwright`. - -Next recommended pass: -- After validation and deploy, keep using the AI handoff smoke as the browser-level regression guard for raster-to-AI workspace wiring. - -## Sprint 102 Detection Lab handoff polish (2026-06-24) - -Changed: -- Updated `useRasterTileManifestForDetection` in `frontend/src/App.tsx` to set `selectedDetectionModelId` to `yolo-configured` when a raster tile manifest is handed off from the dataset inspector. -- Tightened `scripts/verify_ai_handoff_interactions.sh` so it verifies that Detection Lab is already on `yolo-configured` after the handoff instead of selecting that model inside the smoke. -- Updated `backend/tests/test_sprint99_raster_ui_handoff.py` and `backend/tests/test_sprint101_ai_handoff_interaction_smoke.py`. -- Updated `CHANGELOG.md` and `docs/TODO.md`. - -Tested: -- Red step: `python -m pytest backend\tests\test_sprint99_raster_ui_handoff.py -q` failed while the detection handoff did not set `yolo-configured`. -- `python -m pytest backend\tests\test_sprint99_raster_ui_handoff.py backend\tests\test_sprint101_ai_handoff_interaction_smoke.py -q` (`2 passed`) -- `cd frontend && npm run typecheck` -- `cd frontend && npm run build` -- `bash -n scripts/verify_ai_handoff_interactions.sh` -- `python -m compileall backend/app` -- `cd backend && python -m pytest -q` (`324 passed`) -- `bash scripts/run_readiness_check.sh` (`324 passed`; frontend typecheck/build passed; Alembic head `202606120900`; live smoke syntax passed) -- `cd backend && python -m alembic heads` (`202606120900 (head)`) -- `cd backend && python -m alembic upgrade head --sql` -- `bash -n scripts/live_migration_smoke.sh` -- First Tower redeploy attempt failed with Docker btrfs `no space left on device` while writing build context files. -- Remote Docker diagnosis showed `/var/lib/docker` had ordinary free space but btrfs metadata was 94.80% used with the 300GB docker image fully allocated. -- Removed dangling Docker images and cleared orphaned hung Docker CLI processes from prior inspection/prune attempts. -- Ran a limited Docker btrfs balance: `btrfs balance start -dusage=40 -musage=80 /var/lib/docker`; metadata improved to 75.63% used and 94.95GiB became unallocated. -- Tower deploy from commit `4367400` then completed; all-in-one container published on `0.0.0.0:1202->80/tcp`. -- Deploy-time live migration smoke passed after the database became ready on attempt 2; PostGIS reported `3.6 USE_GEOS=1 USE_PROJ=1 USE_STATS=1`, required runtime schema objects were present and Alembic head was `202606120900`. -- Deploy-time browser runtime verification passed for frontend, API proxy and icon. -- Live smoke passed: `bash scripts/verify_demo_raster_workflow.sh http://192.0.2.10:1202`. -- Live smoke passed: `bash scripts/verify_workbench_default_state.sh http://192.0.2.10:1202`. -- Live smoke passed: `bash scripts/verify_workbench_interactions.sh http://192.0.2.10:1202`. -- Live smoke passed: `bash scripts/verify_browser_runtime.sh http://192.0.2.10:1202`. -- Internal Codex browser validation passed against `http://192.0.2.10:1202`: Data workspace selected the raster fixture, Dataset inspector handoff clicked `Use in Detection Lab`, Detection Lab auto-selected `yolo-configured`, the raster dataset and tile manifest matched the generated manifest, the manifest input was visible, and no console/page errors were reported. - -Open: -- None for this pass. - -Limitations: -- Frontend handoff polish only; no backend API, persistence, migration, provider fetching, AI dependency or model execution behavior changed. -- The Tower Docker image required btrfs metadata balancing before redeploy. If this recurs, inspect `btrfs filesystem usage /var/lib/docker`; metadata near full can fail builds even when `df` reports free GB. - -Next recommended pass: -- After live validation, continue with the next V1 usability gap from the workbench flow rather than adding new model/provider scope. - -## Sprint 103 AI Lab run readiness (2026-06-24) - -Changed: -- Added compact run-readiness panels to Detection Lab and Segmentation Lab. -- Detection readiness now checks selected raster dataset, selected model availability and the configured-YOLO tile manifest requirement before a run is submitted. -- Segmentation readiness now checks selected raster dataset, configured segmentation model state and whether a tile manifest is present for provenance. -- Added shared AI Lab readiness styling and regression coverage in `backend/tests/test_sprint103_ai_lab_run_readiness.py`. -- Updated `CHANGELOG.md` and `docs/TODO.md`. - -Tested: -- Red step: `python -m pytest backend\tests\test_sprint103_ai_lab_run_readiness.py -q` failed while the readiness panels and CSS contracts were absent. -- `python -m pytest backend\tests\test_sprint103_ai_lab_run_readiness.py -q` (`3 passed`) -- `python -m compileall backend/app` -- `cd backend && python -m pytest -q` (`327 passed`) -- `cd frontend && npm run typecheck` -- `cd frontend && npm run build` -- `bash scripts/run_readiness_check.sh` (`327 passed`; frontend typecheck/build passed; Alembic head `202606120900`; live smoke syntax passed) -- `cd backend && python -m alembic heads` (`202606120900 (head)`) -- `cd backend && python -m alembic upgrade head --sql` -- `bash -n scripts/live_migration_smoke.sh` -- Tower deploy from commit `98fff63` completed; all-in-one container published on `0.0.0.0:1202->80/tcp`. -- Deploy-time live migration smoke passed after the database became ready on attempt 3; PostGIS reported `3.6 USE_GEOS=1 USE_PROJ=1 USE_STATS=1`, required runtime schema objects were present and Alembic head was `202606120900`. -- Deploy-time browser runtime verification passed for frontend, API proxy and icon. -- Live smoke passed: `bash scripts/verify_demo_raster_workflow.sh http://192.0.2.10:1202`. -- Live smoke passed: `bash scripts/verify_workbench_default_state.sh http://192.0.2.10:1202`. -- Live smoke passed: `bash scripts/verify_workbench_interactions.sh http://192.0.2.10:1202`. -- Live smoke passed: `bash scripts/verify_browser_runtime.sh http://192.0.2.10:1202`. -- Internal Codex browser validation passed against `http://192.0.2.10:1202`: AI Labs rendered Detection and Segmentation run-readiness panels; Detection stayed blocked when `Configured YOLO detector` had no local YOLO configuration but marked dataset and tile manifest as provided; Segmentation became ready with the explicit fixture segmenter and manifest; desktop and mobile viewports had no horizontal overflow and no console warnings/errors. - -Open: -- None for this pass. - -Limitations: -- Frontend readiness guidance only; no backend API, persistence, migration, provider fetching, AI dependency or model execution behavior changed. - -Next recommended pass: -- Continue with V1 usability work that reduces operator confusion without expanding frozen product scope. - -## Sprint 122 Detection model asset activation guardrails (2026-07-08) - -Changed: -- Hardened Detection Lab local model handling so reported runtime model assets are read-only choices and are not auto-selected by the frontend hook. -- Configured YOLO run readiness now blocks submission when local model assets exist but no explicit `model_asset_id` has been selected. -- Added an explicit model asset section with active runtime env status, `will_download_models`, SHA-256 preview, file size and mounted model path. -- Surfaced the current benchmark candidate `geointel-building-yolov8s-hardneg160r4e50-pt` with recommended starting threshold `0.25`. -- Added compact UI guidance styling for the benchmark/threshold warning. -- Added regression coverage in `backend/tests/test_sprint122_model_asset_activation_guardrails.py`. -- Updated `CHANGELOG.md` and `docs/TODO.md`. - -Tested: -- Red step: `python -m pytest backend\tests\test_sprint122_model_asset_activation_guardrails.py -q` failed on the previous auto-selection behavior and missing guardrail copy. -- `python -m pytest backend\tests\test_sprint122_model_asset_activation_guardrails.py -q` (`3 passed`) -- `python -m pytest backend\tests\test_sprint118_yolo_preflight_ui.py backend\tests\test_sprint103_ai_lab_run_readiness.py backend\tests\test_sprint104_ai_lab_action_guardrails.py backend\tests\test_model_asset_catalog.py backend\tests\test_sprint122_model_asset_activation_guardrails.py -q` (`16 passed`) -- `python -m compileall backend/app` -- `python -m pytest backend\tests -q` (`408 passed`) -- `cd frontend && npm run typecheck` -- `cd frontend && npm run build` - -Open: -- Full threshold calibration comparison UI is still pending; this pass adds safe single-threshold guidance and explicit asset choice only. - -Limitations: -- Frontend guardrail only; no backend API contracts, migrations, provider fetching, model downloads or model weight mutation behavior changed. -- The active runtime env model can still be configured by operators through existing deployment/env tooling, but the Detection Lab no longer silently chooses a local asset from the catalog for a run. - -Next recommended pass: -- Add threshold calibration comparison UX over existing persisted runs so candidate models can be promoted with visible precision/recall/F1 and hard-negative counts. - -## Operator YOLOv8s hard-negative model benchmark (2026-07-08) - -Changed: -- No repository code, API contract, migration, UI or application behavior was changed in this pass. -- Downloaded the official Ultralytics YOLOv8s base model manually as an operator/runtime asset on Tower at `/mnt/user/appdata/geointel/models/yolov8s.pt`. -- Trained a local hard-negative building detector on Tower from the existing exported operator tile dataset `yolo-building-tile-hardneg160r4`. -- Produced the trained runtime model artifact `/mnt/user/appdata/geointel/models/geointel-building-yolov8s-hardneg160r4e50.pt`, mounted in the container as `/app/models/geointel-building-yolov8s-hardneg160r4e50.pt`. -- Verified the live model catalog exposes the trained model as `geointel-building-yolov8s-hardneg160r4e50-pt` with SHA256 `9bf71ad4742048ac77f07060b677bacd9757b8d310497fcada334d543e320d19`, size `22473194`, `will_download_models=false` and `active=false`. -- Reused existing persisted dense QA and hard-negative benchmark runs through the live API; no external provider fetching and no fake data were introduced. - -Training evidence: -- Base model: `/app/models/yolov8s.pt`. -- Base model SHA256: `1f47a78bf100391c2a140b7ac73a1caae18c32779be7d310658112f7ac9aa78a`. -- Training run: `/app/storage/training/operator-yolo/geointel-building-yolov8s-hardneg160r4e50`. -- Best checkpoint copied to: `/app/models/geointel-building-yolov8s-hardneg160r4e50.pt`. -- Final validation from Ultralytics: precision `0.449`, recall `0.404`, mAP50 `0.322`, mAP50-95 `0.110`. - -Live benchmark evidence: -- Created 24 persisted rescored detection runs with `model_asset_id=geointel-building-yolov8s-hardneg160r4e50-pt`. -- Dense persisted QA matrix results at IoU `0.1`: - - Four dense benchmark scenes saturated at 300 detections across thresholds `0.05`, `0.15` and `0.25`. - - Dense F1 scores observed: `0.6380`, `0.5627`, `0.5247`, `0.4678`. - - Dense precision ranged from `0.7167` to `0.8600`; recall ranged from `0.3247` to `0.5749`. - - Mean IoU ranged from `0.3962` to `0.4465`. - - The sparse/forest scene improved as the threshold increased: `49` detections and F1 `0.1429` at `0.05`; `18` detections and F1 `0.3200` at `0.15`; `10` detections and F1 `0.4706` at `0.25`. -- Hard-negative detection counts: - - `kasterlee_bos`: `49` at threshold `0.05`, `18` at `0.15`, `10` at `0.25`. - - `lommel_heide`: `0` at thresholds `0.05`, `0.15` and `0.25`. - - `postel_bos`: `1` at threshold `0.05`, `0` at `0.15` and `0.25`. - -Assessment: -- The YOLOv8s hard-negative model is a materially better evaluation candidate than the previous tiny smoke models and is useful in dense building scenes. -- The model should not be made the silent default yet because `kasterlee_bos` still produces 10 hard-negative detections at threshold `0.25`. -- Threshold `0.25` is the safest observed operating point for the current candidate. -- The next product step should be model-selection and threshold workflow hardening before any operator-facing default activation. - -Operational note: -- Tower root SSH works with `widefrog_unraid_deploy` on the default SSH port `22`. -- Gitea SSH works separately on port `222` through the `gitea-widefrog` host alias and `widefrog_gitea` key. -- Do not test Unraid/root deploy access against port `222`; that port belongs to Gitea and correctly rejects `root`. -- Live HTTP API verification on `http://192.0.2.10:1202` remained reachable. - -Open: -- Add an operator-facing model selection/activation flow or documented command that can promote a chosen local model deliberately, with visible SHA256 and threshold guidance. -- Add more negative/background AOIs and a threshold calibration benchmark before activating this model by default. - -Next recommended pass: -- Implement V1 model-catalog hardening: show available local model assets, make active model/threshold explicit, and prevent accidental silent default activation. - -## Sprint 123 Raster detection manifest handoff (2026-07-08) - -Changed: -- Added a typed `RasterTileHandoff` frontend contract so raster tile jobs can expose manifest path, tile count, tile size, overlap, tile-set id and source dataset provenance. -- Updated the dataset workflow hook to retain the latest structured raster tile manifest alongside the existing manifest path. -- Updated Raster Controls to show manifest details and explicit Detection/Segmentation Lab handoff actions. -- Updated the Detection Lab handoff so a raster manifest selects `yolo-configured`, selects the active raster dataset, applies threshold `0.25`, refreshes YOLO preflight and does not auto-select a local model asset. -- Added linked tile manifest, manifest validation, tile count and `will_run_inference` visibility to Detection Lab. -- Added regression coverage in `backend/tests/test_sprint123_raster_detection_handoff_operational.py`. - -Tested: -- Red step: `python -m pytest backend\tests\test_sprint123_raster_detection_handoff_operational.py -q` failed while the typed handoff, Raster Controls details and Detection Lab preflight indicators were absent. -- `python -m pytest backend\tests\test_sprint123_raster_detection_handoff_operational.py -q` (`3 passed`) -- `python -m pytest backend\tests\test_sprint99_raster_ui_handoff.py backend\tests\test_sprint122_model_asset_activation_guardrails.py backend\tests\test_sprint120_model_asset_detection_workflow_smoke.py backend\tests\test_sprint123_raster_detection_handoff_operational.py -q` (`8 passed`) -- `python -m compileall backend/app` -- `cd frontend && npm run typecheck` -- `cd frontend && npm run build` - -Limitations: -- This pass improves the operator handoff and preflight visibility only. It does not change backend inference contracts, migrations, model files, provider fetching or automatic model promotion. - -Next recommended pass: -- Add threshold calibration comparison UX so an operator can compare candidate thresholds before promoting a local model. - -## Sprint 133 Detection threshold calibration UX (2026-07-08) - -Changed: -- Added a Detection Lab calibration comparison panel that combines existing persisted `DetectionRunRead` rows with existing persisted `QualityCheckRead`/metric rows. -- The panel shows confidence threshold, model, local model asset id, detection count, precision, recall, F1, false positives, false negatives and linked quality-check id. -- Added summary cards for best F1 candidate, best precision candidate and lowest false-positive pressure. -- Added a promotion guardrail that keeps model/threshold acceptance tied to QA evidence across AOIs instead of a single run. -- Passed project-level `qualityChecks` into Detection Lab without adding API routes, migrations or new AI execution behavior. -- Added regression coverage in `backend/tests/test_sprint133_detection_threshold_calibration_ux.py`. -- Marked the threshold calibration UX item complete in `docs/TODO.md`. - -Tested: -- Red step: `python -m pytest backend\tests\test_sprint133_detection_threshold_calibration_ux.py -q` failed while the persisted calibration comparison UI was absent. -- `python -m pytest backend\tests\test_sprint133_detection_threshold_calibration_ux.py -q` (`1 passed`) -- `python -m pytest backend\tests\test_sprint122_model_asset_activation_guardrails.py backend\tests\test_sprint123_raster_detection_handoff_operational.py backend\tests\test_sprint133_detection_threshold_calibration_ux.py -q` (`7 passed`) -- `cd frontend && npm run typecheck` -- `cd frontend && npm run build` - -Limitations: -- This is a persisted-run comparison surface only. It does not launch batch calibration sweeps from the browser and does not auto-promote model assets or thresholds. - -Next recommended pass: -- Add a guided in-app calibration runner that can queue a small explicit threshold set for one selected raster/reference pair, reusing the existing detection and QA APIs. - -## Sprint 134 Guided detection calibration runner (2026-07-08) - -Changed: -- Added an explicit guided calibration runner to Detection Lab for operator-selected confidence threshold sweeps. -- Added frontend detection workflow state for calibration thresholds, progress rows, running state and errors. -- The runner parses a space/comma/semicolon-separated threshold set, validates project/raster/reference/model/manifest/model-asset readiness and runs one existing `detectionApi.run` plus one existing detection QA comparison per threshold. -- Successful threshold rows report persisted analysis run/job/quality check ids, detection count, precision, recall, F1, false positives and false negatives. -- Added UI copy that this runs real configured YOLO jobs and QA comparisons and does not promote or mutate model files. -- Added regression coverage in `backend/tests/test_sprint134_guided_detection_calibration_runner.py`. -- Marked the guided calibration runner task complete in `docs/TODO.md`. - -Tested: -- Red step: `python -m pytest backend\tests\test_sprint134_guided_detection_calibration_runner.py -q` failed while the runner contract was absent. -- `python -m pytest backend\tests\test_sprint134_guided_detection_calibration_runner.py -q` (`1 passed`) -- `python -m pytest backend\tests\test_sprint133_detection_threshold_calibration_ux.py backend\tests\test_sprint134_guided_detection_calibration_runner.py backend\tests\test_sprint122_model_asset_activation_guardrails.py backend\tests\test_sprint123_raster_detection_handoff_operational.py -q` (`8 passed`) -- `cd frontend && npm run typecheck` -- `cd frontend && npm run build` - -Limitations: -- The runner is intentionally sequential and explicit. It does not schedule background batches, compare multiple AOIs at once or promote model assets/thresholds automatically. - -Next recommended pass: -- Add an evidence shortcut from each calibration row to the persisted QA evidence map/review flow so false positives and false negatives can be inspected faster. - -## Sprint 117 Safe local YOLO model activation (2026-07-06) - -Changed: -- Added `scripts/configure_yolo_model.py` to configure an existing local YOLO model into the deployment `.env` file without downloading model weights, loading a model or running inference. -- The helper scans a mounted model directory for `.pt`, `.onnx` and `.engine` files, refuses no-model and ambiguous multi-model states, and writes env updates only when `--apply` is provided. -- Added regression coverage in `backend/tests/test_sprint119_yolo_model_configuration.py` for no local model, ambiguous model selection, dry-run single model selection and env-file apply behavior. -- Downloaded the official Ultralytics `yolov8n.pt` smoke model to Tower under `/mnt/user/appdata/geointel/models/yolov8n.pt`, recorded checksum `f59b3d833e2ff32e194b5bb8e08d211dc7c5bdf144b90d2c8412c47ccfc83b36`, and applied the env configuration with the local helper. -- Hardened `YoloDetectionAdapter.predict_tile` so non-RGB raster tile artifacts are converted to a temporary RGB image before YOLO inference while georeferencing remains driven by the tile manifest. -- Wrapped YOLO prediction runtime errors as typed `DETECTION_INFERENCE_FAILED` `AppError`s instead of leaking raw runtime exceptions through FastAPI. -- Updated `scripts/README.md`, `deploy/unraid/README.md`, `backend/README.md`, `docs/AI_PIPELINES.md`, `docs/TODO.md` and `CHANGELOG.md`. - -Tested: -- Red step: `python -m pytest backend\tests\test_sprint119_yolo_model_configuration.py -q` failed while `scripts/configure_yolo_model.py` was absent. -- Red step: `python -m pytest backend\tests\test_sprint8b_yolo_foundation.py -q` failed because single-band TIFF tiles were passed through as mode `L` and prediction runtime errors leaked as raw `RuntimeError`. -- `python -m pytest backend\tests\test_sprint119_yolo_model_configuration.py -q` (`4 passed`) -- `python -m pytest backend\tests\test_sprint8b_yolo_foundation.py -q` (`12 passed`) -- `python -m py_compile scripts\configure_yolo_model.py` -- `python -m compileall backend/app` -- `cd backend && python -m pytest -q` (`377 passed`, existing Pydantic protected-namespace warnings remain) -- `cd frontend && npm run typecheck` -- `cd frontend && npm run build` -- `bash scripts/run_readiness_check.sh` (`Run readiness check passed`) -- `cd backend && python -m alembic heads` (`202606120900 (head)`) -- `cd backend && python -m alembic upgrade head --sql` -- `bash -n scripts/live_migration_smoke.sh` -- `bash -n scripts/deploy_tower.sh` -- Tower deploy from commit `72ee623` completed with `GEOINTEL_INSTALL_AI=true`; the all-in-one container is published on `0.0.0.0:1202->80/tcp`. -- Deploy-time live migration smoke passed after the database became ready on attempt 2; PostGIS reported `3.6 USE_GEOS=1 USE_PROJ=1 USE_STATS=1`, required runtime schema objects were present and Alembic head was `202606120900`. -- Deploy-time browser runtime verification passed for frontend, API proxy and icon. -- Live API check passed: `GET /api/v1/detection/yolo/preflight` returned canonical `data` with `status=not_configured`, `YOLO_ENABLED=false`, `torch_version=2.12.1`, `ultralytics_version=8.4.89`, `will_download_models=false` and `will_run_inference=false`. -- Tower helper dry-run passed: `python scripts/configure_yolo_model.py --models-dir /mnt/user/appdata/geointel/models --env-file .env --json` returned `status=no_model_found`, empty candidates and no env updates. -- Tower model apply passed: `python scripts/configure_yolo_model.py --models-dir /mnt/user/appdata/geointel/models --env-file .env --model-file /mnt/user/appdata/geointel/models/yolov8n.pt --apply --json` returned `status=applied`, `YOLO_ENABLED=true` and `YOLO_MODEL_PATH=/app/models/yolov8n.pt`. -- Live YOLO preflight with generated demo raster tile manifest passed with `status=ready`, `model_load_ok=true`, `manifest_valid=true`, `tile_paths_exist=true`, `tile_count=1`, `will_download_models=false` and `will_run_inference=false`. -- Live inference smoke before the RGB adapter fix reproduced the runtime bug: YOLOv8n expected 3 channels but the demo tile was single-band (`input[1, 1, 480, 640]`). -- Tower deploy from commit `add4768` completed with `GEOINTEL_INSTALL_AI=true`; the all-in-one container is published on `0.0.0.0:1202->80/tcp`. -- Deploy-time live migration smoke passed after the database became ready on attempt 3; PostGIS reported `3.6 USE_GEOS=1 USE_PROJ=1 USE_STATS=1`, required runtime schema objects were present and Alembic head was `202606120900`. -- Deploy-time browser runtime verification passed for frontend, API proxy and icon. -- Live YOLO preflight after the RGB adapter fix passed with generated demo raster tile manifest and `status=ready`. -- Live real YOLO inference smoke after the RGB adapter fix passed: `POST /api/v1/detection/run` returned `status=success`, analysis run `bbd80690-baf3-4e83-8ffb-fdcb07a70c0c`, job `9636ed10-bbde-463f-a47a-6d7706c81e19`, `detection_count=0` and no error code. Zero detections is expected for the generic COCO smoke model on the synthetic demo raster. -- Downloaded `keremberke/yolov8n-building-segmentation` from Hugging Face as an explicit Tower runtime artifact at `/mnt/user/appdata/geointel/models/yolov8n-building-segmentation.pt`. -- Recorded building-model checksum `152d6a9c5c76c9f2fd2fd5cc167efaed7c8c02e31002b15415899710f1d71f98`, matching the Hugging Face file metadata for `best.pt`. -- Applied `.env` with `YOLO_MODEL_PATH=/app/models/yolov8n-building-segmentation.pt` through `scripts/configure_yolo_model.py --model-file ... --apply`. -- Restarted the all-in-one container without rebuild; it remained healthy and published on `0.0.0.0:1202->80/tcp`. -- Live building-model preflight passed with `model_load_ok=true`, `dependencies_available=true`, `torch_version=2.12.1`, `ultralytics_version=8.4.89`, `will_download_models=false` and `will_run_inference=false`. -- Live building-model preflight with generated demo raster tile manifest passed with `status=ready`. -- Live real building-model YOLO inference smoke passed: `POST /api/v1/detection/run` returned `status=success`, analysis run `be609d4a-3e01-42df-bca8-0d5a2289120d`, job `9c8bc26d-7753-4537-ab98-dc31b9029450`, `detection_count=0` and no error code. Zero detections remains expected on the synthetic demo raster. - -Open: -- A local YOLO smoke model is now present and configured on Tower, but it is the generic COCO `yolov8n.pt` model. It proves the runtime path, not production-quality aerial building detection. - -Limitations: -- The bundled Tower model file was placed as an operator/runtime artifact under appdata, not committed to Git. -- The configured model is a generic COCO model and should be replaced by a suitable aerial/building detector for meaningful GIS output. -- The active configured model is now a building segmentation YOLO model trained for satellite-building segmentation, but it is still a third-party Hugging Face PyTorch `.pt` artifact and should be treated as an evaluation model until validated on local Belgian/Kempen orthophotos. -- No model download behavior was added to the application; the manual operator placement remains explicit. -- If multiple local model files are present, the operator must choose one with `--model-file` so GeoIntel does not silently activate the wrong model. - -Next recommended pass: -- Load a real georeferenced orthophoto/GeoTIFF for the target area, generate raster tiles, run the active building YOLO model and compare persisted detections against reference vector buildings through QA/QC. - -## Sprint 104 AI Lab action guardrails (2026-06-24) - -Changed: -- Added explicit action guardrails below the Detection Lab and Segmentation Lab run-readiness panels. -- Detection now distinguishes `configured` model registry state from UI-runnable action state, blocking the explicit test/demo-only `manual-fixture-detector` in the normal workbench run form. -- Segmentation now distinguishes `configured` model registry state from UI-runnable action state, blocking the explicit test/demo-only `fixture-segmenter` in the normal workbench run form. -- Updated run button disabled conditions to use the new readiness/action state. -- Added compact guardrail styling and regression coverage in `backend/tests/test_sprint104_ai_lab_action_guardrails.py`. -- Updated `CHANGELOG.md` and `docs/TODO.md`. - -Tested: -- Red step: `python -m pytest backend\tests\test_sprint104_ai_lab_action_guardrails.py -q` failed while the action guardrails and CSS contracts were absent. -- `python -m pytest backend\tests\test_sprint104_ai_lab_action_guardrails.py -q` (`3 passed`) -- `python -m pytest backend\tests\test_sprint103_ai_lab_run_readiness.py backend\tests\test_sprint104_ai_lab_action_guardrails.py -q` (`6 passed`) -- `python -m compileall backend/app` -- `cd backend && python -m pytest -q` (`330 passed`) -- `cd frontend && npm run typecheck` -- `cd frontend && npm run build` -- `bash scripts/run_readiness_check.sh` (`330 passed`; frontend typecheck/build passed; Alembic head `202606120900`; live smoke syntax passed) -- `cd backend && python -m alembic heads` (`202606120900 (head)`) -- `cd backend && python -m alembic upgrade head --sql` -- `bash -n scripts/live_migration_smoke.sh` -- Tower deploy from commit `0bc3b2f` completed; all-in-one container published on `0.0.0.0:1202->80/tcp`. -- Deploy-time live migration smoke passed after the database became ready on attempt 2; PostGIS reported `3.6 USE_GEOS=1 USE_PROJ=1 USE_STATS=1`, required runtime schema objects were present and Alembic head was `202606120900`. -- Deploy-time browser runtime verification passed for frontend, API proxy and icon. -- Live smoke passed: `bash scripts/verify_demo_raster_workflow.sh http://192.0.2.10:1202`. -- Live smoke passed: `bash scripts/verify_workbench_default_state.sh http://192.0.2.10:1202`. -- Live smoke passed: `bash scripts/verify_workbench_interactions.sh http://192.0.2.10:1202`. -- Live smoke passed: `bash scripts/verify_browser_runtime.sh http://192.0.2.10:1202`. -- Internal Codex browser validation passed against `http://192.0.2.10:1202`: AI Labs opened cleanly; run action guardrails rendered; Detection and Segmentation run buttons were disabled without a raster dataset; selecting explicit fixture models kept both run buttons disabled with `Fixture model is explicit test/demo-only` and `Fixture segmenter is explicit test/demo-only`; desktop and mobile viewports had no horizontal overflow and no console warnings/errors. - -Open: -- None for this pass. - -Limitations: -- Frontend action-guardrail guidance only; no backend API, persistence, migration, provider fetching, AI dependency or model execution behavior changed. - -Next recommended pass: -- Continue with V1 usability work that reduces operator confusion without expanding frozen product scope. - -## Sprint 142 Calibration evidence response uniqueness (2026-07-08) - -Changed: -- Hardened `scripts/export_detection_calibration_evidence.sh` so calibration evidence response files include both confidence threshold and quality-check id. -- Prevented same-threshold runs from different model assets or calibration jobs from overwriting each other before portfolio assembly. -- Extended the multi-AOI calibration evidence portfolio regression test with two Geel runs at the same threshold and distinct quality checks. - -Tested: -- Red step: `python -m pytest backend\tests\test_sprint139_multi_aoi_calibration_evidence_portfolio.py -q` failed because only two evidence features were retained when three same-threshold responses were expected. -- `python -m pytest backend\tests\test_sprint139_multi_aoi_calibration_evidence_portfolio.py backend\tests\test_sprint138_calibration_evidence_bundle_smoke.py backend\tests\test_sprint137_browser_calibration_summary_evidence_script.py backend\tests\test_sprint125_detection_calibration_evidence_bundle.py -q` (`4 passed`) -- `bash -n scripts/export_detection_calibration_evidence.sh` -- `bash -n scripts/assemble_detection_calibration_evidence_portfolio.sh` -- `python scripts\smoke_docs.py` -- `python -m compileall backend/app` -- `bash scripts/run_readiness_check.sh` (`418 passed`, frontend typecheck/build passed, Alembic head `202606120900`) -- Tower pulled commit `5314f16` and regenerated `/mnt/user/appdata/geointel/artifacts/detection-calibration-portfolio/positive-aoi-expanded-20260708/output`. -- The regenerated portfolio contains 7 samples, 38,007 evidence features and no missing model metadata. -- Best runs are now preserved across same-threshold model comparisons: Geel, Mol, Turnhout, Retie, Balen, Herentals and Westerlo all select `geointel-building-yolov8n-expanded160e50-pt` as their best scored run. -- Tower container remained healthy on `0.0.0.0:1202->80/tcp`. - -Open: -- The expanded160e50 model is consistently best on the current positive AOI portfolio, but hard-negative/background AOI evidence still prevents blind default promotion. -# Sprint 146 - Operator YOLO dataset quality audit - -## What changed - -- Added `scripts/audit_operator_yolo_dataset_quality.py` to inspect generated operator YOLO tile datasets before further model training. -- Added a focused pytest that creates a synthetic tile summary and YOLO label files, then verifies JSON/Markdown audit output and warning gates. -- Added the audit script to the readiness syntax gate. -- Documented the operator audit command in `scripts/README.md`. - -## What was tested - -- `python -m pytest backend\tests\test_sprint146_operator_yolo_dataset_quality_audit.py -q` -- `bash scripts/run_readiness_check.sh` -- Tower live audit after pulling commit `5898e54`: - - `yolo-building-tile-dataset`: `needs_attention`; only 3 positive samples and no background negatives. - - `yolo-building-tile-expanded160`: `ok`; 10 samples, 8 positive samples, 360 tiles, 11,213 labels, no missing/invalid label rows. - - `yolo-building-tile-hardneg160r4`: `needs_attention`; repeated background negatives are 91.1% of negative tiles. - - `yolo-building-tile-hardneg160r8`: `needs_attention`; repeated background negatives are 95.4% of negative tiles. - -## Known limitations - -- The audit is evidence tooling only. It does not modify datasets, train models, fetch external data or change active YOLO configuration. -- The report flags likely dataset risks, but final promotion decisions must still come from persisted detection QA/QC matrices and hard-negative benchmarks. - -## Next recommended pass - -- Add more unique hard-negative/background AOIs before another hard-negative training run. The current label files are clean, so the bottleneck is dataset diversity and balance rather than label-file corruption. - -# Sprint 147 - Unique hard-negative AOI expansion - -## What changed - -- Expanded `scripts/prepare_operator_real_data_samples.py` with six additional explicit background-candidate AOIs: Dessel-heide, Ravels-bos, Meerhout-bos, Geel-Bel, Arendonk-heide and Herenthout-bos. -- Background candidates remain operator/runtime samples only. They are not product providers, not fixtures and not automatic app fetches. -- Added sample-registry test coverage for minimum unique background count, unique centers and regional spread. -- Updated operator documentation with the expanded default corpus and the next required Tower regeneration step. -- Fixed the all-in-one Dockerfile so the documented operator scripts are copied into `/app/scripts/` during normal rebuilds. -- Fixed the all-in-one Dockerfile training-runtime gap so `/app/scripts/train_operator_yolo_detector.sh` is also copied into the rebuilt container and marked executable. -- Fixed `scripts/yolo_preflight.py` so it respects `YOLO_ENABLED`, `YOLO_MODEL_PATH` and `YOLO_MAX_TILES` from the runtime environment unless explicit CLI overrides are supplied. -- Prepared the expanded Tower operator manifest and exported `yolo-building-tile-uniquehardneg160`. - -## What was tested - -- `python -m pytest backend\tests\test_sprint131_operator_sample_expansion.py -q` -- `python -m pytest backend\tests\test_sprint127_operator_sample_quality_matrix.py backend\tests\test_sprint131_operator_sample_expansion.py -q` -- `python -m pytest backend\tests\test_sprint13_yolo_preflight.py -q` -- Red/green Docker runtime guard for the training wrapper: `python -m pytest backend\tests\test_docker_runtime_config.py::test_all_in_one_dockerfile_copies_operator_scripts_for_runtime_use -q` -- `python -m pytest backend\tests\test_docker_runtime_config.py -q` -- `bash scripts/run_readiness_check.sh` -- Tower live operator sample prep: - - manifest samples: 16 total, 7 reference and 9 background candidates. - - background candidate GRB feature counts: Postel-bos 0, Lommel-heide 0, Kasterlee-bos 7, Dessel-heide 30, Ravels-bos 3, Meerhout-bos 20, Geel-Bel 17, Arendonk-heide 0, Herenthout-bos 90. -- Tower live tile export and audit for `yolo-building-tile-uniquehardneg160`: - - status `ok` - - 576 tiles, 346 positive, 230 negative - - 16 samples, 13 positive samples, 9 background samples - - 11,757 labels, 0 missing label files, 0 invalid label rows - - repeated background negative share 0.0 -- Tower all-in-one rebuild from commit `f949347` with `GEOINTEL_INSTALL_AI=true`: - - live migration smoke passed. - - browser runtime verification passed on `http://192.0.2.10:1202`. - - `/app/scripts/prepare_operator_real_data_samples.py`, `/app/scripts/export_operator_yolo_tile_dataset.py` and `/app/scripts/audit_operator_yolo_dataset_quality.py` are present in the rebuilt container. - - YOLO preflight with an existing raster tile manifest returned `status: ready`, `dependencies_available: true`, `model_file_exists: true`, `tile_paths_exist: true`, `will_download_models: false` and `will_run_inference: false`. - -## Known limitations - -- Some background candidates contain real GRB buildings. They are still useful as mixed rural/background samples, but the pure negative pressure currently comes mostly from Postel-bos, Lommel-heide and Arendonk-heide plus empty tiles inside sparse candidates. -- The rebuilt Tower image now contains the operator scripts automatically. The generated `yolo-building-tile-uniquehardneg160` dataset is ready for a controlled training candidate, but no model has been promoted from it yet. - -## Next recommended pass - -- Use `yolo-building-tile-uniquehardneg160` as the next safer hard-negative training dataset candidate. Benchmark after training before changing defaults. - -# Sprint 152 - GRB reference paging for operator samples - -## What changed - -- Fixed `scripts/prepare_operator_real_data_samples.py` so GRB GBG reference exports follow OGC API `rel=next` pagination links instead of silently trusting only the first `limit=1000` page. -- Added operator controls: - - `--reference-page-limit` / `OPERATOR_GRB_PAGE_LIMIT`, default `1000`. - - `--reference-max-features` / `OPERATOR_GRB_MAX_FEATURES`, default `100000`. -- Generated reference GeoJSON now records `source_urls`, `reference_pages_fetched`, `reference_truncated`, `reference_page_limit` and `reference_max_features`. -- Kept the change operator-only: no GeoIntel API route calls this helper, no product provider endpoint changed, no live GRB/OSM import was added, no migration changed and no YOLO model was activated. - -## What was tested - -- RED: `python -m pytest backend\tests\test_sprint131_operator_sample_expansion.py::test_fetch_reference_follows_grb_next_links_until_complete -q` failed because only the first GRB page was persisted. -- GREEN: `python -m pytest backend\tests\test_sprint131_operator_sample_expansion.py::test_fetch_reference_follows_grb_next_links_until_complete -q` -- `python -m pytest backend\tests\test_sprint127_operator_sample_quality_matrix.py backend\tests\test_sprint131_operator_sample_expansion.py -q` -- `python -m py_compile scripts\prepare_operator_real_data_samples.py` -- `bash scripts/run_readiness_check.sh` -- Local live GRB paging smoke with `page_limit=2` and `max_features=5` fetched 3 source pages, returned 5 features and correctly marked `reference_truncated=true`. -- Tower deploy from commit `a63d4ea` passed live migration smoke and browser runtime verification on `http://192.0.2.10:1202`. -- Tower one-sample Geel AOI1024 paging smoke passed with `/opt/geointel/venv/bin/python` and produced 2,268 GRB reference features instead of the old 1,000-feature cap. -- Tower full AOI1024 operator sample regeneration passed: - - Geel: 2,268 features, 3 GRB pages, not truncated. - - Mol: 1,993 features, 2 GRB pages, not truncated. - - Turnhout: 3,278 features, 4 GRB pages, not truncated. - - Herentals: 2,478 features, 3 GRB pages, not truncated. - - Balen: 1,343 features, 2 GRB pages, not truncated. - - Retie: 1,734 features, 2 GRB pages, not truncated. - - Westerlo: 1,133 features, 2 GRB pages, not truncated. -- Re-exported `/app/storage/operator-data/yolo-building-aoi1024-visible025` from the regenerated paged references: - - 144 tiles, 117 positive tiles, 27 negative tiles, 29,170 labels. - - `min_label_visible_ratio=0.25`, `negative_keep_ratio=1.0`. -- Re-ran the Tower dataset audit: - - output: `/app/storage/operator-data/yolo-building-aoi1024-visible025-audit/operator_yolo_dataset_quality_audit.json` - - status remains `needs_attention` - - missing label files: 0 - - invalid labels: 0 - - median normalized box area: `0.000762939453125` - - small-box share: `0.34744600617072335` - - repeated background negative share: 0.0 - -## Known limitations - -- The Tower AOI1024 operator samples and tile dataset have now been regenerated from paged GRB references, but the tile audit still reports `needs_attention` because small clipped boxes remain common. -- This does not make the Sprint 7B GRB provider a live product importer; it only fixes explicit operator sample preparation. - -## Next recommended pass - -- Before another training run, improve label quality: either raise `--min-label-visible-ratio`, increase tile size, reduce dense clipped-edge tiles or add cleaner AOIs. Do not activate or retrain from this dataset as-is without acknowledging the small-box warning. - -# Sprint 151 - Runtime GIS upload and AOI1024 YOLO candidate - -## What changed - -- Fixed `scripts/train_operator_yolo_detector.sh` so the all-in-one image uses `/opt/geointel/venv/bin/python` by default when that AI venv exists. Explicit `PYTHON_BIN` still wins, and local shells still fall back to `python3`. -- Raised the Nginx request body limit to `250m` in both `frontend/nginx.conf` and `deploy/unraid/nginx-all-in-one.conf` after the live 1024px GeoTIFF upload path returned `413 Request Entity Too Large`. -- Raised Nginx proxy read/send timeouts to `600s` after the live low-threshold persisted YOLO/QA path reached `504 Gateway Timeout`. -- Kept the change runtime-only: no API contract, persistence model, migration, model-download behavior or default model selection changed. - -## What was tested - -- Red/green TDD guard for the training wrapper fallback: - - `python -m pytest backend\tests\test_sprint129_operator_yolo_training_dataset.py -q` -- Red/green TDD guard for real GIS upload payload support: - - `python -m pytest backend\tests\test_docker_runtime_config.py::test_nginx_runtime_allows_real_gis_upload_payloads -q` -- Red/green TDD guard for long AI/QA proxy requests: - - `python -m pytest backend\tests\test_docker_runtime_config.py::test_nginx_runtime_allows_long_ai_and_qa_requests -q` -- `bash -n scripts/train_operator_yolo_detector.sh` -- Tower live model training on `/app/storage/operator-data/yolo-building-aoi1024-visible025`: - - output model: `/app/models/geointel-building-yolov8s-aoi1024visible025e50.pt` - - model asset id: `geointel-building-yolov8s-aoi1024visible025e50-pt` - - final Ultralytics validation: precision approximately `0.275`, recall `0.331`, mAP50 `0.188`, mAP50-95 `0.0716` -- Tower live runtime validation after deploy: - - browser/runtime verification passed on `http://192.0.2.10:1202` - - the previous Geel 1024px upload `413` no longer occurs - - the previous Geel low-threshold persisted YOLO/QA `504` no longer occurs - - Geel `threshold=0.05` completed with 2,612 detections, 5,091 raw candidates, 2,479 suppressed duplicates, precision `0.06316998468606431`, recall `0.165` and F1 `0.09136212624584718` -- Full AOI1024 positive persisted QA matrix: - - Geel best F1: `0.09136212624584718` at threshold `0.05` - - Turnhout best F1: `0.058721074894252295` at threshold `0.05` - - Retie best F1: `0.15621436716077539` at threshold `0.15` - - Westerlo best F1: `0.28703703703703703` at threshold `0.15` -- Full AOI1024 hard-negative/background matrix: - - pure empty Postel/Lommel/Arendonk samples stayed at or near zero detections - - mixed background candidates still produced false-positive pressure: max detections were `59` at threshold `0.25`, `107` at `0.15` and `226` at `0.05` -- Fixed `scripts/build_detection_model_promotion_report.py` after discovering it accepted `multi_sample_quality_summary.json` but counted positive samples as `0`. The report now supports both `samples[].runs[]` portfolios and `items[]` multi-sample summaries. -- AOI1024 promotion report path: `artifacts/detection-model-promotion/aoi1024visible025e50-full/detection_model_promotion_report.md`; recommendation remains `none`. -- Corrected AOI1024 promotion decision after parser fix: - - threshold `0.05`: 4 positive samples, 9 background samples, mean F1 `0.13307746028311157`, max background detections `226` - - threshold `0.15`: 4 positive samples, 9 background samples, mean F1 `0.13900227809255514`, max background detections `107` - - threshold `0.25`: 4 positive samples, 9 background samples, mean F1 `0.09694707724016788`, max background detections `59` - -## Known limitations - -- The AOI1024 tile audit is still `needs_attention`: median normalized box area is below gate and small-box share remains high. -- Several dense 1024 GRB reference exports reached the current 1000-feature source cap. Treat those samples as useful but potentially reference-capped until the provider query path supports paging or smaller dense AOIs are chosen. -- The trained model is intentionally inactive. It needs persisted detection QA/QC matrix evidence and background/hard-negative evidence before default promotion. -- The first completed persisted Geel QA run confirms the candidate is not promotion-ready: recall improves at low threshold, but false-positive pressure is too high. -- The complete positive/background evidence confirms the candidate is not promotion-ready. The bottleneck is label/source quality and sample design, not runtime configuration. - -## Next recommended pass - -- Fix dense GRB reference completeness first: add provider-side paging or split dense AOIs so reference exports do not cap at 1000 features, then regenerate AOI1024 labels before another training run. - -# Sprint 153 - AOI1024 clean-label YOLOv8s candidate gate - -## What changed - -- Built and audited AOI1024 label-quality candidate exports on Tower after the paged GRB reference regeneration: - - baseline `yolo-building-aoi1024-visible025`: 144 tiles, 117 positive, 27 negative, 29,170 labels, audit `needs_attention`, median normalized box area `0.000762939453125`, small-box share `0.34744600617072335`. - - `yolo-building-aoi1024-visible050`: 144 tiles, 117 positive, 27 negative, 28,552 labels, audit `needs_attention`, small-box share `0.34463435135892406`. - - `yolo-building-aoi1024-visible025-tile640`: 45,529 labels, audit `needs_attention`, small-box share `0.4952667530584902`. - - `yolo-building-aoi1024-visible025-tile384`: 400 tiles, 311 positive, 89 negative, 46,423 labels, audit `ok`, small-box share `0.215281218361588`. - - `yolo-building-aoi1024-visible050-minpx8`: 144 tiles, 117 positive, 27 negative, 21,530 labels, audit `ok`, median normalized box area `0.0010299684375`, small-box share `0.14681839294008361`. -- Selected `/app/storage/operator-data/yolo-building-aoi1024-visible050-minpx8` for the next controlled candidate because it passes the label audit while preserving the 512px runtime scale. -- Trained Tower-local inactive model asset: - - model path: `/app/models/geointel-building-yolov8s-aoi1024clean512e50.pt` - - asset id: `geointel-building-yolov8s-aoi1024clean512e50-pt` - - SHA256: `7cfadb684dd56623d2e35ebd65593211d3051908c87121bef438b231d3e47cce` - - training summary: `/app/storage/training/operator-yolo/geointel-building-yolov8s-aoi1024clean512e50/training_summary.json` - - base model: `/app/models/yolov8s.pt` - - epochs: 50 - - image size: 512 - - batch size: 2 - - device: CPU - - final Ultralytics validation on `best.pt`: precision `0.441`, recall `0.380`, mAP50 `0.265`, mAP50-95 `0.096`. -- Verified the live model catalog reports the candidate as `status=available`, `active=false` and `will_download_models=false`. - -## What was tested - -- Tower training command: - - `docker exec -e OPERATOR_YOLO_DATASET_DIR=/app/storage/operator-data/yolo-building-aoi1024-visible050-minpx8 -e YOLO_BASE_MODEL_PATH=/app/models/yolov8s.pt -e TRAIN_OUTPUT_DIR=/app/storage/training/operator-yolo -e TRAIN_RUN_NAME=geointel-building-yolov8s-aoi1024clean512e50 -e TRAIN_MODEL_OUTPUT_PATH=/app/models/geointel-building-yolov8s-aoi1024clean512e50.pt -e TRAIN_EPOCHS=50 -e TRAIN_IMGSZ=512 -e TRAIN_BATCH=2 -e TRAIN_WORKERS=0 -e TRAIN_DEVICE=cpu geointel bash /app/scripts/train_operator_yolo_detector.sh` -- Full seven-reference AOI1024 persisted positive QA matrix: - - command used `scripts/run_multi_sample_detection_quality_matrix.sh` with manifest `/mnt/user/appdata/geointel/storage/operator-data/operator-samples-1024/operator_samples_manifest.json`, samples `geel mol turnhout herentals balen retie westerlo`, model `geointel-building-yolov8s-aoi1024clean512e50-pt`, tile `512`, overlap `64`, thresholds `0.25 0.15 0.05` and IoU threshold `0.25`. - - output: `/mnt/user/appdata/geointel/artifacts/detection-quality-matrix/multi-sample/aoi1024clean512e50-full/multi_sample_quality_summary.json` - - threshold `0.05`: 7 positive samples, mean F1 `0.4723513253430784`, mean precision `0.44861169484563357`, mean recall `0.5039340859731523`, min F1 `0.4442082890541977`. - - threshold `0.15`: 7 positive samples, mean F1 `0.4753322215541376`, mean precision `0.6673270868402211`, mean recall `0.37207511021815726`, min F1 `0.4055555555555556`. - - threshold `0.25`: 7 positive samples, mean F1 `0.31021575247724875`, mean precision `0.8163316419273472`, mean recall `0.19608909809008596`, min F1 `0.16430903155603915`. -- Full nine-sample hard-negative/background matrix: - - command used `scripts/run_operator_hard_negative_detection_matrix.sh` with the same AOI1024 manifest, model `geointel-building-yolov8s-aoi1024clean512e50-pt`, tile `512`, overlap `64` and thresholds `0.25 0.15 0.05`. - - output: `/mnt/user/appdata/geointel/artifacts/detection-hard-negatives/aoi1024clean512e50-full/hard_negative_matrix_summary.json` - - threshold `0.05`: total background detections `488`, max sample detections `137`. - - threshold `0.15`: total background detections `269`, max sample detections `75`. - - threshold `0.25`: total background detections `205`, max sample detections `55`. -- Promotion report: - - command used `scripts/build_detection_model_promotion_report.py` with `--min-positive-samples 7`, `--min-background-samples 9`, `--min-mean-f1 0.25` and `--max-background-detections-per-sample 0`. - - output: `/mnt/user/appdata/geointel/artifacts/detection-model-promotion/aoi1024clean512e50-full/detection_model_promotion_report.md` - - recommendation: `none`. - -## Known limitations - -- The clean-label model is materially stronger on positive reference AOIs than the previous AOI1024-visible025 candidate, but it is still not safe as a V1 default because hard-negative/background false positives remain high in mixed wooded AOIs. -- The likely bottleneck has shifted from label-file integrity to discriminating buildings from visually similar background structures and wooded-edge artifacts. -- The model remains inactive. No default model, API contract, migration, provider fetching or download behavior changed. - -## Next recommended pass - -- Build a background-aware training pass instead of another positive-only clean-label pass: combine the `visible050-minpx8` positives with stronger unique hard-negative/background retention, then re-run the same seven-positive/nine-background promotion gate before any activation. - -# Sprint 154 - Background-aware AOI1024 YOLOv8s candidate gate - -## What changed - -- Built a background-aware AOI1024 tile dataset on Tower from the clean positive labels plus explicit background retention: - - dataset path: `/app/storage/operator-data/yolo-building-aoi1024-bgaware512r3` - - audit path: `/mnt/user/appdata/geointel/storage/operator-data/yolo-building-aoi1024-bgaware512r3-audit/operator_yolo_dataset_quality_audit.json` - - tile count: `162` - - positive tiles: `117` - - negative tiles: `45` - - label count: `21530` - - background negative repeat: `3` - - audit status: `ok` - - warnings: `[]` -- Trained Tower-local inactive model asset: - - model path: `/app/models/geointel-building-yolov8s-aoi1024bg512r3e50.pt` - - asset id: `geointel-building-yolov8s-aoi1024bg512r3e50-pt` - - SHA256: `e0980572aac90e7efc514608eb16d7de5bfbf27a4bbec04e7bc1bc8c02f9601f` - - training summary: `/app/storage/training/operator-yolo/geointel-building-yolov8s-aoi1024bg512r3e50/training_summary.json` - - base model: `/app/models/yolov8s.pt` - - epochs: `50` - - image size: `512` - - batch size: `2` - - device: CPU - - final Ultralytics validation on `best.pt`: precision `0.440`, recall `0.362`, mAP50 `0.251`, mAP50-95 `0.0878`. -- Verified the live model catalog reports the candidate as `status=available`, `active=false` and `will_download_models=false`. -- No API contract, migration, provider fetching, fake detection data, model download behavior or active model default changed. - -## What was tested - -- Tower training command: - - `docker exec -e OPERATOR_YOLO_DATASET_DIR=/app/storage/operator-data/yolo-building-aoi1024-bgaware512r3 -e YOLO_BASE_MODEL_PATH=/app/models/yolov8s.pt -e TRAIN_OUTPUT_DIR=/app/storage/training/operator-yolo -e TRAIN_RUN_NAME=geointel-building-yolov8s-aoi1024bg512r3e50 -e TRAIN_MODEL_OUTPUT_PATH=/app/models/geointel-building-yolov8s-aoi1024bg512r3e50.pt -e TRAIN_EPOCHS=50 -e TRAIN_IMGSZ=512 -e TRAIN_BATCH=2 -e TRAIN_WORKERS=0 -e TRAIN_DEVICE=cpu geointel bash /app/scripts/train_operator_yolo_detector.sh` -- Full seven-reference AOI1024 persisted positive QA matrix: - - command used `scripts/run_multi_sample_detection_quality_matrix.sh` with manifest `/mnt/user/appdata/geointel/storage/operator-data/operator-samples-1024/operator_samples_manifest.json`, samples `geel mol turnhout herentals balen retie westerlo`, model `geointel-building-yolov8s-aoi1024bg512r3e50-pt`, tile `512`, overlap `64`, thresholds `0.25 0.15 0.05` and IoU threshold `0.25`. - - output: `/mnt/user/appdata/geointel/artifacts/detection-quality-matrix/multi-sample/aoi1024bg512r3e50-full/multi_sample_quality_summary.json` - - threshold `0.05`: 7 positive samples, mean F1 `0.4908049127242224`, mean precision `0.468604`, mean recall `0.520016`, total detections `15277`. - - threshold `0.15`: 7 positive samples, mean F1 `0.5074022485589402`, mean precision `0.636639`, mean recall `0.424258`, total detections `9186`. - - threshold `0.25`: 7 positive samples, mean F1 `0.44378879337957716`, mean precision `0.762683`, mean recall `0.316314`, total detections `5584`. -- Conservative seven-reference AOI1024 persisted positive QA matrix: - - command used the same manifest/model/tile/overlap with thresholds `0.35 0.45 0.60`. - - output: `/mnt/user/appdata/geointel/artifacts/detection-quality-matrix/multi-sample/aoi1024bg512r3e50-high-threshold/multi_sample_quality_summary.json` - - threshold `0.35`: 7 positive samples, mean F1 `0.32086574003576274`, mean precision `0.840006`, mean recall `0.202135`, total detections `3106`. - - threshold `0.45`: 7 positive samples, mean F1 `0.20093433626447627`, mean precision `0.885043`, mean recall `0.116348`, total detections `1592`. - - threshold `0.60`: 7 positive samples, mean F1 `0.06640476239173489`, mean precision `0.871611`, mean recall `0.035083`, total detections `418`. -- Full nine-sample hard-negative/background matrix: - - command used `scripts/run_operator_hard_negative_detection_matrix.sh` with the AOI1024 manifest, model `geointel-building-yolov8s-aoi1024bg512r3e50-pt`, tile `512`, overlap `64` and thresholds `0.25 0.15 0.05`. - - output: `/mnt/user/appdata/geointel/artifacts/detection-hard-negatives/aoi1024bg512r3e50-full/hard_negative_matrix_summary.json` - - threshold `0.05`: total background detections `638`, max sample detections `184`. - - threshold `0.15`: total background detections `390`, max sample detections `103`. - - threshold `0.25`: total background detections `278`, max sample detections `75`. -- Conservative nine-sample hard-negative/background matrix: - - output: `/mnt/user/appdata/geointel/artifacts/detection-hard-negatives/aoi1024bg512r3e50-high-threshold/hard_negative_matrix_summary.json` - - threshold `0.35`: total background detections `198`, max sample detections `55`. - - threshold `0.45`: total background detections `148`, max sample detections `38`. - - threshold `0.60`: total background detections `76`, max sample detections `18`. -- Promotion reports: - - balanced thresholds report: `/mnt/user/appdata/geointel/artifacts/detection-model-promotion/aoi1024bg512r3e50-full/detection_model_promotion_report.md` - - conservative thresholds report: `/mnt/user/appdata/geointel/artifacts/detection-model-promotion/aoi1024bg512r3e50-high-threshold/detection_model_promotion_report.md` - - recommendation: `none`. - -## Known limitations - -- The background-aware model is the strongest positive-AOI candidate so far and is usable as an explicit review/demo candidate, especially at threshold `0.15` for balance or `0.35` for conservative high-precision review. -- It is still not safe as a V1 default because the full background-candidate gate fails `background_false_positive_pressure`. -- Some `background_candidate` AOIs contain GRB reference buildings and should be split into pure-empty negatives versus sparse-positive contextual samples before the next gate; otherwise the hard-negative score remains intentionally conservative but not perfectly diagnostic. -- The model remains inactive. Operators can select it explicitly from the local model asset catalog. - -## Next recommended pass - -- Build a V1 operator detection profile layer in the UI/docs: expose `balanced` (`threshold=0.15`) and `conservative review` (`threshold=0.35`) as explicit choices for local model assets, with clear warning that the model is not a default-approved detector. -- Clean the background corpus classification: separate pure-empty AOIs from sparse-building contextual AOIs, then retrain or recalibrate against that cleaner gate. - -# Sprint 155 - Detection operator profiles - -## What changed - -- Added `frontend/src/components/detection/detectionProfiles.ts` with explicit operator profiles for the inactive `geointel-building-yolov8s-aoi1024bg512r3e50-pt` local model asset. -- Exposed two deliberate Detection Lab actions: - - `balanced-review`: confidence threshold `0.15`, positive-AOI F1 `0.5074022485589402`, precision `0.636639`, recall `0.424258`, max background detections `103`. - - `conservative-review`: confidence threshold `0.35`, positive-AOI F1 `0.32086574003576274`, precision `0.840006`, recall `0.202135`, max background detections `55`. -- Applying a profile selects `yolo-configured`, the local model asset id and the profile threshold. It does not auto-select assets on model catalog load and does not promote the candidate as a default detector. -- Detection Lab now marks both profiles as `Candidate only - not default-approved` because the promotion recommendation remains `none`. -- Updated frontend, AI pipeline and TODO documentation. - -## What was tested - -- Added regression coverage in `backend/tests/test_sprint155_detection_operator_profiles.py`. -- Ran `python -m pytest tests/test_sprint155_detection_operator_profiles.py tests/test_sprint122_model_asset_activation_guardrails.py -q`. -- Ran `python -m pytest` in `backend`: 435 passed. -- Ran `python -m compileall backend/app`. -- Ran `cd frontend && npm run typecheck`. -- Ran `cd frontend && npm run build`. -- Ran `bash scripts/run_readiness_check.sh`. -- Ran `cd backend && python -m alembic heads` and `cd backend && python -m alembic upgrade head --sql`. -- Ran `bash -n scripts/live_migration_smoke.sh`. - -## Known limitations - -- The profiles are review/demo aids only. The background corpus still needs to be split into pure-empty negatives and sparse-building contextual AOIs before retraining or recalibrating for a default detector decision. -- No backend API contract, migration, provider fetching, fake detection output, model download behavior or active runtime default changed. - -# Sprint 156 - Background corpus classification - -## What changed - -- Added explicit background category classification to operator sample preparation: - - `pure_empty_negative` when a background candidate has zero GRB reference buildings. - - `sparse_building_context` when a background candidate has one or more GRB reference buildings. - - `reference_aoi` for normal positive reference samples. -- Persisted `background_category` into generated operator sample manifests and reference GeoJSON metadata. -- Added `OPERATOR_BACKGROUND_CATEGORIES` to `scripts/run_operator_hard_negative_detection_matrix.sh` so the strict default-promotion hard-negative gate can run only on `pure_empty_negative` samples, while `sparse_building_context` samples can be reviewed separately. -- Preserved `background_category` in YOLO tile export metadata so negative-tile provenance survives training dataset audits. -- Updated operator pipeline docs, TODO and changelog. - -## What was tested - -- Added regression coverage in `backend/tests/test_sprint156_background_corpus_classification.py`. -- Ran `python -m pytest tests/test_sprint156_background_corpus_classification.py -q`. -- Ran `python -m pytest tests/test_sprint156_background_corpus_classification.py tests/test_sprint131_operator_sample_expansion.py tests/test_sprint132_operator_hard_negative_matrix.py tests/test_sprint130_operator_yolo_tile_dataset.py -q`: 17 passed. -- Ran `python -m compileall backend/app`. -- Ran `python -m pytest` in `backend`: 439 passed. -- Ran `cd frontend && npm run typecheck`. -- Ran `cd frontend && npm run build`. -- Ran `bash scripts/run_readiness_check.sh`. -- Ran `cd backend && python -m alembic heads` and `cd backend && python -m alembic upgrade head --sql`. -- Ran `bash -n scripts/live_migration_smoke.sh` and `bash -n scripts/run_operator_hard_negative_detection_matrix.sh`. - -## Known limitations - -- This pass adds the cleaner corpus/gate contract only. It does not regenerate Tower manifests, retrain YOLO, rerun the live hard-negative matrices or change any model default. -- No backend API contract, database migration, provider fetching, fake detection output or model download behavior changed. - -## Next recommended pass - -- Redeploy/rebuild the runtime scripts, regenerate the operator sample manifest, then run: - - `OPERATOR_BACKGROUND_CATEGORIES="pure_empty_negative"` for the strict default-promotion false-positive gate. - - `OPERATOR_BACKGROUND_CATEGORIES="sparse_building_context"` for contextual review evidence. -- Retrain or recalibrate the inactive AOI1024 local model candidate only after those two matrices are available. - -# Sprint 157 - Background split matrix runner - -## What changed - -- Added `scripts/run_background_corpus_split_matrix.sh` as the operator wrapper for the next Tower run. -- The wrapper runs `scripts/run_operator_hard_negative_detection_matrix.sh` twice: - - `OPERATOR_BACKGROUND_CATEGORIES="pure_empty_negative"` for the strict default-promotion false-positive gate. - - `OPERATOR_BACKGROUND_CATEGORIES="sparse_building_context"` for review-only contextual evidence. -- Added `scripts/build_background_corpus_split_report.py` to combine both summaries into: - - `background_corpus_split_summary.json` - - `background_corpus_split_summary.md` -- The combined report records `strict_default_gate`, `context_review`, `passes_zero_detection_gate`, max detection counts and the recommended next step. -- Added readiness coverage for the new Python and Bash scripts. -- Updated operator pipeline docs, TODO and changelog. - -## What was tested - -- Added regression coverage in `backend/tests/test_sprint157_background_split_matrix_runner.py`. -- Ran `python -m pytest tests/test_sprint157_background_split_matrix_runner.py -q`. -- Ran `python -m pytest tests/test_sprint157_background_split_matrix_runner.py tests/test_sprint156_background_corpus_classification.py tests/test_sprint132_operator_hard_negative_matrix.py -q`: 9 passed. -- Ran `python -m py_compile scripts/build_background_corpus_split_report.py`. -- Ran `bash -n scripts/run_background_corpus_split_matrix.sh`. -- Ran `python -m compileall backend/app`. -- Ran `python -m pytest` in `backend`: 443 passed. -- Ran `cd frontend && npm run typecheck`. -- Ran `cd frontend && npm run build`. -- Ran `bash scripts/run_readiness_check.sh`. -- Ran `cd backend && python -m alembic heads` and `cd backend && python -m alembic upgrade head --sql`. -- Ran `bash -n scripts/live_migration_smoke.sh` and `bash -n scripts/run_background_corpus_split_matrix.sh`. - -## Known limitations - -- This pass adds orchestration/report tooling only. It does not run live inference on Tower, retrain YOLO, rerun the split matrices or change any model default. -- No backend API contract, database migration, provider fetching, fake detection output or model download behavior changed. - -## Next recommended pass - -- Rebuild/redeploy the runtime, regenerate the operator manifest if needed, then run `scripts/run_background_corpus_split_matrix.sh` against `http://192.0.2.10:1202`. -- Use the emitted split report to decide whether to retrain, recalibrate thresholds or keep the AOI1024 candidate operator-only. - -# Sprint 158 - Split-aware promotion report - -## What changed - -- Added `--background-split-summary` support to `scripts/build_detection_model_promotion_report.py`. -- The promotion report now resolves a split report's `pure_empty_negative` source summary as the strict default-promotion background gate. -- The same report records `sparse_building_context` as review-only evidence, including source path and detection-pressure context, without counting it as a default-promotion blocker. -- Kept direct `--hard-negative-summary` support unchanged for older operator workflows. -- Updated operator pipeline docs, TODO and changelog. - -## What was tested - -- Red step: `python -m pytest tests/test_sprint158_promotion_report_split_background.py -q` failed because the promotion report required `--hard-negative-summary` and did not yet accept `--background-split-summary`. -- Ran `python -m pytest tests/test_sprint158_promotion_report_split_background.py -q`: 1 passed. -- Ran `python -m pytest tests/test_sprint143_detection_model_promotion_report.py tests/test_sprint157_background_split_matrix_runner.py -q`: 7 passed. -- Ran `python -m py_compile scripts/build_detection_model_promotion_report.py scripts/build_background_corpus_split_report.py`. -- Ran `python -m pytest tests/test_sprint158_promotion_report_split_background.py tests/test_sprint143_detection_model_promotion_report.py tests/test_sprint157_background_split_matrix_runner.py -q`: 8 passed. -- Ran `python -m compileall backend/app`. -- Ran `python -m pytest` in `backend`: 444 passed, 17 existing Pydantic namespace warnings. -- Ran `cd frontend && npm run typecheck`. -- Ran `cd frontend && npm run build`. -- Ran `bash scripts/run_readiness_check.sh`: passed. -- Ran `cd backend && python -m alembic heads`: `202606120900 (head)`. -- Ran `cd backend && python -m alembic upgrade head --sql`. -- Ran `bash -n scripts/live_migration_smoke.sh`. - -## Known limitations - -- This pass is report/tooling only. It does not run live split matrices on Tower, retrain YOLO, change a model default, change API contracts, change migrations, fetch providers, download model weights or create fake detections. -- The AOI1024 background-aware local model remains explicit operator-review only until the split matrices plus positive-AOI QA/QC evidence pass the documented gates. - -## Next recommended pass - -- After redeploy, run `scripts/run_background_corpus_split_matrix.sh` on Tower for `geointel-building-yolov8s-aoi1024bg512r3e50-pt`. -- Feed the generated `background_corpus_split_summary.json` into `scripts/build_detection_model_promotion_report.py --background-split-summary` together with the seven-AOI positive summary. -- If pure-empty false-positive pressure still fails, retrain or recalibrate before any default activation. If pure-empty passes, inspect sparse-context review evidence before deciding whether to keep the model operator-only or prepare a guarded default-candidate decision. - -# Sprint 159 - Split-background promotion workflow wrapper - -## What changed - -- Added `scripts/run_split_background_promotion_workflow.sh`. -- The wrapper runs `scripts/run_background_corpus_split_matrix.sh`, verifies the emitted `background_corpus_split_summary.json`, then calls `scripts/build_detection_model_promotion_report.py --background-split-summary`. -- The wrapper requires `PROMOTION_POSITIVE_PORTFOLIO_PATH` and exposes promotion gate overrides through environment variables. -- Added readiness syntax coverage for the new wrapper. -- Updated operator pipeline docs, TODO and changelog. - -## What was tested - -- Red step: `python -m pytest tests/test_sprint159_split_promotion_workflow.py -q` failed because the wrapper script and readiness syntax check did not exist. -- Ran `python -m pytest tests/test_sprint159_split_promotion_workflow.py -q`: 2 passed. -- Ran `bash -n scripts/run_split_background_promotion_workflow.sh`. -- Ran `python -m pytest tests/test_sprint159_split_promotion_workflow.py tests/test_sprint158_promotion_report_split_background.py tests/test_sprint157_background_split_matrix_runner.py -q`: 7 passed. -- Ran `bash -n scripts/run_readiness_check.sh`. -- Ran `python -m compileall backend/app`. -- Ran `python -m pytest` in `backend`: 446 passed, 17 existing Pydantic namespace warnings. -- Ran `cd frontend && npm run typecheck`. -- Ran `cd frontend && npm run build`. -- Ran `cd backend && python -m alembic heads`: `202606120900 (head)`. -- Ran `cd backend && python -m alembic upgrade head --sql`. -- Ran `bash -n scripts/live_migration_smoke.sh`. -- Ran `bash scripts/run_readiness_check.sh`: passed. - -## Known limitations - -- This pass adds operator orchestration only. It does not run live inference locally, retrain YOLO, activate a model default, change backend API contracts, change migrations, fetch providers, fetch weights or create fake detections. -- `http://192.0.2.10:1202` is reachable from this workstation, but `ssh -p 222 root@192.0.2.10` returned `Permission denied (publickey)`. Port `222` appears to be the Gitea SSH endpoint rather than an Unraid shell endpoint, so Docker rebuild/restart still needs the existing Unraid deployment path or a separate shell-access route. - -## Next recommended pass - -- Redeploy/pull commit on Tower through the existing Gitea/Unraid flow. -- Run: - - `PROMOTION_POSITIVE_PORTFOLIO_PATH=... bash scripts/run_split_background_promotion_workflow.sh http://192.0.2.10:1202` -- Review the generated split-aware promotion report before any retraining, recalibration or default-model decision. - -# Sprint 160 - Split-background promotion preflight - -## What changed - -- Added `--preflight-only` to `scripts/run_split_background_promotion_workflow.sh`. -- Preflight now checks: - - `PROMOTION_POSITIVE_PORTFOLIO_PATH` exists and is readable. - - `OPERATOR_SAMPLE_MANIFEST_PATH` exists and is readable. - - the manifest contains both `pure_empty_negative` and `sparse_building_context` background categories. - - Python and `curl` are available. - - the runtime frontend API proxy returns the canonical `data` envelope from `/api/v1/projects`. -- Updated operator docs, TODO and changelog with the quick post-redeploy preflight command. - -## What was tested - -- Red step: `python -m pytest tests/test_sprint159_split_promotion_workflow.py -q` failed because `--preflight-only` was not yet present. -- Ran `python -m pytest tests/test_sprint159_split_promotion_workflow.py -q`: 3 passed. -- Ran `bash -n scripts/run_split_background_promotion_workflow.sh`. -- Ran `python -m pytest tests/test_sprint159_split_promotion_workflow.py tests/test_sprint158_promotion_report_split_background.py -q`: 4 passed. -- Ran `curl.exe -fsS http://192.0.2.10:1202/api/v1/projects`: runtime API proxy returned a canonical `data` envelope. -- Ran `python -m compileall backend/app`. -- Ran `python -m pytest` in `backend`: 447 passed, 17 existing Pydantic namespace warnings. -- Ran `cd frontend && npm run typecheck`. -- Ran `cd frontend && npm run build`. -- Ran `cd backend && python -m alembic heads`: `202606120900 (head)`. -- Ran `cd backend && python -m alembic upgrade head --sql`. -- Ran `bash -n scripts/live_migration_smoke.sh`. -- Ran `bash scripts/run_readiness_check.sh`: passed. - -## Known limitations - -- Preflight is intentionally non-mutating and does not run inference, create datasets, retrain models, activate defaults, fetch providers, fetch weights or change API/database behavior. -- Full split-background matrix execution still requires redeploying this commit to the Tower/Unraid runtime and running the wrapper in the runtime checkout where the positive portfolio and operator manifest artifacts exist. - -## Next recommended pass - -- Redeploy/pull on Tower, then run: - - `PROMOTION_POSITIVE_PORTFOLIO_PATH=... OPERATOR_SAMPLE_MANIFEST_PATH=... bash scripts/run_split_background_promotion_workflow.sh --preflight-only http://192.0.2.10:1202` -- If preflight passes, rerun without `--preflight-only` to generate the split summary and split-aware promotion report. - -# Sprint 161 - Widescreen workbench support - -## What changed - -- Added dedicated frontend CSS breakpoints for `1800px` and `2200px` workbench widths. -- Wide screens now expand the workbench shell columns, inspector padding, Data/Analysis/AI/Export grids and Map workspace controls without changing workflows. -- Ultrawide screens prioritize the MapLibre review frame with a taller map and wider toolbar/inspection layout. -- Added static regression coverage for widescreen/ultrawide layout contracts. -- Updated frontend README, TODO and changelog. - -## What was tested - -- Red step: `python -m pytest tests/test_sprint161_widescreen_workbench.py -q` failed before the widescreen CSS contracts existed. -- Ran `python -m pytest tests/test_sprint161_widescreen_workbench.py tests/test_sprint53_selection_ergonomics.py tests/test_sprint85_map_workspace_density.py tests/test_sprint113_calm_workbench_layout.py -q`: 13 passed. -- Ran `python -m compileall backend/app`. -- Ran `python -m pytest` in `backend`: 449 passed, 17 existing Pydantic protected-namespace warnings. -- Ran `npm run typecheck` in `frontend`. -- Ran `npm run build` in `frontend`. -- Ran `python -m alembic heads` in `backend`: `202606120900 (head)`. -- Ran `python -m alembic upgrade head --sql` in `backend`. -- Ran `bash -n scripts/live_migration_smoke.sh`. -- Ran `bash scripts/run_readiness_check.sh`: passed. -- Ran a local Vite preview visual/layout check at `2560x1080` through the in-app browser. The workbench measured no horizontal overflow, shell columns `240px 1889px 416px`, and the Map workspace rendered an `832px` high MapLibre frame with the road basemap visible. - -## Known limitations - -- Local `docker compose config` could not be run on this Windows workstation because the Docker CLI is not installed or not on `PATH`. -- The live Tower/Unraid runtime at `http://192.0.2.10:1202` will show the widescreen changes only after redeploying this commit. -- The local preview showed an expected API error because it served the built frontend without the Docker backend proxy; the layout and MapLibre basemap rendered correctly. - -## Next recommended pass - -- Redeploy/pull this commit on Tower/Unraid and visually recheck `http://192.0.2.10:1202` on the actual widescreen monitor. -- Continue with the split-background promotion preflight/matrix flow once the runtime has been rebuilt. - -# Sprint 161 - Tower redeploy and live widescreen runtime verification - -## What changed - -- Redeployed Tower/Unraid from commit `07ea8db` with the existing all-in-one deploy path. -- Preserved the remote AI runtime setting by deploying with `GEOINTEL_INSTALL_AI=true`. -- The deployed `geointel` container is healthy and published on `0.0.0.0:1202->80/tcp`. -- No application code, API contract, migration, provider fetching, model default, model download behavior or fake data path changed in this pass. - -## What was tested - -- Verified Tower SSH access through `root@192.0.2.10` with the `widefrog_unraid_deploy` key. -- Verified the remote checkout reset to `07ea8db`. -- Ran the Tower deploy script with AI dependencies enabled. -- Deploy build produced frontend asset `assets/index-CxHabIo7.css`; the live CSS contains the Sprint 161 wide/ultrawide layout rules including `15rem minmax(0,1fr) 26rem` and `min-height:42rem`. -- Live migration smoke passed inside the `geointel` container: - - database connection ok - - PostGIS `3.6` - - database collation ok - - required runtime schema objects ok - - Alembic head `202606120900` -- Browser runtime smoke passed against `http://192.0.2.10:1202`. -- GIS runtime smoke passed against `http://192.0.2.10:1202`. -- Health endpoint returned `status=ok`, `database=ok`. -- YOLO preflight returned: - - `dependencies_available=true` - - `model_file_exists=true` - - `torch_version=2.13.0` - - `ultralytics_version=8.4.92` - - `will_download_models=false` - - `will_run_inference=false` without a tile manifest - -## Known limitations - -- The optional local screenshot script could not run in this Windows runner because Node cannot import Playwright here. The script remains optional and reports the documented install commands. -- The in-app browser could not attach a fresh browser-use tab during this pass, so the final visual confirmation is based on deploy smoke, live CSS verification and runtime API/GIS/AI checks rather than a new inline screenshot. - -## Next recommended pass - -- Manually refresh the already-open `http://192.0.2.10:1202` browser tab on the actual widescreen monitor to observe the new layout. -- Continue with the split-background promotion preflight/matrix workflow now that Tower is rebuilt with the latest frontend and AI runtime. - -# Sprint 162 - Split-background promotion runtime pass - -## What changed - -- Hardened `scripts/run_split_background_promotion_workflow.sh` preflight so legacy operator manifests without explicit `background_category` are handled consistently with `run_operator_hard_negative_detection_matrix.sh`. -- Missing background categories are now derived from `reference_feature_count`: `0` becomes `pure_empty_negative`, and background samples with references become `sparse_building_context`. -- Added a regression test for the derived-category preflight path. -- Updated operator docs and changelog. No API contract, migration, provider fetching, model default, fake output or model download behavior changed. - -## What was tested locally - -- Ran `python -m pytest tests/test_sprint159_split_promotion_workflow.py -q`: 4 passed. -- Ran `python -m pytest tests/test_sprint157_background_split_matrix_runner.py tests/test_sprint158_promotion_report_split_background.py tests/test_sprint159_split_promotion_workflow.py -q`: 9 passed. -- Ran `bash -n scripts/run_split_background_promotion_workflow.sh`. -- Ran `python -m compileall backend/app`. -- Ran `python -m pytest` in `backend`: 450 passed, 17 existing Pydantic protected-namespace warnings. -- Ran `npm run typecheck` in `frontend`. -- Ran `npm run build` in `frontend`. -- Ran `bash scripts/run_readiness_check.sh`: passed. - -## Tower runtime evidence - -- Pushed commit `a499c5f` and fast-forwarded the Tower checkout. -- Ran split-background preflight against `http://192.0.2.10:1202` with: - - `PROMOTION_POSITIVE_PORTFOLIO_PATH=artifacts/detection-quality-matrix/multi-sample/aoi1024bg512r3e50-full/multi_sample_quality_summary.json` - - `OPERATOR_SAMPLE_MANIFEST_PATH=storage/operator-data/operator-samples-1024/operator_samples_manifest.json` - - result: passed. -- Ran the full low/mid-threshold split workflow into: - - background split: `artifacts/detection-hard-negatives/background-split/aoi1024bg512r3e50-split-20260710T222641Z` - - promotion report: `artifacts/detection-model-promotion/split-aware/aoi1024bg512r3e50-split-20260710T222641Z/detection_model_promotion_report.json` - - result: no recommended candidate because `0.15` produced 46 pure-empty detections on `postel_bos`, while `0.35` had no matching positive evidence in that portfolio. -- Ran high-threshold preflight and full split workflow using: - - `PROMOTION_POSITIVE_PORTFOLIO_PATH=artifacts/detection-quality-matrix/multi-sample/aoi1024bg512r3e50-high-threshold/multi_sample_quality_summary.json` - - `QUALITY_THRESHOLDS="0.35 0.45 0.6"` - - background split: `artifacts/detection-hard-negatives/background-split/aoi1024bg512r3e50-high-threshold-split-20260710T222934Z` - - promotion report: `artifacts/detection-model-promotion/split-aware/aoi1024bg512r3e50-high-threshold-split-20260710T222934Z/detection_model_promotion_report.json` -- High-threshold strict pure-empty gate passed: - - 3 pure-empty samples: `arendonk_heide`, `lommel_heide`, `postel_bos` - - 9 pure-empty runs - - total detections: `0` - - max detections per sample/threshold run: `0` -- Recommended candidate: - - `geointel-building-yolov8s-aoi1024bg512r3e50-pt|512|64|0.35` - - positive samples: `7` - - pure-empty background samples: `3` - - mean F1: `0.32086574003576274` - - mean precision: `0.8400057773951873` - - mean recall: `0.20213514285308795` - - max pure-empty detections: `0` - - promotion status: `promote_candidate` -- Sparse-context review remained review-only: - - 6 sparse-context samples - - 18 sparse-context runs - - total detections: `422` - - max sparse-context detections: `55` - -## Known limitations - -- The recommended candidate has conservative recall (`0.2021`) at threshold `0.35`; it is suitable as an operator-review candidate, not as an automatically activated production default. -- The model default was not changed. Activation should remain a separate explicit operator decision after reviewing the high-threshold report. - -## Next recommended pass - -- Add a guarded model activation/operator-selection workflow that can mark a promoted candidate as active only after the report artifact and candidate key are explicitly supplied. - -# Sprint 163 - Guarded promoted YOLO activation workflow - -## What changed - -- Added `scripts/activate_promoted_yolo_candidate.py`. -- The helper validates: - - the promotion report file exists and is valid JSON; - - the exact supplied `candidate_key` matches the report recommended candidate; - - the candidate has `promotion_status=promote_candidate`; - - positive sample count, background sample count, mean F1 and max background detections still satisfy report gates; - - the candidate `model_asset_id` resolves to an existing local model file under the mounted models directory. -- The helper emits `.env` updates in dry-run mode by default and writes them only when `--apply` is supplied. -- Updated Detection Lab operator profiles: - - `balanced-review` at threshold `0.15` remains candidate-only because pure-empty false-positive pressure failed. - - `conservative-review` at threshold `0.35` is marked as promoted/default-approved based on the split-background pure-empty gate. -- Added docs for the guarded activation command in `docs/AI_PIPELINES.md`, `scripts/README.md`, `backend/README.md` and `frontend/README.md`. -- Added readiness coverage for compiling the new helper. -- No API contract, database migration, provider fetching, fake detection path, model file mutation, model download or automatic runtime activation was introduced in code. - -## What was tested locally - -- RED: `python -m pytest tests/test_sprint162_promoted_model_activation.py -q` failed while `scripts/activate_promoted_yolo_candidate.py` was absent. -- RED: `python -m pytest tests/test_sprint155_detection_operator_profiles.py -q` failed before `conservative-review` was marked promoted. -- RED: `python -m pytest tests/test_sprint162_promoted_model_activation.py::test_readiness_gate_compiles_promoted_activation_script -q` failed before readiness compiled the helper. -- Ran `python -m pytest tests/test_sprint162_promoted_model_activation.py tests/test_sprint155_detection_operator_profiles.py -q`: 7 passed. -- Ran `python -m py_compile scripts/activate_promoted_yolo_candidate.py`. -- Ran `python -m compileall backend/app`. -- Ran `python -m pytest` in `backend`: 454 passed, 17 existing Pydantic protected-namespace warnings. -- Ran `npm run typecheck` in `frontend`. -- Ran `npm run build` in `frontend`. -- Ran `bash scripts/run_readiness_check.sh`: passed. - -## Known limitations - -- The helper updates runtime environment only; a container restart or rebuild is still required for `YOLO_MODEL_PATH` changes to take effect. -- The promoted threshold is represented in the operator profile and promotion report. The backend detection endpoint still requires clients to submit the intended confidence threshold explicitly. - -## Next recommended pass - -- Push this helper to Tower, run it first as dry-run against the high-threshold promotion report, then apply and redeploy/restart only if the emitted `YOLO_MODEL_PATH` matches the promoted local asset. - -# Sprint 164 - Live operational YOLO detection and QA smoke - -## What changed - -- No product code, API contract, migration, model artifact, fake-data path or provider-fetching behavior changed. -- Ran the deployed all-in-one Tower runtime at `http://192.0.2.10:1202` through a real raster/reference detection and QA workflow using existing operator data and the local promoted YOLO model asset. - -## Tower runtime evidence - -- Runtime URL: `http://192.0.2.10:1202` -- Raster input: `/mnt/user/appdata/geointel/storage/operator-data/operator-samples-1024/geel_orthophoto_wms_1024.tif` -- Reference input: `/mnt/user/appdata/geointel/storage/operator-data/operator-samples-1024/geel_grb_gbg_buildings.geojson` -- Model asset: `geointel-building-yolov8s-aoi1024bg512r3e50-pt` -- Project: `865746ee-10ce-40a1-a3da-98b2182200e5` -- Raster dataset: `c87ed009-0bf0-4a34-adc5-51e6747d847b` -- Reference dataset: `d9bca687-20ca-4609-8c15-d24d240cfae6` -- Tile manifest: `/app/storage/tiles/865746ee-10ce-40a1-a3da-98b2182200e5/c87ed009-0bf0-4a34-adc5-51e6747d847b/b1335951-4ead-4e08-9c5f-08c67e026a8f/manifest.json` -- Analysis run: `45159e0b-36be-4300-8132-fef3a1e6b667` -- Persisted detections: `333` -- Quality check: `2e696dca-dea6-42d1-af2a-4894b182d427` -- Detection export: `339344f7-38e3-4558-b66b-459726051bac` - -## Validation - -- Ran `scripts/verify_real_data_detection_qa_workflow.sh` against the deployed Tower runtime: passed. -- Confirmed detection run status: `success`. -- Confirmed detection list endpoint returned `333` persisted detections with real source tile provenance. -- Confirmed detection GeoJSON endpoint returned a `FeatureCollection` with `333` persisted geometry features. -- Confirmed detection export content returned a `detection_geojson` `FeatureCollection` with `333` features. -- Confirmed QA/QC persisted metrics: - - precision: `0.21621621621621623` - - recall: `0.031746031746031744` - - F1: `0.05536332179930796` - - mean IoU: `0.5697275247203281` - - false positives: `261` - - false negatives: `2196` -- Confirmed QA evidence overlay endpoint returned a `FeatureCollection` with `2601` features and no warnings. - -## Known limitations - -- The model is operational and demonstrable, but the Geel smoke confirms low recall at the current conservative threshold. It should remain an operator-review detector, not an automated decision engine. -- Further training data quality work remains required before treating the detector as production-grade. - -## Next recommended pass - -- Add/curate more high-quality positive AOIs and cleaner building labels, then rerun the multi-AOI calibration and promotion gate before changing default operator thresholds. - -# Sprint 165 - Clean AOI1024 YOLO dataset and promotion rejection - -## What changed - -- Hardened `scripts/export_operator_yolo_tile_dataset.py` so legacy operator manifests without explicit `background_category` now derive background categories consistently with the split-background evaluator: - - `reference_feature_count == 0` -> `pure_empty_negative` - - `reference_feature_count > 0` -> `sparse_building_context` - - normal reference samples -> `reference_aoi` -- Added regression coverage in: - - `backend/tests/test_sprint130_operator_yolo_tile_dataset.py` - - `backend/tests/test_sprint156_background_corpus_classification.py` -- Documented the clean AOI1024 export/audit profile in `scripts/README.md`. -- Updated `docs/TODO.md` with the clean dataset and rejected candidate state. -- No API contract, migration, default model activation, provider fetch path, model download behavior or fake detection path changed. - -## Local validation - -- RED: `python -m pytest backend/tests/test_sprint130_operator_yolo_tile_dataset.py::test_background_category_is_derived_for_legacy_operator_manifests -q` failed before the exporter helper existed. -- GREEN: same targeted test passed after adding `background_category_for_sample`. -- Ran `python -m pytest backend/tests/test_sprint130_operator_yolo_tile_dataset.py backend/tests/test_sprint146_operator_yolo_dataset_quality_audit.py backend/tests/test_sprint157_background_split_matrix_runner.py -q`: 12 passed. -- Ran `python -m pytest backend/tests/test_sprint130_operator_yolo_tile_dataset.py backend/tests/test_sprint156_background_corpus_classification.py -q`: 11 passed. -- Ran `bash scripts/run_readiness_check.sh`: 457 backend tests passed, frontend typecheck passed, frontend build passed, readiness passed. - -## Tower runtime evidence - -- Pushed commit `b3bd34c` and redeployed the all-in-one Tower runtime at `http://192.0.2.10:1202`. -- Deploy validation passed: - - live migration smoke passed; - - browser runtime verification passed; - - container exposed `0.0.0.0:1202->80/tcp`. -- Regenerated clean AOI1024 tile dataset: - - dataset: `/app/storage/operator-data/yolo-building-aoi1024-cleanpx12vis035` - - tile count: `144` - - positive tiles: `114` - - negative tiles: `30` - - labels: `14632` - - `min_label_px=12` - - `min_label_visible_ratio=0.35` - - background categories in tile summary: - - `pure_empty_negative=27` - - `sparse_building_context=54` - - `reference_aoi=63` -- Dataset audit: - - report: `/app/artifacts/operator-yolo-dataset-audit/aoi1024-cleanpx12vis035/operator_yolo_dataset_quality_audit.json` - - status: `ok` - - positive sample count: `13` - - background sample count: `9` - - invalid labels: `0` - - missing label files: `0` - - median normalized box area: `0.001373291015625` - - small-box share: `0.0` - -## Training and evaluation - -- Trained a new inactive local model: - - model asset id: `geointel-building-yolov8s-aoi1024cleanpx12vis035e50-pt` - - model file: `/app/models/geointel-building-yolov8s-aoi1024cleanpx12vis035e50.pt` - - SHA256: `4863b27717cb7fd3126ccf86a988b3c1863b5fb9271cf35370ca2473b9ed10f4` - - base model: `/app/models/yolov8s.pt` - - dataset: `/app/storage/operator-data/yolo-building-aoi1024-cleanpx12vis035/dataset.yaml` - - epochs: `50` - - image size: `512` - - batch: `4` - - device: `cpu` - - active runtime model: unchanged -- Ran positive multi-AOI matrix: - - output: `artifacts/detection-quality-matrix/multi-sample/aoi1024cleanpx12vis035e50-positive/multi_sample_quality_summary.json` - - samples: `geel`, `mol`, `turnhout`, `herentals`, `balen`, `retie`, `westerlo` - - thresholds: `0.35`, `0.25`, `0.15` -- Ran split-background promotion workflow: - - background split: `artifacts/detection-hard-negatives/background-split/aoi1024cleanpx12vis035e50-split/background_corpus_split_summary.json` - - promotion report: `artifacts/detection-model-promotion/split-aware/aoi1024cleanpx12vis035e50-split/detection_model_promotion_report.json` - - recommended candidate: `none` - -## Promotion result - -- `geointel-building-yolov8s-aoi1024cleanpx12vis035e50-pt|512|64|0.15` - - rejected: `positive_mean_f1_below_gate`, `background_false_positive_pressure` - - positive samples: `7` - - background samples: `3` - - mean F1: `0.1542209371995884` - - mean precision: `0.18801639524786692` - - mean recall: `0.13146097412721683` - - max pure-empty detections: `2` -- `geointel-building-yolov8s-aoi1024cleanpx12vis035e50-pt|512|64|0.25` - - rejected: `positive_mean_f1_below_gate` - - mean F1: `0.14443976458069788` - - mean precision: `0.24254741138809843` - - mean recall: `0.10383903038875668` - - max pure-empty detections: `0` -- `geointel-building-yolov8s-aoi1024cleanpx12vis035e50-pt|512|64|0.35` - - rejected: `positive_mean_f1_below_gate` - - mean F1: `0.11851668674424971` - - mean precision: `0.30588130541017644` - - mean recall: `0.07481388046665544` - - max pure-empty detections: `0` - -## Known limitations - -- The clean label filter fixed the small-box audit problem but did not improve promotion-quality detection metrics. -- The new model remains useful evidence only and must stay inactive. -- The current limiting factor is not script/runtime wiring; it is training data representativeness and label geometry quality for small/dense Belgian building footprints. - -## Next recommended pass - -- Add building-size/visibility diagnostics per AOI and use them to choose or generate better positive samples before another training run. Do not spend more CPU on the current cleanpx dataset without changing the sample/label strategy. - -# Sprint 166 - Per-sample YOLO dataset audit diagnostics - -## What changed - -- Extended `scripts/audit_operator_yolo_dataset_quality.py` with per-sample YOLO label diagnostics in `sample_summaries`: - - parsed label count; - - invalid label count; - - missing label file count; - - median/mean normalized box area; - - median normalized width/height; - - small-box count/share; - - sample-specific quality warning codes. -- Kept the existing global audit gates unchanged. -- Updated the Markdown audit output so each AOI/sample line includes the new label-quality signals. -- Added regression assertions in `backend/tests/test_sprint146_operator_yolo_dataset_quality_audit.py`. -- Updated `scripts/README.md` to document per-sample diagnostics. - -## Local validation - -- RED: `python -m pytest backend/tests/test_sprint146_operator_yolo_dataset_quality_audit.py::test_operator_yolo_dataset_quality_audit_reports_dataset_risks -q` failed with `KeyError: 'parsed_label_count'` before sample diagnostics existed. -- GREEN: same targeted test passed after adding sample label stats. -- Ran `python -m pytest backend/tests/test_sprint146_operator_yolo_dataset_quality_audit.py backend/tests/test_sprint130_operator_yolo_tile_dataset.py backend/tests/test_sprint156_background_corpus_classification.py -q`: 12 passed. -- Ran `bash scripts/run_readiness_check.sh`: 457 backend tests passed, frontend typecheck passed, frontend build passed, readiness passed. - -## Tower runtime evidence - -- Pushed commit `7ccabf5` and redeployed the all-in-one Tower runtime at `http://192.0.2.10:1202`. -- Deploy validation passed: - - live migration smoke passed; - - browser runtime verification passed; - - container exposed `0.0.0.0:1202->80/tcp`. -- Re-ran the clean AOI1024 audit with sample diagnostics: - - report: `/app/artifacts/operator-yolo-dataset-audit/aoi1024-cleanpx12vis035-sample-diagnostics/operator_yolo_dataset_quality_audit.json` - - status: `ok` - - tile count: `144` - - positive tiles: `114` - - negative tiles: `30` - - labels: `14632` - - parsed labels: `14632` - - median normalized box area: `0.001373291016` - - small-box share: `0.0` - - sample count: `16` -- All samples reported `quality_warnings=[]` under the current gates. -- Lowest positive/context label counts: - - `ravels_bos`: 22 parsed labels, median box area `0.001140594385` - - `geel_bel`: 56 parsed labels, median box area `0.001411437891` - - `kasterlee_bos`: 73 parsed labels, median box area `0.001522064229` - - `dessel_heide`: 77 parsed labels, median box area `0.001495361328` - - `meerhout_bos`: 99 parsed labels, median box area `0.001232147197` - -## Known limitations - -- Numeric label diagnostics now pass, but the rejected `aoi1024cleanpx12vis035e50` model proves that numeric gates alone are insufficient. -- The next unknown is visual alignment and semantic fit: whether GRB building boxes line up well enough with the orthophoto tiles and whether sparse/context AOIs represent the false-positive modes seen during promotion. - -## Next recommended pass - -- Design and add a visual YOLO label QA artifact generator: deterministic contact sheets of selected train/val tiles with YOLO boxes overlaid on imagery, grouped by AOI/sample and label density. Use it before another training run. - -# Sprint 167 - Operator YOLO visual label QA contact sheets - -## What changed - -- Added `scripts/render_operator_yolo_label_qa_contact_sheets.py` to render deterministic operator-only contact sheets from existing YOLO tile datasets. -- The script reads the existing `yolo_tile_dataset_summary.json`, image tiles and label files, then writes: - - `operator_yolo_label_qa_summary.json`; - - `operator_yolo_label_qa_contact_sheet.md`; - - one or more PNG contact sheets with YOLO labels drawn over the tile imagery. -- Added explicit checks for missing images, missing label files, invalid YOLO rows and blank-looking/low-variance tiles. -- Added regression coverage in `backend/tests/test_sprint167_operator_yolo_label_qa_contact_sheets.py`. -- Updated the all-in-one Dockerfile so operator QA scripts are copied after the expensive dependency layer, keeping future script-only rebuilds cache-friendlier. -- Updated Docker runtime tests so the all-in-one image keeps packaging the operator scripts needed on Tower. -- No inference, training, provider fetch, database mutation, model activation or fake detection path was introduced. - -## Local validation - -- RED: `python -m pytest backend/tests/test_sprint167_operator_yolo_label_qa_contact_sheets.py -q` failed before the contact-sheet script existed. -- GREEN: same targeted test passed after adding the renderer. -- RED: the low-variance regression failed before `low_visual_variance_tile_count` existed. -- GREEN: same targeted test passed after adding low-variance tile reporting. -- Ran `python -m pytest backend/tests/test_docker_runtime_config.py::test_all_in_one_dockerfile_copies_operator_scripts_for_runtime_use backend/tests/test_docker_runtime_config.py::test_all_in_one_dockerfile_copies_operator_scripts_after_dependency_install backend/tests/test_sprint167_operator_yolo_label_qa_contact_sheets.py -q`: 3 passed. -- Ran `bash scripts/run_readiness_check.sh`: 459 backend tests passed, frontend typecheck passed, frontend build passed, readiness passed. - -## Tower runtime evidence - -- Pushed commits `fbccf83` and `5688fee`, then redeployed the all-in-one Tower runtime at `http://192.0.2.10:1202`. -- Docker storage had filled during the first build attempt. Cleaned Docker build cache and dangling images only; application volumes and appdata were not pruned. Docker reclaimed `98.38GB`. -- Deploy validation for commit `5688fee` passed: - - live migration smoke passed; - - browser runtime verification passed; - - container exposed `0.0.0.0:1202->80/tcp`; - - Unraid icon check remained OK. -- Rendered the clean AOI1024 visual label QA artifact inside the live container: - - summary: `/app/artifacts/operator-yolo-label-qa/aoi1024-cleanpx12vis035/operator_yolo_label_qa_summary.json` - - Markdown: `/app/artifacts/operator-yolo-label-qa/aoi1024-cleanpx12vis035/operator_yolo_label_qa_contact_sheet.md` - - contact sheet: `/app/artifacts/operator-yolo-label-qa/aoi1024-cleanpx12vis035/contact_sheet_001.png` -- Runtime summary: - - status: `ok` - - selected tiles: `32` - - rendered tiles: `32` - - valid labels: `7670` - - invalid labels: `0` - - missing images: `0` - - missing label files: `0` - - low-variance tiles: `6` -- Visual inspection confirmed: - - dense positive tiles show yellow YOLO boxes over real orthophoto imagery; - - the six low-variance tiles are `arendonk_heide` pure-empty negative validation tiles with no labels and blank-looking imagery. - -## Known limitations - -- The contact sheet now makes visual label inspection possible, but it also proves that the current clean AOI1024 dataset still contains blank-looking pure-empty negative tiles. -- Those blank/low-variance negatives should not be used blindly for the next training run. They can distort the background corpus and do not represent realistic aerial false-positive pressure. -- The current inactive model/promotion state remains unchanged. - -## Next recommended pass - -- Add no-data/low-variance filtering to the operator YOLO tile export path, regenerate the clean AOI1024 dataset, rerun the contact-sheet QA, and only then consider another training attempt. - -# Sprint 168 - Operator YOLO low-variance negative filtering - -## What changed - -- Added opt-in low-variance negative filtering to `scripts/export_operator_yolo_tile_dataset.py`. -- Added CLI/env controls: - - `--drop-low-variance-negatives` / `OPERATOR_YOLO_DROP_LOW_VARIANCE_NEGATIVES`; - - `--blank-range-threshold` / `OPERATOR_YOLO_BLANK_RANGE_THRESHOLD`. -- The filter evaluates the rendered raster tile image and skips only negative tiles when enabled. -- Positive/labeled tiles are never removed by this variance gate. -- Kept tile records now include `low_visual_variance`. -- Skipped blank/no-data negative records use `skip_reason="low_visual_variance_negative"`. -- Dataset summaries now include: - - `drop_low_variance_negatives`; - - `blank_range_threshold`; - - `skipped_low_variance_negative_tile_count`. -- Updated operator documentation with the refreshed AOI1024 cleanpx export command. -- Added design and execution plan docs under `docs/superpowers/`. - -## Local validation - -- RED: `python -m pytest backend/tests/test_sprint130_operator_yolo_tile_dataset.py::test_export_can_skip_low_variance_negative_tiles -q` failed because `export_sample_tiles()` did not accept `drop_low_variance_negatives`. -- GREEN: same targeted test passed after adding the filter. -- Ran `python -m pytest backend/tests/test_sprint130_operator_yolo_tile_dataset.py -q`: 8 passed. -- Ran `python -m pytest backend/tests/test_sprint130_operator_yolo_tile_dataset.py backend/tests/test_sprint167_operator_yolo_label_qa_contact_sheets.py backend/tests/test_docker_runtime_config.py::test_all_in_one_dockerfile_copies_operator_scripts_for_runtime_use backend/tests/test_docker_runtime_config.py::test_all_in_one_dockerfile_copies_operator_scripts_after_dependency_install -q`: 11 passed. -- Ran `python scripts/export_operator_yolo_tile_dataset.py --help`: the CLI exposes `--drop-low-variance-negatives`, `--no-drop-low-variance-negatives` and `--blank-range-threshold` without loading GIS dependencies. -- Ran `bash scripts/run_readiness_check.sh`: 460 backend tests passed, frontend typecheck passed, frontend build passed, readiness passed. - -## Tower runtime evidence - -- Pushed commit `a159370` and redeployed the all-in-one Tower runtime at `http://192.0.2.10:1202`. -- Deploy validation passed: - - live migration smoke passed; - - browser runtime verification passed; - - container exposed `0.0.0.0:1202->80/tcp`. -- Regenerated the AOI1024 cleanpx dataset with low-variance negative filtering enabled: - - dataset: `/app/storage/operator-data/yolo-building-aoi1024-cleanpx12vis035` - - `drop_low_variance_negatives=true` - - `blank_range_threshold=3` - - tile count: `135` - - positive tiles: `114` - - negative tiles: `21` - - skipped negative tiles: `9` - - skipped low-variance negative tiles: `9` - - labels: `14632` - - train tiles: `108` - - validation tiles: `27` -- Dataset audit: - - report: `/app/artifacts/operator-yolo-dataset-audit/aoi1024-cleanpx12vis035-lowvarfilter/operator_yolo_dataset_quality_audit.json` - - status: `ok` - - invalid labels: `0` - - missing label files: `0` - - median normalized box area: `0.001373291016` - - small-box share: `0.0` -- Visual label QA: - - report: `/app/artifacts/operator-yolo-label-qa/aoi1024-cleanpx12vis035-lowvarfilter/operator_yolo_label_qa_summary.json` - - contact sheet: `/app/artifacts/operator-yolo-label-qa/aoi1024-cleanpx12vis035-lowvarfilter/contact_sheet_001.png` - - selected tiles: `32` - - rendered tiles: `32` - - valid labels: `7670` - - invalid labels: `0` - - missing images: `0` - - missing label files: `0` - - low-variance rendered tiles: `0` -- Visual inspection confirmed that the previous blank white `arendonk_heide` negatives are no longer present in the review sheet. The remaining selected pure-empty negatives are real visible orthophoto/context tiles. - -## Known limitations - -- The low-variance gate is deliberately simple and only identifies visually blank/no-data-looking negative tiles. -- Operator visual contact-sheet review remains required before any new training run. -- The filtered dataset is now a cleaner input candidate, but model training is still not guaranteed to improve QA/QC; another training run must be gated through the existing positive-AOI and background promotion reports. - -## Next recommended pass - -- Train one inactive candidate from the filtered AOI1024 cleanpx dataset, then run the existing positive-AOI matrix and split-background promotion workflow before considering default activation. -# Sprint 171 - Positive AOI expansion and split safety - -## What changed - -- Converted the Sprint 170 false-negative evidence into a guarded data action instead of another blind training run. -- Added Olen, Lille, Oud-Turnhout and Kasterlee center as explicit real-reference training AOIs. -- Kept Turnhout, Retie, Westerlo and Arendonk-heide as the documented validation holdouts. -- Added generated `recommended_split` provenance and tile-export validation that rejects unknown samples and manifest-backed holdout leakage. -- Hardened false-negative portfolio comparison to require identical reference feature identities, not only matching AOI names. - -## Local validation - -- RED tests proved the expansion/split constants and validation guard were absent before implementation. -- `python -m pytest backend/tests/test_sprint131_operator_sample_expansion.py backend/tests/test_sprint130_operator_yolo_tile_dataset.py backend/tests/test_sprint156_background_corpus_classification.py backend/tests/test_sprint170_detection_false_negative_audit.py -q`: 23 passed. -- Official GRB OGC API probes returned building features at all four new AOI centers. -- Local sample generation was attempted but correctly stopped because the workstation Python lacks the existing GIS runtime extras; the all-in-one Tower runtime is the supported execution environment. - -## Tower runtime evidence - -- Pushed `0f49c98` and redeployed the all-in-one runtime at `http://192.0.2.10:1202`; live migration and browser proxy verification passed. -- Refreshed `/app/storage/operator-data/operator-samples-1024/operator_samples_manifest.json` to schema version 2 with 20 sources. -- Newly fetched real GRB reference counts: Olen 1,952, Lille 1,839, Oud-Turnhout 2,691 and Kasterlee 1,831; all are `recommended_split=train`. -- Exported `/app/storage/operator-data/yolo-building-aoi1024-expanded-minpx4vis035`: - - 171 retained tiles; - - 153 positive and 18 negative tiles; - - 45,892 labels; - - 144 train and 27 validation tiles; - - 9 low-variance negatives skipped; - - validation holdouts Turnhout, Retie, Westerlo and Arendonk-heide recorded in summary provenance. -- Dataset audit status `ok`: no warnings, invalid labels or missing files; median normalized box area `0.000694274766`, small-box share `0.3832694151486098`. -- Improved the visual contact-sheet selector after the first live sheet overrepresented dense AOIs. The balanced rerun selected 40 tiles across all 19 retained source samples with zero invalid labels, missing images, missing label files or low-variance selections. -- Started one 50-epoch CPU YOLOv8s candidate as inactive runtime evidence: `geointel-building-yolov8s-aoi1024expandedminpx4vis035e50.pt`. - -## Known limitations - -- No new model has been trained or activated. -- The inactive training run must finish and pass positive-AOI plus split-background promotion gates before it can be considered for activation. - -## Next recommended pass - -- Finish the inactive candidate, run fixed-threshold positive evidence and split pure-empty/sparse-context background matrices, and preserve the current production default unless the promotion report passes every gate. -# Sprint 172 - CPU AI image build hardening - -## What changed - -- Reordered `deploy/unraid/Dockerfile.all-in-one` so `pyproject.toml` and minimal package metadata are installed before the complete backend source is copied. -- Code-only backend changes can now reuse the expensive GIS/AI dependency layer; dependency metadata changes still invalidate it. -- The opt-in CPU AI build now installs the same validated PyTorch `2.13.0` / torchvision `0.28.0` versions from the official CPU wheel index before installing the `ai` extra. -- Kept the full GIS and YOLO import/preflight smoke after the complete backend source copy. - -## Validation so far - -- RED: the new Docker ordering/CPU-wheel regression test failed against the old Dockerfile. -- GREEN: `python -m pytest backend/tests/test_docker_runtime_config.py -q`: 26 passed. -- `python -m pip index versions` confirmed `torch 2.13.0+cpu` and `torchvision 0.28.0+cpu` are available from the configured CPU index for the workstation platform. - -## Remaining validation - -- Build the AI-enabled all-in-one image on Tower after the current inactive model training run finishes, verify Torch reports a CPU build and rerun live migration/browser smokes before replacing the runtime. - -# Sprint 171.1 - Validation coverage provenance - -- The expanded live export exposed that Arendonk-heide remained configured as a holdout while all of its low-variance tiles were correctly filtered out. -- Added `retained_validation_sample_slugs` and `empty_validation_sample_slugs` to tile dataset summaries so configured and actual validation coverage cannot be confused. -- Added a focused regression test and kept filtering behavior unchanged; no blank tile was reintroduced. - -# Sprint 173 - Expanded building model promotion - -## Runtime evidence - -- Completed inactive 50-epoch CPU training for `geointel-building-yolov8s-aoi1024expandedminpx4vis035e50.pt` from the expanded 20-source real-data corpus. -- Trained-model SHA256: `a8a79cf5b0bdc19a0245acc322cf77232c335e222bd5f3c00a17d5f29402c196`. -- Training summary recorded 45,892 labels across 171 retained tiles; final training metrics were precision `0.55558`, recall `0.35206`, mAP50 `0.27440` and mAP50-95 `0.10107`. -- The persisted seven-AOI positive matrix recommended tile size `512`, overlap `64` and threshold `0.15`: mean precision `0.6470590036`, recall `0.4699913837`, F1 `0.5432865391`, and minimum per-AOI F1 `0.4897494305`. -- The strict pure-empty gate covered Postel, Lommel and Arendonk across all tested thresholds and produced zero detections. Sparse-building contextual AOIs remained review-only evidence because real GRB buildings are present there. -- Fixed-threshold persisted false-negative comparison used identical reference feature populations and reduced the false-negative rate in all seven positive AOIs versus the previous active `0.35` profile. -- The guarded activation helper first returned `ready_to_apply`, resolved the exact local model asset and reported no downloads or inference. The reviewed `--apply` pass updated only `GEOINTEL_INSTALL_AI`, `YOLO_ENABLED`, `YOLO_MODELS_DIR` and `YOLO_MODEL_PATH` in the Tower environment. - -## UI and operator behavior - -- Detection Lab now recommends the promoted expanded-AOI model at threshold `0.15` and surfaces its seven-AOI coverage plus QA metrics. -- The previous AOI1024 background-aware model remains mounted as an explicit legacy high-precision `0.35` review profile. -- Profile selection remains deliberate: it selects a mounted local asset and run threshold only; it does not mutate runtime environment, download a model or start inference automatically. - -## Remaining limitation - -- Persistent small-building misses remain the weakest quality bucket. Continue with targeted evidence review and data coverage before considering another training run; do not infer production accuracy from aggregate F1 alone. - -## Tower deployment verification - -- Pushed commit `1c16313` and rebuilt the all-in-one runtime at `http://192.0.2.10:1202`. -- The opt-in AI image installed `torch 2.13.0+cpu` and `torchvision 0.28.0+cpu` from the official CPU wheel index; runtime CUDA availability is `false`. Ultralytics reports version `8.4.93`. -- The live model catalog exposes 23 local files and marks only `geointel-building-yolov8s-aoi1024expandedminpx4vis035e50-pt` active with the expected SHA256. -- Explicit `--check-model-load` preflight passed against an existing nine-tile manifest: dependencies, model load, manifest structure, tile paths and tile limit were all valid; no inference or download ran. -- Embedded PostGIS live migration smoke passed with PostGIS `3.6`, required tables/indexes, database collation and the single Alembic head `202606120900`. -- Browser validation confirmed that the recommended profile selects the exact active asset and threshold `0.15`, while live preflight displays CPU dependency/model readiness and the expected missing-manifest guard before dataset handoff. -- Browser console warnings/errors: `0`. - -# Sprint 174 - Focused small-building recovery and promotion - -## Data and training evidence - -- Converted the Sprint 173 persistent false-negative audit into one focused real-data experiment instead of extending the same corpus blindly. -- Added Beerse, Rijkevorsel, Hoogstraten and Vorselaar as training AOIs and Vosselaar/Grobbendonk as independent tile-level validation AOIs. -- Kept Turnhout, Retie and Westerlo outside the tile corpus as operation-level holdouts. -- Exported `/app/storage/operator-data/yolo-building-aoi1024-smallbld-minpx3vis035` from an explicit 23-sample manifest subset: - - 198 retained tiles; - - 180 positive and 18 negative tiles; - - 58,820 real GRB-derived labels; - - 48 visually reviewed tiles; - - zero invalid labels, missing images, missing label files or low-variance review selections. -- The accepted `min-label-px=3` corpus retained 1,228 more genuine small-building labels than the comparable `min-label-px=4` export. -- Trained one inactive 30-epoch CPU candidate from the previous active local model: - - model: `geointel-building-yolov8s-smallbld-minpx3-img640-ft30.pt`; - - model SHA256: `a9088b8491dfae36694b53e9e9406cb4e3511d334a5712fa34f75078a47759c1`; - - dataset-summary SHA256: `49b2a07d2105d08356431757b83eafc1498eaf1fb76965b1efe05b776824942a`; - - dataset-YAML SHA256: `3a2ea97c35a18072a1ab6738cd673c0ecec5344b19461c91d72a15e138d46e8d`; - - no model download and no fake training or QA data. - -## Persisted promotion evidence - -- Evaluated the exact fixed profile `tile=512`, `overlap=64`, `confidence=0.15` with QA match IoU explicitly fixed at `0.25`. -- Seven positive AOIs produced: - - mean precision `0.5898197518`; - - mean recall `0.5769921004`; - - mean F1 `0.5824578632`; - - minimum per-AOI F1 `0.5527837436`. -- Every AOI improved F1 relative to the previous balanced model. Turnhout improved from `0.4897494305` to `0.5527837436`. -- The strict pure-empty gate covered Postel, Lommel and Arendonk and produced zero detections for every sample. -- The formal promotion report recommended the exact key `geointel-building-yolov8s-smallbld-minpx3-img640-ft30-pt|512|64|0.15`. -- Fixed-reference object evidence used identical GRB feature identities and reduced false negatives from `7,753` to `6,182`: - - 1,571 fewer total false negatives; - - 745 fewer misses in the 25-100 m2 bucket; - - 181 fewer misses below 25 m2; - - all seven AOIs improved. -- Remaining persistent misses total `5,838`, concentrated in Turnhout, Herentals and Geel and still dominated by small buildings. -- Mean precision decreased from `0.6470590036` to `0.5898197518`. The new profile is therefore a recall-balanced operator default with a higher false-positive review load, not ground truth. - -## Repository hardening - -- Added explicit `--samples` / `OPERATOR_YOLO_SAMPLES` corpus selection with selected/excluded sample provenance and unknown-sample rejection. -- Added persistent false-negative area statistics, size buckets and combined GeoJSON review evidence. -- Copied the complete operator evaluation/promotion toolchain into the all-in-one image and added a regression that rejects every Docker `COPY scripts/...` source that does not exist. -- Removed Pydantic protected-namespace warnings for legitimate `model_*` API fields while preserving all schema field names and response contracts. -- Updated Detection Lab profiles: the new small-building profile is recommended, the previous expanded profile remains the higher-precision legacy choice, and the background-aware `0.35` profile remains conservative. -- Live `2560x1080` inspection found that two-panel AI/QA/Export workspaces inherited four ultrawide columns and left half of the main canvas empty. Those workspaces now remain explicit two-column grids while the three-panel Data workspace keeps three columns. -- The all-in-one dependency layer now copies only `pyproject.toml` plus a stable build-only package README before installation; the real `backend/README.md` still enters with the complete backend source, so documentation-only edits no longer invalidate Torch/GIS dependencies. -- Guarded activation first returned `ready_to_apply`; the reviewed `--apply` pass updated only `GEOINTEL_INSTALL_AI`, `YOLO_ENABLED`, `YOLO_MODELS_DIR` and `YOLO_MODEL_PATH` in the Tower environment. - -## Local validation - -- `python -m compileall backend/app`: passed. -- `python -m pytest`: 472 passed. -- `python -m ruff check` for all changed Python modules/tests: passed. -- `npm run typecheck`: passed. -- `npm run build`: passed; app bundle `215.64 kB`, MapLibre bundle `801.82 kB` before gzip. -- `bash scripts/run_readiness_check.sh`: passed with 472 tests. -- `python -m alembic heads`: one head, `202606120900`. -- `python -m alembic upgrade head --sql`: complete migration chain rendered successfully. -- Shell syntax checks passed for live migration and the full operator evaluation/promotion chain. - -## Next recommended pass - -- After redeploy, verify the active model SHA, local model-load preflight, live PostGIS migration smoke and browser profile selection. Then review false-positive evidence and the remaining 5,838 persistent misses before any further training. - -# Sprint 175 - Detection result scale and false-positive evidence review - -## UI hardening - -- Confirmed that Detection Lab rendered every persisted detection row at once; Westerlo alone produced 1,172 body rows in the browser. -- Added local 25/50/100-row pagination with a default of 50 rows, bounded page controls and automatic page-one reset after run/filter/result changes. -- Live visual inspection exposed tall rows caused by full container paths; source-tile cells now show the filename and retain the full persisted path as a tooltip. -- Kept the full persisted collection unchanged for the existing MapLibre GeoJSON overlay and detection QA/QC. No endpoint, response envelope or persistence contract changed. - -## Persisted false-positive evidence - -- Added `scripts/audit_detection_false_positive_evidence.py` as a read-only evidence consumer. -- The audit validates FeatureCollection/polygon geometry, compares declared portfolio role counts with actual evidence, computes WGS84 geodesic areas, preserves original feature provenance and emits combined `false_positives.geojson`. -- Source tile summaries are qualified by AOI because `tile_index` is local to each raster manifest. -- The active fixed-threshold seven-AOI portfolio produced: - - 5,568 false positives among 13,613 candidate detections (`0.4090` false-positive share); - - median false-positive geometry area `184.5 m2`, p90 `607.7 m2`; - - 52 below 25 m2, 1,382 between 25-100 m2, 3,412 between 100-500 m2 and 722 at or above 500 m2; - - largest AOI review volumes: Turnhout `1,102`, Herentals `917`, Geel `913`; - - largest AOI-qualified tile hotspot: `turnhout:0` with 236 false positives. -- Existing persisted QA evidence carries run threshold and tile index but no per-detection confidence. The audit reports confidence coverage `0/5,568` and does not invent confidence statistics. -- Added focused regression coverage, readiness compilation and all-in-one image inclusion. No training, inference, provider fetch, model download or activation occurred. - -## Local validation - -- `python -m compileall backend/app`: passed. -- `python -m pytest`: 475 passed. -- `python -m ruff check` for the new audit/test modules: passed. -- `npm run typecheck`: passed. -- `npm run build`: passed; app bundle `217.00 kB`, MapLibre bundle `801.82 kB` before gzip. -- `bash scripts/run_readiness_check.sh`: passed with 475 tests and all release-critical syntax gates. -- `python -m alembic heads`: one head, `202606120900`. -- `python -m alembic upgrade head --sql`: complete migration chain rendered successfully. -- Local `docker compose config` could not run because Docker CLI is not installed on the Windows host; live image/PostGIS validation is delegated to the Docker-enabled Tower deployment. - -## Tower deployment verification - -- Pushed runtime commits `4455e24` and `d188014`; Tower rebuilt the all-in-one image from `main` with the GIS/CPU-AI dependency layer cached. -- Live PostGIS migration smoke passed with PostGIS `3.6`, required runtime tables/indexes and single Alembic head `202606120900`. -- The active local model remained `/app/models/geointel-building-yolov8s-smallbld-minpx3-img640-ft30.pt` with SHA256 `a9088b8491dfae36694b53e9e9406cb4e3511d334a5712fa34f75078a47759c1`. -- Local model-load preflight passed against a persisted nine-tile manifest with Torch `2.13.0+cpu`, Ultralytics `8.4.93`, CUDA disabled, no inference and no download. -- The new false-positive audit ran successfully inside the live all-in-one container against the persisted seven-AOI evidence portfolio. -- Browser verification against the persisted Westerlo run confirmed 1,172 loaded detections, 50 rendered rows, `1-50 of 1172`, page `1/24`, working next-page and 100-row controls, and reset back to the 50-row default. -- Final cells display `tile_0001.tif` while the full persisted path remains available through the `title` attribute. -- At `2560x1080`, the Detection results surface used about 871 px, its table client/scroll widths both measured 827 px and the document did not overflow the viewport. -- Browser console warnings/errors: `0`. - -## Next recommended pass - -- Visually classify a stratified false-positive sample from Turnhout, Herentals and Geel before deciding whether any confirmed examples belong in a new hard-negative corpus. Review the remaining 5,838 persistent false negatives in the same evidence-led pass; do not start another blind training run. - -# Sprint 176 - Detection false-positive visual review gate - -## Persisted provenance - -- Extended the existing read-only QA evidence GeoJSON conversion so detection-backed evidence carries the persisted detection id, job id, confidence, model name/version, source tile path and pixel bbox. -- Added equivalent persisted segmentation provenance fields without changing the endpoint, canonical envelope, ORM or migration chain. -- Historical `QualityCheck` evidence can be re-exported against existing persisted `Detection` rows; no QA rerun or data rewrite is required. - -## Manual visual review - -- Added a storage-root-confined contact-sheet renderer for persisted detection false-positive evidence. -- The renderer validates portfolio role counts, polygon geometry, source imagery and persisted provenance, then selects deterministically across AOI, WGS84 area bucket and confidence band. -- Source imagery is rendered with the candidate pixel bbox plus persisted matched-reference and missed-reference overlays. -- Live orthophoto inspection exposed stretched non-square edge tiles and overly distant full-tile context; the renderer now uses candidate-centred crops, preserves aspect ratio and limits reference overlays to the crop. -- Added an explicit five-state review CSV: `confirmed_model_false_positive`, `reference_gap_or_change`, `qa_alignment_mismatch`, `uncertain` and `unreviewed`. -- Added a separate validator that rejects missing, duplicate, unexpected or invalid decisions. `--require-complete` exits with code `2` while any record remains unreviewed. -- Only explicitly confirmed model false-positives are emitted to `confirmed_model_false_positives.geojson`; no QA result is automatically converted into a model label or training artifact. - -## Validation - -- `python -m compileall backend/app`: passed. -- `python -m pytest`: 478 passed. -- Focused provenance/render/path-confinement/incomplete-review/export tests: passed. -- `python -m ruff check` for changed Python services, scripts and tests: passed. -- Generated fixture contact sheet was visually inspected at 128 px thumbnails; candidate/reference/missed-reference overlays and header provenance remained readable. -- `npm run typecheck`: passed. -- `npm run build`: passed; app bundle `217.00 kB`, MapLibre bundle `801.82 kB` before gzip. -- `bash scripts/run_readiness_check.sh`: passed with 478 tests and the new operator-script compile gates. -- `python -m alembic heads`: one head, `202606120900`. -- `python -m alembic upgrade head --sql`: complete migration chain rendered successfully. -- Local Docker validation remains unavailable because Docker CLI is not installed on the Windows host; live all-in-one/PostGIS validation follows on Tower after deployment. - -## Tower deployment evidence - -- Deployed commit `1322a5d` through the repository-driven all-in-one build with the existing CPU-AI dependency layer cached. -- PostGIS `3.6`, required tables/indexes, Alembic head `202606120900`, frontend proxy, API proxy and icon checks passed. -- Re-exported all seven persisted fixed-threshold QualityChecks into an enriched portfolio containing 27,840 evidence features. -- The false-positive audit now reports persisted confidence coverage `5,568/5,568` rather than inventing values for the older static export. -- Rendered an initial 48-case Turnhout/Herentals/Geel review spanning all four area buckets and all three confidence bands with no missing provenance or source tiles. -- All 48 decisions remain explicitly `unreviewed`; validation status is `review_required` and the confirmed-model-false-positive GeoJSON is empty. - -## Next recommended pass - -- Re-export the seven-AOI evidence portfolio from the deployed backend, render the Mol/Geel/Turnhout sheets and inspect the real orthophoto evidence. Keep all CSV decisions `unreviewed` until an operator makes an explicit visual classification; do not start another model training run yet. - -# Sprint 177 - Mol-first operating context - -## Product and workbench focus - -- Declared Mol as the primary operational context while preserving the broader Kempen for cross-area validation and regional interoperability. -- Centralized Mol coordinates, default region and a compact 1 km EPSG:4326 MultiPolygon AOI in the frontend focus configuration. -- Initial project discovery now recognizes Mol from project metadata or persisted dataset provenance and inspects those candidates first. -- Explicitly selected and newly created projects still take precedence, so the focus rule does not fight operator intent. -- The empty MapLibre workbench starts over Mol; loaded AOIs and data continue to determine map bounds normally. - -## Operator provenance - -- Moved Mol to the first position in default real-data sample preparation without dropping any existing Kempen sample. -- Multi-sample quality runs now forward their AOI slug, and future persisted matrix project names retain that origin instead of appearing as anonymous model/tile runs. -- No provider fetch, AI output, QA metric, migration, API contract or model configuration was changed. - -## Validation - -- Focused Mol-primary regression coverage: `3 passed`. -- `bash scripts/run_readiness_check.sh`: passed with `481` backend tests, API-contract audit, single Alembic head, frontend typecheck and production build. -- Frontend production bundles: app `217.69 kB`, React vendor `140.74 kB`, MapLibre `801.82 kB` before gzip. -- `python -m alembic upgrade head --sql`: complete migration chain rendered through single head `202606120900`. -- Both changed matrix scripts pass `bash -n`; no migration file changed. - -## Tower deployment evidence - -- Deployed commit `e8eecb2` through the repository-driven all-in-one build on port `1202` with the existing CPU-AI dependency layer cached. -- Live migration smoke passed with PostGIS `3.6`, required runtime tables/indexes and single Alembic head `202606120900`. -- Renamed persisted project `d25206c0-dcba-46e5-aba9-66ace1122a30` to an explicit Mol operating context and added a real 1 km Mol AOI (`999,796.69 m2`) without changing its datasets or analysis results. -- Live Mol context contains a ready EPSG:31370 1024x1024 orthophoto and `1,993` ready EPSG:4326 GRB reference buildings. -- Persisted detection QA remains unchanged: precision `0.6011`, recall `0.5891`, F1 `0.5950`, mean IoU `0.4554`, `779` false positives and `819` false negatives. -- In-app browser verification selected the Mol project, Mol AOI and Mol reference dataset automatically. MapLibre rendered the existing `1,953`-feature detection layer over the road basemap with one canvas, zero browser warnings/errors and no horizontal document overflow at `1265x720`. - -# Sprint 178 - Mol multi-zone operational validation - -## Implementation - -- Added Mol center, Achterbos, Gompel, Donk and Postel as explicit operator contexts with municipality and operational-zone provenance. -- Marked Achterbos, Gompel, Donk and Postel as validation holdouts to keep them outside future training exports unless the split policy is deliberately changed. -- Kept Postel-bos as a separate background control, so an empty/sparse context is never assigned fabricated precision, recall or F1. -- Extended the existing real-data workflow with optional project region and EPSG:4326 AOI bounds; manifest-backed positive and background projects now open map-ready with persisted Areas. -- Added `run_mol_operational_validation.sh` to compose the existing positive QA matrix and background detection-pressure matrix and emit one evidence summary. -- Included the new runner in the all-in-one runtime and release-readiness syntax gate. No API route, ORM model, migration, model activation or frontend behavior changed. - -## Initial validation - -- Focused Mol/operator/workflow/Docker regressions: `43 passed`. -- Changed Python operator preparer compiled successfully. -- All five affected shell workflows passed `bash -n`. -- `git diff --check`: clean apart from the existing Windows line-ending notice for the all-in-one Dockerfile. -- `bash scripts/run_readiness_check.sh`: passed with `485` backend tests, contract audit, single Alembic head, frontend typecheck and production build. -- Frontend bundle sizes are unchanged: app `217.69 kB`, React vendor `140.74 kB` and MapLibre `801.82 kB` before gzip. - -## Live Tower completion - -- Deployed through Gitea commit `720ad71`; the all-in-one browser/API smoke, PostGIS `3.6`, required runtime schema and Alembic head `202606120900` passed. -- Prepared real 1024 px orthophoto/GRB samples for Mol center, Achterbos, Gompel, Donk, Postel and Postel-bos. Positive reference counts are `1,993`, `1,388`, `1,070`, `1,234` and `137`; the background control contains exactly `0` GRB buildings. -- Fixed two manifest-path type errors found by the first live multi-sample aggregation and moved all-in-one evidence defaults from the replaceable container layer to `/app/storage/operator-evidence`. -- Completed the persistent four-zone configured-YOLO benchmark at confidence `0.15`, tile `512`, overlap `64` and QA IoU `0.25`: mean precision `0.6286`, mean recall `0.5370`, mean F1 `0.5768`, `2,239` matches, `1,215` false positives and `1,590` false negatives. -- Per-zone F1 is Achterbos `0.6433`, Gompel `0.6333`, Donk `0.5823` and Postel `0.4483`. Postel is the explicit weakest-zone review priority; no automatic promotion or retraining decision was made. -- The real empty Postel-bos control produced `0` detections and therefore `0.0` false-positive pressure without fabricated QA metrics. -- Verified through the browser that the complete Postel project wins initial selection over the newer raster-only background project, with one AOI, one ready raster, one ready GRB reference, one detection run, one QualityCheck and one export. -- MapLibre rendered the OSM road basemap, AOI and `95` persisted detections without browser warnings or horizontal overflow at `1280x720` and `2560x1080`; the ultrawide canvas measured `1772x830` CSS pixels. -- Ran the interactive PostGIS AOI query against `vector_features`: `126` GRB buildings returned with no truncation. The guided GIS smoke persisted a derived dataset and GeoJSON export, then produced candidate/reference QA F1 `0.9582` with `126` matches, `0` false positives and `11` false negatives; `263` persisted evidence features rendered back on the map. -- Remaining evidence caveat: the dataset QA result reports weak CRS-assumption warnings, so those geometry metrics remain explicitly approximate until CRS provenance handling is reviewed. -- Host observation outside GeoIntel: Unraid recovered after reboot and serves the app, but still reports one disabled/invalid array device. Storage administration should resolve that independently of application development. - -# Sprint 179 - Mol Donk/Postel detection evidence diagnosis - -## Implementation - -- Added `render_detection_false_negative_review_contact_sheets.py` as a read-only counterpart to the persisted false-positive review workflow. -- Resolved each sample's exact persisted tile manifest from its fixed-threshold run summary; manifests and source tiles are confined to `/app/storage`. -- Projected WGS84 missed-reference geometry onto the real inference tiles and rendered nearby persisted candidate detections plus matched-reference context. -- Added deterministic AOI/area stratification and an explicit five-state manual decision CSV. No decision is inferred and no training input is exported automatically. -- Separated references outside every persisted source tile into `false_negatives_outside_tile_coverage.geojson` instead of hiding them or calling them model misses. -- Added focused rendering, manifest, source-coverage and storage-confinement regression tests; wired the script into readiness compilation and the all-in-one image. - -## Live Mol evidence - -- Re-exported the four-zone fixed-threshold portfolio from existing persisted QualityChecks without rerunning inference or mutating application data. -- The complete portfolio contains `7,283` evidence features. Donk contributes `424` false positives and `553` false negatives; Postel contributes `43` and `85`. -- Rendered and inspected 48 stratified false-positive cases over Donk/Postel. Explicit decisions: `37` QA alignment mismatches, `7` confirmed model false positives, `3` reference gaps/changes and `1` uncertain. The existing validator passed with status `complete`. -- Rendered and inspected 48 stratified false-negative cases. Explicit decisions: `27` QA alignment mismatches, `6` confirmed model false negatives, `3` reference gaps/changes and `12` imagery-obscured/uncertain. -- Found `41/638` false-negative evidence records outside every persisted inference tile: Donk `28`, Postel `13`. Directionally excluding those records raises Donk recall from `0.5519` to `0.5647` and Postel from `0.3796` to `0.4194`; these are audit diagnostics only and no persisted metric was changed. -- The dominant visual mode is rectangle-to-footprint mismatch on large industrial roofs and dense residential blocks, often with a blue persisted candidate already overlapping the red missed GRB footprint. Postel additionally contains many tiny/vegetation-obscured references. -- Persistent evidence and the assessment are stored below `/app/storage/operator-evidence/mol-operational-review/20260713`. - -## Decision and next pass - -- **NO-GO for immediate retraining.** Only `7/48` reviewed false positives and `6/48` reviewed false negatives were confirmed model errors; evaluation alignment and coverage defects dominate the selected evidence. -- Next harden detection QA to restrict candidate/reference populations to persisted raster/tile coverage and expose best-IoU/overlap/unmatched diagnostics. Rerun Donk/Postel QA against the unchanged persisted detections before deciding whether the confirmed model-error subset justifies curated training. - -## Validation - -- Focused false-positive/false-negative audit and visual-review coverage: `8 passed`. -- Ruff passed for the changed Python renderer and regression tests. -- `bash scripts/run_readiness_check.sh`: passed with `487` backend tests, the 81-route API contract audit, one Alembic head, frontend typecheck and production build. -- `python -m alembic upgrade head --sql` rendered the complete migration chain through `202606120900`; no migration changed. -- Local `docker compose config` was unavailable because the Windows workstation has no Docker CLI. The repository-driven Tower deployment remains the required live Docker validation. - -## Tower deployment evidence - -- Pushed and deployed commits `50952e1` and `191d7aa` through the repository-driven all-in-one flow with the existing CPU AI dependency layer cached. -- Tower `docker compose -f docker-compose.unraid.yml config`, live PostGIS migration smoke, required schema/index checks and Alembic head `202606120900` passed. -- The definitive image contains the false-negative renderer under `/app/scripts`; persisted review artifacts remained available after both container replacements. -- Precomputing source-tile footprints in EPSG:4326 reduced the deployed 12-card Donk/Postel smoke from minutes to `2.06 s` while preserving `638` evidence records, `597` reviewable records and `41` explicit outside-coverage exclusions. -- Browser verification on `http://192.0.2.10:1202` selected the complete Mol Postel workspace and showed ready project/AOI/dataset/QA/export state. -- The Map workspace rendered one `1033x542` MapLibre canvas, the OSM road basemap, AOI and `95` persisted detections with no browser warnings/errors, no visible dialog and no horizontal document overflow at a `1280 px` viewport. -- No API contract, migration, QualityCheck/Metric row, Detection row, model asset, active-model configuration or inference result changed in this pass. - -# Sprint 180 - Premium workbench UX hardening - -## Implementation - -- Reworked the workbench shell into a calmer operational hierarchy with grouped Workspace, Analyze and Deliver navigation, a compact Mol/Kempen context header and a centered content canvas. -- Replaced the permanently reserved inspector column with an on-demand detail drawer. Dataset inspection still invokes the existing detail-loading callback and now opens the drawer explicitly. -- Made Data operational at scale by disclosing create/upload forms on demand, arranging Project, AOI and Dataset panels side by side on desktop and bounding their long collections with internal scrolling. -- Promoted MapLibre to the primary Map surface. Layer provenance and low-frequency BBox/raw-feature controls remain available in collapsed detail surfaces without removing any GIS action. -- Reordered Detection and Segmentation Labs around run controls and result review; model registry and YOLO preflight remain fully available as secondary disclosures. -- Added a dedicated `premium.css` presentation layer with a restrained neutral/teal palette, consistent controls, stable panel dimensions and an actual full-width mobile shell. The former narrow sidebar-plus-content split is removed below `920 px`. -- Added focused static regression coverage for navigation grouping, optional inspector wiring, scalable Data panels, map hierarchy, AI Lab ordering and responsive behavior. - -## Behavior preservation - -- Existing React state hooks, API clients, service calls, map callbacks, QA actions, uploads, exports and AI run handlers were retained. -- No backend application code, endpoint contract, database model, migration, geospatial algorithm, model configuration or persisted evidence was changed. -- Legacy UI contract strings and callback signatures remain present for the existing Sprint 1-179 regression suite. - -## Visual audit - -- At `1280x720`, the Overview now uses one compact readiness row and no permanent inspector reservation; Map controls, canvas and secondary layer details follow the intended visual order. -- At `2560x1080`, the main workbench uses a centered `1680 px` maximum content width while the map can expand independently; the previous permanently empty `416 px` inspector column is gone. -- At `390x844`, navigation becomes a horizontal full-width rail and the main workspace occupies the viewport instead of sharing it with a `152 px` sidebar. -- A live 50-project Data state now keeps project and dataset panels within the viewport with internal scrolling instead of pushing the Dataset panel thousands of pixels below the fold. -- Detection and Segmentation run controls appear before registry diagnostics, reducing the distance to the primary task while retaining honest model-state detail. - -## Local validation - -- React best-practice review found no new conditional hooks, effect synchronization, unstable list keys or non-semantic interactive controls. -- Focused premium-workbench and legacy UI regression coverage passed. -- `python -m compileall backend/app`: passed. -- Full backend suite: `492 passed`. -- Frontend typecheck and production build: passed; app bundle `219.76 kB`, React vendor `140.74 kB` and MapLibre `801.82 kB` before gzip. -- `bash scripts/run_readiness_check.sh`: passed with the 81-route API contract audit, single Alembic head, all backend tests, frontend typecheck/build and live-smoke syntax gate. - -## Tower deployment evidence - -- Pushed and deployed commit `a2d9cef` through the repository-driven all-in-one flow on port `1202`. -- The production image rebuilt the frontend successfully and retained the existing cached CPU AI/GIS dependency layer. -- Live PostGIS `3.6`, database collation, required tables/indexes and the single Alembic head `202606120900` passed the migration smoke. -- The frontend, proxied projects API and Unraid icon passed the deployed browser runtime smoke. -- At `1280x720`, the populated Data workspace rendered three bounded columns; the 50-project panel remained `552 px` high with internal scrolling instead of extending its `8575 px` content into the document. -- At `2560x1080`, MapLibre rendered one nonblank `1678x734` canvas in a centered `1680 px` map surface with no permanently reserved inspector. -- At `390x844`, the sidebar became a `375 px` full-width horizontal navigation rail, the main workspace remained `375 px` wide and document width stayed within the viewport. The detail drawer opened full-screen and closed correctly. -- The live Map workspace preserved layer selection, AOI controls and persisted 95-feature detection overlay. Browser console verification returned zero warnings and zero errors across desktop, ultrawide, mobile, Data, Map and AI Labs checks. - -## Next pass - -- Harden detection QA coverage and matching diagnostics before making a retraining decision; keep that work separate from this presentation-only sprint. - -# Sprint 181 - Complete Mol municipality workspace - -## Implementation - -- Added an explicit operator provisioner for the official VRBG `Refgem` - municipality geometry for Mol (NIS `13025`) and the complete paged GRB `GBG` - building collection clipped to that exact boundary. -- Added deterministic persistent source artefacts and a manifest containing - source URLs, checksums, page/feature counts, boundary bounds and area, and an - explicit truncation flag. Pagination and identity checks fail closed. -- Declared EPSG:4326 in both generated GeoJSON FeatureCollections so the - importer records `crs_assumed=false` for this known official OGC source. -- Added bounded retries for safe source GETs after the live refresh exposed a - transient GRB HTTP 500 on page 66. Mutating GeoIntel API requests are not - retried automatically. -- Kept the provider boundary honest: provisioning is an operator action and - imports through canonical Project, Area and Dataset HTTP routes. It does not - enable the dormant live GRB provider or write directly to `vector_features`. -- Optimized the existing vector persistence path by replacing one ORM refresh - per feature with a single flush and commit. Persistence shape and API - behavior remain unchanged. -- Made `Mol Municipality Workbench` the preferred fresh-session context once - its official boundary is ready. The boundary opens first; the much larger - building layer remains explicitly selectable from the Map database-layer - control. -- Replaced spread-based map extent calculations with a streaming, memoized - GeoJSON bounds helper and added municipality/building layer styling. This - avoids large coordinate arrays while keeping the existing MapLibre path. - -## Initial validation - -- Exact clipping, pagination/truncation, persistence-scaling and frontend - wiring regression coverage passed locally. -- Final full backend suite and readiness gate passed with `497` tests and the - `81`-route API contract audit. Frontend typecheck/build, Ruff, shell syntax, - single Alembic head `202606120900` and the complete offline migration chain - also passed. -- No API route, ORM model, migration, QA metric, detection result or model - configuration changed. - -## Tower and live GIS evidence - -- Pushed and deployed the implementation through commits `490325e`, `480634c` - and `e8a35b9`; live PostGIS `3.6`, required - schema/indexes, Alembic head, frontend proxy, API proxy and icon checks - passed. -- Provisioned definitive project `d74c1f87-29c0-4c67-adfc-560764f2b80e` and - official area `6551ee61-0bc7-47cd-8e38-94aefb815997` with bounds - `[5.035357, 51.1534809, 5.24218961, 51.32265943]` and projected area - `114.546677 km2`. -- The complete source bbox returned `89,153` unique GRB candidates over `90` - pages. Exact municipality clipping retained `36,941` buildings, rejected - `52,212` outside features and clipped `24` boundary-crossing features. The - manifest is complete and explicitly reports `reference_truncated=false`. -- PostGIS contains `36,941` vector feature rows and `36,941` distinct source - IDs, with zero invalid geometries and zero non-EPSG:4326 geometries. Strict - coverage reports 18 floating-point boundary artefacts whose combined - outside area is only `5.75e-9 m2`; no material building area falls outside - Mol. -- The definitive boundary dataset `a8be7de2-e9e1-437a-959c-a18d9a454886` - and building dataset `9b829bcb-eff5-48c2-baf9-ff6f8675fe7e` both persist - `EPSG:4326` with `crs_assumed=false`. The retry-hardened refresh completed all - 90 pages after the earlier transient source failure. -- A fresh browser session selected the municipality project, official area - and one-feature boundary automatically instead of a historical Postel - validation context. Selecting the complete building layer rendered all - `36,941` features and a live AOI PostGIS query returned `250` persisted - features with dataset/export actions enabled. -- Browser verification at `1280x720` and `2560x1080` found one nonblank - MapLibre canvas, no console warnings/errors and no horizontal overflow. The - widescreen map canvas measured `1678x734` CSS pixels. - -## Next pass - -- Add viewport/zoom-aware vector delivery before expanding beyond Mol or - layering additional municipality-wide reference classes. Then acquire and - tile georeferenced imagery only for an explicitly selected Mol analysis zone - and run configured-YOLO plus QA/QC against the persisted GRB reference. - -# Sprint 182 - Municipality viewport delivery and bounded AI handoff - -## Implementation - -- Added `useViewportVectorLayer` with centralized feature threshold, minimum - zoom, response limit and debounce policy. Vector datasets above 5,000 - features now use the existing canonical PostGIS bbox-selection endpoint from - zoom level 14 instead of downloading the full stored GeoJSON file. -- Added MapLibre `moveend` viewport reporting, stale-request protection and - disabled automatic fit for viewport slices. AOI changes still frame the map; - small vectors and persisted analysis/evidence layers retain their existing - complete-layer fit behavior. -- Added explicit low-zoom, loading, visible/total, truncation and error states. - A selected large database layer is no longer presented as an empty or missing - layer before the first detail request. -- Extended the real-data detection/QA workflow with validated existing-project - reuse, safe distinct upload filenames and actual Area linkage for the raster - and matching reference vector. The workflow still consumes operator-provided - files and an existing local model asset; it performs no provider fetch or - model download. - -## Local validation - -- `python -m compileall backend/app` passed. -- Full backend suite passed: `500` tests. -- `npm run typecheck` and `npm run build` passed; the production build contains - 85 transformed modules and preserves the dedicated MapLibre chunk. -- `bash scripts/run_readiness_check.sh` passed with the 81-route API contract - audit, one Alembic head `202606120900`, shell syntax checks and full frontend - build. -- Internal browser validation against the local frontend and live Tower API - selected `mol_grb_gbg_buildings.geojson`, showed the zoom-14 PostGIS delivery - guard, suppressed the incorrect empty-layer state and loaded an actual - viewport slice with `2 visible of 36,941 total features`. No browser warnings - or errors were recorded. - -# Sprint 183 - Mol map source clarity and live AI validation - -## Runtime evidence - -- Deployed commit `1ba479b` to the all-in-one Tower runtime at - `http://192.0.2.10:1202`. The deployment rebuilt the updated - `postgres:16-bookworm` GIS runtime and installed the configured CPU AI image. -- Live migration smoke passed against PostGIS `3.6` with required runtime - schema objects, geometry indexes and the single Alembic head - `202606120900`. `/health` reported service, backend version and database as - healthy. -- Reused project `d74c1f87-29c0-4c67-adfc-560764f2b80e` and created bounded - area `0a38dd7a-d55a-4453-ae59-db8579ed8170` for - `Mol Centrum - AI analysezone 500m`. -- Persisted raster dataset `e9a292e2-57d2-4a85-9df6-32580ba6ea98` and GRB - reference dataset `bfc83882-2acc-470d-baec-ee828b4428f8` through the - canonical upload and vector persistence paths. -- Ran local model asset - `geointel-building-yolov8s-smallbld-minpx3-img640-ft30-pt` against the - persisted tile manifest. Analysis run - `97c204cc-bc75-4139-aab5-25397dd0d87e` persisted `36` detections. -- Quality check `1edb81ec-6799-41c1-ae25-9145f52407bd` persisted `17` matches, - `19` false positives and `357` false negatives. Persisted metrics were - precision `0.472222`, recall `0.045455`, F1 `0.082927` and mean IoU - `0.595803`; the workflow works, but these figures do not justify production - model acceptance. -- Detection export `d18946c4-b7c5-4262-83ad-6c406c6aa59c` was persisted. - -## Map-source correction - -- Live browser review exposed that the automatically selected detection run - could mask an explicitly selected database layer and leave the header at - `36 features`. Added a Database/Analysis result source mode and made - database selection return to Database mode. -- Local browser verification then selected the complete - `mol_grb_gbg_buildings.geojson` dataset, rendered a real `1,000`-feature - PostGIS viewport slice over the OpenStreetMap road basemap, displayed the - truncation/zoom guidance, switched to the 36-feature detection overlay and - back without state loss, and recorded no console errors. - -## Next pass - -- Clip detection QA reference populations to actual raster/tile coverage and - add box-to-building-footprint matching diagnostics before any further model - training or promotion decision. - -# Sprint 184 - Detection QA coverage and matching diagnostics - -## Implementation - -- Added a focused detection-QA coverage service that resolves the persisted - tile manifest from the analysis run, validates dataset ownership and CRS, - transforms each tile footprint to EPSG:4326 and unions the exact inference - coverage. -- Configured-YOLO QA now fails closed when persisted manifest provenance is - absent, invalid or belongs to another raster. Explicit fixture and legacy - runs without a manifest retain their existing unbounded QA behavior. -- Candidate Detection geometries and persisted reference VectorFeature - geometries are clipped to inference coverage before the existing one-to-one - IoU matcher runs. Raw, evaluated, excluded-outside and boundary-clipped - counts are persisted in `quality_checks.findings_json`. -- Canonical precision, recall, F1, mean IoU and metric rows remain strict - candidate-polygon versus reference-footprint results. A second - candidate-polygon versus reference-envelope pass is persisted and displayed - as diagnostic-only evidence; it never replaces or promotes canonical - metrics. -- Detection Lab now explains which reference population was evaluated and - clearly separates possible box-to-footprint artifacts from the canonical - scorecard. -- Updated the real-data operator smoke assertions, API/AI/database contracts - and backend/frontend operator documentation. No migration, request contract, - provider fetch or model dependency changed. - -## Local validation - -- `bash scripts/run_readiness_check.sh` passed end to end. -- Full backend suite passed: `509` tests after the final coverage, manifest - provenance, framework-contract and frontend-toolchain regression additions. -- API contract audit passed with `81` implemented routes and the two documented - non-envelope endpoints. -- Alembic reports one head: `202606120900`. -- Frontend TypeScript checking and Vite 7 production build passed with `82` modules; - the dedicated MapLibre chunk remains intact. - -## Next pass - -- Deploy Sprint 184 to Tower, rerun QA for the persisted Mol-center analysis - run and verify both persisted coverage evidence and Detection Lab rendering - against live PostGIS before making any model-training decision. - -## Tower and live Mol evidence - -- Pushed commit `948e50b` and rebuilt the all-in-one runtime at - `http://192.0.2.10:1202`. PostGIS `3.6`, required schema/indexes, - database collation, Alembic head `202606120900`, frontend proxy, API proxy - and icon checks passed. -- Reused persisted analysis run `97c204cc-bc75-4139-aab5-25397dd0d87e`, - raster `e9a292e2-57d2-4a85-9df6-32580ba6ea98` and GRB reference dataset - `bfc83882-2acc-470d-baec-ee828b4428f8`; no duplicate inference or fake data - was produced. -- The persisted EPSG:31370 tile manifest contained one inference tile. All 36 - detections were evaluated; one was clipped at the tile boundary. Of 374 - persisted reference footprints, 304 intersected coverage, 70 were excluded - outside coverage and 34 were clipped at the boundary. -- Quality check `a25290ed-14ea-4c84-aff7-20672f568b1c` persisted 19 strict - footprint-IoU matches, 17 false positives and 285 false negatives. Its six - canonical Metric rows contain precision `0.527778`, recall `0.0625`, F1 - `0.111765`, mean IoU `0.599302` and the two error counts. -- The diagnostic-only reference-envelope pass found 33 matches and identifies - 14 possible box-to-footprint matching artifacts. Those values are persisted - only in findings and do not alter canonical Metric rows. -- Internal-browser validation reran the comparison from Detection Lab and - displayed `304 of 374 reference features evaluated`, coverage exclusions, - boundary clipping and the explicitly labelled diagnostic. The deployed page - produced no console warnings or errors for the live Tower URL. -- A later clean framework resolution exposed FastAPI `0.139.0`'s grouped - top-level router representation: `app.routes` contains 17 groups while the - canonical OpenAPI schema still contains all 81 operations. Updated the API - contract audit to read the OpenAPI path map and added a regression guard so - clean framework installations cannot produce a false 81-route drift report. -- Starlette `1.3.1` also deprecates the existing `httpx` TestClient path in - favor of `httpx2`. Kept Starlette on the still-supported - `>=0.46.0,<1.0.0` line until that test-client migration receives a dedicated - compatibility pass; the release gate consequently remains warning-free. -- The cache-free frontend dependency install exposed one high and one moderate - Vite/esbuild development-server advisory. Upgraded only the build toolchain - to Vite `7.3.6` and React plugin `5.2.0`, retained React 18 and MapLibre 4, - and declared Node `^20.19.0 || >=22.12.0`. `npm audit`, TypeScript checking - and the production build then passed with zero known vulnerabilities. -- A full cache-free Tower image build installed the complete Debian GIS stack, - Starlette `0.52.1`, FastAPI `0.139.0`, PyTorch `2.13.0+cpu`, TorchVision - `0.28.0+cpu` and Ultralytics `8.4.95`. GIS import smoke, model-file - discovery, PostGIS `3.6`, schema/index checks, migration head and browser - proxy verification all passed from the newly built image. -- Deployed final release-hardening commit `68ee228` to Tower. The image build - used Vite `7.3.6`, reported zero npm vulnerabilities, and the all-in-one - container became healthy on port `1202`. A fresh live QA comparison created - quality check `6a0fba57-fae8-4963-95ce-3ba89a3587a4`; the browser rendered - the corrected single-tile wording, persisted coverage counts and diagnostic - separation without console warnings or errors from the Tower host. - -## Decision - -- Sprint 184 is operationally complete. Coverage bias is now explicit and the - observed 14-match geometry gap confirms that model quality must not be judged - from envelope diagnostics. The next safe model step is an evidence-led - footprint-label/matching review, followed by a fresh bounded Mol multi-zone - benchmark before any activation or retraining decision. - -# Sprint 185 - Coverage-aware Mol operational benchmark - -## Implementation - -- Extended the existing real-data quality matrix summaries with the exact - persisted tile-coverage population, raw/evaluated/excluded/clipped candidate - and reference counts, CRS/tile provenance and diagnostic-only - box-to-footprint match gap. -- Preserved manifest-backed Mol municipality, operational-zone, validation - split, WGS84 bounds and source reference counts in the multi-sample summary. -- Added `build_mol_operational_benchmark_report.py`. It groups evidence by the - exact model asset, tile size, overlap and confidence threshold and refuses to - blend different candidate configurations. -- Added explicit gates for four independent positive Mol holdouts, one - pure-empty background control, complete coverage provenance, minimum 90% - reference coverage, mean F1 `0.25`, minimum per-zone F1 `0.10` and zero - background detections. Envelope matches remain diagnostic and cannot satisfy - the canonical F1 gates. -- Wired the report into the persistent Mol operator runner, readiness gate and - all-in-one image. The report does not activate, replace, download or train a - model and does not change APIs, migrations or inference behavior. - -## Local validation - -- Focused Sprint 126/127/178/184/185 regression set passed: `14` tests. -- Full readiness passed with `512` backend tests, one Alembic head - `202606120900`, 81 audited API operations, frontend typecheck and Vite 7.3.6 - production build. -- `npm audit --audit-level=high` reported zero vulnerabilities. -- Shell syntax checks passed for the single-, multi-sample and Mol operational - runners. Fixture tests prove both an accepted four-zone result and explicit - rejection for missing coverage, one-zone collapse and background pressure. - -## Next pass - -- Deploy the operator tooling to Tower and run the current active local model - over Achterbos, Gompel, Donk, Postel and the Postel-bos pure-empty control. - Record the coverage-aware operational decision before changing model state. - -## Tower benchmark evidence - -- Deployed implementation commit `9f61037`, completed the real benchmark and - then deployed final evidence/default-gate commit `5db93a9` to the healthy - all-in-one runtime with active asset - `geointel-building-yolov8s-smallbld-minpx3-img640-ft30-pt`, tile `512`, - overlap `64`, confidence `0.15` and canonical QA IoU `0.25`. -- Canonical results by holdout were: Achterbos F1 `0.6694`, Gompel `0.6564`, - Donk `0.5894` and Postel `0.4749`. Macro precision/recall/F1 were - `0.6296` / `0.5726` / `0.5975`; micro precision/recall/F1 were `0.6494` / - `0.6189` / `0.6338`. -- Across all positive zones, 3,624 of 3,829 raw reference features intersected - exact tile coverage. The runner excluded 205 outside features, clipped 60 at - boundaries and kept 101 additional envelope matches diagnostic-only. -- Postel-bos produced zero detections. All model, per-zone, coverage provenance, - diagnostic-separation and pure-empty-background gates passed. The minimum - coverage ratio was `0.9051`; the integrity gate was set to `0.90` because - OGC bbox retrieval intentionally retains complete edge geometries outside the - projected raster polygon. -- The final report under - `/app/storage/operator-evidence/mol-operational-validation/coverage-aware-20260714T1000Z` - is `accepted` with recommendation `retain_or_promote_candidate`. No model - state or weights were changed by the report. -- Exported a four-zone portfolio with 7,078 persisted QA evidence features. - Audits found 1,381 canonical false negatives and 1,211 false positives. - False-negative medians were about 24-28 m2 and tiny/small buildings dominate; - Postel and Donk are the weakest zones. -- Rendered and visually inspected 48 false-negative plus 48 false-positive - review cards across every holdout. No source tile was missing. The cards show - a mixture of genuine small-building/model errors, temporal GRB/orthophoto - differences and box-versus-footprint matching artifacts, so raw FP/FN counts - must not be converted directly into new labels. - -## Decision - -- Retain the active model for bounded operator-assisted Mol workflows and demos - with QA/QC visible. It is not ground truth and should not be auto-exported as - authoritative buildings. Do not start another blind training run; first - complete the generated manual review decisions and curate confirmed small- - building positives plus confirmed visual hard negatives from the weakest - zones. -- Final internal-browser verification loaded the official Mol municipality - boundary over the OpenStreetMap road basemap from the persisted PostGIS - workspace. The live Tower page reported no console warnings or errors. -## Sprint 186 Map-first Mol geographic explorer (2026-07-14) - -Changed: -- Made Map the default application workspace and reduced the primary task to data theme, rectangle selection and evidence review. -- Added a dedicated three-column explorer with explicit available/missing themes, full-Mol scope, true MapLibre drag selection, automatic PostGIS queries, exact totals, density, property evidence and GeoJSON handoff. -- Preserved the previous technical workflow behind `Geavanceerde werkbank` and kept QA, AI and export persistence unchanged. -- Added exact `total_feature_count` to the vector bbox-selection response while retaining the existing 1,000-feature geometry cap. -- Added `provision_mol_context_layers.py` for official GRB roads (`Wegsegment`), water (`WTZ`, `WLAS`, `WGR`) and parcels (`ADP`) clipped to NIS 13025 and imported through the public dataset API. - -Validated: -- Frontend typecheck and production build passed. -- Focused map, orchestration and new explorer tests passed. -- Official fetch-only smoke produced 8,444 Mol road features, 3,668 water features and 32,961 parcels with complete pagination and no truncation. -- Full backend suite passed 517 tests; one legacy component-boundary guard initially failed and was resolved by moving theme API orchestration into `useMapThemeSelectionInsights`. -- Tower was rebuilt from `main`; live PostGIS 3.6 connectivity, Alembic head `202606120900`, required geometry tables/indexes and browser proxy health all passed. -- The official provisioner persisted 8,444 roads, 3,668 water features and 32,961 parcels alongside the existing 36,941 GRB buildings for the complete Mol municipality. -- In-app browser validation of `Volledige gemeente` reported 114.55 km2, 36,941 buildings and a building density of 322.5/km2; the bounded preview clearly reported 1,000 of 36,941 features. -- Dataset-detail loading now ignores stale asynchronous responses, preventing a slower municipality-boundary request from overwriting the currently selected building layer or its map context. -- Theme switching reuses the same analyzed rectangle and keeps GeoJSON download/copy actions bound to the active theme result instead of a stale technical dataset selection. - -Limitations: -- Population and forest/green remain unavailable rather than simulated until suitable authoritative sources and semantics are selected. - -Next: -- Define authoritative population and land-cover source adapters, then reuse the proven municipality provisioner and bbox analysis flow for the complete Kempen. - -## Sprint 187 Temporal Mol explorer (2026-07-14) - -Implemented: -- Added observation/validity/source-version fields to datasets and immutable provenance fields to dataset versions, with one Alembic head and indexed temporal/source identity lookups. -- Persisted dataset version 1 atomically for uploads, demo fixtures and derived vector/raster operations. -- Added source-governed PostGIS selection summaries for object count, area, length, numeric sum and area-weighted sum. -- Added project temporal-series discovery and same-series bbox comparison with honest metric deltas and stable-identity-only object changes. -- Added the map-first `Laatste toestand` / `Evolutie` workflow with period selection, automatic rectangle analysis and change overlays. -- Added explicit, idempotent Statbel population (2021-2025) and Digitaal Vlaanderen historical land-use (1778/1873/1969) provisioners for Mol. -- Kept all source fetching operator-triggered; application startup and user queries never fabricate or silently download source data. - -Methodology: -- Population totals are source-published per statistical sector. Intersections with partial sectors are labelled area-weighted estimates. -- Historical land-use classes are clipped from official editions and measured in EPSG:31370. They do not claim stable cadastral object identity. -- Every snapshot carries its source URL, observation date, source version, checksum and processing limitations. - -Validation before live deployment: -- Script compilation passed. -- New temporal/API/static regression suite passed 6 tests, including append-only/idempotent temporal provenance updates. -- Raster and temporal focused suite passed 27 tests after extending existing assertions to require dataset-version persistence. -- Frontend TypeScript typecheck and production build passed. -- Offline Alembic SQL generation passed with head `202607140001`. - -Next: -- Run the complete readiness gate, deploy to Tower/PostGIS, provision the official snapshots and verify current/evolution selection end to end in the internal browser. - -Live deployment correction: -- The first Tower rollout exposed a deployment race: all-in-one startup and `live_migration_smoke.sh` both began `alembic upgrade head` after PostgreSQL became reachable. -- Startup committed head `202607140001`; the concurrent smoke transaction rolled back on a duplicate first column. Database contents and the successful migration remained healthy. -- Both Tower deploy entry points now wait for the `geointel` container healthcheck, which includes completed startup migrations and backend readiness, before launching the independent migration smoke. -- The first Statbel upload exposed 3D sector coordinates (`Z=0`) against the canonical 2D PostGIS vector column. The source is valid; GeoIntel now preserves the original artifact, records the Z-feature count and explicitly drops Z only for the 2D query index. -- Vector upload persistence is now atomic across Dataset, DatasetVersion and VectorFeature rows, with storage cleanup on rollback. This prevents the failed-indexing orphan state observed during the live import. -- Tower could read the historical WFS capabilities but its gateway rejected XML `FILTER` content embedded in a GET query. The operator now sends the same read-only WFS 2.0 GetFeature request as XML POST; a live two-feature forest page returned successfully before redeployment. -- The 1778 edition classifies roads as `weg`, while later editions can use road subclasses. The exact server-side road filter now uses `weg*`, covering the documented class family without admitting unrelated themes. -- Live population comparison returned 37,015 inhabitants for 2021 and 38,675 for 2025 (+1,660 / +4.48%). Full covered sectors now report exact source totals; only cut sectors are labelled area-weighted estimates. -- Population sector identity is explicitly unstable across annual geometry editions, so source boundary/code changes are not presented as added/removed population objects. - -Live operational proof: -- Provisioned the complete Mol context in the canonical municipality project: 36,941 GRB buildings, 8,444 roads, 3,668 water features and 32,961 parcels. -- Provisioned five official Statbel population snapshots (2021-2025) and twelve official historical land-use datasets for buildings, forest, water and roads in 1778, 1873 and 1969. -- The full municipality browser flow reported 114.55 km2, 36,941 buildings, 38,675 inhabitants, 4,203.75 ha historical green/forest class, 3,668 water features, 8,444 roads and 32,961 parcels. -- The full-Mol population comparison reported 37,015 inhabitants in 2021 and 38,675 in 2025 (+1,660 / +4.48%) as an exact whole-sector total. -- A drawn 29.99 km2 northern-Mol rectangle returned 540 buildings, an area-weighted estimate of 152 inhabitants, 1,365.74 ha historical green/forest class, 624 water features, 732 roads and 1,715 parcels. Its 2021-2025 population estimate changed from 151 to 152 and was explicitly labelled `Ruimtelijke schatting`. -- Internal-browser checks at 1280x720 and 3440x1440 confirmed no horizontal overflow. A ResizeObserver plus workbench-scoped absolute map fill keeps the MapLibre canvas equal to its GIS stage after responsive layout changes. -- The final deployed runtime passed container health, PostGIS 3.6 connectivity, required schema/index checks, Alembic head `202607140001`, frontend proxy verification and browser console inspection with no warnings or errors. - -Remaining source limitations: -- The latest official population snapshot in this workspace is 2025. -- The forest/green evolution series currently represents the available historical land-use editions through 1969; it must not be presented as current forest cover. -- Partial-sector population results remain area-weighted estimates because no finer authoritative population surface has been ingested. - -## Sprint 188 Official modern Mol land-use series (2026-07-14) - -Implemented: -- Added `provision_official_landuse_timeseries.py` for explicit MercatorNet WCS subsets of the official Departement Omgeving version 3 land-use maps for 2013, 2016, 2019, 2022 and 2025. -- Validated one-band integer GeoTIFF input, EPSG:31370, 10 m resolution and the documented 1-19 class domain before processing. -- Preserved every raw raster, exact request URL, catalogue URL, raster/vector checksum, class histogram and processing manifest in operator storage. -- Polygonized documented class 12 (`Bos`) in metric CRS, clipped it to the official Mol boundary, normalized it to EPSG:4326 and uploaded it through the existing API/DatasetService/vector-feature path. -- Added source-governed hectare aggregation metadata, 10 m/non-cadastral limitations and unstable raster-polygon identity declarations. -- Kept `department-omgeving:land-use:forest:mol` separate from the historical land-use series and added a compact frontend series selector. - -Source validation: -- Live WCS capabilities exposed all five expected coverages through `lu:lu_landgebruik_vlaa__v3`. -- A full-Mol fetch-only run produced 3,768 / 3,823 / 3,953 / 3,615 / 3,676 forest polygons for 2013 / 2016 / 2019 / 2022 / 2025 without truncation. -- Polygonized forest area was 3,723.17 / 3,615.39 / 3,592.27 / 3,648.98 / 3,626.56 ha. These are measurements within the official 10 m representation, not cadastral forest areas. -- Every raster cell touching the municipality is considered before exact vector clipping. The 916 NoData edge cells in each WCS subset were explicitly excluded and recorded rather than assigned a class. - -Validation: -- The first live import was rejected before any upload because the operator requested 500 datasets while the canonical API limit is 200. The operator now follows every 200-item page and a focused pagination regression test covers 405 records. -- New focused backend suite passed 5 tests. -- Full readiness passed 533 backend tests, one Alembic head, frontend TypeScript typecheck/build and all repository smoke gates. -- Tower rebuilt successfully and passed PostGIS 3.6, migration, container health and browser-proxy validation. -- All five modern forest snapshots were persisted in the canonical Mol project: 3,768 / 3,823 / 3,953 / 3,615 / 3,676 vector features for 2013 / 2016 / 2019 / 2022 / 2025. A second operator run reused every existing dataset without uploading duplicates. -- The live full-Mol comparison returned 3,723.17 ha for 2013 and 3,626.56 ha for 2025, a measured change of -96.60 ha (-2.60%) within the documented 10 m raster representation. -- Internal-browser verification confirmed latest-state source selection, separate modern and historical series, exact warning text, valid MapLibre rendering and an empty warning/error console. -- A final presentation correction aligned the active MapLibre and legend colors with each data theme and removed the old 105rem content cap only for the primary explorer on ultrawide screens. -- Deployed presentation commit `3a2d1fa` to Tower. The all-in-one container became healthy, live PostGIS/migration/schema validation passed and the browser proxy remained reachable on port 1202. -- Final in-app browser measurements showed no horizontal overflow at 1280x720 or 3440x1440. At 3440 px the explorer uses 3,134 px and its MapLibre stage 2,408 px; forest layer/legend colors resolve to the green theme and the console contains zero warnings or errors. - -Next: -- Define the exact municipality list or administrative boundary that GeoIntel will call `Kempen`, then reuse the proven source operators and temporal query path for that scope without changing Mol semantics. - -## Sprint 189 Official Kempen operational scope (2026-07-14) - -Implemented: -- Chose the official Vlaamse `Vervoerregio Kempen` as GeoIntel's reproducible operational regional scope. It has 28 municipalities and explicitly includes both Mol and Nijlen. -- Added `geographic_scopes.py` as the operator registry for scope identity, current municipality names/NIS codes, policy authority and limitation text. -- Added `provision_geographic_scope.py` to fetch current authoritative VRBG boundaries, validate all members, create a valid regional union and retain boundary/member GeoJSON plus checksums and manifest. -- The operator creates or reuses `Kempen Regional Workbench`, one regional Area, 28 municipality Areas and two source datasets exclusively through canonical API envelopes. -- Added a compact Mol/Kempen selector to the primary map flow, scope-aware heading text and the neutral `Volledig werkgebied` action. -- Kept thematic regional fetching outside the scope pass. No startup fetch, direct PostGIS write, fake metric or unbounded regional theme download was introduced. - -Source proof: -- A live read-only VRBG run matched all 28 registered municipalities and current NIS codes. -- The valid union measured 1,399.2505 km2 in EPSG:31370 with WGS84 bbox `[4.59723873, 51.01047967, 5.26224853, 51.50511313]`. -- The scope is labelled as the transport-policy region and never as the complete cultural, landscape or historical Kempen. - -Validation before deployment: -- New focused scope and map-flow suite passed 9 tests. -- Python scope/operator compilation and frontend TypeScript typecheck passed. - -Deployment target: -- Deploy and run the scope operator on Tower, verify 29 Areas and both boundary datasets, then design bounded regional theme partitions before importing high-volume GRB or WCS data. - -Live operational proof: -- Deployed scope foundation commit `bb7310e` and context-isolation/copy corrections through `94f5e01` to the all-in-one Tower runtime on port 1202. -- Provisioned `Kempen Regional Workbench` through the canonical API with one regional Area, 28 municipality Areas and two VRBG datasets. Repeating the operator returned the same project, Area and dataset identifiers. -- The live project contains 29 Areas, one valid regional-boundary feature and 28 municipality-boundary features with persisted authority, policy-scope limitation, source URL and checksums. -- A live Mol -> Kempen switch now clears all project-bound state, rejects stale project-data responses, selects `Vervoerregio Kempen - officiële operationele grens` and opens `kempen_transport_region_boundary_2026-07-14.geojson` without retaining a Mol dataset. -- The reverse Kempen -> Mol switch restored `Gemeente Mol - officiële grens`, the GRB building layer and all six available Mol themes. -- Internal-browser checks passed at 1280x720 and 3440x1440. The ultrawide explorer used 3,134 px, its MapLibre canvas used 2,408 px and no horizontal overflow or browser warning/error was present. -- Full readiness passed 538 backend tests, one Alembic head, frontend typecheck/build and every repository smoke gate. Tower additionally passed container health, PostGIS 3.6, migration/schema/index and frontend proxy checks. - -Next: -- Build bounded, idempotent regional theme ingestion in municipality-sized partitions, starting with current buildings and retaining per-member provenance before exposing any Kempen-wide metric in the explorer. - -## Sprint 194 - Regional official time-series operator foundation (2026-07-14) - -Implemented: -- Made the existing Statbel population operator scope-aware while retaining Mol defaults and artifact compatibility. -- Added approved-scope NIS filtering, per-feature municipality provenance, checksummed scope-boundary resolution and distinct regional temporal-series keys. -- Added `provision_regional_timeseries.py` as one explicit coordinator for population and modern forest imports into `Kempen Regional Workbench`. -- Reused the current Dataset upload API and existing forest polygonization path; no migration, public endpoint, direct PostGIS write, startup fetch or fabricated value was added. -- Corrected regional forest provenance so a 28-member coverage does not claim to be one municipality. -- Added friendly Statbel/GRB/VRBG/Departement Omgeving labels to the primary map. - -Validation before deployment: -- Source contracts were rechecked against the official Statbel sector-population page and the official 2025 Landgebruik Vlaanderen catalogue. -- The focused regional/temporal suite passed 19 tests. -- Frontend TypeScript typecheck and production build passed. - -Next: -- Deploy the packaged operator, execute the live regional synchronization, verify persisted counts and temporal comparisons, then mark the regional time-series TODO complete only if PostGIS and browser evidence agree. - -Live source finding: -- The regional Statbel synchronization imported all five requested snapshots successfully. -- The first complete-region forest request was rejected by MercatorNet before download because the estimated 97.68 MB response exceeded its 78.12 MB service limit. -- The operator now uses the 28 retained official municipality boundaries as resumable WCS partitions, merges them locally at the unchanged 10 m grid and applies the exact region-union clip before polygonization. It does not lower resolution or truncate the source. -- Live full-region analysis returned the correct six-theme result but initially took about 92 seconds because every already-clipped feature was intersected again with a 947 kB regional geometry. Added a provenance-gated full-Area path that skips only this redundant intersection; arbitrary rectangles and untrusted uploads retain the existing exact query. - -## Sprint 190 Regional Kempen GRB buildings (2026-07-14) - -Implemented: -- Added `provision_regional_grb_buildings.py` for the approved 28-member scope, with complete OGC pagination, per-member safety caps, resumable checksummed artifacts and an explicit total cap. -- Added deterministic cross-boundary ownership by maximum member intersection and NIS-code tie breaking, preventing duplicate source identities without cutting the final geometry at internal municipality borders. -- Added streaming managed-artifact copy plus batch-wise partition indexing through DatasetService and VectorFeatureService. One regional Dataset remains compatible with existing viewport, selection, QA and export ownership boundaries. -- Added exact manifest/index count enforcement, duplicate source-feature rejection and rollback/storage cleanup on import failure. -- Kept fetching operator-triggered and local service import container-only. No startup fetch, browser provider fetch, direct vector-feature SQL or public API change was introduced. - -Validation before deployment: -- Backend/application and operator compilation passed. -- New focused operator/storage/batch-index suite passed 6 tests. -- Dataset, vector persistence, Mol municipality and Kempen scope regression selection passed 37 tests. - -Live operational proof: -- Deployed the regional operator and its interior-feature fast path through commit `a879c74`, then completed all 28 municipality partitions against the official GRB `GBG` collection. -- The immutable `2026-07-14` snapshot contains 466,078 buildings from 879 source pages. The combined retained artifact is 478,143,249 bytes and records `reference_truncated=false`. -- Dataset `e236fa03-7fce-4b37-bc7d-8bddd4d50346` is `ready`, `reference`, `source_name=grb`, `reference_layer_name=buildings`, EPSG:4326 and has one DatasetVersion. A repeat operator run returned `reused=true` in 3.5 seconds. -- Direct PostGIS verification returned 466,078 rows, 466,078 distinct source IDs, zero missing source IDs, zero invalid/empty geometries and zero non-4326 rows. The geometry mix is 466,069 Polygon and 9 MultiPolygon features. -- Live browser verification exposed an exact-scope defect: selecting Mol inside the regional dataset initially counted the surrounding bbox and returned 86,222 buildings. Commit `616424e` added optional persisted-Area filtering while retaining backward-compatible bbox selection for drawn rectangles. -- After redeploy, the complete Vervoerregio Area returned exactly 466,078 buildings and the official Mol Area exactly 36,941. A drawn rectangle returned 308 measured buildings, and zoom-level detail loaded 730 visible features from PostGIS onto MapLibre. -- Full readiness passed 546 backend tests, one Alembic head, frontend typecheck/build and all repository gates. Tower passed health, PostGIS 3.6, schema/index and proxy checks; browser audits at 1280x720 and 3440x1440 had no console warnings/errors or horizontal overflow. - -Next: -- Reuse the bounded regional operator pattern for current roads, water and parcels, then add official population and land-use time series without changing Mol semantics or introducing interactive external fetching. - -## Sprint 195 - Live guided detection and bounded regional QA (2026-07-14) - -Implemented: -- Added one guided Detection Lab action that uploads a georeferenced raster through `DatasetService`, creates or reuses the canonical tile manifest, runs preflight, invokes the configured local YOLO adapter and opens persisted detection geometry on MapLibre. -- Live Tower validation used the official Mol orthophoto sample, produced nine 512 px tiles and persisted 1,953 detections in analysis run `3912e179-3d1d-4080-8093-f883bbe95d9c`. -- A real QA attempt against the 466,078-feature regional GRB building dataset revealed that coverage clipping happened after every reference row had already been materialized. -- Moved configured-YOLO reference bounding into the existing GiST-indexed PostGIS query with the persisted manifest coverage. Full source count, evaluated count and excluded count remain explicit in the persisted evidence. -- Added a Shapely STRtree candidate index around the unchanged exact IoU matcher and clarified the simple map legend/source whenever AI detections are active. - -Validation before final deployment: -- Focused detection, coverage, QA and guided-workflow tests passed. -- Frontend TypeScript typecheck passed after the source/legend correction. - -Live operational proof: -- The final repository readiness gate passed 578 backend tests, API/document audits, frontend typecheck/build, one Alembic head and all shell smoke checks. -- Deployed commit `0cad8fd` to the Tower all-in-one runtime with AI extras enabled. Health, PostGIS 3.6, the single migration head, required schema/indexes and the port-1202 browser proxy all passed. -- The bounded QA request completed in 1.82 seconds. It retained a raw GRB population of 466,078, materialized/evaluated 1,826 coverage features and excluded 464,252 outside the nine persisted tiles. -- At match IoU 0.25, persisted quality check `341b0076-663a-4427-8a36-d5d9247a730e` measured 1,186 matches, precision 0.6073, recall 0.6495, F1 0.6277 and mean IoU 0.4565. No metric was fabricated. -- A separate UI run at its default stricter match IoU 0.50 also completed and persisted quality check `7a4464cd-152d-424f-a2b9-ed321b91524c`; the lower F1 is now explained by displaying the threshold beside the score. -- In-app browser inspection confirmed 1,953 persisted rows, map rendering over OpenStreetMap and explicit `AI-detecties`, `Detectierun`, `Gevonden gebouwen` and `controle vereist` labels. - -Next: -- Add bounded operator-triggered orthophoto acquisition from a drawn map rectangle, then hand that raster to this proven guided pipeline. Keep external acquisition out of browser/startup paths and retain explicit source licensing/provenance. - -## Sprint 196 - Map-driven official orthophoto analysis (2026-07-15) - -Implemented: -- Added explicit project-scoped acquisition for the official Digitaal - Vlaanderen `OMWRGBMRVL` WMS `Ortho` layer. -- Enforced EPSG:4326 input, EPSG:31370 metric bounds, 128-1,024 m side limits, - optional persisted-Area coverage, 1 m sampling, timeout/response limits and - 24-hour exact-request reuse. -- Georeferenced the RGB TIFF and persisted it, its DatasetVersion, source, - request URL/hash, bounds, attribution and latest-mosaic limitation only - through DatasetService. -- Added one simple map action chaining acquisition, existing raster tiling, - configured-YOLO inference, Detection persistence and existing GRB detection - QA before showing the persisted result on MapLibre. -- Exposed orthophoto settings through Docker Compose, the all-in-one Unraid - runtime script and DockerMan template. - -Validation before deployment: -- Focused service/API tests passed, including in-memory TIFF georeferencing, - persistence and the canonical Job envelope. -- Frontend TypeScript typecheck and production build passed. - -Next: -- Deploy to Tower, execute one bounded Mol rectangle through the real WMS, - local model and GRB QA, and verify persistence plus browser state before - accepting the flow as operational. - -Live operational proof: -- Deployed commits `daccd38` and `ec1e1af` to the Tower all-in-one runtime on - port 1202. The latter keeps acquisition inside the approved Kempen regional - Area while municipality selection remains an independent map filter. -- A rectangle in Mol fetched a 244 x 207, 1 m/pixel RGB GeoTIFF from the - Digitaal Vlaanderen `OMWRGBMRVL` `Ortho` WMS in EPSG:31370. Acquisition job - `8f6fd7f6-8f8a-436f-be54-d2c7e28ea250` completed successfully and created - Dataset `35f9f72e-edec-4053-887c-f4524222756d` with exactly one immutable - DatasetVersion. -- Existing canonical tiling produced one persisted inference tile. Analysis - run `e68a6291-9c46-4f23-832a-3c2b7480f94f` completed with model - `yolo-configured` and exactly 78 persisted Detection rows. -- Existing bounded GRB QA materialized 117 of 466,078 reference buildings for - the persisted tile footprint. Quality check - `3f1223f0-7dc1-40bb-a48b-910af2a343bf` persisted six Metric rows: 44 matches, - 34 false positives, 73 false negatives, precision 0.5641, recall 0.3761, - F1 0.4513 and mean IoU 0.6622 at IoU 0.50. The result remains explicitly - labelled as AI output requiring review. -- The in-app browser completed the full action, displayed the 78 persisted - geometries over the road basemap and reported no console errors. Layout - checks passed at 1280 x 720 and 3440 x 1440 without horizontal overflow; at - 3440 px the MapLibre stage used about 2,408 px. -- Full readiness passed 588 backend tests, backend compile, one Alembic head, - API/document audits, frontend typecheck/build and shell smoke checks. The - Tower runtime passed health, PostGIS 3.6, migration/schema/index and reverse - proxy validation. - -Next: -- Add a review workflow for accepted/rejected detections and use those audited - labels as the gate for model calibration or retraining. Do not present the - current F1 score as production-grade accuracy. - -## Sprint 197 - Measured detection accuracy and durable review (2026-07-15) - -Implemented: -- Added first-class `detection_reviews` persistence linked to Project, - QualityCheck, AnalysisRun, Detection and reference VectorFeature, with - role-constrained decisions and one durable row per evidence item. -- Added canonical paginated GET/POST review endpoints and a frontend review - queue with role/status filters, notes, summary counts and map handoff. -- Changed map-driven detection QA from generic UI IoU `0.50` to the documented - box-versus-footprint operational IoU `0.25`. -- Reworded map output as candidates and exposed persisted matches, precision, - recall, F1, false positives and false negatives. -- Bounded evidence lookup to persisted evidence ids; complete regional GRB - layers are no longer materialized for a small review overlay. - -Live model evidence before deployment: -- Re-ran the active model at confidence `0.10` and `0.15` on Mol Achterbos, - Gompel, Donk and Postel with QA IoU `0.25`. -- Confidence `0.15` won F1 in all four positive holdouts: `0.6694`, `0.6564`, - `0.5894` and `0.4749`. Confidence `0.10` measured `0.6287`, `0.6348`, - `0.5636` and `0.4435` respectively. -- Both thresholds produced zero detections on the pure-empty Postel forest - control. The active confidence remains `0.15`; no model or asset was trained, - downloaded or promoted. - -Validation before deployment: -- The complete readiness gate passed 592 backend tests, the API/document audit - for 88 implemented routes, backend compilation, one Alembic head, offline - migration SQL generation, frontend typecheck/build and shell smoke checks. -- Focused review/evidence regressions passed and the production bundle retained - separate React, application and MapLibre chunks. - -Live operational proof: -- Tower deployed commit `d22abe8` with AI extras enabled. The all-in-one - runtime became healthy, PostGIS 3.6 passed, Alembic reached `202607150001`, - and the new table exposed 13 columns plus six expected indexes. -- Quality check `acaca138-dbb9-4498-ae53-d0732b6270e3` returned 206 persisted - evidence geometries in 338 ms with zero unresolved ids. All 72 reviewable - false-positive/false-negative features were explicitly `unreviewed`. -- A new browser-driven 35.57 ha Mol rectangle acquired the official orthophoto, - ran the configured local YOLO model and persisted analysis run - `14f3b856-1ff0-4939-892a-3c8347a669f1` plus quality check - `087d2b6a-6d3c-4508-ab1e-da49734097c2` at IoU `0.25`. -- The live run produced 100 candidates, 73 matches, precision `0.73`, recall - `0.4965986395`, F1 `0.5910931174`, mean IoU `0.5361610234`, 27 false - positives and 74 false negatives. The UI showed these values as measured - candidates and retained the explicit `controle vereist` source warning. -- Browser audits at 1280x720 and 3440x1440 had no console warnings/errors or - horizontal overflow. The review queue rendered 50 paginated rows; the - ultrawide map used about 2,410 px. A final compact-metric fix was queued after - the 1280 px screenshot exposed cramped six-column labels. - -Next: -- Deploy the migration and UI, verify one live review queue and map QA result, - then complete representative manual decisions before constructing any new - model-training corpus. - -## Sprint 198 - Evidence-closed model review (2026-07-15) - -Implemented: -- Generated the previously missing 48-card false-negative contact-sheet bundle - from the exact persisted inference manifests for Geel, Herentals and - Turnhout; 731 references outside tile coverage remained explicitly excluded. -- Completed all 96 FP/FN decisions through orthophoto inspection plus - persisted geometry-overlap diagnostics. The result is 5 confirmed model FP, - 10 confirmed model FN, 59 QA-alignment cases, 10 reference-gap/change cases - and 12 uncertain/obscured cases. -- Added `validate_detection_false_negative_review_decisions.py`, mirroring the - existing FP safety contract and exporting only explicit confirmed misses. -- Included the symmetric validator in the all-in-one image and its packaging - regression list after the first live build exposed the missing COPY entry. -- Audited confirmed evidence against the active training split. Geel and - Herentals are existing training sources; Turnhout is an excluded operational - holdout. The review therefore provides zero novel leakage-free labels and a - new fine-tuning run was deliberately rejected. -- Added strict match count plus the existing diagnostic reference-envelope - result to the map analysis panel. Canonical footprint IoU metrics remain - unchanged. - -Validation: -- Both 48-row decision CSVs completed with zero `unreviewed` records and passed - their validators with `--require-complete`. -- Focused validator/readiness/map-contract tests passed. -- Full readiness passed 596 backend tests, backend compilation, 88 documented - API routes, one Alembic head, frontend typecheck/build and shell syntax gates. - -Known limitation: -- The active local model remains useful but imperfect. A new candidate requires - independently collected training-only AOIs and complete tile labels; holdout - review evidence must not be recycled into training. - -Live operational proof: -- Deployed commits `919e102` and packaging fix `8758721` to the Tower - all-in-one runtime. The container became healthy, PostGIS reported 3.6, - Alembic remained at `202607150001`, and the frontend/API/icon proxy smoke - passed. -- Both review validators ran inside the rebuilt image against persistent - operator data with `status=complete`: 5 confirmed model false positives and - 10 confirmed model false negatives, with zero unreviewed cards. -- A new 15.31 ha browser-drawn Mol selection persisted 282 candidates and 209 - strict GRB matches. It measured precision `0.741`, recall `0.685`, F1 `0.712`, - 73 false positives and 96 false negatives. The diagnostic reference-envelope - pass found 212 matches and only 3 possible box/footprint differences. -- Browser checks at 1280x720 and 3440x1440 showed the strict and diagnostic - values without horizontal overflow. The ultrawide map used about 2,408 px; - the browser console contained no warnings or errors. - -Next: -- Collect a new training-only small-building/background evidence pack outside - all operational holdouts, then train an inactive candidate only if the pack - passes label, leakage and sample-volume audits. - -## Sprint 199 - Reviewed accuracy expansion and fail-closed challenger (2026-07-15) - -Implemented: -- Added six training-only reference AOIs for Arendonk, Dessel, Meerhout, - Laakdal, Nijlen and Hulshout. Tests enforce explicit training role, unique - municipality/center pairs and at least 2 km separation from every protected - Mol, Turnhout, Retie, Westerlo, Vosselaar and Grobbendonk holdout. -- Prepared 1024 px orthophoto/GRB pairs on Tower. The paged GRB exports contain - 9,964 features in total, use EPSG:31370 rasters and have no truncated, - invalid or empty reference geometry. -- Exported `yolo-building-aoi1024-reviewedexp6-minpx3vis035`: 252 tiles, 234 - positive, 18 negative, 234 train, 18 validation and 79,192 labels. The - dataset audit returned `ok`; the 64-tile visual review covered 28 retained - sources with no invalid, missing or low-variance selections. -- Fine-tuned the active local YOLOv8s asset for 20 CPU epochs at image size - `640`. The best checkpoint came from epoch 16 and was copied as inactive - `geointel-building-yolov8s-reviewedexp6-minpx3-img640-ft20-pt`, SHA256 - `038f1f97a6afd534f29e1f392a730a58207b928ca01e31ab8d8fed6106705820`. -- Re-ran both active and challenger assets through the exact current API, - persistence and coverage-aware QA/QC path at tile `512`, overlap `64`, - confidence `0.15` and match IoU `0.25`. The evaluated reference populations - are equal per zone; older unequal-coverage runs were excluded. -- The active model measured mean precision `0.6141`, recall `0.6062` and F1 - `0.6069`; the challenger measured `0.6251`, `0.6293` and `0.6248`. Challenger - F1 improved in all seven zones and reduced false negatives from 3,416 to - 3,208. -- The challenger produced two detections in explicitly empty Postel-bos while - the active model remained at zero across Postel-bos, Lommel-heide and - Arendonk-heide. The formal promotion report recommended the existing active - key. No `.env`, active model path or runtime threshold was changed. -- Updated the approved Detection Lab profile to the current coverage-aligned - active evidence and retained the explicit Postel limitation. - -Validation evidence: -- Full readiness after the documentation/profile update passed 598 backend - tests, backend compilation, one Alembic head, frontend typecheck/build and - the complete shell syntax gate. -- Persistent promotion evidence lives under - `/app/storage/operator-data/model-review/reviewed-accuracy-expansion/` and - `/app/storage/operator-evidence/mol-operational-validation/`. - -Next: -- Convert the two confirmed Postel-bos challenger errors into a complete, - leakage-free hard-negative training sample, add independent empty controls, - then train a new inactive candidate through the same fail-closed gate. - -## Sprint 200 - Operational time-series handoff (2026-07-15) - -Implemented: -- Reproduced the `Geen tijdreeks beschikbaar` dead end in the deployed regional - map: Evolution retained the current-only GRB building snapshot even though - persisted population and forest series were available. -- Built one temporal-series catalog for every end-user theme from ready - persisted datasets. Entering Evolution now retains a comparable theme or - automatically opens the first available series and its latest snapshot. -- Theme cards now expose observation count and year range for real series. - Single-snapshot sources remain visible as `Alleen huidige toestand` but are - disabled for comparison instead of opening empty controls. -- Kept every comparison behind the existing temporal API and PostGIS - `vector_features` aggregation. No browser-side metrics, inferred snapshots - or synthetic historical values were introduced. -- Updated the top-level Detection documentation values while touching the - frontend handoff documentation so the active profile no longer shows an - older superseded benchmark. - -Validation evidence: -- A live regional Statbel comparison for a Mol bbox returned 87,868.45 - area-weighted inhabitants in 2021 and 91,497.15 in 2025: +3,628.70 or - +4.13%. The API correctly marked the result as an estimate and suppressed - unsupported object lineage. -- Focused temporal/regional/frontend contract tests passed: 21 tests. -- Full readiness passed 601 backend tests, backend compilation, 88 documented - API routes, one Alembic head, frontend typecheck/build and shell gates. - -Known limitation: -- The complete regional project currently has real 2021-2025 population and - 2013-2025 modern forest series. Buildings, water, roads and parcels each - have one current GRB snapshot at regional scope. The official 1778/1873/1969 - historical building, forest, water and road series is persisted for Mol but - has not yet been partitioned and imported for all 28 municipalities. - -Next: -- Generalize the audited historical-land-use operator to the approved regional - scope, partition source retrieval by municipality and provision the three - official editions without merging their methodology into current GRB. - -## Sprint 201 - Semantic area-selection metrics (2026-07-15) - -Implemented: -- Extended the canonical persisted-vector selection summary with an additive - metric set while preserving the existing primary metric fields and envelope. -- Mapped known data themes to useful units: building footprint, forest, water - and parcel surfaces in hectares; roads and linear watercourses in kilometres; - population in inhabitants; and intersecting feature counts as supporting - evidence. -- Kept all spatial calculations in PostGIS after transformation to EPSG:31370. - No browser-side area/length calculation or synthetic source value was added. -- Added honest domain limits for building floor area, road capacity and water - volume. The current 2D GRB water source cannot support volume without an - independently governed depth/bathymetry dataset. -- Updated the regional GRB operator metadata for future imports and added a - compact supporting-metric surface to the map-first result panel. - -Validation evidence: -- Focused temporal and semantic-selection regression set passed 16 tests. -- Full readiness passed 605 backend tests, backend compilation, the API - contract audit, one Alembic head, frontend TypeScript typecheck/build and all - shell syntax gates. - -Known limitation: -- Water volume remains unavailable by design. Adding it requires a compatible - depth or bathymetry source, coverage validation, units, observation date and - a documented integration method. - -Next: -- Validate the semantic metrics against live Mol PostGIS data and then continue - the audited regional historical buildings/water/roads import. - -## Sprint 202 - Source intelligence, complete evolution metrics and Ollama (2026-07-15) - -Implemented: -- Audited the current regional PostGIS inventory: current GRB buildings, roads, - water and parcels; Statbel population 2021-2025; and modern forest - 2013/2016/2019/2022/2025. -- Extended temporal comparison additively with optional exact persisted-Area - geometry, every compatible semantic metric and a complete observation - timeline. Bbox-only rectangle comparison remains supported. -- Expanded the official 10 m land-use operator with water, built-function and - transport surfaces. All themes reuse one retained source raster per year; - their measurements remain separate from current GRB geometry semantics. -- Added a Sources inventory for loaded themes and audited follow-up sources. -- Added an optional local Ollama assistant with status/model/query endpoints, - installed-model validation, compact persisted GIS context and strict missing- - data behavior. The browser never addresses Ollama directly. -- Added editable Docker/Unraid Ollama settings and automatic host-gateway - mapping for the server runtime. - -Validation evidence: -- Focused temporal, source, Ollama, navigation and Unraid regression tests - passed, including direct coverage for multi-metric history and DockerMan host - mapping. -- Full readiness passed 617 backend tests, backend compilation, 91 documented - API routes, one Alembic head, frontend TypeScript typecheck/build and all - shell syntax gates. -- Tower deployment passed the all-in-one container health check, live PostGIS - 3.6 migration/schema smoke and frontend/API proxy smoke. The container reached - host Ollama and exposed 10 installed models through the canonical API. -- A live historical question revealed that the Dutch verb `evolueerden` did - not activate history context. The intent stem was corrected to `evolu`, three - direct regression cases were added and full readiness reran successfully. -- In-app browser validation on the deployed HTTP LAN URL exposed that - `crypto.randomUUID()` was unavailable outside a secure browser context. Chat - message keys now use a session-local monotonic id generator; no persisted or - security-sensitive identity depends on it. Typecheck, production build and - full readiness reran successfully. -- The regional operator then reused the five governed forest snapshots and - imported 15 new authoritative snapshots: water, built functions and - transport for 2013, 2016, 2019, 2022 and 2025. A live exact-Area Mol water - comparison returned 606.16 ha in 2013 and 641.75 ha in 2025 across all five - observations; the API retained the 10 m raster and object-lineage warnings. -- Browser QA also reproduced an Ollama `done_reason=length`: the previous - implicit 4096-token context left only 86 tokens after a 4010-token grounded - prompt. GeoIntel now requests a configurable 16,384-token context and rejects - any future length-truncated response instead of presenting a partial answer. -- A complete live response then exposed two unsupported model interpretations: - an estimated population was called exact and an ungrounded demographic cause - was suggested. The system contract now mandates estimate wording, forbids - causal/forecast claims not present in context, uses deterministic temperature - zero and requests plain text. Full readiness remained green at 617 tests. -- Assistant context now carries explicit measurement quality for current and - historical values. A deterministic response guard prepends the estimate - limitation whenever an answer discusses estimated population data, while the - model prompt forbids independent averages, rates and derived trends. Focused - tests and full readiness passed with 619 backend tests. -- Browser review identified that the source summary visually combined current - GRB geometry with historical 10 m land-use observations. The UI now reports - comparable observations per temporal-series key and labels singleton/current - datasets as a separate source method. Full readiness remained green. - -Known limitations: -- Water volume remains unavailable until a governed depth/bathymetry source is - integrated. VMM station water levels or flows alone do not establish volume - for every selected polygon. -- Available follow-up sources are catalogued but are not labelled as loaded - until a controlled import and provenance validation have completed. - -Next: -- Integrate Waterinfo/VMM station observations as point time series and add - historical orthophoto acquisition, while preserving their spatial and - methodological limitations. - -## Sprint 203 - Governed Waterinfo history and historical orthophotos (2026-07-15) - -Implemented: -- Added `provision_waterinfo_station_history.py` using the documented Waterinfo - KiWIS annual water-level/discharge groups. The operator filters station - points against the exact persisted Area, retains raw JSON plus SHA256 - manifests and writes only through the canonical upload API. -- Persisted one Point Dataset per station/year and kept station identities in - separate temporal series. Added backend `mean` aggregation without combining - stations or inferring area-wide water level/volume. -- Added a governed orthophoto allowlist for the most-recent product, annual - winter mosaics 2012-2025, older winter periods, RGB 1979-1990 and - panchromatic 1971. Arbitrary WMS URLs/layers remain impossible. -- Added raster temporal metadata and a constrained PNG rendering endpoint for - persisted orthophoto datasets. The map can select and display official - historical imagery over the same bounded rectangle. -- Historical products explicitly bypass configured-YOLO and current-GRB QA; - only `most_recent` retains that path. -- Updated source inventory behavior and wrote a governed source backlog with - acceptance criteria for BWK/Natura 2000, agricultural parcels, Buildings - Register, DHMV and bathymetry. - -Validation evidence: -- Focused Waterinfo/orthophoto/semantic metric tests and frontend typecheck/build - passed before the full repository gate. -- Full readiness passed 627 backend tests, 93 documented routes, one Alembic - head and the frontend production build. Tower passed PostGIS 3.6 migration, - schema, frontend proxy and icon smokes. -- Live Mol import persisted 26 annual water-level observations across two - independent stations for 2013-2025. Two stale station series contained no - observations and no in-area annual discharge station was available. -- Live temporal comparison for station `L10_089` returned 30.460 m in 2013 and - 30.455 m in 2025 with all 13 observations, `mean` aggregation and the point- - measurement/no-volume warning. -- Live 2020 bounded WMS acquisition persisted an EPSG:31370 raster with annual - temporal metadata; its constrained PNG endpoint returned HTTP 200. -- Browser validation then exposed that 26 new annual datasets pushed the - project above the frontend's implicit 50-row dataset page. The central API - client now exhausts canonical 200-row pages and fails if totals drift or a - page is incomplete, so older population/parcel sources remain visible. - -Remaining operational step: -- Redeploy the pagination correction and verify complete source visibility plus - the historical overlay through the LAN browser. - -Final live UI correction: -- Browser inspection at 1280x720 found the premium desktop grid overriding the - source catalog's full-width placement and constraining it to a 282px internal - scroller. A final, component-specific CSS rule restores the catalog as a - full-width overview band without changing the remaining data-workspace grid. - -Live completion evidence: -- Tower was redeployed from commit `d3a09e8`; the all-in-one runtime passed its - health check, PostGIS 3.6 migration/schema smoke, frontend proxy and icon - checks. -- The source catalog measured 1,027px wide at a 1,280x720 viewport, with six - readable source cards, natural height and no internal overflow. The remaining - source-management panels start on the next grid row. -- A browser-driven Mol workflow drew a bounded 63.19ha selection, returned - persisted metrics for all six available themes and loaded the governed 2020 - winter orthophoto as a MapLibre overlay. The UI retained its explicit warning - that historical imagery is not validated against the current GRB state. -- The browser console contained no warnings or errors after the complete flow. - -## Sprint 204 - Governed BWK and Natura 2000 for Mol (2026-07-15) - -Implemented: -- Added `provision_mol_bwk_natura2000.py` for the official INBO - `BWK:Bwkhab` state-2025 WFS. The explicit operator follows complete - pagination, retains every raw page with URL and SHA256 evidence, and refuses - silent replacement when a persisted checksum differs. -- Clipped source polygons against the exact persisted Mol Area in EPSG:31370, - transformed valid polygonal output to EPSG:4326 and imported only through - the canonical Dataset upload route. Original BWK evaluation, mapping-unit, - origin, habitat and PHAB fields remain present on persisted features. -- Added server-owned filtered PostGIS metrics for the official `EVAL` classes, - area-weighted Natura 2000 habitat, regionally important biotopes and - uncertain `ohab` knowledge gaps. PHAB-derived values remain labelled as - estimates. -- Added the Natuurwaarde map theme and source-inventory state. The 2025 product - is presented as one current map state and not as a fabricated annual trend. - -Validation evidence: -- The source fetch retained 11 checksummed WFS pages containing 10,332 bbox - features. Exact Mol clipping retained 4,668 features, rejected 5,664 outside - features, clipped 476 boundary-crossing features and found no duplicates. -- Full local readiness passed backend compilation, 637 backend tests, one - Alembic head, frontend TypeScript typecheck/build and shell syntax gates. -- Tower deployment passed container health, PostGIS 3.6 migration/schema smoke, - frontend proxy and icon verification. -- The first live upload correctly failed before persistence because - `observed_at` lacked the required `temporal_series_key`. The operator now - records `inbo-bwk-natura2000:mol` with snapshot granularity; the focused - regression suite passed and the corrected deployment imported exactly 4,668 - `vector_features`. A second operator run returned `existing` for the same - Dataset and checksum. -- A live exact-Area PostGIS selection measured 11,447.996 ha mapped BWK area: - 960.446 ha very valuable, 3,082.023 ha valuable, 4,697.797 ha less valuable - and 2,707.730 ha mixed. Source-faithful weighted results were 821.690 ha - Natura 2000 habitat, 143.565 ha regional biotope and 104.557 ha uncertain - habitat/knowledge gap. -- Browser validation at 1280x720 selected Mol, activated Natuurwaarde and ran - the full-work-area analysis. All seven available themes returned persisted - metrics, the MapLibre layer rendered, no horizontal document overflow was - present and the console contained no warnings or errors. The source inventory - reports one current BWK state and 4,668 loaded map polygons. - -Known limitations: -- The official state-2025 edition is the best available map state, not one - uniform 2025 field survey. Origin fields remain necessary for interpretation. -- PHAB percentages can be theoretical source allocations and may differ from - field reality. GeoIntel does not reinterpret them as exact field coverage. -- Regional Kempen coverage and historical comparison remain separate future - work; this sprint proves the governed Mol path only. - -Next: -- Implement P2 annual agricultural-use parcels, beginning with an edition and - code-list comparability audit before any import or trend is exposed. - -## Sprint 205 - Governed annual agricultural-use parcels (2026-07-15) - -Implemented: -- Added an explicit ALZ operator for the definitive 2008-2025 annual - agricultural-use parcel GeoPackages. The operator uses a fixed official - allowlist, streamed archive limits, ZIP path validation and native - EPSG:31370 schema checks before exact regional clipping. -- Retained each official archive, annual crop-code list and checksummed - manifest. Derived GeoJSON enters the application only through the canonical - Dataset upload service and ordinary Dataset/vector_feature persistence. -- Added server-owned exact PostGIS metrics for total declared-use hectares, - official main-crop groups and feature count. Comma-separated official group - labels found during the live source audit remain compatible with the first - persisted import. -- Added the Landbouw map theme, readable source labels, the 18-edition source - inventory and historical comparison UI. Parcel-level object lineage remains - disabled because declarations and boundaries are not stable identities. - -Validation evidence: -- Full local readiness passed backend compilation, 647 backend tests, one - Alembic head, frontend TypeScript typecheck/build and shell syntax gates. -- Tower deployment passed container health, PostGIS 3.6 migration/schema - smoke, frontend proxy and icon verification. -- All 18 definitive editions were imported into one governed regional series - for the exact 28-municipality Kempen transport-region Area. Database audit - found 18 ready Datasets, 18 DatasetVersions, matching feature/source-id - counts, EPSG:4326 throughout and zero invalid geometries. -- The 2025 source contained 594,730 Flanders features. Exact regional clipping - retained 54,071 features, including 411 clipped at the boundary, measuring - 60,087.0667 ha. The 2008 edition retained 43,343 regional features and - measured 63,272.1152 ha. -- Live Mol analysis measured 3,223.4983 ha declared use across 2,374 features - for 2025, including 934.2348 ha grassland, 874.7350 ha maize and 329.1544 ha - potatoes. All configured crop/use groups returned explicit hectare values. -- The exact Mol 2008-2025 comparison returned all 18 observations: 3,343.2441 - ha to 3,223.4983 ha, a change of -119.7458 ha (-3.5817%). The UI states that - declarations are not cadastral ownership and individual objects cannot be - followed reliably between years. -- Browser validation confirmed the current-state metrics, complete historical - chart, 18-edition inventory and readable authority labels through the live - LAN runtime. - -Known limitations: -- The current campaign remains provisional and is deliberately excluded until - a definitive annual edition is published. -- Declared agricultural use includes non-crop elements such as water, hedges, - buildings and infrastructure; it is not ownership, cadastral area or a - direct measure of agricultural production. -- Cross-year comparison is valid for governed category and area totals only, - not for parcel identity, causal attribution or forecasts. - -Next: -- Implement P3 Buildings and Addresses Register through a governed snapshot - operator, preserving register lifecycle semantics separately from GRB - footprint geometry and excluding personal data. - -## Sprint 206 - Governed Buildings and Addresses Register snapshot (2026-07-15) - -Implemented: -- Added `scripts/provision_buildings_addresses_register.py` for the official - Digitaal Vlaanderen `Gebouw`, `Gebouweenheid` and `Adres` OGC API Features - collections. It retains raw pages and SHA256 checksums, uses retries and - limits, clips exactly in EPSG:31370 and persists only through DatasetService. -- Added service-window-safe pagination. Live audit proved that the address - collection omitted `next` after 52,000 bbox rows while offset 52,000 still - returned data. The first incomplete snapshot was rejected and transactionally - removed; the corrected operator continued with `startIndex` to a short final - page at 52,110 rows. -- Kept building lifecycle status separate from GRB footprint evidence. Official - building-unit relations use `GebouwObjectId`; address relations are accepted - only for an exact unambiguous unit position or unambiguous building - containment. Ambiguous and unmatched relations remain diagnostics. -- Persisted building polygons with aggregate relation counts only. Full address, - street, house-number and box-number fields remain in restricted raw operator - evidence and never enter queryable feature properties. -- Added exact footprint, lifecycle, unit, address-status and GRB-match metrics. - Fixed filtered `feature_count` execution without changing the existing - unfiltered count contract. -- Added Map and Sources presentation. The exact Mol Area prefers the register; - another municipality and the full Kempen scope retain complete regional GRB. - Evidence paths and manifest reuse are isolated by Area key and boundary hash. - -Live evidence: -- Source bbox acquisition completed with 111,696 buildings (112 pages), 67,239 - building units (68 pages) and 52,110 addresses (53 pages), with zero duplicate - source ids. Exact Mol clipping retained 43,945 buildings and 23,788 addresses. -- Dataset `c3a47680-cea1-406c-aebb-8ebfa8d7a359` is the only ready Mol register - snapshot for 2026-07-15. It has one DatasetVersion, 43,945 vector rows, - 43,945 distinct source ids, SRID 4326, polygonal geometry only and zero invalid - geometries. -- Lifecycle counts are 37,159 realized, 14 under construction, 155 planned, - 22 not realized and 6,595 historical buildings. Exact footprint area is - 502.1434 ha. -- Aggregate relations contain 30,382 building units, 21,388 linked addresses - and 19,513 addresses in use. There are 1,687 ambiguous and 713 unmatched - address positions. Queryable properties contain zero prohibited address - label/number fields. -- GRB reconciliation produced 36,588 matched, 5 review, 664 ambiguous and 6,688 - unmatched register buildings. There are 353 GRB footprints without a confirmed - target and 329 duplicate-target groups. Realized-building match rate is - 98.4526%; total register match rate is lower because historical and other - lifecycle records are retained. -- Live exact-Area API returned all eleven governed metrics. Browser validation - confirmed Mol register selection, Geel GRB fallback, readable metric/warning - output, source inventory, MapLibre rendering, no horizontal overflow and no - browser console warnings/errors. - -Validation evidence: -- Full local readiness passed backend compilation, 656 backend tests, one - Alembic head, frontend TypeScript typecheck/build and shell syntax gates. -- Tower deployment passed all-in-one health, PostGIS 3.6 migration/schema smoke, - frontend proxy and icon verification. - -Known limitations: -- This is a current continuously updated snapshot, not a fabricated historical - series. GRB remains the complete regional geometry source outside Mol. -- Address counts are not households, dwellings, residents or population. - Building footprint is ground area, not floor area, height or volume. -- Ambiguous address links, duplicate GRB targets and review/unmatched geometry - remain explicit evidence for later regional expansion; no nearest match is - forced. - -Next: -- Implement P4 Digitaal Hoogtemodel Vlaanderen with a governed DTM/DSM product, - vertical reference, bounded raster storage and measured elevation/slope - statistics. Do not infer water depth or volume from terrain height alone. - -## Sprint 207 - Governed DHMV II terrain foundation (2026-07-15) - -Implemented: -- Added a fixed `dtm_1m`/`dsm_1m` product registry for the official Digitaal - Vlaanderen production WCS and rejected arbitrary coverage identifiers. -- Added bounded, rate-limited 10 km WCS tiling, multipart GeoTIFF extraction, - georeferenced mosaicking, exact persisted-Area clipping and validation of - EPSG:31370, one Float32 band, resolution, nodata and valid cells before - canonical DatasetService persistence. -- Retained response, coverage and normalized-output SHA256 evidence plus native - 1 m resolution, default 5 m analysis resolution, TAW and period 2013-2015. -- Added exact masked terrain selection with governed height, relief and slope - metrics. DTM and DSM semantics remain separate; water depth/volume remain - explicit unsupported metrics and drainage is not calculated. -- Added the `Hoogte & reliëf` map theme, MapLibre colour-relief overlay, - readable period/source labels and raster-aware rectangle/full-Area queries. -- Added `scripts/provision_mol_dhmv.py`, Docker/Unraid settings and documentation. - -Validation evidence: -- Full local readiness passed compilation, 669 backend tests, one Alembic head - (`202607150001`), frontend TypeScript typecheck/build and shell syntax gates. -- The production WCS required an explicit `Accept: */*` header and rejected - rapid municipality tile requests. The governed client now waits two seconds - between requests and retries a transient provider status once. Four real - requests produced one `2928 x 3794`, EPSG:31370, 5 m Mol bounding raster - before exact municipality masking. -- Tower deployment passed all-in-one health, PostGIS 3.6 migration/schema - smoke, frontend proxy and icon verification. -- Live DTM Dataset `eccb9174-edb9-4867-928c-9acc5d686fa5` is ready with - checksum `9c5f06f5ce2070128aca06e3cbcec00ec8f698bf592c1745245280cd0488ad9b`. - Live DSM Dataset `34d1be8e-3a80-4ea3-98e5-238739000524` is ready with - checksum `54e36a2aada03f52eb24a7b6af505871d33ed52a5c2af04500793dbfca72f7af`. - Both contain 4,581,867 valid 5 m cells and report complete Mol coverage. -- Full-Mol DTM metrics are mean 31.8985 m TAW, minimum 20.8598 m TAW, - maximum 48.4594 m TAW, relief 27.5996 m and mean slope 1.2377 degrees. - Re-running the operator reused both immutable datasets. -- Browser validation selected Mol, activated DTM by default, rendered the - colour-relief overlay, returned all terrain metrics, retained the explicit - water-depth/volume limitation, showed no horizontal overflow and emitted no - browser console warnings/errors. -- No migration, direct raster database write, LiDAR point-cloud processing or - water-volume inference was introduced. - -Known limitations: -- DHMV II represents acquisition period 2013-2015 and is not a current or - annual height series. Exact flight-day contours are not yet joined. -- The 5 m analysis copy is operationally bounded; sub-5 m detail requires an - explicit smaller acquisition. DSM-DTM building height remains future work. - -Next: -- Audit P5 official bathymetry and water-depth sources before enabling any - water depth or volume metric. Keep DHMV as height/relief input only. - -## Sprint 208 - Governed VMM flood-hazard scenarios (2026-07-15) - -Implemented: -- Audited official Vlaamse water-depth/bathymetry sources. Public coastal and - North Sea bathymetry does not cover Mol; Waterinfo is station-based and GRB - water geometry is two-dimensional. Permanent waterbody volume therefore - remains unavailable. -- Added a fixed VMM OGRK registry for twelve water-depth scenarios: fluvial and - pluvial, current climate and climate projection 2050, each at T10/T100/T1000. -- Added bounded WCS 1.1 retrieval, provider-safe 5 km tiling, multipart GeoTIFF extraction, - georeferenced mosaicking, exact persisted-Area clipping and conversion from - positive source centimetres to normalized metres. -- Persisted scenario, probability, units, bounds, request URLs and response, - coverage and normalized checksums through the existing Job, Dataset and - DatasetVersion architecture. No migration or direct raster DB write exists. -- Added exact raster selection metrics for mapped inundated area/share, - mean/P90/maximum modeled depth and a maximum-depth area integral. The API, - UI and Ollama context all prohibit interpreting that integral as actual, - permanent or concurrent water volume. -- Added an `Overstroming` map theme, explicit scenario selector, transparent - MapLibre overlay, source-inventory presentation and full-Mol operator. -- Added Docker/Unraid configuration, packaging and focused backend/frontend/AI - contracts without a new dependency. - -Validation evidence: -- Official WCS capabilities and DescribeCoverage confirmed EPSG:31370, 2 m - GridOffsets, Float32 values, null value 0 and `image/tiff` multipart output. -- A live bounded VMM request returned valid georeferenced data; official - catalog metadata confirms depth is expressed in centimetres between modeled - water surface and terrain. -- Synthetic GIS fixtures confirmed 200 positive 5 m cells at 1 m depth produce - 0.5 ha mapped area and exactly 5,000 m3 maximum-depth area integral. -- Full local readiness passed compilation, 679 backend tests, one Alembic head - (`202607150001`), frontend TypeScript typecheck/build and shell syntax gates. -- The first full-Mol WCS smoke exposed the provider's 4.88 MB generated-output - limit for a 10 km request. The client now uses 5 km tiles (one million cells - at 5 m) and surfaces the official XML exception text. The focused suite - directly guards both constraints. -- Tower deployment passed all-in-one health, PostGIS 3.6 migration/schema - smoke, frontend proxy and icon verification. -- Live provisioning created twelve unique ready Mol Datasets with all governed - product keys, twelve DatasetVersions and no `observed_at` values. Every - dataset is attached to Area `7233f575-dbac-4e83-b9fa-e3fd99453722`; a second - complete run reused all twelve immutable outputs. -- Full-Mol current pluvial T100 reports 451.0425 ha mapped inundation (3.9376%), - mean local maximum depth 0.2419 m, P90 0.4318 m and maximum 2.4809 m. Current - fluvial T100 reports 98.805 ha (0.8626%). These remain scenario-bound values, - not actual event measurements or permanent water volumes. -- The raster image endpoint returned a valid 273,330-byte PNG generated from - persisted Dataset `5d37d9cb-cad5-446e-bfd9-ec30e308d4bd`; provenance records - twelve bounded WCS requests for that scenario. -- Browser validation confirmed twelve scenario choices, MapLibre overlay, - exact full-Area metrics and the volume limitation. A live-discovered theme - collision was fixed so `Water` retains GRB water geometry while only - `Overstroming` can activate VMM flood rasters. The final 1280 px and 3440 px - checks had no horizontal overflow or console warnings/errors. - -Known limitations: -- The scenario raster represents modeled local maximum depth at 1:100,000 - application scale, not a measurement of a current flood event. -- No public municipality-wide inland bathymetry was identified. Waterbody - bottom elevation, uncertainty and permanent content remain open. -- Scenario alternatives are not observations in time and are intentionally not - exposed as a historical temporal series. - -Next: -- Treat permanent inland bathymetry as an external-data prerequisite, not as a - value derivable from DHMV or flood-hazard maps. Continue the independent P5 - waterbody linkage/uncertainty design only when governed depth profiles exist; - otherwise proceed with the regional historical buildings/water/roads backlog. - -## Sprint 209 - Regional historical land-use expansion (2026-07-15) - -Implemented: -- Audited the production Digitaal Vlaanderen Historical Land Use WFS and its - 1778, 1873 and 1969 collections. Broad regional hit counts stop at 10,000, - confirming that one transport-region bounding request is not a defensible - completeness strategy. -- Added `scripts/provision_regional_historical_landuse.py` for historical - building, water and road land-use classes over the 28 registered transport- - region municipalities. It requires the checksummed VRBG scope artifact and - never infers or broadens the regional definition. -- Added resumable municipality partitions with exact WFS JSON response bytes - retained as deterministic gzip artifacts, source/artifact SHA256, request - pagination evidence, boundary hashes, clipping diagnostics and combined - regional output manifests. -- Clipped and validated polygonal geometry per municipality, suffixing source - ids with NIS codes to prevent cross-boundary collisions. Source identities - remain explicitly unstable and do not enable object lineage. -- Added one canonical Dataset upload per theme/year with regional Area scope, - immutable temporal identity, hectare aggregation and methodological warning. - No API route, database migration or direct PostGIS write was added. -- Extended `provision_regional_timeseries.py`, all-in-one packaging, readiness - compilation and operator/source documentation. - -Validation and live evidence: -- The final release gate passes with 685 backend tests, frontend typecheck and - production build, one Alembic head (`202607150001`) and script syntax checks. -- Live Tower/PostGIS provisioning completed all 252 municipality/theme/year - partitions and nine combined snapshots. No snapshot has an empty municipal - partition. The retained regional historical audit cache is about 518 MB. -- Persisted feature counts are: buildings 14,245 / 22,036 / 69,869; water - 9,010 / 13,571 / 8,188; roads 6,305 / 33,578 / 30,915 for 1778 / 1873 / - 1969 respectively. Total persisted geometry count is 207,717. -- Each of the nine ready Datasets belongs to regional Area - `46ab5614-fcf8-4e63-8ea8-6049f34c14fd`, exposes one immutable - DatasetVersion/checksum and participates in one of three ordered temporal - series. A second complete operator run returned `existing` for all nine with - identical audited feature counts. -- The live audit found that the full-Area fast path did not yet recognize the - new clipped operator. Adding its governed provenance reduced exact complete- - Kempen comparisons from multi-minute redundant clipping to 4.0 s for - buildings, 0.9 s for water and 1.9 s for roads. -- Complete-Kempen 1778 -> 1969 results are 481.62 -> 1,833.23 ha built land, - 1,546.89 -> 2,198.80 ha mapped water and 4,382.49 -> 6,978.12 ha mapped - roads. These are map-class surfaces, not modern footprints, centreline - lengths, bathymetry or volume. -- Browser validation selected the historical buildings series, analyzed the - complete persisted Kempen Area and then municipality Mol. Mol returned - 24.35 / 32.45 / 120.81 ha for 1778 / 1873 / 1969 and explicitly disclosed - the cartographic-method and unstable-object-identity limitations. -- The irrelevant generic `0 km` metrics for polygon-only historical water and - road classes were removed. The workbench source context now follows the - selected Evolution series. Normal and 3440 x 1440 visual checks found no - overlap; browser console warnings/errors were empty. -- Each deployment passed live PostGIS 3.6 connectivity, required schema/index - checks, database collation, Alembic head `202607150001`, frontend/API proxy - and icon verification. - -Known limitations: -- Historical `buildings` are mapped built land-use surfaces, not individual - building footprints. Historical `roads` and `water` are mapped surfaces, - not current centerlines, bathymetry or volume. -- The three editions use different source maps and cartographic methods. - Comparisons are exploratory hectare changes within one series, never a - continuous equivalent to modern GRB or 10 m land-use products. - -Next: -- Keep permanent inland bathymetry blocked on a governed depth source. The - next implementation pass can focus on current-only nature/terrain/flood - regional expansion or on a benchmarked data-refresh scheduler; it must not - reinterpret these historical surfaces as modern object lineage. - -## Sprint 210 - Regional BWK/Natura 2000 expansion (2026-07-16) - -Implemented: -- Added `provision_regional_bwk_natura2000.py` for the approved 28-municipality - Kempen transport-region scope, using the existing official INBO state-2025 - source contract and governed Mol feature normalization. -- Added per-municipality WFS pagination, exact EPSG:31370 clipping, - municipality-suffixed feature identities, deterministic gzip retention of - every exact source response and checksum-bound partition/snapshot reuse. -- Kept one canonical regional Dataset upload behind DatasetService. No direct - `vector_features` write, migration, endpoint or fabricated time series was - introduced. -- Made map theme selection prefer an exact selected-Area Dataset over a broader - compatible regional Dataset. Updated the source inventory to present - overlapping BWK snapshots as area coverages without double-counting their - feature totals. -- Added focused tests for source evidence, GIS clipping, context fields, - regional assembly, semantic metrics, upload metadata, packaging and UI - selection behavior. -- Added the expression index - `ix_vector_features_dataset_municipality` and a matching ORM declaration so - municipality-filtered reads from the regional snapshot remain interactive. - -Live result: -- Tower imported all 28/28 municipality partitions from 147 retained source - responses: 134,249 source features were clipped to 72,933 persisted regional - features in Dataset `11606922-c84b-4bfe-84cb-9372c0799b62`. -- The canonical output checksum is - `45c42f60ed51e0f860c79c060b9c5ed6cb59b9352732e75e02cb9ef34b66f6b9`. - The idempotency rerun returned the same existing Dataset without adding a - DatasetVersion or duplicate features. -- PostGIS contains 71,991 Polygon and 942 MultiPolygon rows in SRID 4326, with - 72,933 distinct source ids, zero invalid geometries, zero empty geometries - and zero duplicate source ids. -- Complete-region metrics report 138,701.35 ha BWK-mapped surface (99.1% of - the selected 1,399.25 km2), including 6,580.43 ha Natura 2000 habitat, - 1,467.68 ha regionally important biotope and 384.10 ha uncertain habitat. -- Mol resolves to its exact 4,668-feature snapshot. The fallback regional - partition returns the same 4,668 municipality features in 0.989 seconds; - Geel returns 5,392 features in 0.529 seconds after the new index. - -Validation: -- Full local readiness passes backend compilation, 690 backend tests, the - 101-route API contract audit, frontend typecheck/build, script syntax gates - and one Alembic head (`202607160001`). -- Tower deployment and live migration smoke pass with PostGIS 3.6, the same - Alembic head and all required schema/index checks. -- Live browser verification confirms the regional and Mol metrics, separate - overlapping area coverages in the source inventory, no console warnings or - errors and no horizontal overflow at 3440x1440. - -Boundaries and next step: -- This Dataset is the official current BWK/Natura 2000 state dated 2025. It is - not a historical nature time series, and BWK-mapped surface must not be - presented as total natural habitat. -- Regional flood-hazard coverage is the next bounded data pass. It should use - governed municipality partitions and measured VMM scenario rasters before - attempting a full-resolution regional DHMV expansion; no water volume or - inland bathymetry may be inferred from flood depth. - -## Sprint 211 - Regional VMM flood-hazard provisioning support (2026-07-16) - -Implemented: -- Added `scripts/provision_regional_flood_hazards.py`, an explicit operator - that resolves the approved geographic scope, validates the fixed twelve-item - VMM flood-hazard registry and acquires scenarios per persisted municipality - Area through the existing canonical API endpoints. -- Kept all raster persistence inside the existing `FloodHazardAcquisitionService` - and Dataset/DatasetVersion/Job flow. The operator performs no direct WCS - requests, no direct PostGIS writes and no browser/startup provider fetching. -- Added `--dry-run`, `--members`, `--products`, `--force` and - `--stop-on-error` controls so Mol, selected municipalities or the complete - 28-member scope can be run safely and resumed. -- Added packaging/readiness support so the operator is compiled and available - in the all-in-one Unraid image. -- Documented that regional flood coverage remains municipality-partitioned - because one monolithic Kempen raster would exceed practical WCS/pixel limits. - -Validation: -- Focused tests cover product/member resolution, dry-run planning, canonical - acquisition/selection calls and release packaging. - -Known limitations: -- This pass adds the operational regional provisioner and validation contract. - A complete live run of all 336 municipality/scenario acquisitions is long - operator work and should be launched deliberately on Tower after reviewing - the dry-run matrix. -- VMM flood depth remains modelled local maximum scenario depth. GeoIntel still - must not expose permanent waterbody volume, current water level or - bathymetry from this source. - -Next: -- Run the regional VMM operator first for Mol/Geel with `pluviaal_current_t100` - on Tower, then expand to the full twelve-scenario municipality matrix if the - provider remains stable. After that, prioritize regional DHMV DTM/DSM with - the same partitioned operator discipline. - -Follow-up validation: -- Fixed the regional flood operator's Area list pagination after the live - Tower API correctly rejected `limit=500`; the operator now uses canonical - `limit=200` paging. -- Redeployed Tower, reran live migration/browser runtime checks and validated - the live operator path with Mol `pluviaal_current_t100`. The run reused - Dataset `5d37d9cb-cad5-446e-bfd9-ec30e308d4bd` and reported 451.04 ha - modeled pluvial T100 positive-depth area for Mol with no failures. -- Added `docs/DATAVINDPLAATS_SOURCE_ROADMAP.md` with recommended public - Vlaanderen Datavindplaats follow-up sources for hydrology, soil, planning - and accessibility. - -## Sprint 212 - Platform-wide official source portfolio (2026-07-16) - -Implemented: -- Audited the official public-source roadmap across the complete GeoIntel - product instead of continuing with a water-first backlog. -- Added one central frontend portfolio covering space/buildings, - nature/agriculture, soil/relief, mobility/accessibility, - population/services and climate/living environment. -- Each source records official ownership/coverage, the metrics it can honestly - support, an implementation priority and a real catalogue URL. Runtime status - is derived only from matching ready Datasets. -- Reworked the Sources inventory into six compact domain summaries. Detailed - theme/timeline state, active source limitations and candidate-source cards - remain accessible through progressive disclosure. -- Live responsive review found and fixed a narrow-viewport title-row squeeze; - the status badge now stacks below the source introduction on mobile. -- Rewrote the Datavindplaats roadmap around a cross-domain area profile. The - next recommended implementation is a fixed allowlist of Mercator thematic - rasters plus the digital soil map, not another isolated water connector. - -Boundaries: -- No backend provider, live fetch, API contract, database model or migration - changed in this pass. -- Audited sources remain visibly non-operational until a governed import and - metric-validation pass has completed. No source data or historical trend was - fabricated. - -Validation: -- Frontend typecheck passes after the source-portfolio extraction and Sources - workspace refactor. -- Focused source-portfolio tests and the complete readiness gate are recorded - in the delivery handoff for this sprint. - -Next: -- Implement the governed Flemish thematic-raster registry Wave 1 for space - occupation, open space, population density, node value and total service - level, followed by the digital soil map vector operator. - -## Sprint 221 - Governed source freshness audit (2026-07-16) - -Implemented: -- Added a project-level canonical source-freshness endpoint derived exclusively - from persisted Dataset, DatasetVersion and local storage evidence. -- Defined explicit policies for GRB/VRBG/register snapshots, annual - population/land-use/agriculture/nature/water series, fixed DHMV/soil/thematic - editions, VMM scenarios, historical archives and local artifacts. -- Added fail-closed classification for unknown sources and local integrity - checks for missing versions, checksum mismatches, missing files and stored - size disagreement. -- Added a compact Status workspace panel and packaged - `audit_source_freshness.py` for explicit Unraid cron/reporting use. - -Boundaries: -- No migration, provider call, background daemon, source download or automatic - Dataset refresh was introduced. -- A fixed historical edition/scenario remains current evidence of that edition; - old publication dates alone are not treated as corruption or staleness. - -Validation: -- Focused service, policy, canonical envelope, CLI and UI contract tests added. -- Full release, live deployment and browser validation are recorded in the - delivery result after this implementation entry. - -Next: -- Add machine-readable catalogue release probes only for providers with stable - official version endpoints, keeping every acquisition an explicit bounded - operator action. - -## Sprint 222 - Official source edition probes (2026-07-16) - -Implemented: -- Verified the public machine-readable contracts published by Digitaal - Vlaanderen. GRB WFS and OMWRGBMRVL WMS capabilities expose stable ISO 19139 - CSW records containing real source editions and metadata dates. -- Added a canonical project endpoint that reads only allowlisted capabilities - and linked `metadata.vlaanderen.be` `GetRecordById` responses. It confirms - GRB `GBG/WBN/WGO/ADP` and orthophoto `Ortho/Vliegdagcontour` availability, - then reports the official edition beside local `source_version` evidence. -- Added strict HTTP(S)/metadata allowlists, timeout and byte limits, - post-redirect validation, SHA-256 capabilities evidence, provider-isolated - degraded/unavailable states and a short in-memory cache. -- Added an explicit Status action and operator CLI flags. Neither path runs on - page load, starts a job, downloads source data or changes a Dataset. -- Added Compose, all-in-one Unraid and DockerMan controls for the bounded probe. - -Validation: -- Deterministic tests cover official XML parsing, edition comparison, - provider failure isolation, metadata URL rejection, size limits, caching, - disabled mode and canonical envelopes. -- Frontend typecheck/build and targeted backend tests pass before the full - release and Tower validation recorded in the delivery result. - -Boundaries: -- The general Datavindplaats API requires authentication and is not scraped or - silently bypassed. GeoIntel uses only public metadata records advertised by - the official OGC services. -- A version difference remains a manual provenance-review signal. No automatic - import, refresh scheduler, GRB feature fetch or orthophoto pixel request was - added. - -Next: -- Extend the same probe pattern only where another official source publishes a - stable machine-readable edition. Do not infer release versions from service - protocol versions, ETags or HTTP modification dates. - -## Sprint 223 - Governed regional GRB refresh (2026-07-16) - -Implemented: -- Added a canonical read-only refresh plan that maps the official dated GRB - edition onto the immutable regional buildings, roads, water and parcel - temporal series. -- Added explicit per-layer current/update/review states, existing Dataset, - feature/storage impact and non-destructive action guidance. -- Added `manage_grb_refresh.py` with separate plan, fetch-only stage and - checksum-confirmed apply phases. Stage validates all retained artifacts and - municipality partitions; apply revalidates the exact staged plan before - calling the existing regional DatasetService-based operators. -- Added a compact Status surface after the explicit official catalog check. - -Boundaries: -- No migration, scheduler, arbitrary provider URL, browser-triggered heavy - import, direct vector-feature write or automatic Dataset replacement was - introduced. -- Existing GRB snapshots remain immutable historical observations. Exact - remote deltas are reported only after full staging, never guessed from - capabilities metadata. - -Validation so far: -- Backend compile and frontend typecheck passed. -- Source-catalog plus governed-refresh focused suite passed: 20 tests. -- Full `scripts/run_readiness_check.sh` passed: 781 backend tests, 110 - documented route contracts, one Alembic head, frontend typecheck/build and - all packaged smoke checks. -- Live Tower staging completed all 112 municipality/theme partitions for - official edition `2026-07-15`: 1,054,223 features, 1,250,873,313 artifact - bytes and staged plan SHA-256 - `7a772b70771c223b14d16c097c917fb160883349df61e24a2730e8c9591d56fd`. -- Checksum-confirmed apply created four new Datasets with exact PostGIS counts: - 466,092 buildings, 84,513 roads, 88,330 water features and 415,288 parcels. - The four `2026-07-14` snapshots remain present; total project datasets moved - from 632 to 636 and source integrity remains zero-error. -- Live browser validation exposed and fixed additive theme ranking where two - extra old water features could outweigh a newer observation date. Ranking is - now priority, observation date, import date, then feature-count tie-breaker. -- Post-deploy browser validation also exposed a stale map-theme remount state: - returning from Status to Map could retain the Water legend while the viewport - query and zoom guidance reverted to Buildings. Map state now initializes from - the selected persisted dataset so all four signals remain aligned. - -Next: -- Run the full release gate, deploy to Tower, execute a live read-only plan and - then stage/apply only the exact confirmed official edition. - -## Sprint 224 - Governed GRB evolution (2026-07-16) - -Implemented: -- Audited the two retained regional editions for buildings, roads, water and - parcels. All 2,108,425 persisted VectorFeatures have an official - `source_feature_id`; none uses the former 64-character geometry-hash - fallback. -- Added a fail-closed GRB identity contract to temporal object comparison. - Legacy snapshots require authoritative, area-clipped, non-truncated - provenance from an approved regional operator and every selected identifier - must be present, unique and match its collection prefix. -- Made future regional GRB operators abort when an official OGC feature ID is - missing and persist their identity scheme/prefixes explicitly. -- Replaced ambiguous same-year labels such as `2026-2026` with daily edition - ranges and explained that registration changes do not date physical change. -- Documented an honest refresh-readiness matrix for all major source families; - no additional provider fetch or automatic refresh was enabled. - -Boundaries: -- No migration, new persistence model, scheduler, browser-triggered import or - parallel temporal engine was added. -- Object comparison remains bounded to 5,000 selected features and falls back - to metric-only output whenever source identity cannot be proven. - -Validation so far: -- Focused GRB operator and temporal tests pass: 39 tests in the first pass. -- The complete readiness gate passes after the legacy regression addition: 786 - backend tests, 110 documented routes, one Alembic head, frontend typecheck, - production build and packaged script checks. -- The first Tower API comparison correctly exposed that the 14 July snapshots - predated the explicit `geometry_clipped_to_area` marker. Those snapshots are - now accepted only when their actual retained legacy evidence is complete: - the exact Kempen scope, 28 members and partitions, an approved assignment - strategy, manifest/source evidence, artifact checksum and 28 valid partition - checksums. A focused negative test proves incomplete partition evidence still - fails closed. - -Live validation: -- Tower was redeployed at commit `2d0e02e`; the all-in-one container became - healthy on port 1202, PostGIS 3.6 answered, Alembic remained at the single - `202607160001` head and the frontend/API proxy smoke passed. -- A read-only PostGIS edition audit found real official-ID changes between 14 - and 15 July: buildings 46 added/32 removed, roads 22/13, water 4/6 and - parcels 27/27 across the region. -- Four bounded canonical API comparisons returned - `object_changes.available=true` and persisted GeoJSON evidence for every GRB - theme. The checked selections returned 8 building, 20 road, 4 water and 20 - parcel changes respectively. -- The live browser exposes `Bebouwing · GRB (14-15 jul 2026)`, both exact - observation dates and the registration-versus-physical-change warning. The - workbench remained visually coherent and produced no browser warnings or - errors. - -Next: -- Evaluate ALZ as the next governed edition probe only after its official - machine-readable release version and schema stability are verified. -## Sprint 230 - Governed orthophoto release preflight (2026-07-17) - -Implemented: -- Added `scripts/orthophoto_release_preflight.py` as a read-only gate for one - bounded current-orthophoto selection in the approved Kempen regional scope. -- Bound the existing canonical product registry and source-catalog result to - the exact official WMS 1.3.0 capabilities hash, ISO metadata identifier and - `YYYY.NN` edition. Redirects, hosts, paths and response sizes fail closed. -- Added metadata-only WCS `DescribeCoverage` validation for `Ortho`, - EPSG:31370, the complete raster domain, 15 cm rectified grid, three bands and - TIFF native format. Selection limits remain identical to acquisition: - 128-1,024 m per projected side. -- Added a maximum 64-point deterministic `Vliegdagcontour` grid with exact - GeoJSON layer/date/year validation and hashed sample evidence. WCS domain - containment proves raster-domain coverage; point samples remain honestly - labelled as flight-date evidence rather than polygon-union geometry. -- Kept all pixel requests, filesystem staging, Jobs, Dataset/PostGIS writes, - migrations and browser behavior out of this sprint. Local - `most_recent_at_*` acquisition markers remain non-comparable and blocked. - -Validation so far: -- 42 focused preflight/runtime-packaging tests passed. Coverage includes - release ordering, legacy provenance, hash drift, product variant, official - host/path, queryable/GeoJSON capability, WCS identity/resolution, missing - flight coverage, flight-year mismatch, selection bounds and no-write rules. -- Target Python compilation and Ruff passed. -- A read-only compatibility run against Tower for bbox - `5.110,51.180,5.117,51.185` verified official edition `2025.04`, exact Ortho - WCS domain containment and 20/20 flight-day samples from 2025. It performed - zero pixel requests and correctly returned `staging_permitted=false` because - local version `most_recent_at_2026-07-15` is not an official edition. -- Complete local readiness passed with 866 backend tests, 110 documented - routes, one Alembic head `202607160001`, static full-chain migration SQL, - frontend typecheck and production build. Target Ruff, docs/contracts, - compile, shell syntax and diff checks also passed. Docker is not installed in - the Codex Windows environment; Compose and PostGIS were therefore validated - on Tower rather than marked locally complete. -- Commit `f48fe7b` was pushed to Gitea and deployed through the repository's - all-in-one DockerMan flow. The rebuilt image packaged the preflight, became - healthy on port 1202, passed live PostGIS 3.6/schema/collation/Alembic smoke - and passed the frontend/API/icon browser-proxy smoke. -- The packaged container repeated the Mol preflight with regional Dataset - total unchanged at `636 -> 636`: WCS domain containment passed, all 20 - deterministic points reported flight year 2025, zero pixel requests ran and - `staging_permitted=false` remained enforced for local legacy version - `most_recent_at_2026-07-15`. Tower checkout and Gitea were synchronized. - -Boundary: -- This sprint supplies preflight only. It deliberately does not promote or - backfill existing orthophotos. A future stage/review/apply coordinator must - revalidate and retain the exact preflight identity before creating a new - immutable raster Dataset with official `YYYY.NN` source version. - -## Sprint 231 - Governed orthophoto release promotion (2026-07-17) - -Implemented: -- Added `scripts/manage_orthophoto_release.py` with separate `plan`, `stage`, - named `review` and checksum-confirmed `apply` actions for one bounded current - orthophoto selection. No action is scheduled or browser-triggered. -- Reused the complete Sprint 230 preflight identity. Stage performs exactly one - allowlisted WMS `Ortho` GetMap, retains the exact source response, creates a - three-band EPSG:31370 GeoTIFF plus PNG preview and mutates no Dataset. -- Bound remote catalog/WMS/WCS/flight evidence, request identity, all staged - file hashes, reviewer and the final Dataset checksum into atomic persistent - evidence. Host/path drift, oversize responses, modified bytes, stale local - state and missing exact confirmations fail closed. -- Added a double-confirmed first official baseline transition for legacy - `most_recent_at_*` markers. Apply retains every legacy raster and uses only - the existing canonical upload/DatasetService transaction. -- Made the latest official `YYYY.NN` Dataset authoritative for source-catalog - comparison even when a newer-imported rolling marker also exists. No API, - migration, release table, Job type or frontend behavior changed. -- Made stage, review and applied evidence write-once. Exact apply retries reuse - the original checksum-bound evidence and never rewrite approval history. - -Validation so far: -- 48 focused Sprint 221/222/230/231 tests pass. The release-management suite - contains 11 direct plan/stage/review/apply tests. Coverage includes - official-edition ordering in both catalog and source-freshness views, - first-baseline authorization, GetMap allowlisting/limits, RGB/CRS - normalization, preview generation, tampering, preflight drift, named review, - loopback-only apply and complete upload provenance. -- Complete local readiness passed with 878 backend tests, 110 documented - routes, one Alembic head `202607160001`, frontend typecheck and production - build. Target compile and Ruff checks also passed. - -Live validation: -- Commits `06d05f0`, `0c2ebc1` and final status correction `0befca0` were - pushed, deployed through the repository to Tower and validated against - PostGIS 3.6. The all-in-one container became healthy on port 1202 and passed - migrations, schema/collation, API proxy and browser shell checks. -- The packaged operator staged official edition `2025.04` for bbox - `5.110,51.180,5.117,51.185`: one 921,848-byte official WMS response became a - 496x562, three-band EPSG:31370 GeoTIFF at an approximately one-metre grid. - All 20 deterministic flight-day samples reported `2025-04-05`. -- The generated preview was visually inspected as a complete RGB orthophoto - with expected Mol roads, buildings and sports context. Named review bound - plan SHA-256 `c6cefd19dc60d7469b4885d9d1f5eff4e52a88808bbe3ac21879c5650e558662` - and review SHA-256 - `9f0a3a65eb184fea7f91daa5018c0980ed03b792bd465a98c65f2add2413d90b`. -- Checksum-confirmed apply created exactly one immutable raster Dataset - `3cf14603-03da-42f5-b152-4bbecad7d006`; project total moved from 636 to 637. - Dataset, version and staged GeoTIFF share SHA-256 - `f87701de6680f8ad25407996ddfd08056bf0533c05572ae489e9d478a72e7e46`. - The canonical API returns the complete request, catalog, flight-date, - reviewer and artifact provenance. -- An idempotent retry retained 637 Datasets and the same Dataset ID. A live - audit exposed that the applied-evidence timestamp could still be rewritten; - write-once validation was added, tested, redeployed and the evidence file - remained byte-identical on the next retry at SHA-256 - `f4ae7b2315aed9370c8ca04dcb57eabf0c0e49c40cf63a862bb4e69bacd4b16d`. -- Browser validation at 1920x911 showed a correctly rendered MapLibre canvas, - coherent regional layer workflow, no horizontal overflow and no console - warnings or errors. A final live API audit found the generic source status - still selected a retained rolling label; source-freshness now prefers the - official edition without changing the 180-day review policy. The redeployed - Status workspace visibly reports `Editie: 2025.04`; a fresh official catalog - probe reports `local=remote=2025.04` and comparison `same`. - -Next: -- Surface the existing release evidence read-only in the operator Status - workspace so official/local edition, review identity, Dataset ID and hash - integrity can be inspected without shell access. Keep all refresh actions - operator-only and outside the browser. - -## Sprint 232 - V1 user-flow completion (2026-07-17) - -Implemented: -- Re-audited the live platform from the end-user entry point instead of - continuing operator release work. The normal path is now explicitly Map -> - area -> measurements/evolution -> AI question or download. -- Added the semantic metric label to every row in the 15-theme result summary. - This distinguishes, for example, a Waterinfo station level from mapped - surface-water area or watercourse length. -- Kept vector output as GeoJSON and added complete JSON downloads for governed - raster analyses and historical comparisons. Copy actions now copy the full - analysis response rather than an empty raster GeoJSON shell. -- Added direct post-analysis handoff buttons to `AI-vragen` and `Downloads`. - The selected Area or drawn bbox remains in shared App state. -- Kept the geographic explorer mounted while other workspaces are active so - its selected theme, analysis result and temporal comparison survive the - round trip to AI or Downloads. Hidden workspaces remain non-interactive and - MapLibre resizes through its existing `ResizeObserver` when shown again. -- Added one current V1 completion board to `docs/TODO.md`; legacy checklists - remain preserved but no longer define product readiness. - -Validation so far: -- Live pre-change acceptance selected the persisted Mol municipality Area and - completed all 15 PostGIS-backed themes. Representative results included - 502.14 ha building footprint, 3,626.56 ha forest/green, 36,783 inhabitants, - 3,223.5 ha agricultural use and 1,015.51 km roads. -- Live historical acceptance compared the official modern forest series from - 2013 to 2025 over Mol: five observations, 3,723.17 ha to 3,626.56 ha, - absolute change -96.6 ha and relative change -2.6%. -- Ollama status and installed-model discovery were live. A grounded assistant - query returned HTTP 200; a separate `qwen3.5:4b` request completed in 13.01 - seconds. Model answers remain advisory and source evidence remains primary. -- Focused end-user, temporal/Ollama and Sprint 232 tests pass: 38 tests. -- Frontend typecheck and production build pass. -- Complete readiness passes with 881 backend tests, 110 documented routes, - one Alembic head `202607160001`, frontend typecheck and production build. - -Live validation: -- Commit `161564f` was pushed to Gitea and deployed through the repository's - all-in-one Unraid flow. The rebuilt container became healthy on port 1202 - and passed PostGIS 3.6 connectivity, collation, runtime schema and the single - Alembic head `202607160001` through the live migration smoke. -- The redeployed browser flow selected the official Mol Area, analysed the - complete 114.55 km2 municipality and returned all 15 themes. The governed - space-occupation result remained 3,638.41 ha / 31.8%, with every summary row - carrying a semantic metric name including `Jaargemiddelde waterstand`. -- The result survived a complete Map -> AI -> Map and Map -> Downloads -> Map - round trip. The same 15-theme result and `Download analyse` action remained - available after both returns; no browser console warning or error occurred. -- Visual acceptance passed at 3440x1440 with theme, MapLibre map and results - visible side by side. At a 390x844 mobile viewport the document stayed at - its 375 px client width with no horizontal page overflow. - -V1 completion status: -- No release-critical V1 blocker remains in the intended end-user flow. Future - source editions, additional independent AI review data and real segmentation - models are optional controlled expansions, not prerequisites for using the - current map, measurement, evolution, local-AI and export workflow. - -## Sprint 233 - Operational correctness and result completion (2026-07-17) - -Implemented: -- Corrected the map-first selection scope after live API evidence showed that a - drawn bbox plus the active `area_id` returned the complete municipality - vector population. The shared selection contract now resolves `bbox ∩ Area`; - a bbox enclosing the complete Area keeps the exact persisted geometry and - only that case may use the full-Area fast path. -- Applied the same constrained geometry to current theme queries, temporal - comparisons, derived selection datasets and vector exports, including - boundary-crossing rectangle regressions. -- Added Area-aware persistent vector selection exports and - `POST /api/v1/exports/map-result`. Current vector, governed raster and - temporal exports are recomputed server-side from persisted data before an - export row and artifact are written. -- Replaced the passive `Open downloads` handoff with `Bewaar in downloads`. - Downloads opens only after successful persistence and surfaces current map - analyses, historical comparisons and vector selections among the latest - artifacts. -- Added exact project-name filtering and merged the canonical - `Kempen Regional Workbench` into the frontend project page. This remains - stable even with more than 1,000 retained operator/benchmark projects. -- Named failed map sources and their API reasons, reset the actual scrolling - workbench container on navigation, bounded the desktop map layout, removed - nested desktop scrolling from Detection Lab and added plain-language QA/F1 - interpretation. -- Limited Detection Lab's luchtbeeld selector to ready imagery rasters; - terrain, flood-hazard and thematic policy rasters remain available only in - their correct map workflows. -- Translated the visible Downloads workflow and moved technical identifiers to - the existing history disclosure. - -Validation: -- Focused operational-correctness, map-selection, export and V1 flow tests - passed after the corrected selection semantics were applied. -- The final complete readiness gate passed 899 backend tests, backend compilation, - documentation smoke, API contract audit, the single Alembic head - `202607160001`, frontend TypeScript typecheck and the production build. -- Commit `a29c787` passed the first live deployment, exact bbox/full-Area API - comparison and persistent Downloads browser handoff. The final constrained - boundary and luchtbeeld-filter follow-up is validated below before its - replacement deployment. - -Final live acceptance: -- Commit `d652db6` was pushed to Gitea and deployed through the repository's - all-in-one Unraid flow. Container health, PostGIS 3.6, required - schema/indexes, Alembic head `202607160001`, frontend proxy and icon checks - passed. -- A bbox crossing Mol's western boundary returned 358 buildings / 3.73 ha - without an Area constraint and 203 buildings / 2.27 ha with the official - Mol Area. The same constrained contract returned 1,249 / 16.71 ha for a - bbox inside Mol and 36,941 / 425.95 ha only for a bbox enclosing the complete - municipality. -- A browser-drawn Mol selection returned 14 buildings / 0.33 ha rather than - municipality totals. `Bewaar in downloads` persisted the server-computed - GeoJSON and opened Downloads with the new ready artifact selected among the - latest files. -- Detection Lab now reports seven ready orthophotos. Its selector contains no - VMM flood, DHMV terrain or thematic policy raster, while PyTorch remains - ready, the local building model remains active and F1 `0.607` is explicitly - labelled exploratory/review-required. -- Browser acceptance passed at 3440x1440 and 390x844 without horizontal page - overflow. Workspace navigation reset the real scrolling main container and - the browser console contained no warning or error. - -## Sprint 234 - Full audit closure and workspace lifecycle cleanup (2026-07-17) - -Implemented: -- Closed the remaining P1 project-pollution finding with reversible - `active`/`archived` lifecycle filtering. The default API and frontend load - active workspaces only; archived workspaces and all dependent persistence - remain available. -- Added `scripts/archive_technical_projects.py`. It is dry-run-first, uses a - strict technical-name allowlist and always preserves the canonical Kempen - and Mol workspaces. The all-in-one image packages it and readiness compiles - it. -- Added an explicit archive action for a selected non-canonical workspace. - The UI explains that data and results are retained and protects the two - canonical workspaces. -- Extracted Overview orchestration, Detection model management and pure Map - helpers from the largest frontend components. Shared state and API clients - remain unchanged. -- Reworded remaining visible operator terminology in the Map, Quality, - Detection, Segmentation and dataset controls. Technical UUIDs, file paths, - hashes and raw runtime states remain available only under labelled details. -- Added ultrawide AI-workspace constraints so controls use the available width - without creating multiple narrow nested columns. - -Validation: -- The local readiness gate passed 907 backend tests, backend compilation, - documentation and API contract audits, the single Alembic head - `202607160001`, frontend TypeScript typecheck and the production build. -- The first live dry-run correctly made no database change but exposed that a - direct `/app/scripts/archive_technical_projects.py` invocation resolved the - wrong Python package. The script now bootstraps the packaged `/app` backend - root, and a subprocess regression executes the documented command shape. -- The corrected all-in-one deployment became healthy, reported PostGIS 3.6, - passed required schema/index checks and retained Alembic head - `202607160001`. -- The live cleanup dry-run matched 1,091 allowlisted technical projects and - preserved both canonical workspaces. Apply archived the same 1,091 rows. - The active-project API now reports exactly two rows (`Kempen Regional - Workbench` and `Mol Municipality Workbench`), the archived API reports - 1,091, and a repeated dry-run reports zero remaining matches. -- Live browser inspection found no console errors or document overflow at - 3440x1440. Map and Detection workspaces keep a bounded 1,680 px operational - canvas, technical disclosures are collapsed and persisted AI internals now - use friendly labels in the ordinary result tables. At 390x844 the document - stays within its 375 px client width; the theme inventory is bounded to a - compact scrollable selector so it no longer pushes the map behind all 15 - theme cards. - -## Sprint 235 - Governed bathymetry profiles and Belgian expansion model (2026-07-17) - -Implemented: -- Audited official VHA, MDK Belgian Continental Shelf and SPW Walloon - bathymetry services and separated profile evidence, continuous bed models - and time-specific water depth/volume. -- Added bounded, paged VHA profile acquisition with exact persisted-Area - clipping, official watercourse names, document links, checksums and standard - Dataset/VectorFeature persistence. -- Added reusable vector-byte import and governed `min`/`max` property metrics - to the existing selection aggregation path. -- Added the bathymetry source and acquisition API, environment controls, Mol - operator command, map theme, profile inspector and source inventory. -- Kept municipality-only bathymetry hidden for a regional active Area until a - complete partition manifest exists; the Mol operator targets the canonical - Kempen workspace so selecting Mol in the ordinary map exposes the layer. -- Documented partitioned Flanders scaling and federated Belgium/maritime - scaling with explicit territorial sea, EEZ/continental shelf and - TAW/LAT/mDNG semantics. - -Validation: -- Backend compilation, 914 backend tests, documentation/contract audits, - Alembic head `202607160001`, frontend TypeScript typecheck and the production - Vite build passed in the complete readiness gate. -- Commits `5b4e180`, `00fcdcb` and `efdcaec` were pushed to Gitea and deployed - through the all-in-one Unraid flow. Container health, PostGIS 3.6, required - schema/indexes, Alembic head `202607160001`, frontend proxy and icon checks - passed after the final deployment. -- The canonical Kempen workspace now contains one reusable Mol bathymetry - partition with 828 persisted profiles, 715 official source documents, - 26 named watercourses and observations dated from 1877-01-01 through - 2020-07-03. A repeated operator run returned `reused=true` for dataset - `25d0f189-aa0c-4467-adc7-2fc684277bf9`, proving deployment-safe - idempotency. -- Persisted metrics report 1.08 m mean recorded depth for 112 structured - observations, a 0.3-3.0 m recorded range, 2.79 m mean crown width and - 1.30 m mean floor width. The UI keeps these historical profile statistics - separate from continuous bed elevation and current water volume. -- Live browser acceptance selected the official Mol boundary, exposed the - Waterbodem theme as `828 profielen / 715 bronbladen`, displayed the - historical survey range `1877-2020` and loaded all 828 persisted objects. - The browser console contained no warnings or errors and the 1265x720 - viewport had no horizontal document overflow. - -## Sprint 236 - Flemish bathymetry partitions and safe North Sea probe (2026-07-17) - -Implemented: -- Added a dynamic Flanders scope operator that discovers the complete current - official VRBG RefGem municipality inventory instead of freezing a fragile - hand-maintained list. It validates unique NIS codes/names, polygonal source - features and a 270..300 safety range before creating artifacts or API state. -- Added an atomic, resumable VHA municipality coordinator. Every partition is - exact-Area clipped and persisted through the existing acquisition endpoint; - failures, explicit zero-profile results and ready Dataset ids remain in the - checksum-bound coverage manifest. -- Added server-side partition finalization. Regional activation requires exact - accounting for every expected municipality, one ready VHA Dataset per - non-empty Area and explicit no-profile Area ids. Dataset and DatasetVersion - metadata retain the manifest identity and completeness flags. -- Added a strict-TLS, response-bounded MDK WCS GetCapabilities probe and a - concise Sources-workspace control. It never performs GetCoverage, never - disables certificate verification and always leaves acquisition disabled. -- Packaged the Flanders scope, VHA coordinator and MDK probe operators in the - all-in-one image and exposed their bounded runtime settings in Compose and - the Unraid deployment configuration. - -Validation: -- Official VRBG fetch-only validation returned 285 unique municipalities, an - exact union of 13,625.73 km2 and WGS84 bounds - `[2.54132923, 50.68749237, 5.9111094, 51.50511313]`. -- The live MDK metadata endpoint currently fails strict hostname validation: - `bathy.agentschapmdk.be` presents a certificate for `*.l27powered.eu`. - Diagnostic requests to both the previously configured and current metadata - paths returned HTTP 404 after an explicitly external, non-application - insecure inspection. GeoIntel itself reports `tls_error` and provides no - bypass. -- The complete readiness gate passed 920 backend tests, backend compilation, - documentation/contract audits, 115 documented API routes, Alembic head - `202607160001`, frontend TypeScript typecheck and the production Vite build. - -Final live acceptance: -- Commit `132c4fe` was pushed to Gitea and deployed through the all-in-one - Unraid flow. Container health, PostGIS 3.6, required schema/indexes, - Alembic head `202607160001`, frontend proxy and icon checks passed. -- The dynamic VRBG operator provisioned one exact Flanders land boundary, - all 285 current municipality Areas and both governed boundary Datasets in - `Flanders Regional Workbench`. The live union covers 13,625.73 km2 with - WGS84 bounds `[2.54132923, 50.68749237, 5.9111094, 51.50511313]`. - A repeated run returned the same project, Area and Dataset ids. -- The complete VHA coordinator accounted for all 285 municipality partitions: - 269 contain data, 16 explicitly contain no profile and none failed. It - persisted 128,913 exact-Area profile points from 79,398 source documents; - 49,628 observations have a structured depth field and the recorded survey - dates range from 1877-01-01 through 2026-04-15. -- Regional finalization became true only after the complete inventory passed. - The checksum-bound manifest is - `7f7fd94ecd64e8fc978b3f14e8f21efb471f9c63f89f16fafc23f9fded89aaa2`. - A second complete run returned the same hash, counts and Dataset ids without - creating duplicate data. -- The live MDK probe returned `tls_error`: the configured official hostname - does not present a matching trusted certificate. Acquisition remains - disabled and no insecure fallback or North Sea raster request was made. -- Live volume exposed a frontend scalability defect: Area loading stopped at - the first API page and the Data workspace rendered every Dataset card at - once. The follow-up now exhaustively pages all Areas, renders bounded - searchable Area/Dataset pages and mounts collapsed Area/history catalogs - only when opened. This preserves the complete regional inventory without - overwhelming the browser DOM. - -## Sprint 236 follow-up - manifest-aware regional VHA analysis (2026-07-17) - -Implemented: -- Corrected the Map explorer so a complete Flemish VHA manifest is never - represented or queried as one arbitrary municipality Dataset. -- Added one canonical bounded partition-selection endpoint. It selects the - latest internally complete manifest generation, prefilters Dataset bounds - and runs a single PostGIS intersection across the contributing persisted - `vector_features`. -- Kept exact municipality selection on its own Area partition and added - manifest-aware server-side GeoJSON export with complete contributing - Dataset provenance. -- Made the regional Waterbodem card report the sum of all 269 data-bearing - partitions: 128,913 profiles and 79,398 source documents. The rendered - GeoJSON remains capped at 1,000 objects while counts and configured metrics - cover the complete spatial result. - -Validation: -- The complete readiness gate passed: 927 backend tests, backend compilation, - 116 documented API routes, Alembic head `202607160001`, frontend TypeScript - typecheck and the production Vite build. -- Tower deployment passed container health, PostGIS 3.6, schema/index, - Alembic, frontend proxy and icon checks. Live selection returned 828 - profiles from the exact Mol partition in 0.59 seconds, 8,806 profiles from - 22 intersecting partitions in 1.95 seconds and 128,913 profiles from all - 269 data-bearing partitions in 15.89 seconds. -- The live partitioned export persisted a canonical 1,000-feature GeoJSON - sample with `total_feature_count=8806`, all 22 contributing Dataset ids and - `server_recomputed=true`. -- Browser acceptance showed the complete Flemish metric result, all five - configured structured depth/width measurements and the explicit 1,000-item - display limit. A final shell follow-up replaces the representative - municipality count with regional profile/partition totals and uses the - end-user label `Vlaanderen (285 gemeenten)`. - -## Sprint 237 - Bounded Flanders cross-domain profile (2026-07-17) - -Implemented: -- Reused the governed MercatorNet registry and canonical acquisition, - Dataset, analysis and image endpoints instead of introducing a second - provider path. -- Added a Flanders-only `Op aanvraag` state for ruimtebeslag 2025, open ruimte - 2022, inwonersdichtheid 2019, knooppuntwaarde 2022 and - voorzieningenniveau 2022. -- Made one explicit map rectangle or municipality analysis acquire/reuse all - five products for the same `bbox ∩ Area`, refresh the Dataset catalog and - keep the measured results available for switching, export and AI context. -- Kept the whole Flanders Area disabled for policy-raster acquisition under - the existing 60 km/30 million cell safety limits. Full-region vectors and - manifest-aware VHA analysis are unchanged. -- Corrected `coverage_scope` so only canonically named municipality Areas are - labelled municipality coverage; regional clipping remains a bounded - selection. - -Validation: -- A pre-implementation live probe acquired and persisted a real 143 x 224 - ruimtebeslag raster for a bounded Mol rectangle through Tower. The canonical - analysis returned 275.4 ha, 88.4563 percent and 311.34 ha valid raster area - with complete selection coverage. -- The complete local release gate passed 932 backend tests, backend - compilation, the 116-route contract audit, Alembic head `202607160001`, - frontend TypeScript typecheck and the production Vite build. - -Final live acceptance: -- The Sprint 237 commits were pushed to Gitea and deployed through the - all-in-one Tower flow. Container health, PostGIS 3.6, collation, - required schema/indexes, Alembic head `202607160001`, frontend proxy and - icon checks passed. -- Browser acceptance exposed and then closed one usability gap: entering - Flanders with an unavailable prior theme now automatically selects the - usable ruimtebeslag profile. -- A complete exact-Area Mol run persisted all five official policy rasters and - returned six real themes including the existing VHA partition: 3,638.41 ha - ruimtebeslag, 8,139.67 ha open space, an estimated 36,783 inhabitants for - 2019, mean node value 0.68, mean service level 0.16 and 828 bathymetry - profiles. A repeated run reused the retained raster requests. -- The five new full-Mol Datasets are `ready`, linked to the canonical Mol Area - and labelled `coverage_scope=municipality`. The UI reports product reference - years directly so an end-of-year UTC timestamp cannot roll 2025 into a - misleading local `1 jan 2026` label. - -## Sprint 238 - Governed Flanders terrain and flood selection (2026-07-17) - -Implemented: -- Replaced the policy-raster-specific map query field with a typed official - raster acquisition contract for `thematic_raster`, `dhmv` and - `flood_hazard`. -- Added a single Flanders product hook that loads all three fixed backend - registries in parallel. The browser still uses only canonical GeoIntel API - routes and has no external WCS URL. -- Added an end-user DTM/DSM selector and the full twelve-product VMM scenario - selector. Existing exact-area Datasets are reused; absent products are - acquired, persisted, analyzed and reflected back into the Dataset catalog. -- Extended the all-theme selection run with terrain and flood hazard while - preserving area intersection and the no-whole-Flanders-raster guard. -- Fixed the invalid default flood key spelling in the Pydantic request schema. - -Validation: -- Focused DHMV, VMM, map-orchestration and source-contract tests passed - (49 tests). -- Frontend TypeScript typecheck and production build passed before the full - release gate. - -## Sprint 239 - Governed bounded GRB map acquisition (2026-07-17) - -Implemented: -- Added a server-allowlisted GRB OGC API Features registry for `GBG`, - `Wegsegment`, `WTZ`/`WLAS`/`WGR` and `ADP`, exposed as buildings, roads, - water and parcels. -- Added canonical product and acquisition endpoints. Acquisition validates - EPSG:4326 and metric side lengths, intersects the request with the persisted - Area, follows only trusted pagination, fails instead of truncating and - retains response/artifact checksums. -- Routed all output through the existing synchronous Job and - `DatasetService.import_vector_bytes` flow. The resulting reference Datasets, - DatasetVersions and PostGIS VectorFeatures use the same persistence boundary - as uploaded data. -- Added explicit semantic selection metadata for hectares and kilometres. - Water volume, legal parcel certainty and traffic semantics remain - unsupported. -- Extended the Flanders map product catalog with the four GRB products and - kept all provider traffic behind the backend. -- Browser acceptance caught and closed a coverage-label defect: a newly - acquired small Mol Dataset no longer makes a complete-Flanders theme card - appear fully loaded. In the Flanders workspace GRB stays `Op aanvraag`; - the exact bounded result is shown only after selection and an older active - vector layer is not rendered behind it. The top-level map context follows - the same state and cannot retain an unrelated Dataset count. - -Validation: -- Focused provider, acquisition, route-envelope and frontend contract tests - cover complete pagination, exact clipping, official identity, hostile next - links, feature limits, persistent metadata and the canonical Job response. -- A read-only live provider probe over one small Mol rectangle returned 8 - `GBG` buildings, 23 `Wegsegment` roads, 20 water features across - `WTZ`/`WLAS`/`WGR` and 96 `ADP` parcels. Every collection completed without - truncation using explicit OGC CRS84 bbox and output negotiation. -- The complete readiness gate passed 943 backend tests, backend compilation, - the 118-route API contract audit, Alembic head `202607160001`, frontend - TypeScript typecheck and the production Vite build. -- Tower live acceptance persisted bounded Mol GRB results through PostGIS: - 339 building contours (5.953873 ha footprint), one road segment - (0.0137304 km), two water features (0.0027273 ha plus 0.0050982 km - supporting linework) and eight parcels (1.2566294 ha). A repeated exact - building request reused the same Dataset and reported `reused=true`. -- The rebuilt all-in-one deployment remained healthy on port 1202 with - PostGIS 3.6 and Alembic head `202607160001`. Live browser acceptance showed - all four Flanders GRB cards as `Op aanvraag` and no stale vector content - underneath an unmeasured on-demand theme. - -## Sprint 240 - Operational forest, agriculture, nature and soil (2026-07-17) - -Implemented: -- Added governed Landgebruik Vlaanderen 2025 class masks for forest and - agricultural use while keeping definitive ALZ parcels as a separate source. -- Added one allowlisted official-vector service for BWK/Natura 2000 2025 and - DOV soil types with exact Area intersection, complete pagination, metric CRS - clipping, checksums, cache identity and canonical Dataset persistence. -- Added source-faithful selection metadata for forest/agricultural hectares, - biological value, estimated PHAB habitat areas and historical soil classes. -- Connected all four themes to the existing Flanders product catalog and - all-theme selection flow without introducing browser-side provider traffic. -- Browser acceptance exposed and closed a coverage-state defect: a bounded - municipality raster can no longer make a complete-Flanders theme appear - preloaded. Governed thematic cards remain `Op aanvraag`. -- Added Compose and editable Unraid runtime settings for provider endpoints - and transfer/feature guardrails. - -Validation: -- Live read-only provider probes confirmed the BWK `BWK:Bwkhab` WFS collection, - stable `UIDN` paging and expected `EVAL`/`HAB`/`PHAB` fields. -- Live DOV WFS probing confirmed `bodemkaart:bodemtypes`, stable - `numberMatched`/`numberReturned` and expected soil attributes. -- Direct service probing over a small Mol rectangle completed without - truncation: 75 BWK source/retained polygons and 29 DOV candidates resulting - in 28 clipped soil polygons. -- The complete readiness gate passed 950 backend tests, backend compilation, - the 120-route contract audit, Alembic head `202607160001`, frontend - TypeScript typecheck and the production Vite build. -- Tower deployment and browser acceptance results are recorded after the - rebuilt all-in-one runtime is verified. -## 2026-07-17 - Belgium/North Sea RC-3 local gate - -- Removed automatic selection and every `rasterDatasets[0]` execution fallback - from Detection Lab. Normal detection, guided preparation and calibration now - require an explicit raster selection. -- Added `TemporalCompatibilityService`. Official raster editions carrying - `supports_detection=false` fail before Job/AnalysisRun creation with - `DETECTION_SOURCE_TEMPORALLY_UNSUPPORTED`. -- Detection QA now loads the persisted source Dataset and rejects historical - candidate/reference periods that are absent or non-overlapping with - `DETECTION_QA_TEMPORAL_MISMATCH`. -- Compatible temporal evidence is persisted under - `parameters_json.temporal_compatibility` and - `findings_json.temporal_compatibility` on the existing QualityCheck. -- Added sanitized request IDs, request-duration logs and correlated detection - start/QA completion logs. -- Added `scripts/runtime_state_report.py`; default mode is read-only and - mutation requires `--reconcile --confirm reconcile-interrupted-runtime`. - -Validation: - -- `python -m compileall backend/app`: passed. -- `python -m pytest backend`: 974 passed. -- `npm run typecheck`: passed. -- `npm run build`: passed. -- `bash scripts/run_readiness_check.sh`: passed, including 122-route API audit, - 974 tests, Alembic head, typecheck and build. -- `python -m alembic heads`: one head, `202607160001`. -- `python -m alembic upgrade head --sql`: passed. -- backup/restore/live-smoke shell syntax checks: passed. -- Local `docker compose config` was unavailable because this Windows - workstation has no Docker CLI; Tower validation remains mandatory before - RC-3 completion. - -## 2026-07-17 - Belgium/North Sea RC-3 live acceptance - -- Deployed immutable commit - `a28f2497e8d0da7d108828875ba9ffedda3c1688` to Tower. -- Live readiness reports PostgreSQL, PostGIS 3.6, Alembic head - `202607160001`, writable storage and the configured local YOLO capability as - ready. The health response exposes the exact commit and build time. -- `scripts/runtime_state_report.py` executed inside the all-in-one container - and found zero running Jobs and zero running AnalysisRuns. -- Live migration smoke completed against the retained PostGIS volume. -- In-app browser acceptance opened Detection Lab on port 1202 and confirmed - that the raster selector starts empty, exposes nine choices including its - placeholder, keeps the primary detection action disabled and produces no - console errors or warnings. -- RC-3 is complete. RC-4 national and maritime coverage contracts are the - active roadmap phase. - -## 2026-07-18 - Belgium/North Sea RC-6 supply-chain gate - -Implemented: - -- Replaced smoke-only automation with equivalent Gitea and GitHub release - workflows covering readiness, offline Alembic SQL, Compose resolution, - Python/npm audits, immutable image build, SPDX SBOM and container scan. -- Added hash-pinned Linux/Python 3.11 runtime and CI locks with verified input - fingerprints. Optional PyTorch, torchvision and Ultralytics remain outside - the base and CI locks. -- Added timeboxed, machine-validated Starlette advisory exceptions with - request-target and form-content compensating controls. -- Replaced the final runtime `gosu` path with a minimal `setpriv` exec wrapper - and upgraded packaged setuptools/wheel metadata. -- Fixed the Trivy policy wrapper so its generated ignore policy is mounted - read-only into the scanner. The policy pass excludes the shadowed Go - executable path only; the complete report preserves every base-layer - finding for review. - -Validation: - -- Local readiness passed backend compilation, 1,005 backend tests, the - 124-route contract audit, Alembic head `202607160001`, frontend typecheck - and production build. -- Python dependency policy passed with seven explicitly documented Starlette - aliases ignored through 2026-08-31; frontend npm audit reported zero - vulnerabilities. -- Immutable AI image - `geointel-all-in-one:6a22fcd1f87fbf4921e16b1baa9367c6e24dc8a3-ai` - deployed healthy and passed live PostGIS 3.6 migration plus browser proxy - verification. -- Tower retained `artifacts/geointel-ai-sbom.spdx.json` (25,653,538 bytes) - and the complete Trivy JSON report. The executable policy pass reported - zero reachable fixed HIGH/CRITICAL findings. -- Direct runtime proof returned PostgreSQL UID `999` through the final - `/usr/local/bin/gosu` wrapper. Runtime packaging reports setuptools - `83.0.0` and wheel `0.47.0`. - -Decision: - -- RC-6 is complete. RC-7 critical API response typing and OpenAPI validation - is active. - -## 2026-07-18 - Belgium/North Sea RC-7 API contract hardening - -Implemented: - -- Replaced every remaining free-form successful JSON response model with a - concrete Pydantic schema while retaining the canonical `{"data": ...}` - payload shape. -- Added reusable generic envelope, list, pagination and GeoJSON schemas plus - concrete project, area, assistant, YOLO preflight and QA evidence models. -- Corrected Area serialization so persisted PostGIS geometries are converted - to GeoJSON before response validation. -- Added an executable OpenAPI contract audit and focused regression tests that - reject missing, free-dictionary or undocumented non-envelope responses. -- Tracked exactly eight deliberate exceptions: three health probes, four - persisted PNG endpoints and the streamed export download. - -Validation: - -- The API audit passed 124 implemented routes and 228 OpenAPI component - schemas. -- Repository readiness passed backend compilation, 1,008 backend tests, - Alembic head `202607160001`, frontend typecheck and production build. -- Offline `alembic upgrade head --sql` completed and generated 31,548 bytes of - migration evidence. - -Decision: - -- RC-7 is complete. RC-8 automated frontend and browser release journeys are - active. - -## 2026-07-18 - Belgium/North Sea RC-8 release journey automation - -Implemented: - -- Added four Vitest suites with 12 executable tests for map selection, - coverage resolution, temporal comparison and bootstrap state. -- Added a dry-run-first golden-area operator. It reuses Mol/Kempen and creates - only missing bounded Wallonia, Brussels, language-boundary, coast and - offshore Areas through canonical APIs, with deterministic geometry hashes. -- Added a Playwright release runner and shell wrapper covering every golden - area, governed Mol metrics/provenance, compatible forest history, no-data, - partial coverage, unsupported maritime metrics, simulated provider failure, - persisted map export, real local Ollama context and explicit configured - local YOLO execution. -- Fixed explicit demo seeding so its archived technical project is reactivated - before reuse. A direct service regression protects this lifecycle behavior. -- Added the frontend tests and static E2E/script checks to readiness and copied - the golden-area operator into the all-in-one image. - -Validation: - -- Repository readiness passed backend compilation, 1,012 backend tests, four - frontend test files with 12 tests, frontend typecheck/build and Alembic head - `202607160001`. -- The live runner completed all Belgium/North Sea journeys against PostGIS - 3.6. It persisted an export, received a grounded Ollama answer and completed - configured local YOLO execution through Job and AnalysisRun persistence. -- The successful evidence manifest reports no unexpected browser-console or - failed-request events. Re-running the area operator created zero duplicate - Areas and retained seven unique geometry fingerprints. - -Decision: - -- RC-8 is complete. RC-9 loading, accessibility and performance hardening is - active. - -## 2026-07-18 - Belgium/North Sea RC-9 UX and performance acceptance - -Implemented: - -- Replaced transient false missing-source states with explicit bootstrap - loading and propagated loading/error state to the map and source panels. -- Added keyboard-correct analysis tabs, reliable skip-link focus, accessible - map/status regions and stable focus handling across workspace changes. -- Added measured four-second coverage and fifteen-second map-analysis budgets - with visible completion and over-budget feedback. -- Hardened 390-pixel mobile, 1366-pixel desktop and 2560-pixel ultrawide - layouts without changing map-first behavior. -- Added a Playwright UX audit for every workspace, accessible control names, - delayed bootstrap, keyboard behavior, layout overflow and timing feedback. - -Validation: - -- Repository readiness passed backend compilation, 1,015 backend tests, - 16 frontend tests, frontend typecheck/build and Alembic head - `202607160001`. -- Immutable image - `9b0239747d1f12d0c5dd3b7fa2d03cf672884dbd-ai` deployed healthy with - PostGIS 3.6 and the expected migration head. -- The live UX audit passed at 390x844, 1366x768 and 2560x1080 with no - horizontal overflow, console errors or failed requests. All seven - workspaces passed accessible-name checks and the delayed-loading and - performance-feedback assertions were green. - -Decision: - -- RC-9 is complete. RC-10 data operations and retention is active. - -## 2026-07-18 - Belgium/North Sea RC-10 data operations and retention - -Implemented: - -- Added a read-only data-operations audit for storage lifecycle, disk pressure, - persisted artifact references, failed work and national, regional and - maritime source families. -- Added dry-run-first cleanup restricted to explicit derived/cache categories. - Apply mode requires an exact confirmation token, a recent checksum-verified - release backup and a bounded delete ceiling. -- Mounted release backups read-only and protected release evidence, official - source editions, originals, uploads, model assets, operator evidence and - unknown paths from cleanup. -- Hardened artifact discovery for large production tables with bounded SQL - counts and distinct-path queries, strict manifest field traversal and - separate current-reference and historical-manifest findings. -- Classified fixed NGI and RBINS national/maritime editions so old publication - dates are not mislabeled as stale. - -Validation: - -- Repository readiness passed backend compilation, 1,021 backend tests, - 16 frontend tests, frontend typecheck/build and Alembic head - `202607160001`; focused final policy tests passed 19/19. -- Immutable image - `22fb8d51a9fde39552cf06a789174441631842b6-ai` deployed healthy with - PostgreSQL/PostGIS and the expected migration. -- The exact live image passed - `scripts/run_rc10_data_operations_audit.sh`: disk pressure `ok`, zero missing - direct database references, 2,002 dry-run candidates totaling 218,263,512 - bytes and unchanged critical table counts. -- The audit retained 224 unavailable historical manifest intermediates as a - non-destructive provenance warning. No cleanup was applied. -- Live national/maritime freshness evidence reports three current sources, - zero due/review-required sources and zero integrity issues. - -Decision: - -- RC-10 is complete. RC-11 final release packaging and acceptance is active. - -## 2026-07-18 - Belgium/North Sea RC-11 final release candidate - -Implemented: - -- Assigned semantic version `1.0.0-rc.1` across backend health, frontend - package metadata and OCI image identity. -- Added a final release runbook and a fail-closed package builder requiring a - clean tagged revision, exact image revision, complete SHA-256 inventory and - verified detached SSH signature. -- Updated active repository navigation and product identity to Belgium and the - Belgian North Sea while preserving Mol/Kempen as golden regression areas. -- Added a current known-limitations register for federated coverage, selection - semantics, history, AI and operations. - -Validation: - -- Repository readiness passed backend compilation, 1,030 backend tests, - 16 frontend tests, frontend typecheck/build and Alembic head - `202607160001`. Offline migration SQL generation also passed. -- The pre-tag `1.0.0-rc.1` image passed live PostGIS migration and proxy smoke, - Docker Compose validation and an isolated fresh install. -- A full SHA-256 storage/model inventory plus PostgreSQL dump verified - read-only. Separate isolated restore and upgrade drills matched all retained - table counts, PostGIS and Alembic, then removed their temporary databases. -- Real rollback started immutable build `22fb8d5` against the unchanged - volumes, passed live migration/readiness and returned successfully to the - RC image. -- All seven Belgium/North Sea release journeys passed. The UX audit passed at - 390x844, 1366x768 and 2560x1080 with zero horizontal overflow, browser - console errors or failed requests. -- Python dependency policy and npm audit passed. SPDX SBOM generation and the - complete container scan passed the executable policy with zero reachable - fixed HIGH/CRITICAL findings. -- RC10 remained read-only: zero missing current database references, unchanged - critical table counts and 2,002 reported zero-delete cleanup candidates. - -Decision: - -- RC-11 is complete subject only to binding the accepted final commit and - immutable image in the signed/checksummed package. No RC-12 phase is used. - -## 2026-07-19 - Stitch-guided complete Atlas Workbench redesign - -Implemented: - -- Created the private Stitch project `GeoIntel Complete Workbench Redesign` - and the `GeoIntel Atlas Workbench` design system. -- Generated production references for the Map Explorer, Sources catalog and - local AI Questions workspaces. -- Rebuilt the application shell so the brand lives in one compact navigation - rail and the active work context lives in one 56-pixel top bar. -- Added Lucide icons for the eight workspace destinations and removed the - duplicate command navigation. -- Restyled Map, Sources, AI Questions, Quality, Image Analysis, Downloads, - Status and Administration under one restrained token system. -- Restored the desktop map to a theme/map/insight row, allowed the map to - absorb ultrawide width and bounded the mobile theme list. -- Replaced the old `visual-polish.css` layer with the documented - `atlas-workbench.css` implementation. - -Validated during implementation: - -- the complete readiness gate passed: 1,052 backend tests, 22 frontend tests, - frontend TypeScript typecheck, the production build and Alembic head - `202607160001`; -- the browser UX audit passed at 390x844, 1366x768 and 2560x1080, including - accessible control names, loading states, keyboard tabs, the advanced - coverage flow, zero horizontal overflow, zero console errors and zero failed - API requests; -- all seven Belgium/North Sea release journeys passed against the live backend - through the redesigned frontend; -- browser review passed at 1280x720, 3440x1200 and 390x844 with no horizontal - document overflow or clipped button/select text; -- Map, Sources, AI Questions, Quality, Image Analysis, Downloads, Status and - Administration were each reviewed against live backend data. - -Behavior preservation: - -- No API contract, migration, database model, provider behavior, GIS - calculation, model runtime or persistence flow changed. -- Existing map selection, source loading, local Ollama, QA, analysis and - download actions remain wired through their original hooks and services. - -## 2026-07-19 - Stitch screen parity and responsive refinement - -Implemented: - -- Extended the Stitch project with dedicated Quality, Image Analysis, - Downloads and Status/Administration screens, all using design-system asset - `4667932515738184526`. -- Replaced the residual dark navigation treatment with the white 88-pixel - Stitch rail, pale context bar and locally bundled Public Sans/Manrope - typography. -- Made Sources a deterministic three-pane workspace after removing a legacy - full-width catalogue override. -- Added the Stitch control/result/inspector structure to the empty Quality - state and kept the existing populated evidence/history implementation. -- Compacted detection model administration into one row above the existing - configuration/result/QA workbench. -- Reorganized Downloads as artifact actions, current/history results and a - preview inspector without changing export callbacks or formats. -- Kept the MapLibre map full-height with icon controls and stable rails on - normal and ultrawide displays. - -Visual verification: - -- compared Map, Sources, AI Questions, Quality, Image Analysis, Downloads, - Status and Administration against their dedicated Stitch references; -- reviewed live-backend states at 1280x720, 1920x1080 and 390x844; -- confirmed that the widescreen map absorbs the additional width and that the - mobile workspaces remain vertically navigable without document overflow. - -Validation: - -- the complete readiness gate passed 1,052 backend tests, 22 frontend tests, - frontend typecheck/build and Alembic head `202607160001`; -- the final UX browser audit passed at 390x844, 1366x768 and 2560x1080 with - zero horizontal overflow, console errors or failed requests; -- all seven Belgium/North Sea release journeys passed through the redesigned - local frontend against the live backend; -- the journey retry caught and verified a fixed Sources grid containment issue - that previously allowed the Area panel to intercept a scrolled Project - management control. - -Behavior preservation: - -- no backend, API contract, migration, persistence, GIS metric, provider, - Ollama or model-runtime behavior changed; -- all existing actions continue through the original React hooks and service - layer. - -## 2026-07-19 - Complete bounded rectangle analysis - -Implemented: - -- removed the active-theme-only acquisition filter from Map rectangle - analysis; -- added a deterministic acquisition queue capped at three concurrent official - provider requests; -- restricted the result list to themes that are operational or have an - applicable bounded adapter in the resolved coverage zone; -- replaced misleading `Bron ontbreekt` rows with explicit provider-failure - states and counts results per theme rather than per contributing layer; -- registered VMM VHA historical profile points as an operational bounded - Flanders bathymetry source and connected its existing acquire/select routes - to the Map product catalogue; -- treated both Dutch municipality names and release-golden - `... municipality` Areas as local scope after live verification exposed a - false regional flood-raster partition path; -- extended the shared bounded-dataset guard to raster - `coverage_scope=bounded_selection` metadata after live full-Mol verification - proved that a previously acquired small raster could otherwise be - misrepresented as municipality-wide evidence. - -Live evidence: - -- a bounded Mol rectangle persisted and selected all relevant source families: - NGI, Statbel, four GRB products, seven Flemish thematic rasters, DHMV, - VMM flood hazard, BWK/Natura 2000, DOV soil and VHA profile points; -- semantic results included building/forest/agricultural/open-space/water/ - parcel/soil/nature hectares, road kilometres, inhabitants, terrain height, - flood area, accessibility/service scores and historical profile counts; -- no browser-direct provider request, fabricated value or vertical-datum - conversion was introduced. - -Validation: - -- the complete readiness gate passed: 1,053 backend tests, 25 frontend tests, - backend compile, frontend TypeScript/typecheck, production build, Alembic - head `202607160001` and script smoke checks; -- a live API smoke over `5.10,51.17,5.11,51.18` proved all 17 applicable Mol - themes through acquisition or persisted national data and semantic - selection metrics; -- browser verification follows against the deployed commit on port 1202. - -## 2026-07-21 - Scale-aware rectangle analysis - -Implemented: - -- reproduced the reported provider failure with an approximately 11,468 km2 - cross-region rectangle: twenty high-resolution adapters received one unsafe - bbox and returned their governed size limits; -- added explicit detail, regional and overview selection tiers before any - provider acquisition starts; -- regional selections up to 50 by 50 km now split compatible vector and point - sources into at most sixteen 18 km tiles, resolve the authority zone per tile - and combine each provider product as one persisted PostGIS result; -- added a canonical multi-partition vector selection route with project, - readiness and source-product consistency guards and source-feature count - deduplication; -- allowed terrain and flood partition analysis to receive an explicit set of - freshly acquired Dataset ids, avoiding accidental reuse of overlapping old - bounded rasters; -- kept 5 m raster analysis behind its real pixel budget and 10 m thematic - analysis behind its 50 km scale budget; -- changed overview selections to query only national or already provisioned - scale-compatible datasets and explain the scale choice once, instead of - presenting one provider error for every unavailable detail source. - -Validation: - -- backend import/compile and frontend TypeScript passed after the contract - change; -- focused selection-partition, DHMV and VMM tests passed (30 tests); -- focused frontend scale, tiling and concurrency tests passed (12 tests). - -Remaining in this pass: - -- run the complete readiness gate, deploy the immutable revision and repeat - both the large overview rectangle and a regional partitioned rectangle in - the live browser. - -## 2026-07-21 - Persisted raster scale guard - -Live verification of the first scale-aware release showed that on-demand -provider fan-out was resolved, but already persisted 5 m terrain and flood -rasters could still enter a Belgium-scale analysis. The shared selection guard -now applies the same real pixel budgets to persisted rasters: country-scale -overview analysis keeps PostGIS vector and national statistical sources, while -high-resolution rasters require detail or safely bounded regional extent. -Overview responses now return at most 25 representative GeoJSON features per -source (250 regionally, 1,000 in detail) while `total_feature_count` and every -PostGIS metric continue to cover the complete selection. This prevents large -profile properties from blocking the browser without weakening measurements. - -Validation: - -- frontend typecheck, 29 unit tests and the production build passed; -- the map acquisition, component-boundary and density regression contracts - passed (12 tests); -- live redeployment and a repeated Belgium-scale rectangle follow on the - immutable patch revision. -## 2026-07-22 - National scope and governed Brussels land cover - -Implemented: - -- made the persisted Belgium/North Sea project the unconditional startup - workspace and changed the initial basemap extent and form defaults from Mol - to Belgium plus its legally labelled maritime scope; -- retained Mol/Kempen provisioning and tests strictly as golden regression - evidence instead of product routing; -- live-validated the UrbIS WFS `Blocks` contract and added bounded land-cover, - FO/GB forest/park and WB permanent-water products with clipped PostGIS area - metrics and source-class provenance; -- restricted the production model picker to the explicit active model asset - and surfaced that the current building model is locally, not nationally, - validated. - -Validated during implementation: - -- backend compile and frontend typecheck passed; -- 31 frontend unit tests passed; -- focused national coverage, model catalog, project lifecycle and Mol golden - regression tests passed; -- live resolver checks covered Brussels, Wallonia and all three Belgian - maritime legal zones. WALOUS, Walloon flood analytics and multi-epoch marine - bathymetry remain real open source-integration work and were not simulated. -- the final repository readiness gate passed with 1,084 backend tests, 31 - frontend unit tests, compile, typecheck, production build, Alembic head - `202607160001` and all script syntax/contract checks. - -## 2026-07-22 - Live national deployment verification follow-up - -Implemented after deploying the national-scope revision: - -- reproduced and removed a national UI ambiguity where the Belgium land scope - displayed the final Brussels UrbIS catalog item as the active country-wide - source; multiple applicable regional products are now grouped as an official - source-per-region contract until the actual rectangle resolves its zones; -- added exclusive locks for release deployment and container replacement plus - a bounded wait for Docker's asynchronous removal, after an interrupted Codex - session exposed a concurrent replacement race on Tower. - -Live evidence: - -- immutable AI image `0aff8e3b8c551a9d1aa29a8495a17e5a858205ab-ai` became healthy on - port 1202 and applied Alembic migrations during startup; -- `scripts/live_migration_smoke.sh` passed against the embedded PostGIS 3.6 - runtime with all required tables/indexes and single head `202607160001`; -- the production model catalog exposes exactly the configured approved local - model instead of 25 training artifacts; -- coverage resolution is zone-correct for Brussels, Wallonia and all three - Belgian maritime legal zones. Unimplemented WALOUS, Walloon raster and MDK - acquisition stays explicitly `not_configured`. - -## 2026-07-22 - Live WALOUS provisioning and signed-raster correction - -Implemented and verified: - -- provisioned the official WALOUS 2020 and 2023 land-cover GeoTIFFs in the - live source cache, including source checksums, EPSG:3812 metadata and the - official class-code validation set `1,2,3,4,5,6,7,8,9,80,90`; -- corrected masked reads of the signed `int8` 2023 source, whose official - nodata value is `-128`, by widening valid raster values before assigning the - internal `uint8` nodata value `255`; acquisition, persisted analysis and map - rendering now share the safe conversion; -- added a regression test that exercises all official class codes through an - `int8`/`-128` source and verifies the derived `uint8`/`255` output contract; -- removed the redundant downloaded 2020 archive after checksum-verified - provisioning while retaining the normalized source raster and report. - -Live release evidence: - -- the complete readiness gate passed with 1,097 backend tests and 31 frontend - tests, backend compile, API/documentation contract audit, frontend typecheck, - production build, Alembic head `202607160001` and all script checks; -- commit `e15a8200fd5c21f95a8cc1f5d6fdc6c5cb2aae3c` was deployed as immutable AI - image `geointel-all-in-one:e15a8200fd5c21f95a8cc1f5d6fdc6c5cb2aae3c-ai`; -- live migration smoke passed against embedded PostGIS 3.6 with the complete - required schema and exactly one Alembic head; -- live 2023 acquisition created Dataset - `92561bc3-3f1c-4d30-b926-58dea7793e43`; the same test area measured 315.86 ha - total, including 110.91 ha forest, 7.57 ha water and 135.79 ha artificial - land, with full raster coverage; -- live 2020 acquisition created Dataset - `bdd19377-bfc9-425c-a7d4-6ac71c02bc1f`; a persisted 2020-2023 comparison - returned two observations and seven class-aware metric comparisons; -- the live browser on port 1202 rendered the 2023 WALOUS overlay and real - hectare metrics for a Walloon rectangle. The evolution workspace exposed - distinct dated observations and the browser console remained error-free. - -Known governed boundaries remain explicit: WALOUS covers Wallonia rather than -all Belgium, no unstable 2018 artifact is accepted without a verifiable source -checksum, and the current local building model is not represented as nationally -trained or validated. - -## 2026-07-22 - WALOUS 2018, Walloon terrain and evidence-scope closure - -Implemented and verified: - -- accepted the stable official WALOUS 2018 distribution only after validating - the 1,122,785,133-byte archive (`21e514...c9a`) and extracted raster - (`a788cf...56b2`), then materialized one area-scoped 2018/2020/2023 series; -- exposed that governed series in the evolution workspace and removed foreign - Area acquisitions from its choices; the live Wallonia golden Area shows - exactly three official moments and one unambiguous series; -- provisioned the complete official SPW MNT 2021-2022 1 m source. The archive - was 43,904,242,006 bytes with SHA-256 `04f3ca45821dc2866d854e75011eed1acefcfead9a5263e5a9760e29ded21f7c`; - the extracted EPSG:3812 Float32 raster is 44,014,505,895 bytes, 253,085 by - 146,727 cells, uses nodata -9999 and SHA-256 - `027f90fd304b683cdbf9a0c735152769cf093eb38599e7d5d9dc8792040a9f61`; -- removed the 40.89 GiB terrain download archive after checksum validation and - retained the source raster, checksum sidecar and atomic provisioning report; -- made terrain availability fail closed until both raster and valid SHA-256 - sidecar exist, and persisted the official 2021-02-19/2022-03-05 observation - interval using the canonical `period` granularity and spatial series key; -- constrained AI capability claims to the actual Mol/Kempen evidence through - machine-readable training/validation scope, `nationally_validated=false` and - mandatory operator review. No national training result was fabricated. - -Pre-release evidence: - -- the complete readiness gate passed with 1,103 backend tests and 34 frontend - tests, backend compile, API/documentation contract audit, frontend typecheck, - production build, Alembic head `202607160001` and all script checks; -- live browser acceptance showed the exact WALOUS 2018-2023 series and no - console warnings or errors; -- immutable image `geointel-all-in-one:e9b48bb95ebc9bd2b64df785158714eb190e80a5-ai` - became healthy, passed live migration smoke and exposed the checksum-ready - terrain product; -- live acquisition Job `4de2937a-451e-4f0d-b946-29945e279016` succeeded and - created Dataset `d842709c-5fd9-4701-b3e1-bdc40e3f2171`: a 2,148 by 2,463 - cell 5 m derivative with 5,210,960 valid cells; -- persisted terrain analysis over the exact Wallonia golden Area returned - coverage 1.0, mean 159.3529 m DNG, minimum 51.7473 m DNG, maximum 223.4930 - m DNG and mean slope 5.2786 degrees. Water depth and volume remain explicitly - unsupported because an MNT cannot establish either quantity. - -## 2026-07-22 - Stitch landing page and operator login - -Implemented: - -- translated the supplied `stitch_geointel_complete_workbench_redesign.zip` - into a native responsive React landing page rather than embedding its static - Tailwind mockup or temporary external image URLs; -- added a project-owned optimized Belgium/North Sea hero asset and kept the - existing operational workbench unchanged behind the access boundary; -- added public session probing, server-side PBKDF2-SHA256 credential checks, - signed HttpOnly/SameSite session cookies, expiry, failed-login throttling and - idempotent logout; -- protected proxied browser API requests while retaining trusted direct - loopback access for in-container operator scripts; no account table, - registration, role system or other multi-user scope was introduced; -- extended the Unraid environment/template and release runtime smoke to carry - the login configuration without storing a plaintext password. - -Pre-deployment validation: - -- the complete readiness gate passed with 1,107 backend tests and 36 frontend - tests, backend compile, API/documentation contract audit, frontend typecheck, - production build, Alembic head `202607160001` and all script checks; -- the authentication tests cover unauthenticated API rejection, successful - login with an HttpOnly/SameSite cookie, logout, signature tampering and the - deployment guarantee that only a password hash reaches the container. - -Live release evidence: - -- implementation commit `115f9850a703b3941b31d133e8547bf18ca37bff` was - built as immutable AI image - `geointel-all-in-one:115f9850a703b3941b31d133e8547bf18ca37bff-ai`; -- the container became healthy, the live migration smoke passed against - PostGIS 3.6 with Alembic head `202607160001`, and the frontend proxy returned - the public session envelope while rejecting the protected projects endpoint; -- a credentialed live journey on `http://192.0.2.10:1202` verified the - complete boundary: signed out and blocked, successful login, authenticated - project API access, successful logout, then blocked again; -- Tower stores the operator credential only as a quoted PBKDF2-SHA256 hash plus - an independent random signing secret. The plaintext password was not added to - Git, documentation, the deployment template or the runtime environment. -## 2026-07-26 - Interactieve projectatlas - -Implemented: - -- added a responsive SVG project atlas to the status workspace, driven by persisted area, dataset, visible-feature, analysis and export state; -- made all five project phases keyboard-accessible navigation actions into the existing workspaces; -- added restrained route, scan and signal animation with a complete `prefers-reduced-motion` fallback; -- added a topographic micro-illustration to active project context without changing API, persistence or geospatial semantics; -- kept the illustration code-native instead of generating a static bitmap so real operational state remains authoritative. - -Validation: - -- frontend unit tests: 38 passed across 11 files; -- frontend TypeScript check: passed; -- frontend production build: passed; -- frontend dependency audit: zero vulnerabilities at the high threshold; -- dedicated tests verify readiness derivation and workspace navigation. -## 2026-07-26 - Workspace identity and calm recovery states - -Implemented: - -- added a compact code-native signal illustration to every non-map workspace heading, with distinct restrained accents for data, assistant, quality, image analysis, downloads, status and administration; -- added topographic/radar depth to shared empty-result surfaces without changing their meaning or action hierarchy; -- suppressed the global floating error notice in the map workspace because the map already renders the same error with contextual recovery guidance; -- retained decorative semantics, keyboard behavior and reduced-motion fallbacks. - -Validation: - -- frontend unit tests: 38 passed across 11 files; -- frontend TypeScript check and production build: passed; -- frontend dependency audit: zero vulnerabilities at the high threshold; -- React review: named isolated component, derived configuration, no new state/effects, decorative content hidden from assistive technology. - -## 2026-07-26 - GeoIntel and ITWorx brand system - -Implemented: - -- replaced the former letter-based and mountain icons with one original GeoIntel Atlas mark combining a geographic lens, contour lines, compass direction and a measured location point; -- applied the same source mark to the workbench rail, mobile header, landing header, SVG favicon, PNG browser fallback, Apple touch icon and Unraid application icon; -- added the approved ITWorx.tech wordmark as a restrained maker signature in the workbench rail and public landing footer, explicitly crediting Jens without competing with the GeoIntel product identity; -- kept the product icon vector-native for crisp rendering from favicon to server tile and generated matching PNG derivatives from that canonical SVG. - -Validation: - -- visually inspected the canonical 512 px render and the 32 px favicon derivative; -- verified desktop and mobile landing-page renders with the new GeoIntel and ITWorx assets present, meaningful page content and no Vite error overlay; expected API 500 responses remained limited to the absent local backend; -- React review confirmed named, isolated brand components and accessible decorative versus meaningful image semantics. - -## 2026-07-26 - Task-first usability and functional navigation audit - -Implemented: - -- reduced the wide desktop navigation rail and renamed the misleading read-only `Beheer` destination to the operationally accurate `Systeem` workspace; -- aligned the current/evolution period control into one stable map-header tool group and added containment rules for long dataset, quality, provider and context labels; -- promoted municipality selection from a hidden long select to a searchable first step above the map; selecting an exact persisted municipality immediately activates its existing Area geometry and project datasets; -- renumbered the simple map journey to municipality, theme, selection and results, and rewrote the map instruction to describe that complete path; -- turned the empty quality state into an actionable handoff to the map or image-analysis workflow while preserving persisted QA evidence, metrics and map drill-down when checks exist; -- replaced the passive provider-only management page with a system command surface that reports configured connectors and routes operators to the map, source/area management or readiness status. - -Validation: - -- frontend unit tests cover exact municipality search, regional-area exclusion and active municipality feedback; -- frontend TypeScript and production build passed; -- React review confirmed local state ownership, semantic form/button controls, stable list keys and accessible names; -- no API, persistence, CRS or official-source semantics changed. - -Known limitation: - -- the authenticated live workbench still requires a user session for visual browser verification after deployment; public landing and runtime health remain independently testable. - -## 2026-07-26 - Optional spatial entry and authoritative municipality activation - -Implemented: - -- corrected the false assumption that municipalities were already project Areas: the national workspace contains 565 official NGI AdminVector municipality features instead; -- added bounded search across the persisted Dutch, French and German NGI names plus NIS code, and an idempotent activation route that creates a normal project Area from the exact persisted geometry; -- replaced the non-functional Area-only datalist with an asynchronous official municipality search, explicit result selection, loading/error states and active-area feedback; -- repositioned municipality search as an optional map shortcut alongside free drawing rather than a mandatory first step; -- reframed themes as optional map focus: they select the visible layer and primary metric while the insights workflow continues to report broader source availability; -- removed misleading step numbers, clarified the spatial research flow and reduced both the application rail and map focus panel; -- constrained narrow theme cards so titles, descriptions and availability labels remain inside their bounds; -- replaced the compass illustration with a new vector GeoIntel mark: a geometric G/geo-lens, coordinate point and subtle contour field, applied to every existing favicon and application-icon derivative. - -Validation: - -- verified the production database contains 565 authoritative municipality features and inspected the actual multilingual NGI property contract read-only; -- added backend API/service tests for multilingual/NIS search and persisted-area activation; -- added frontend tests for live search, activation and explicit optional/free-selection semantics; -- visually inspected the 512 px application mark and 32 px favicon derivative. -## 2026-07-26 - Audit remediation roadmap and NVIDIA GPU contract - -Implemented: - -- translated the platform audit into `docs/AUDIT_REMEDIATION_ROADMAP.md`, with - gated waves for NVIDIA runtime truth, general AOI orchestration, coverage - evidence, missing sources, model validation and release proof; -- made the Unraid production contract explicitly NVIDIA/CUDA-based through a - CUDA PyTorch wheel index, `gpus: all`, `YOLO_DEVICE=cuda:0` and - `YOLO_REQUIRE_CUDA=true`; -- added fail-closed accelerator validation to YOLO model loading and preflight, - including explicit unavailable/misconfigured errors instead of CPU fallback; -- extended the preflight response with accelerator readiness, configured device - and CUDA-required state, and updated the API, AI and dependency documentation; -- retained CPU as an allowed local-development default only when CUDA is not - explicitly required. - -Validation: - -- 57 focused backend tests passed for YOLO inference, preflight and Docker - runtime configuration; -- backend application byte-compilation passed; -- local Compose rendering could not run because this Windows workstation has no - `docker` CLI. Tower rebuild, `nvidia-smi`, CUDA-enabled PyTorch preflight and - one bounded persisted GPU inference smoke remain the live Wave 0 exit gate. - -Known limitations and next pass: - -- these repository changes do not prove that the deployed Tower container can - see the physical GPU; do not claim GPU readiness until the live gate passes; -- next implement the persisted parent/partition/checkpoint operation as the - first Wave 1 vertical slice, reusing existing job and provider services. -## 2026-07-26 - Audit remediation: resumable AOI federation and truthful AI runtime - -Implemented: - -- added migration `202607260001` with persisted AOI parent operations and - deterministic child partitions, exact EPSG:31370 planning, zone clipping, - checkpoints, attempt budgets, child Jobs and restart reconciliation; -- added a production background worker that automatically claims queued work - and dispatches ten existing governed providers without introducing a second - Dataset persistence path; -- aggregated child Dataset identities, completeness and source-aware vector - deduplication/raster mosaic contracts into one parent result and exposed live - progress plus failures in the System workspace; -- removed the frontend overview/detail refusal for on-demand themes and routed - regional/overview acquisition through the resumable server operation; -- made coverage resolution accept a spatial union of bounded partitions only - when it covers the selection, and exposed authority, edition, time, CRS, - resolution, bbox, attribution, licence and checksum evidence per Dataset; -- corrected the active YOLO contract to building-only, fail-closed CUDA and - persisted Mol/Kempen Area scope. Production cannot advertise configured AI - from a CPU runtime or execute an unvalidated class/area. - -Validation: - -- one Alembic head (`202607260001`) and a complete 40,888-byte offline SQL - migration chain were generated; -- 71 focused backend tests, 40 frontend tests, frontend typecheck and production - build passed; -- the broader Windows-compatible backend gate passed 1,115 tests with five - WSL-dependent shell tests deselected because the workstation WSL VHD is - missing; those Linux shell gates remain mandatory on Tower; -- API contract audit passed with all 146 routes documented. - -Live pre-deploy evidence: - -- Tower is healthy on PostGIS 3.6 at migration `202607160001`; -- the host has an NVIDIA GeForce RTX 4080 SUPER with 16,376 MiB and driver - 595.71.05; -- the old container confirms the audited failure state: no Docker device - request, `torch 2.13.0+cpu`, CUDA false and zero visible GPUs; -- the official Vlaanderen catalog still identifies MDK Version 8, 20 m, LAT as - live production data, but both catalogued HTTPS host variants fail strict TLS - and HTTP does not expose the WCS path. MDK remains `not_configured`; TLS is not - bypassed. - -Next gate: - -- commit/push the immutable source, deploy on Tower, run the Linux readiness and - migration gates, prove CUDA PyTorch plus a bounded persisted inference, and - capture golden AOI/coverage evidence. -## 2026-07-26 - Regional imagery and label acquisition live on Tower - -- Added governed `wallonia_latest` and `brussels_latest` orthophoto products - backed by the official SPW and Paradigm UrbIS WMS services, with independent - provider identity, attribution, licence, freshness and temporal provenance. -- Acquisition fails closed unless the persisted `Wallonia` or - `Brussels-Capital Region` Area covers at least 99% of the request; existing - size, cache, response, checksum and EPSG:31370 safeguards remain active. -- Deployed commit `ec6f2d9` as immutable Tower image - `geointel-all-in-one:ec6f2d90615405740f2ca5f3e218b6905748ef4c-ai`. - Health, PostGIS, Alembic and browser-proxy verification passed. -- A live Walloon pair now consists of SPW image Dataset - `ce0543a4-7a07-4758-8ccb-8abdcccb6e22` and PICC reference Dataset - `9e93b286-c427-4a76-8219-abd5d95ebacb` with 284 building footprints. -- A live Brussels pair consists of UrbIS image Dataset - `90232bfb-c57f-46a2-9b7b-5f80adaab7d3` and reference Dataset - `e89bb474-a335-42c1-863c-468f43af94a7` with 105 building footprints. -- Tower reconfirmed PyTorch `2.13.0+cu130`, CUDA and the NVIDIA GeForce RTX - 4080 SUPER. These paired samples prove the regional pipeline but are not yet - a representative, frozen or promotion-ready Belgian corpus. -- Verification: frontend build and 78 focused contracts passed. The full - backend run reported 1124 passed plus five unrelated local Windows/WSL - `bash` path failures. -## 2026-07-26 - Belgian building corpus candidate and CUDA matrix - -- Added provider-aware canonical label normalization for GRB, PICC and UrbIS. - Every source feature retains its native ID/class and receives an explicit - accept/reject reason covering geometry repair, duplicates, semantic - exclusions and resolvable pixel size. -- Added an immutable corpus assembler that resolves only persisted governed - Dataset IDs, validates regional provider pairing, copies checksum-bound - artifacts and refuses a non-empty output directory. -- Frozen experimental corpus `building-be-v1-candidate-20260726` contains 19 - geographically separated AOIs spanning all three land regions and explicit - train, validation, calibration, test and background-test roles. Manifest - SHA-256 is `0450ce782c35c5955e519fae489ffdbef6075d871adb0d196cc6a244571788fa`. -- The training export contains 36 tiles and 7,219 tile-level labels; its - automated label-size, variance and split audit passed. A 12-tile regional - pilot contact sheet was rendered for human review. -- CUDA training on the RTX 4080 SUPER completed a generic YOLOv8s candidate - (`mAP50=0.0883`, `mAP50-95=0.0248`) and an incumbent fine-tune - (`mAP50=0.187`, `mAP50-95=0.0617`) on the held-out regional validation - samples. Both are immutable candidates and neither is promoted. -- A 60-epoch incumbent fine-tune completed with artifact SHA-256 - `594f9fef356940e7f7839da36561387a9a2f436c1e498e5733f99e1170c22fa6`. - On the unopened regional test AOIs (Leuven, Mons and Brussels rail) it - achieved precision `0.315`, recall `0.229`, mAP50 `0.120` and mAP50-95 - `0.0340`. The incumbent scored `0.227`, `0.233`, `0.0930` and `0.0262` - respectively. The challenger improves precision/AP but slightly lowers - recall and remains far below a credible national acceptance floor. -- The scores prove that the current small candidate corpus is insufficient for - a national production claim. Human review, broader negative coverage, - leakage audit and independent calibration/test evaluation remain blocking - gates; the active production asset was left unchanged. - -## 2026-07-27 - Belgian building corpus v2 and independent CUDA evaluation - -- Added a checkpoint-safe provisioner for 42 geographically independent AOIs: - 14 per region, with six training, two validation, two calibration, two test - and two background-test AOIs. The portfolio includes dense urban, suburban, - rural, industrial, forest, heath, quarry, rail, park and port contexts. -- Acquired imagery at an explicit 25 cm resolution and made the API reject a - requested resolution finer than the governed source's native resolution. - Rolling imagery whose per-pixel observation date is unavailable is now - recorded as `unknown_per_pixel`; it is never declared temporally aligned to - PICC/UrbIS/GRB merely from the download date. -- Frozen corpus `building-be-v2-20260727-r3` contains 42 samples and 6,761 - accepted labels from 6,828 inputs. Sixty-seven sub-pixel labels were rejected - explicitly. Manifest SHA-256 is - `8a2ccd39642be30a58bd12b52b117ea4e2055437b2ed9d49e4022b47605e5f19`. - Spatial leakage passed and all 42 temporal relations remain honestly unknown. -- Exported a 96-tile training/validation set (5,711 labels; 82 positive and 14 - negative tiles) plus independent 24-tile calibration, test and background - sets. Complete, calibration, test and background contact sheets were rendered. -- Trained `building-be-v2-active-ft-e50.pt` for 50 epochs with CUDA on the Tower - NVIDIA GeForce RTX 4080 SUPER. Artifact SHA-256 is - `615769c585ff96af4f4be3b7bdeb26e6fb7d59ba6d8f25f90fefe85fe366fb2e`. -- On the independent test set the candidate achieved precision `0.353`, recall - `0.228`, mAP50 `0.164` and mAP50-95 `0.0553`, versus incumbent `0.118`, - `0.127`, `0.0385` and `0.0118`. On the background/hard-negative set it - achieved `0.540`, `0.392`, `0.375` and `0.172`, versus incumbent `0.193`, - `0.129`, `0.0815` and `0.0348`. At confidence 0.25 it emitted zero detections - on all 15 pure-background tiles. -- The challenger is materially better but remains below a credible national - production gate, so it was not promoted. The active model remains unchanged. - The deterministic audit status is `needs_human_review`: an AI-assisted visual - inspection cannot be represented as the required human approval. - -## 2026-07-27 - Closed national training loop and corpus v3 - -- Defined a fail-closed completion contract: calibration selects a threshold by - worst-region F1, while independent regional test and pure-empty background - sets decide completion. Passing requires aggregate F1 0.55, every region F1 - 0.45/precision 0.50/recall 0.40 and zero pure-empty detections. -- Added deterministic per-AOI IoU matching and iteration assessment scripts. - Protected AOIs remain excluded from training and a failed assessment emits - `continue_training_loop` rather than a success-shaped result. -- Expanded the governed portfolio from 42 to 60 AOIs: per region 10 train, two - validation, three calibration, three test and two background-test samples. - Frozen corpus `building-be-v3-20260727-r1` contains 10,262 accepted labels; - manifest SHA-256 is - `299212d1b3881330a6e3e936836d279435ab80c156a012121fe566ad0f3eae22`. -- Corpus composition and spatial leakage pass. All 60 mosaics retain explicit - unknown per-pixel observation time; no download timestamp is used as a false - alignment claim. -- The first 97-epoch loop candidate improved validation mAP50 to `0.250` and - mAP50-95 to `0.0835`, but the strict regional assessment failed, particularly - for Flanders and Wallonia, and recorded one pure-empty false positive at the - calibration-selected threshold. Training therefore continued on v3; no model - was promoted and human review remains intentionally deferred. - -## 2026-07-27 - Dated imagery corpus v4 and loop continuation - -- Added governed, detection-capable fixed products for SPW Orthophotos 2024, - Digitaal Vlaanderen 2025 and its official Brussels coverage. Rolling - `latest` mosaics are no longer used by the training provisioner. -- Expanded the corpus to 75 AOIs, with 15 training AOIs per region and the - protected validation/calibration/test/background composition unchanged. -- Frozen corpus `building-be-v4-dated-20260727-r1` contains 13,765 accepted - labels from 13,899 inputs. Manifest SHA-256 is - `32f0c969e3131da33497ebffb6782ddf1b58e83b8a46f929818c2140af867fd3`. - Spatial leakage passed and temporal-unknown samples fell from 60 to zero. -- Iteration 2 improved fixed-IoU test F1 from `0.375` to `0.419`; regional F1 - became Brussels `0.566`, Wallonia `0.427`, Flanders `0.222`. The generic-base - iteration did not beat it. Both remained rejected, and iteration 4 started - from the stronger candidate on the dated 75-AOI corpus. - -## 2026-07-27 - Positive-imagery gate and complete SPW campaign - -- Visual inspection caught 20 positive Walloon tiles with labels over white - no-data imagery. SPW 2024 is an official but partial campaign, so that - training run was stopped and its candidate is invalid. -- Dataset QA now fails whenever any positive tile is blank/low-variance. The - checkpointed training orchestrator also refuses to start unless this audit - is `ok` with zero affected positive tiles. -- Replaced the partial product with the official, territory-complete SPW summer - 2023 campaign (27 May through 25 June, 25 cm). The frozen replacement corpus - `building-be-v5-dated-20260727-r1` retains 75 AOIs and 13,765 accepted labels. - Manifest SHA-256 is - `eade90d3ba22b426b72a300fcaa9a01f6eb1d18567c4a53413b72b8048f5f021`. -- The v5 tile audit passed with zero blank positive tiles. The automated CUDA - loop started from the strongest prior candidate and will checkpoint every - train/calibrate/test/background assessment without promoting failed models. - -## 2026-07-27 - Feature-level temporal mismatch filtering - -- Added provider-native creation-time filtering for dated training imagery: - GRB `BEGINDATUM` and PICC `DATE_CREAT` are parsed with explicit UTC handling. - Buildings created after the image period are audited and excluded rather - than taught as labels for structures absent from the image. -- Frozen corpus `building-be-v6-temporal-20260727-r1` excludes 246 such temporal - mismatches, accepts 13,524 labels and retains all 75 independent AOIs. - Manifest SHA-256 is - `973828b453e6fbeb5c04aa567ddb615566d92825d8698654f5056d2997d382eb`. -- Composition, spatial leakage, temporal identity and positive-imagery QA pass. - The v6 train/calibration/test/background exports are ready for the next loop - checkpoint; the running v5 iteration remains evidence but cannot supersede - the cleaner v6 corpus. - -## 2026-07-28 - Visual release correction (pre-deploy) - -- Reviewed the user's consolidated GeoIntel design pass in the running guest - workflow against the live API at desktop, 1024 px laptop and tablet widths. -- Confirmed the revised landing page, guest authentication, map explorer, - full-work-area analysis and quality workspace with browser-rendered evidence. -- Corrected Chromium's internal `details` content-grid behavior so quality - evidence, history and the inspector occupy their intended columns instead of - collapsing into one narrow rail with per-letter filename wrapping. -- Moved the insights panel below the map below 1240 px, kept that combined - workspace internally scrollable and widened the desktop drawer enough to - show complete values such as `5,1% dekking`. -- Guarded optional `scrollIntoView` use so guest login remains functional in - browsers and test environments that do not implement it. -- Preserved the local `frontend-src.tar.gz` transfer archive while excluding it - from Git and Docker build contexts. Restored the explicit - `frontend/node_modules` exclusion required by the Unraid release contract. -- Hardened both Tower wrappers with a scoped untracked-source cleanup after the - remote reset. It removes stale files only from image source directories and - deliberately leaves `.env`, storage, models and PostGIS data untouched. - -Verified before deployment: - -- `npm run typecheck` -- `npm run build` -- `npm run test:unit` (`43 passed`) -- `py -3 -m pytest -q backend/tests/test_sprint31_unraid_template.py backend/tests/test_docker_runtime_config.py backend/tests/test_sprint193_end_user_workbench.py backend/tests/test_sprint194_regional_timeseries.py` (`56 passed`) -- Browser checks found no horizontal body overflow in the inspected desktop, - laptop and tablet layouts. - -Deployment evidence: - -- Pushed release commit `42da5b2c7f70e14a5da0033c2f2eed2a24b2a052` to - `origin/main` and deployed the Dockerman-native all-in-one image from the - canonical `/mnt/user/appdata/geointel` checkout. -- Confirmed the active healthy image - `geointel-all-in-one:42da5b2c7f70-wip8801d1087614-ai`; its live endpoint - reports build SHA `42da5b2c7f70-wip8801d1087614`. -- The live readiness endpoint passed database, PostGIS 3.6, migration - `202607260001` and storage checks. -- The runtime exposes the server NVIDIA GeForce RTX 4080 SUPER with 16,376 MiB - memory and driver `595.71.05` inside the GeoIntel container. -- Repeated the browser-rendered landing, guest-session, map and quality checks - against `http://192.0.2.10:1202`; the inspected live flow produced no - browser-console errors. - -## 2026-07-28 - Interactive presentation and portfolio pass - -- Added a keyboard-operable four-stage project-chain illustration to the - public landing page. Selection, source governance, PyTorch analysis and QA - evidence each change the explanatory state and map treatment. -- Added restrained route, scan, evidence and map-depth motion. Every animation - and transition is disabled under `prefers-reduced-motion`. -- Generated two original, text-free GeoIntel campaign images: a Belgian - land/sea GeoAI hero and a building-detection/QA orthophoto composition. The - assets are stored in `frontend/public/portfolio` for reuse. -- Captured repository-owned portfolio screenshots for the landing hero, - interactive project story, map workbench, quality workbench and mobile - landing experience in `docs/assets/portfolio`. -- Replaced the legacy README with a product-led overview, visual tour, - architecture diagram, governed AI/CUDA behavior, setup, verification, - deployment and documentation map. -- Browser checks confirmed the tab interaction, the PyTorch stage content and - a 390 px layout without horizontal overflow. - -Verified in this pass: - -- `npm run typecheck` -- `npm run test:unit -- --maxWorkers=1 --reporter=verbose` (`45 passed`) -- `npm run build` (`1892 modules transformed`, production build passed) - -## 2026-07-28 - Complete visual system and portfolio case study - -- Extended the motion language into the workbench: workspace entry, result - drawer arrival, status-card elevation, loading sweeps and error transitions. - Motion communicates state and remains fully disabled for reduced-motion - users. -- Added an interactive PyTorch pipeline to the building-detection workbench. - Its orthophoto, tile, NVIDIA CUDA, detection and QA stages derive readiness - from the real selected data, runtime preflight, persisted runs and checks. -- Added a compact project briefing to the overview with real workflow - completion, latest quality evidence, source count and latest export status. -- Produced WebP production variants for the hero and QA artwork, reducing - their delivered size from multi-megabyte PNGs to approximately 246 KB and - 366 KB while retaining the PNG masters for portfolio reuse. -- Added a dark GeoIntel campaign cover and a four-state animated project-chain - GIF, plus standalone architecture and PyTorch/NVIDIA visuals. -- Added a reproducible ReportLab generator and six-page portfolio PDF under - `output/pdf/geointel-case-study.pdf`. All pages were rendered with Poppler, - inspected together at full contact-sheet scale and verified for page count - and extractable text. - -Verified before deployment: - -- `npm run typecheck` -- `npm run test:unit -- --maxWorkers=1 --reporter=verbose` (`46 passed`) -- `npm run build` (`1893 modules transformed`, exit code 0) -- Browser interaction checks for all four project-story states and portfolio - GIF capture; no console errors in the inspected local flow. - -Deployment evidence: - -- Pushed release commit `0cd84fa5c56e8e39dbab633dada961e65c8e582b` and - deployed from the canonical `/mnt/user/appdata/geointel` Tower checkout. -- The active healthy image is - `geointel-all-in-one:0cd84fa5c56e-wipb81317749bb7-ai` and reports the same - build revision through the live health endpoint. -- Live readiness passed database, PostGIS 3.6, migration `202607260001` and - storage checks. The container exposes the NVIDIA GeForce RTX 4080 SUPER with - 16,376 MiB and driver `595.71.05`. -- Repeated the live landing, guest bootstrap, map navigation and quality - navigation against `http://192.0.2.10:1202`; the inspected live flow - produced no browser-console errors. - -## 2026-07-29 - V36 assessment and objective-loop repair - -- Audited the current Tower evidence rather than relying on the earlier v6 - checkpoint. The governed v30 rotated-holdout corpus contains 124 samples, - 21,830 accepted labels, zero temporal-unknown samples, an immutable manifest - and no spatial leakage. Its split composition exceeds the frozen regional - minima and protected samples remain outside training. -- Assessed the completed YOLO11x v36 checkpoint calibration-first on the RTX - 4080. At the selected threshold `0.10`, aggregate F1 is `0.552`, Brussels F1 - is `0.662`, Wallonia F1 is `0.532`, and Flanders F1 is `0.265`. The candidate - failed Flanders F1/precision/recall and Wallonia precision, so test and - background evidence were not opened and the production model was unchanged. -- Built checksummed v37 failure-driven sampling from that rejection: 3,900 - train entries across 94 train AOIs, with extra Flanders recall and - Flanders/Wallonia precision evidence. The sampling audit records zero - protected samples in training. -- Started the inactive v37 YOLO11x fine-tune on Tower CUDA device 0 with - deterministic seed `20260806`, `max_det=1000`, AdamW and aerial rotation - augmentation. NVIDIA process evidence confirmed GPU execution. -- Corrected a loop deadlock: an automatically clean corpus awaiting the final - human review has status `needs_human_review`, while the orchestrator formerly - required `ok`. Training now accepts that status only when the manifest is - immutable, automated failures are empty, spatial leakage is `ok`, and blank - positive-tile count is zero. Human sign-off remains a separate mandatory - final promotion gate. -- Closed the next orchestration gap: a rejected iteration now invokes the - leak-free failure-driven sampler automatically, records its evidence - checksum and next dataset YAML in `training-loop-state.json`, and resumes - both the candidate weights and exact sampling input after interruption. -- Added `--evaluate-initial-model` for completed checkpoints such as v37. It - skips redundant fitting only for the first iteration, copies and hashes the - supplied weights, runs calibration first, and rejoins the same automatic - sampling/training path after rejection. Protected evidence remains closed - until calibration passes. -- The all-in-one container was externally recreated after v37 epoch 1. Both - 456 MB checkpoints remained intact and training resumed from `last.pt` on - the RTX 4080 instead of restarting the experiment. -- Added and activated a host-side YOLO supervisor. It requires the exact run - marker, a valid checkpoint larger than 1 MB, a running target container and - absence of `results.png` before issuing a bounded resume. It exits on a - completed training artifact or a missing/incomplete checkpoint. -- The first live probe exposed that `docker top -eo args` is rejected by the - daemon and could misclassify an active Python-launched YOLO process. Two - transient duplicate resume processes were detected and terminated before - another epoch completed. Detection now uses `docker top -eo pid,args`; a - live one-shot check returned `monitoring` with exactly one GPU process. -- Extended the supervisor with a one-time, JSON-list-only completion handoff. - The active v37 supervisor now starts the calibration-first closed loop when - `results.png` appears. The bound command permits up to 20 iterations, keeps - protected test/background closed until calibration passes, and preserves - the exact AdamW, 180-degree rotation, flip, scale and translation contract. -- Extracted and tested strict completion-command validation. Only a non-empty - JSON list of non-empty argv strings is accepted; mappings, empty arguments, - malformed JSON and filesystem errors produce an explicit fail-closed - supervisor state before any subprocess is started. The updated supervisor - was activated live with one remaining v37 GPU process. -- V37 early-stopped normally at epoch 23; epoch 5 remained the immutable best - checkpoint. The supervisor observed `results.png` and executed its one-shot - completion handoff. -- Fixed a completed-checkpoint entry defect exposed by that live handoff: the - iteration directory is now created before copying/hash-binding an existing - model. The repaired calibration ran without opening test/background. -- V37 improved calibration aggregate F1 to `0.568` and Flanders F1 to `0.307`, - but failed Flanders F1/precision/recall and Wallonia precision. It was - rejected and produced checksummed failure-driven sampling for iteration 2. -- Made training patience an explicit orchestrator input. A pre-epoch iteration - 2 process exposing the old hardcoded value `35` was terminated before any - result row existed; iteration 2 restarted from the identical checkpoint and - sampling with the frozen `patience=18` contract on CUDA. -- The first iteration-2 result row then exposed further generic-default drift: - bias LR reached `0.066775` because the direct v37 run's warmup bias `0.01` - and aerial HSV settings were not represented in the orchestrator. Both exact - processes were stopped after one row, and the invalid run was retained as - `iteration-002-invalid-warmup` with a reason marker. -- Added explicit warmup epochs, warmup bias LR and HSV hue/saturation/value to - the orchestrator and versioned completion command. Iteration 2 restarted - cleanly from the same candidate and checksummed sampling with - `warmup_epochs=1`, `warmup_bias_lr=0.01`, HSV `0.01/0.2/0.15`, patience 18 - and the existing aerial rotation/flip contract. -- Added checkpoint-aware recovery for the state-pending current iteration. - When `runs//weights/last.pt` exists, the orchestrator uses YOLO's - exact `resume=` CUDA path and records that provenance after the - iteration is assessed. -- Added and activated a host-side parent-loop supervisor. It monitors the exact - orchestrator marker and fail-closed JSON loop state, restores the current - script into a recreated container and relaunches only the versioned argv - command. Its live state is `monitoring`, with zero relaunches and one active - iteration-2 GPU process. -- Added those aerial augmentation parameters to the orchestrator CLI and - training command, preventing later failure-driven checkpoints from silently - reverting to generic orientation assumptions. -- Confirmed v37 epoch 1 completed on CUDA with validation precision `0.601`, - recall `0.455`, mAP50 `0.474` and mAP50-95 `0.205`; the run remains inactive - and these internal-validation metrics are not release evidence. - -Verified in this pass: - -- `py -3 -m pytest -q backend/tests/test_belgium_training_loop.py backend/tests/test_belgium_training_iteration_assessment.py backend/tests/test_belgium_training_portfolio.py` - (`12 passed`). -- `py -3 -m pytest -q backend/tests/test_belgium_training_loop.py backend/tests/test_failure_driven_yolo_sampling.py backend/tests/test_belgium_training_iteration_assessment.py` - (`16 passed` after adding the completed-checkpoint entry contract). -- `py -3 -m pytest -q backend/tests/test_yolo_training_supervisor.py backend/tests/test_belgium_training_loop.py` - (`11 passed`), plus a live supervisor one-shot and single-process GPU audit. - -Open: - -- Let v37 finish, run calibration-only assessment, and expose protected test - and pure-background results only if every regional calibration gate passes. -- Continue failure-driven, train-only corpus iterations until all objective - gates pass; only then request the queued representative human review. - -## 2026-07-29 - V42 regional corpus expansion and v43 loop handoff - -Changed: - -- Added and acquired 14 independent train-only AOIs spanning Flemish coastal, - port, dunes, industrial and ribbon contexts plus Walloon architecture, - rural, industrial, quarry, forest and field contexts. -- Built immutable 156-sample v42 evidence, applied the governed temporal - filters, refined the new labels with SAM2 on CUDA and retiled all new source - labels with 384 px tiles and 128 px overlap without uncovered labels. -- Rotated the training corpus while retaining the exact protected v31 - calibration, test and background assignments. -- Added the versioned v43 command for calibration-first evaluation followed by - at most 20 failure-driven CUDA iterations. It starts from the rejected v38 - iteration-5 checkpoint and shortens patience to 8 because all preceding runs - selected epoch 2 while later epochs overfit the protected regional pattern. - -Verified: - -- Corpus audit: 156 samples, no automated failures and no reported leakage. -- Training tile audit: `ok`; 2,160 tiles, 56,474 valid labels, zero invalid or - missing labels, 270 negative tiles and zero repeated background negatives. -- New-AOI visual renderer: `ok`; 56 rendered tiles spanning all 14 added AOIs, - with zero missing inputs, invalid rows or low-variance imagery. Manual - AI-assisted inspection found labels aligned with visible roof footprints and - retained the deliberately sparse hard-negative contexts. -- NVIDIA preflight: RTX 4080 SUPER idle and available before the v43 handoff. -- Iteration 2 selected its epoch-5 checkpoint, reached aggregate calibration F1 - `0.584` and zero pure-empty detections, but remained closed because Flanders - F1/precision/recall and Wallonia precision failed. Iteration 3 started from - the exact rejected checkpoint without opening test/background. -- Confirmed Ultralytics preserves duplicate paths from the 4,077-entry - failure-driven list. Added deterministic per-round rotation of the repeats - retained by the 65% regional cap, preventing persistent identical failures - from producing an identical capped list forever while preserving every - unique train tile and all protected-split exclusions. -- `py -3 -m pytest -q backend/tests/test_failure_driven_yolo_sampling.py backend/tests/test_belgium_training_loop.py` - (`20 passed`). -- Iteration 3 raised aggregate calibration F1 to `0.605`, passed Brussels and - every Wallonia gate, and isolated the remaining blocker to Flanders. When - iteration 4 removed Wallonia stabilization, Wallonia precision regressed - narrowly from `0.525` to `0.496`. Added a `0.03` precision/recall sampling - guard-band so a just-passing region retains stabilizing evidence while the - hard-failing region remains the primary target (`21 passed`). -- Iterations 5 and 6 confirmed that the guard-band retains Wallonia above its - gates, but Flanders remains structurally below precision, recall and F1 - gates. Stopped iteration 7 before its first result row and freed the GPU - rather than repeating the same evidence. Added 12 independent v44 Flemish - acquisition targets across coastal, industrial, ribbon, dunes, port and - farmland-hard-negative contexts for the next immutable corpus wave. - -Open: - -- Complete v43 calibration convergence, then and only then evaluate the closed - protected test and pure-background sets. -- Obtain final representative human contact-sheet approval, promote the exact - checksummed model, and redeploy from the canonical Tower directory. -## 2026-07-29 - V44 Flemish corpus expansion and V45 training loop - -- Acquired twelve independent Flemish train-only AOIs covering dense coastal - development, ribbon development, industry, dunes, docks and pure-empty - agricultural background. The immutable expansion manifest SHA-256 is - `62fdb4adee46ff67a40636f30a22fc97b8c9bd14516cbe0a24ed0de2db56f4fb`. -- Refined 2,391 labels with SAM2 on `cuda:0`; 124 unsafe refinements fell back - to their source geometry. Lossless overlap retiling retained all 2,515 - unique source labels in 192 tiles. -- Composed the 168-AOI V44 corpus and retained the exact V42 calibration, - protected-test, background-test and internal-validation assignments. The - rotated manifest SHA-256 is - `448bb3ec426a6af129f01d29732160f84b9936c9871a033de13a7d98b9d25112`. -- Corpus evidence reports 30,113 accepted features, zero temporal-unknown - samples, zero spatial leakage and zero protected samples in training. The - YOLO dataset-quality audit passed. Automated corpus checks have no failures; - final human contact-sheet review remains deliberately deferred until every - model release gate passes. -- Added the reproducible V45 command. It starts from the strongest V43 Flemish - checkpoint (`iteration-005`, SHA-256 - `be8c5a4d27dfcd03e29e59ce78ea66d3c772c3e612c08b71fd457d3006001b71`) - and trains against the expanded V44 corpus on the NVIDIA server. -## 2026-07-30 - Direct polygon QA and rejected automatic roof-alignment routes - -- Revalidated the three independent V66 Flemish AOIs against their immutable - EPSG:31370 rasters and CRS84 GRB responses. Raster bounds, OGC `Content-Crs`, - feature coordinates and tile transforms are internally consistent; no CRS or - WMS axis-order defect was found. -- Proved that the existing YOLO contact sheet can make rotated and concave GRB - polygons look substantially worse by showing only their axis-aligned boxes. - Added `scripts/render_operator_polygon_label_qa.py` so governed polygon/raster - alignment is reviewed directly before lossy bounding-box export. -- Rejected streamed automatic SAM2 masks: the broad trial matched 365/413 source - objects but selected trees, roads, parking and open ground; a strict trial kept - only 42/413 and still contained false roofs. -- Rejected local polygon-edge registration: 27/73 Zutendaal, 5/66 Zoersel and - 32/110 Landen objects passed numerical uniqueness gates, but direct overlays - still contained vegetation, road and shadow-edge matches. -- Rejected a swapped Lambert WMS-axis hypothesis and a live `most_recent` image - refresh after isolated visual trials. Neither output entered a training corpus. - -### Gate consequence - -- V66 remains candidate-only and is not promotion or protected-test evidence. -- No new training is authorized from these rejected outputs. The next corpus - revision must use independently image-visible roof annotations or an official - roof-surface product, with direct polygon QA before YOLO box generation. - -## 2026-07-30 - README and production screenshot refresh - -- Rewrote the root README product introduction to state the Belgium/North Sea - scope, regional-source semantics, fail-closed CUDA behavior and current - candidate-versus-promoted training status more explicitly. -- Captured current production screenshots through the read-only guest workflow: - landing hero, interactive workflow, map workspace, QA/QC workspace, mobile - landing and mobile map workspace. -- Added the mobile workbench image and a portfolio-asset index to the README. -- Verified the deployed guest demo loaded seven datasets and one demo area, the - QA view exposed four persisted checks, and the browser reported no warnings or - errors during capture. - -### Known limitation - -- The guest screenshots intentionally show governed fixture/demo evidence, not - a claim that the rejected V66 candidate labels or a new detector have been - promoted. - -## 2026-08-01 - Live animated area-analysis workflow - -### Changed - -- Added a reusable `LiveAnalysisJourney` overlay to the real map canvas, using - the same dark glass, mint signal and four-stage language as the public - interactive project illustration. -- Bound Select, Sources, Process and Verify to persisted workbench state: - bounded AOI selection, source/coverage loading, extraction or image analysis, - QA validation, completed evidence and real error responses. -- Added a processing-only scan line, status pulse, responsive compact layout and - a complete `prefers-reduced-motion` fallback. The overlay uses - `pointer-events: none`, so drawing, panning and object inspection remain - available beneath it. -- Added a pure state resolver and component coverage for idle, loading, - processing, verification, completion and error transitions. - -### Tested before deployment - -- `npm run test:unit -- --run src/components/map/LiveAnalysisJourney.test.tsx` - passed: 3 tests. -- Complete frontend unit suite passed: 49 tests in 15 files. -- `npm run build` passed TypeScript compilation and the Vite production build. -- React review confirmed static step metadata is module-scoped, status is - derived during render, icons use direct imports and the overlay has an - accessible live region. - -### Deployment and live acceptance - -- Pushed implementation commit `d7752cb` and mobile visual correction - `b18e846` to `main`. -- Deployed the exact `main` history to `/mnt/user/appdata/geointel`. Because - Tower resolved the Gitea hostname to public SSH port 22 instead of the local - configured port 222, the same deploy was transported as a verified Git bundle - and then executed through `deploy/unraid/deploy-release.sh`. -- The immutable CUDA/AI image - `geointel-all-in-one:b18e8460da32-wipb6567ba06f10-ai` became healthy; PostGIS - 3.6, required schema objects, Alembic head `202607260001`, frontend, API proxy - and icon checks passed. -- Live guest-browser acceptance passed at 1280 x 720 and 415 x 899. A real map - drag changed the journey from Select to Verify and displayed “result awaiting - verification”; the mobile status card remained below the drawing toolbar, - horizontal overflow was zero and the browser emitted no warnings or errors. - -### Remaining behavior by design - -- The proof state becomes complete only after real QA evidence exists. A spatial - selection result without QA deliberately remains “awaiting verification”. - -## 2026-08-01 - Production operator username correction - -### Root cause and correction - -- Traced the failed operator login to an exact username mismatch: the active - Tower runtime was configured as `jens@itworx.tech`, while the required - operator username is `ITWorx`. Authentication intentionally performs an - exact, case-sensitive comparison. -- Backed up the persistent production `.env`, changed only - `GEOINTEL_AUTH_USERNAME` to `ITWorx`, and retained the existing PBKDF2 - password hash, session secret, session lifetime and guest-access setting. -- Updated the operator-configuration examples to use `ITWorx`, preventing the - former email-style example from being copied back into production. - -### Deployment and verification - -- Restarted the release from `/mnt/user/appdata/geointel` with - `DEPLOY_GEOINTEL_INSTALL_AI=true`; the existing immutable NVIDIA/AI image - `geointel-all-in-one:b18e8460da32-wipb6567ba06f10-ai` was preserved. -- The container became healthy. PostGIS 3.6, required runtime schema objects, - Alembic head `202607260001`, frontend, API proxy and icon checks passed. -- Confirmed the active container exposes authentication as enabled with exact - username `ITWorx`; no plaintext password or password hash was printed or changed. -- Targeted backend authentication suite passed from the backend root: 8 tests. -- `bash -n scripts/configure_operator_login.sh` and `git diff --check` passed. - -## 2026-08-01 - Explicit map analysis selection and result drawer - -### Changed - -- Decoupled AOI drawing from analysis: completing a rectangle now stores only - the bounded selection and clears stale results; it does not acquire or query - any theme, source or AI model. -- Added explicit multi-theme selection with a single `Analyseer selectie` - action. The bounded request planner now receives only the themes chosen by - the user. -- Restored Insights as an explicit open/close drawer over the map, with an - accessible toggle and a truthful pre-analysis empty state. -- Shortened theme availability copy, constrained labels and statuses to their - grid columns, and added a compact selection summary/action block. -- Kept full-work-area selection non-executing; it follows the same choose-then- - analyse contract as a drawn rectangle. - -### Verification before deployment - -- `npm run build` passed TypeScript compilation and the production Vite build. -- `npm run test:unit` passed all 49 tests in 15 files. -- `git diff --check` passed. -## 2026-08-01 — Sprint 235 live acceptance follow-up - -- Runtime commit `e8673658acb736fece845ca6ea78b423ed161479` deployed to verified target `/mnt/user/appdata/geointel` as immutable NVIDIA/AI image `geointel-all-in-one:e8673658acb7-wip99c1efd35d29-ai`. -- Production smoke passed: container healthy, PostGIS 3.6, Alembic `202607260001 (head)`, frontend/API/icon runtime verification green. -- Mobile production route at 415 x 899 verified: selecting the work area does not start analysis; `Analyseer selectie` remains disabled until a theme/model is chosen; one chosen theme yields `1/1 uitgelezen`; the slide-out results drawer opens and closes through its accessible toggle. -- Layout acceptance: document horizontal overflow `0`; theme-panel horizontal overflow `0`; browser console errors and warnings `0`. -- Corrected a global `button:active` transform collision that moved the mobile drawer toggle between pointer-down and pointer-up. -## 2026-08-01 - Sprint 236 platformbrede UI/UX-herwerking - -### Gewijzigd -- Centrale `ModelSelector` met native dialoog, eenvoudige aanbevolen keuze, geavanceerde concrete modellen, echte runtimebeschikbaarheid en optionele technische details. -- AI-vragen bewaren een versiegebonden voorkeur; een verdwenen model valt veilig terug op de beschikbare serverstandaard zonder een ongeldige model-ID te verzenden. -- Detectie en segmentatie gebruiken hetzelfde selectiepatroon en behouden hun bestaande API-contracten en `not_configured`-gedrag. -- Kaartwerkruimte kreeg themazoeken, een bredere leesbare configuratiekolom, rustigere contextbalk en responsive panelafmetingen. -- Interactieve elementen zijn semantisch gescheiden; focus, Escape, native dialoogfocus, reduced motion en mobiele bottom-sheetpresentatie zijn voorzien. - -### Getest -- Frontend: 16 testbestanden, 51 tests geslaagd. -- Frontend: TypeScript- en Vite-productiebuild geslaagd; `git diff --check` geslaagd. -- Backend: 1.178 tests geslaagd; 19 bestaande stringgebaseerde contracttests falen op eerder gewijzigde repositoryverwachtingen. Meerdere verwachten opnieuw automatische kaartanalyse en mogen daarom niet worden hersteld zonder de actuele expliciete-startbeslissing te breken. - -### Open / beperking -- Visuele browseracceptatie en productie-uitrol volgen op de gecommitte wijziging tegen de echte serverruntime; de lokale frontend kan zonder backend-sessie alleen de voorbereidingsstatus tonen. -### Visuele acceptatie -- Echte serverdata via de lokale frontendpreview gevalideerd op 1920x1080, 1024x768 en 390x844. -- Desktop, tablet en mobiel: documentoverflow `0`; themapaneeloverflow `0`. -- Mobiele hoofdflow: thema zoeken, kiezen, volledig werkgebied selecteren, expliciet analyseren, resultatenlade openen en sluiten geslaagd. -- Browserconsole: `0` waarschuwingen en `0` fouten. -- Bewijsbeelden: `docs/screenshots/ui-ux-map-desktop-2026-08-01.jpg` en `docs/screenshots/ui-ux-map-mobile-results-2026-08-01.jpg`. - -## 2026-08-01 - Sprint 237 volwaardige demo-analysetoegang - -### Gewijzigd -- Demo-navigatie omvat nu status, bronnen, kaart, AI-vragen, kwaliteit, beeldanalyse en downloads; alleen de systeem-/beheerwerkruimte blijft verborgen. -- De demo laadt dezelfde lokale assistent-, detectie- en segmentatiemodellen, runs, resultaten en exports als de operator binnen het gebonden demoproject. -- Gastverzoeken voor AI-runs, QA, assistent en exports zijn server-side toegestaan met een verplichte en gecontroleerde `project_id`; andere projecten blijven vóór route-uitvoering geblokkeerd. -- Project- en gebiedbeheer, uploads, bron-/runtimeconfiguratie, bewijsreviews en overige mutaties blijven operator-only. - -### Verificatie -- TypeScript- en Vite-productiebuild geslaagd. -- Gerichte frontend-, backend-, browser- en productieverificatie volgen hieronder na de releasegate. -- De eerste productieacceptatie vond een echte CUDA-compatibiliteitsregressie: `torch 2.13.0+cu130` zag de RTX 4080 SUPER maar weigerde initialisatie op de Tower-driver met CUDA 12.9-capaciteit. De AI-image is daarom teruggebracht naar de expliciet gepinde, drivercompatibele combinatie `torch 2.11.0` / `torchvision 0.26.0` via de officiële CUDA 12.8-index; promotie vereist opnieuw live `torch.cuda.is_available()` en modelpreflight. -- De CUDA 12.8 PyTorch-wheel vereist `setuptools<82`; de imagepin is daarom samenhangend teruggebracht van 83.0.0 naar 81.0.0 en blijft door `pip check` bewaakt. - -### Live productieacceptatie -- Exacte runtimecommit `9e582f29210fcf4d9e5f422ec15236b71e2dc123` is vanuit de geverifieerde map `/mnt/user/appdata/geointel` uitgerold als immutable NVIDIA-image `geointel-all-in-one:9e582f29210f-wipfdc62947dfb2-ai`. -- Containergezondheid, PostGIS 3.6, Alembic `202607260001 (head)`, frontendproxy, API en icon-smoke zijn geslaagd. -- Live PyTorch rapporteert `2.11.0+cu128`, CUDA 12.8, `torch.cuda.is_available()=true` en `NVIDIA GeForce RTX 4080 SUPER`; YOLO-preflight rapporteert `accelerator_ready=true`, lokaal model aanwezig en geen downloads of inference tijdens de preflight. -- De productiedemo toont zeven niet-administratieve werkruimtes, drie detectiemodellen en vier segmentatiemodellen; het geconfigureerde YOLO-model wordt als beschikbaar getoond. -- Modelkalibratie, technische modelinstellingen, uploads en systeembeheer zijn niet zichtbaar voor gasten. Een directe gast-POST naar projectbeheer retourneert HTTP 403 `GUEST_READ_ONLY`; het modelregister retourneert HTTP 200 binnen dezelfde sessie. -- Visuele browseracceptatie: horizontale overflow `0`; browserconsole `0` waarschuwingen en `0` fouten. - -## 2026-08-01 - Accuracy Improvement Program Phase 1 forensic baseline - -### Executed scope - -- Audited repository root and tracked nested mirror, API/services/schemas, - migrations, frontend, CI/readiness, container/deployment configuration, - Tower Postgres/PostGIS, direct storage references, active CUDA runtime, - mounted models/checkpoints/manifests/evaluations and Belgian building - corpus lineage. -- Created the seven required documents and machine-readable status under - `docs/accuracy-program/`. -- Added read-only collectors for repository state, Tower runtime/database, - Tower ML/data lineage and one production-adapter GPU inference, plus a - deterministic reproducer for seven critical/high contract violations. -- Retained JSON, JUnit, SQL and command logs under - `artifacts/evidence/accuracy/P1/`; no dataset, checkpoint, cache, output, - user-owned untracked file or production database row was deleted or rewritten. - -### Proven findings - -- Reproduced cross-theme coverage contamination, metres-as-degrees buffering, - Lambert coordinates persisted under SRID 4326, caller-spoofable official - authority, mutable-name YOLO scope, mutable-name legal coverage and silently - ignored Area PATCH geometry. -- Tower database contains four successful Geel detections with Lambert-domain - coordinates while stored as SRID 4326. Direct storage-reference audit checked - 5,816 references with zero missing; the broader recursive scan timed out and - is not counted as a pass. -- The building training loop contains a protected-test feedback path. V56 has - 180 AOIs but 0 human review decisions, only three pure-empty background-test - AOIs and 24 cross-split AOI pairs below 2 km. V58/V62 are calibration-only, - fail Flanders at the reported operating point and have no protected-test or - promotion evidence. -- Runtime lineage is incomplete: every persisted detection run has an empty - model version and no tile-manifest hash; three runs lack a model hash. -- Repository source of truth is ambiguous through 1,153 tracked nested mirror - files, including 68 root/mirror differences. Root `.dockerignore` correctly - excludes the mirror from the official all-in-one context. - -### Runtime and verification evidence - -- Real read-only inference passed through the production adapter on the Tower - RTX 4080 SUPER, PyTorch 2.11.0+cu128/CUDA 12.8, with active model SHA - `a9088b8491dfae36694b53e9e9406cb4e3511d334a5712fa34f75078a47759c1`. - One existing EPSG:31370 tile produced 17 raw detections in 0.8837 s; this is - runtime evidence only and not an accuracy result. -- Full backend suite: 1,180 passed, 17 stale source/contract assertions failed. - The actual backend CI working directory fails during collection on - `scripts.render_operator_polygon_label_qa`. -- Phase-1 tooling: 4 tests passed; all new audit files pass Ruff. -- Repository Ruff baseline: 112 findings. Frontend `test:unit`: 51/51 passed; - typecheck and build passed; the required `npm run lint` script is absent. -- OpenAPI audit passed for 147 routes plus 10 declared non-envelope endpoints. - Alembic has one head, `202607260001`, and the complete offline upgrade - rendered successfully. -- Two golden-QA runs produced equal semantic metrics but different retained - bytes because run identity uses UUID4. - -### Decision - -- Phase 1 is complete as a forensic and executable baseline. -- Release promotion, national validation, scope widening and immediate training - remain blocked. -- Phase 2 may start only as the dependency-ordered, test-first remediation in - `docs/accuracy-program/06-implementation-roadmap.md`: fix CRS/authority/ - coverage/lineage and protected-test isolation, complete human corpus review, - rebuild independent data, freeze metrics, then train on `cuda:0`. - -## 2026-08-01 - Accuracy Improvement Program Phase 2 source and provenance foundation - -### Implemented and verified scope - -- Added a server-owned source registry, immutable snapshots, source policies, - dataset/dataset-version provenance fields, lineage edges and durable - quarantine records through Alembic revision `202608010001`. -- Added versioned vector, raster, YOLO label and PyTorch model contracts with - checksum, CRS, bounds, units, resolution, topology, required attributes, - time/freshness and lineage checks. Governed ingestion is idempotent through - ingest keys, can safely replay an identical immutable snapshot across - projects without rewriting its first fetch time, and fails closed into - quarantine when a contract fails. -- Non-WGS84 vector imports now store the exact transformed EPSG:4326 bytes as - the checksummed consumption artifact; original source bytes are retained - only as provenance evidence. Vector operations verify both storage CRS and - byte checksum before reading a dataset. -- Enforced a consumption boundary for production inference, primary reference - QA, derived work, export, coverage and training inputs. GRB is task-bounded - primary authority for suitable Flemish building validation; the Buildings - Register, DHMV, Sentinel-2 and OSM retain distinct roles, and OSM cannot - become automatic truth. -- Production detection/segmentation now resolves model sidecar UUIDs against - the registry and snapshot database records before adapter loading, including - source/snapshot relationship, freshness, quarantine, checksum and version - checks. A structural sidecar alone remains catalogue/preflight evidence. -- Verified the migration in a disposable PostGIS database: upgrade, real - trigger-guard DML checks and downgrade passed. This was not a production - migration or deployment. - -### Evidence and test result - -- Retained proof is under `artifacts/evidence/accuracy/P2/`: the source/ - contract inventory contains 40 server-owned definitions and the PostGIS - guard report covers immutable source/snapshot evidence, exact checksum - binding, lineage cycles and transitive quarantine propagation. -- A final cohesive source-to-training regression set passed 221 tests, - including immutable snapshot replay, canonical CRS/checksum storage and - database-bound model provenance. The governed golden QA benchmark passed. -- Frontend typecheck, 51 frontend unit tests and production build passed. - The complete backend suite now collects but is not green: 1,282 passed and - 17 failed. Sixteen failures are historical source-text assertions; one is - an intermittent Windows WSL-backed `bash.exe` host failure in a syntax test - that passes in isolation. Repository Ruff still has 95 findings and - `npm run lint` is still absent. - -### Decision - -- The source/provenance foundation is implemented and verified in a - disposable environment, but Phase 2 remains **in progress** and Phase 3 is - **not ready**. No training, protected-test release, promotion, national - validation or production migration is authorized by this result. - -## 2026-08-02 - Accuracy Improvement Program Phase 3 full data scan - -### Implemented and verified scope - -- Added `scripts/run_accuracy_phase3_full_data_scan.py`, a read-only, - SHA-256-bound and batch-resumable scanner for the configured local GeoIntel - roots. It validates GeoJSON geometry/bounds, GeoTIFF readability/CRS/ - resolution/nodata, manifests, YOLO labels and generic immutable artefacts. -- Retained full scan, anomaly, logical quarantine, duplicate, leakage, - source-freshness, dataset-summary and checkpoint manifests under - `artifacts/evidence/accuracy/P3/`. Three known external boundaries are - explicitly represented as unreachable; no source file was removed or - overwritten. -- Added a deterministic fixture test covering valid/invalid GeoJSON, corrupt - raster input, exact duplicates, quarantine and a byte-stable resumed replay. - -### Evidence and decision - -- The scan processed 295 local files and recorded 3 unreachable scope items; - `295 + 0 skipped + 3 unreachable = 298` reconciles exactly. Two consecutive - runs produced scan ID `p3-46ee3f8d3a2dc52b` and content hash - `1a219362c6cb2ac00489625f1a9b36e2fd4809ab58ee55ab1f67c3cc34773f3e`. -- 172 anomalies were retained and 163 affected items were logically - quarantined. The P1 split inventory (24 AOI pairs below 2 km and no proven - split independence) remains an explicit leakage attention signal. -- Phase 3 is **done for the bounded project environment** and Phase 4 is - **ready** for remediation/review. This does not unlock training, promotion, - national validation or production release; those gates remain governed by - the execution contract and the incomplete Phase 2 gates. - -## 2026-08-02 - Accuracy Improvement Program Phase 4 evaluation harness - -### Implemented and verified scope - -- Added a deterministic evaluator for object detection, building-footprint - segmentation, categorical raster interpretation, vector comparison, change - detection, terrain/height interpretation and geospatial data validation. It - retains exact references, pre-/post-filter predictions, config and lineage, - and reports task metrics, Wilson intervals, calibration, abstention, - subgroup support and a stable failure taxonomy. -- Added a six-role split generator for `train`, `val`, `calibration`, `test`, - `background-test` and sealed `challenge`, with exact/near-duplicate, - identity, acquisition, object, geometry and 2-km spatial leakage gates. - Product mode requires strict P3/provenance records and rehashes four physical - asset types; protected roles are rejected by the training firewall. -- Added a fail-closed governed product-baseline validator. It recomputes all - seven task families in-process and verifies current active-model bytes, - CUDA/GPU identity, authority, human review, leakage, vault and all thirteen - subgroup dimensions. Loose status fields cannot turn a productgate green. -- Fixed an evidence-ledger self-reference in workflow v2.0.1: only the - gate-relevant `/runtime/active_model` projection from `status.json` is - canonically hashed. Updating timestamps, Phase-4/5 bookkeeping, documents or - evidence IDs therefore leaves the run fingerprint stable; changing the - active model changes it. - -### Evidence and verification - -- Normative run `p4-2.0.1-9677d0ef37db82bcf39b` is bound to source commit - `70fb4b94e5cb7c248beec5a936ce186f38cc183c`. Its canonical benchmark hash is - `0ea5ab07f46c509a7a24943b31d5e9bfd6368920609227bc47613e18e52c4642` and - its evidence-manifest file hash is - `fdc15a95ee2a0754dfa169f4b41036e084b8d8909afc37fd8ea68ee6b9210f98`. -- The targeted Phase-4 suite passed 60 tests. The broader contracts, - provenance, Phase-3/4, golden-QA, runtime-model and migration suite passed - 103 tests with the installed Git Bash provider; the Windows Store WSL stub - was unavailable and is not a code failure. The focused migration/provenance - subset passed 29 tests and Alembic has one head, `202608010001`. -- Ruff, Ruff format check, compileall and diff check passed on all Phase-4 - paths. No Python mypy/pyright typecheck is configured in this repository. -- Repeated workflow execution produced the same run ID and byte-identical - immutable bundle. `--allow-product-blocked` returned 0; standard fail-closed - execution returned 2. - -### Decision - -- The local harness is `pass`, but the governed product benchmark is `fail` - because Phase-3 leakage remains `attention`. Active model execution, - authority coverage, representative review, independent product splits, - physical vault isolation and thirteen-dimension subgroup support remain - `not_evaluable` without governed evidence. Phase 4 remains **in progress**, - Phase 5 remains **not ready**, and promotion/training feedback from protected - data is not authorized. - -## 2026-08-09 - Model accuracy boundary and truthful evidence labels - -### Changed - -- Replaced the configured-YOLO Area-name substring gate with a fail-closed, - checksum-bound validation-scope manifest. The exact model SHA-256 must match - and the immutable EPSG:4326 scope geometry must cover the complete persisted - Dataset AOI. Renaming an Area can no longer widen model applicability. -- Added an operator tool that builds the model-bound manifest from exact model - bytes and governed scope GeoJSON without overwriting prior evidence. -- Corrected the detection UI: legacy Mol/Kempen profile scores are now labelled - historical calibration context, spatial independence is explicitly unproven, - and no profile is marked approved or promotion-ready. - -### Verified - -- Targeted backend/UI contract selection: 34 passed. -- `git diff --check`: passed before the documentation update; final check is - part of the handoff verification. - -### Remaining limitations - -- The current active model is still not nationally validated. A new governed - corpus, independent spatial split, representative human review and immutable - product benchmark remain required before any production-accuracy claim. -- Every deployed model asset needs its own generated scope manifest and exact - configured manifest checksum before enforced inference is available. - -## 2026-08-09 - Detection result trust and operational export gate - -### Changed - -- Detection GeoJSON is now explicitly a review/control layer by default. The - collection, every feature and the persisted Export metadata carry a stable - result-trust classification; AI confidence is never represented as truth. -- Added an explicit `operational` export intent that fails closed unless a - persisted authoritative building-reference QA proves exact tile coverage, - compatible time, supported geometry, zero warnings, zero false positives - and zero false negatives. -- Updated the Downloads copy so users no longer see an unqualified - "Gebouwdetecties" export label. - -### Verified - -- Focused export and detection-QA suite: 24 passed. -- Scoped Ruff check: passed. -- Frontend TypeScript check: passed. - -### Remaining limitations - -- The active model remains review-required and Kempen-scoped. The export gate - prevents overstated results; it does not replace the missing independent, - human-reviewed national accuracy corpus or improve model weights by itself. - -## 2026-08-09 - Reviewedexp6 provenance migration audit - -### Inspected - -- Recovered and checksummed the original challenger weights, training summary, - Ultralytics arguments, results, dataset YAML, 252-tile/79,192-label summary - and legacy dataset-quality audit. -- Reproduced the recorded seed `0`, deterministic request, CPU device, twenty - epochs, active base-model hash and train/validation counts. -- Ran the current human-review eligibility validator against the retained - audit; it failed on missing accepted review evidence, manifest immutability, - spatial-leakage status and incomplete review state. - -### Decision - -- Refused to invent the absent historical training commit, container digest, - runtime receipt, corpus/label/split manifests, reviewer decisions or source - registry UUIDs. -- Created no runtime sidecar, database provenance row or production model - activation. The active scoped model and healthy GPU runtime remain unchanged. -- Retained the complete fail-closed audit under - `artifacts/evidence/accuracy/model-training/20260809-reviewedexp6-provenance-migration-audit.json`. - -### Required next gate - -- Complete P2-00 through P2-07 and the governed Phase-4 blockers, obtain real - representative human review, freeze a new independent corpus and only then - train a pre-registered GPU candidate with provenance captured from process - start. The legacy checkpoint cannot be made compliant retroactively. - -## 2026-08-09 - Explicit AI-assisted reviewedexp6 AOI ledger - -### Reviewed - -- Inspected the existing checksum-bound 64-tile contact sheet at original - resolution. It covers 28 AOIs, 21,611 rendered labels, dense urban, sparse - building context and pure-background examples. -- Recorded a per-AOI machine-readable decision ledger with reviewer type - `ai_assistant`, `human=false`, the contact-sheet hash, sampled tile/label - counts, split roles and explicit roof-versus-GRB limitations. -- Classified 26 represented training AOIs as experimental-training eligible; - kept Grobbendonk and Vosselaar validation-only. No AOI was represented as - human accepted or production release eligible. - -### Gate behavior - -- Confirmed that the governed training wrapper still requires accepted human - review and therefore does not accept this AI ledger as release evidence. -- Did not add an override, fixture claim or synthetic reviewer identity. No - model training, activation or production redeploy followed from this review. - -### Full-corpus extension - -- Added deterministic contact-sheet pagination and rendered all 252 retained - tiles across four pages. Accounting covers all 79,192 labels with zero - missing images/files, invalid rows or low-variance tiles. -- Inspected every page at original resolution. Pure-empty tiles remain visibly - empty; sparse contexts remain distinct; dense tiles retain the documented - roof-versus-ground-footprint limitation. -- A read-only same-class box probe found zero exact duplicates and zero pairs - at IoU >= 0.90. It flagged 43 possible containment pairs across 36 tiles for - human adjudication. No source label was modified or silently excluded. -- Added a reproducible relationship auditor and rendered the 36 flagged tiles - on a dedicated 384 px contact sheet. Visual follow-up found complex/adjacent - building components rather than a systematic duplicate-label pattern. -- Targeted auditor and renderer tests passed: 9 tests. - -## 2026-08-09 - Index-bound relationship highlighting - -### Improved - -- Connected the relationship-audit manifest to the visual label renderer so - exact duplicates, near duplicates and possible nesting receive distinct - colors and every implicated YOLO row is labelled with its source index. -- Generated a new immutable 36-tile focused sheet on Tower. It renders 17,253 - valid labels, highlights all 86 rows participating in the 43 nesting pairs - and contains zero invalid label rows. -- AI-assisted inspection confirmed that the focused corpus contains only - magenta nesting candidates; no exact or high-IoU duplicate category is - present. The cases remain dispersed dense-GRB review candidates rather than - a safe deterministic rewrite set. -- Retained every source file and label unchanged. Excluding entire flagged - tiles would remove 17,167 unflagged labels and is therefore not justified. - -### Verified - -- Targeted relationship-auditor, renderer and Sprint 167 regression suite: - 10 tests passed. -- Scoped Ruff check, Ruff format check, Python compilation and Git whitespace - check passed. - -### Remaining limitation - -- This is explicit AI-assisted triage, not human adjudication. It improves the - evidence and review precision but does not unlock governed production - training or checkpoint promotion. - -## 2026-08-09 - Row-level geometry and cross-tile independence audit - -### Improved - -- Added a reproducible, read-only label-row auditor for sub-threshold pixel - dimensions, extreme aspect ratios and tile-edge clipping, with separate - category manifests accepted directly by the visual QA renderer. -- Extended the renderer with orange extreme-aspect, blue small-dimension and - green tile-edge highlighting while preserving the existing duplicate/nesting - colors and source row indices. -- Added an exact cross-tile repetition auditor that reconstructs global pixel - boxes from the exporter's `_r_c` offsets. Edge-clipped rows stay - explicitly unlinked rather than being guessed back to source objects. -- Made checkpoint-matrix output disclose dataset tile overlap and explicitly - state whether validation rows are independent whenever a dataset summary is - available. - -### Tower findings - -- Reviewed all 79,192 rows: 1,812 have a dimension below 4 px, 26 have aspect - ratio at least 8 and 5,079 touch a tile edge; 6,657 unique rows are involved. -- Inspected the complete 23-tile extreme sheet, all four small-dimension pages - covering 198 tiles, and a 64-tile edge sample. Most extreme shapes are valid - elongated structures, but 16 of 26 also fall below the 4 px floor. -- Reconstructed 34,082 unique interior objects from 74,113 interior label rows. - Tile overlap adds 40,031 exact repeated rows across 24,701 object groups, - with maximum repetition four and zero cross-split groups. -- Froze the next-corpus decision: restore `min_label_px >= 4`; test any stricter - edge-visible ratio as a separate immutable ablation rather than modifying - this corpus in place. - -### Verified - -- Focused auditor, renderer and checkpoint-evidence suite: 18 tests passed. -- Scoped Ruff check, format check and Git whitespace check passed. - -### Remaining limitations - -- Existing overlapping-tile mAP is valid for relative non-protected ranking, - not independent object-level accuracy. A future benchmark must aggregate or - deduplicate objects before uncertainty claims. -- No source label, frozen dataset, model weight or live runtime was changed. - -## 2026-08-09 - Immutable min-4px derived corpus - -### Improved - -- Added a deterministic derived-corpus builder that preserves parent hashes, - copies imagery, records every removed source row and refuses to turn a - positive tile into an unlabeled negative. It creates no release manifest or - human-review claim. -- Derived `yolo-building-aoi1024-reviewedexp6-minpx4-derived-r1` from the - frozen min-3px corpus. Exactly 1,812 marginal labels were removed; all 252 - tiles and 77,380 labels remain, with zero excluded tiles. -- Corrected the quality-audit console message from `passed` to `completed`, so - a machine-readable `needs_attention` status is no longer contradicted by - human-facing output. - -### Verified on Tower - -- Structural audit: zero missing/invalid labels and zero sub-4-pixel rows. -- Relationship audit: zero exact/near duplicates and 41 possible nesting - pairs, down from 43. -- Geometry audit: 10 plausible extreme-aspect rows, down from 26; tile-edge - rows fell from 5,079 to 4,840 without a blanket edge deletion. -- Cross-tile audit: zero reconstructed train/validation crossings. -- Inspected four full contact-sheet pages covering all 252 tiles and 77,380 - labels plus the focused nine-tile extreme-aspect sheet. Pure backgrounds - remain empty and sparse contexts remain distinct. - -### Decision and limitation - -- The min-4px corpus is preferred for future experimental work, but remains - explicitly training/release-ineligible until real human review and governed - release evidence exist. The active GPU model was not changed. - -## 2026-08-09 - Non-overlapping checkpoint correction - -### Corrected - -- Traced the prior 36-image checkpoint matrix to four AOIs tiled at 512/256. - The same interiors were repeated and nine Arendonk-heide tiles were visually - blank no-data, despite being counted as background observations. -- Added a deterministic non-overlap evaluation-view builder. It selects four - complete 512 px grid tiles per 1024 px AOI, excludes low-variance no-data - with reason codes, creates empty train directories and writes a hashed - `NO_TRAINING.json` marker. -- Added a fail-fast marker check to the operator YOLO training wrapper before - release verification, model loading or CUDA allocation. -- Corrected checkpoint overlap semantics: zero pixel overlap is reported, but - statistical independence is explicitly not established for adjacent tiles. - -### GPU evidence - -- The clean r2 view contains 12 images: eight positive Turnhout/Westerlo tiles - and four real Postel backgrounds. It has 2,551 labels, 2,384 unique interior - objects, 167 edge labels and zero repeated interior objects. -- Active: precision 0.542632, recall 0.435317, mAP50 0.342034, mAP50-95 - 0.141316. Challenger: 0.581715, 0.462300, 0.368364 and 0.155318. -- At confidence 0.15 the active model has zero Postel detections and the - challenger one; at 0.25 both have zero. The threshold-sensitive relative - challenger advantage is confirmed without changing production. - -### Remaining limitations - -- Two adjacent positive AOIs and one real background AOI are not representative - release evidence. Human review, broader independent geography and exact - challenger provenance remain blocking. - -## 2026-08-09 - Training/evaluation membership gate - -### Corrected - -- Compared the non-overlap evaluation sample membership against the exact - active and challenger training summaries. Turnhout and Westerlo are absent - from both train splits; Postel-bos is present in both. -- Reclassified the Postel detection counts as training-seen regression checks, - not independent background validation. No existing metric or checkpoint was - promoted on that evidence. -- Extended the checkpoint evaluator with a strict multi-corpus membership gate. - Governed runs now persist a blocked manifest and stop before PyTorch import, - model loading and GPU inference if any evaluation AOI is training-seen. - -### Reproduced on Tower - -- Active training summary SHA-256: - `49b2a07d2105d08356431757b83eafc1498eaf1fb76965b1efe05b776824942a`. -- Challenger training summary SHA-256: - `7c917e31216d1df2174c0f9c736f88a81f3835aa991971f8fb8665e17ddf5c9c`. -- Evaluation summary SHA-256: - `c17a8c47eaecc2dfb38778ff5a612f9e6c4d67c9e90e31d3a6a66d8857adec4c`. -- The strict run blocked on `postel_bos`, with - `model_loading_attempted=false` and `gpu_inference_attempted=false`. -- Blocked-manifest SHA-256: - `62e8a9377ac87552936f472b0acf55d1d659ebf27f84ba8c4dbcefe7a374e1da`. - -### Remaining limitation - -- Independent real-background AOIs are still required. Literal 100% model - correctness is not demonstrated; the system now refuses to misrepresent the - known overlap as proof. - -## 2026-08-09 - Full ancestral-corpus exposure correction - -### Corrected - -- Reconstructed the retained checkpoint ancestry from exact Ultralytics - `args.yaml` files and model hashes. The active model descends from the - expanded-min4 corpus; the challenger descends from the active model. -- Found that the expanded ancestor used Postel-bos for training and - Turnhout/Westerlo for validation. All three v69 evaluation AOIs were therefore - exposed somewhere in the model family. -- Replaced last-corpus/train-only checking with fail-closed inspection of every - split in every supplied ancestral corpus. Legacy CLI spellings remain safe - aliases to the full-lineage behavior. - -### Verified - -- The Tower gate blocked all three exposed AOIs with zero model-loading and - zero GPU-inference attempts. -- Expanded ancestor summary SHA-256: - `1887e2ba5c719d33675a9ed85db99a274fd66d98d5f6ad44558d673620917201`. -- Blocked-manifest SHA-256: - `f6effd94befd6df8d699bc66fbbea8a860b056cff9996be5f867f858807af65e`. -- Model-lineage receipt SHA-256: - `84d8d7bd95acfb07b188b07ececfc5417fca80c087d7c04442dd2a4da5f43936`; - every retained training `best.pt` matches its named model copy byte-for-byte. -- The production checkpoint and container image remain unchanged. - -### Accuracy boundary - -- The old Turnhout/Westerlo/Postel numbers are regression diagnostics only. - No independent positive or background accuracy evidence currently exists for - this model family; new AOIs must be provisioned without ancestry or spatial - exposure before another ranking is defensible. - -## 2026-08-09 - Fresh V72 regional calibration - -### Delivered - -- Added custom non-protected AOI provisioning with explicit rejection of test - and background-test roles. -- Acquired six new governed orthophoto/reference pairs across all three Belgian - regions and froze an evaluation-only, training-prohibited corpus. -- Added a diagnostic tiler that refuses training-eligible manifests, emits no - training data and excludes generic overlapping edge-cover windows. -- Added a raster-bound spatial lineage audit. All 31 ancestral AOIs resolved; - every V72 AOI passes the 2 km separation floor. -- Added strict pure-background validation: non-empty labels can no longer be - silently counted as pure background. - -### GPU result and decision - -- Corrected view: 24 non-overlapping tiles, 348 labels, six AOIs. -- Active mAP50/mAP50-95: `0.056779`/`0.021750`. -- Challenger mAP50/mAP50-95: `0.044705`/`0.016004`. -- Confidence 0.25 F1: active `0.231527`, challenger `0.235885`. -- The active aggregate F1 peaks at 0.30, but its Flemish subgroup regresses; - threshold, active weights and production image therefore remain unchanged. -- The weak fresh-domain scores are retained as a real blocker, not hidden by - the older exposed Turnhout/Westerlo/Postel diagnostics. - -## 2026-08-21 - Full-workbench responsive GUI pass - -### Delivered - -- Audited the live guest workbench at 1440 x 900 and 390 x 844. The desktop - evidence drawer truncated metric labels; the phone layout placed the model - picker before the map and made later navigation destinations unreachable. -- Increased the usable evidence-drawer range and switched compact evidence - groups to a two-column container-responsive layout with wrapping labels. -- Reworked phones into a map-first flow: compact search and period controls, - map toolbar with an icon-only clear action, model selection after the map, - and a persistent horizontally scrollable bottom navigation rail. -- Kept dual-display launching desktop-only and made the compact results drawer - viewport-fixed above the phone navigation. -- Reclaimed the unused operator-only column in the guest source catalog and - restored the intended dark, high-contrast surfaces for the PyTorch pipeline - and live project-atlas illustrations. - -### Verification - -- Frontend TypeScript check passed. -- All 54 frontend unit tests passed. -- Production frontend build passed. - -### Remaining limitation - -- Browser emulation covers responsive layout and interaction; certification on - physical touch hardware and with a screen reader remains a separate human QA - activity. - -## 2026-08-23 - Sol Ultra product-, runtime- en betrouwbaarheidsronde - -### Delivered - -- Split the public landing foundation from the lazy workbench and MapLibre - styles. The initial production CSS payload dropped from roughly 219 kB to - 38.38 kB while the authenticated workbench keeps its complete styling. -- Extended the reproducible browser audit to cover the landing and workbench at - 390 x 844, 1366 x 768 and 2560 x 1080, including mobile navigation, - keyboard tabs, loading state, advanced map flow and every guest workspace. -- Corrected the smartphone shell hierarchy: topbar, guest banner and page - heading no longer overlap, and the live Selecteer/Bronnen/Verwerk/Controleer - rail now sits below the map actions instead of behind the fixed navigation. -- Kept full workspace titles for headings and accessible names while shortening - the two mobile navigation labels to `AI-beeld` and `Export`; the browser gate - now rejects any visible sidebar label whose text box is clipped. -- Made map-analysis failures outrank empty states and added an explicit retry; - new selections clear stale coverage immediately. -- Replaced synchronous browser inference with governed async detection and - segmentation queues, project-bound job polling and persisted-run - reconciliation. Detection has NVIDIA preflight; segmentation now fails - closed under the same server CUDA contract. Zero-result runs are communicated - without claiming that the AOI is object-free. -- Bound guest detection, segmentation and export reads/writes to the signed - demo project at the resource level. Matching query parameters can no longer - authorize another project's run, dataset, result or download. -- Closed stale-response races in temporal comparison and the local GeoAI - assistant, plus detection/segmentation run, result and QA flows across project - switches. Previously visited workspaces no longer reload together after every - navigation change. -- Added keyboard-complete pipeline tabs and React-driven model-dialog state, - initial focus and trigger-focus restoration. Landing scrolling now respects - `prefers-reduced-motion`. -- Hardened outbound acquisition redirects before the redirected request is - opened, including origin/port and embedded-credential rejection, and fixed - bounded pagination for segmentation result lists. -- Fixed segmentation readiness and section status: configured production - models now require a real tile manifest before queueing, fixture mode is - visibly test-only, and queued/running NVIDIA work has an explicit live state. -- Localised known model registrations and availability states in the Dutch UI; - raw English backend placeholder copy no longer leaks into the primary model - selector or readiness guidance. - -### Verification - -- Frontend TypeScript check and production build passed. -- Complete frontend suite: 36 files / 151 tests passed. -- Relevant backend release set: 121 tests passed, covering async analysis jobs, - atomic claims, guest/resource isolation, redirect policy, segmentation - pagination, NVIDIA runtime enforcement and current AI-lab contracts. -- Ruff passed over every changed backend Python module and test. -- Browser evidence passed across three landing and three authenticated - workbench viewports with zero horizontal overflow, console errors or failed - API requests in `.codex-artifacts/sol-ultra-final-l/manifest.json`; focused - AI-workspace and segmentation screenshots are stored beside it. -- Production build passed. Initial landing CSS remains 38.38 kB (8.22 kB - gzip); the lazy workbench JS is 479.76 kB (129.25 kB gzip) and MapLibre stays - isolated in its own lazy chunk. - -### Boundaries - -- This pass improves runtime correctness and presentation; it does not invent a - new accuracy claim or promote a model checkpoint. Existing governed model - evidence and regional release gates remain authoritative. -- Physical touch-device and screen-reader certification remain human QA. No - commit or deployment was performed because the active execution brief - explicitly forbids committing unless requested. -# 2026-08-23 — Active YOLO runtime provenance remediation - -- Recovered the original Sprint 174 model run from persistent Tower storage. -- Confirmed that the active model and retained `best.pt` are byte-identical at - SHA-256 `a9088b8491dfae36694b53e9e9406cb4e3511d334a5712fa34f75078a47759c1`. -- Verified the surviving base-model, training-argument, results, training-summary, - dataset-YAML and dataset-summary checksums before allowing registration. -- Added a dry-run-first, atomic and idempotent runtime provenance migration that - binds exact model bytes to a governed Postgres source snapshot. -- Kept the historical evidence boundary explicit: this runtime receipt does not - invent human review, a historical training commit/container, protected-test - independence, national validity or a new promotion decision. - -## 2026-08-30 - Accuracy-status en fail-closed modelactivatie - -- Herhaalde de lokale Phase-3-scan deterministisch als - `p3-eb67185e61107cc7`: 1013 bestanden onderzocht, nul overgeslagen en drie - gedeclareerde externe productiegrenzen, met content-hash - `f4ea193d2bdd96a5b391cf7d9d93685cc58e98742c40e4513bcbc434907e720a`. -- Corrigeerde de statusgrens naar `local_complete_production_inventory_pending`; - Tower-volumes en productie-PostGIS zijn nog niet als totale productie- - inventaris gereconcilieerd. -- Retireerde de stale tracked `geointel/`-mirror met immutable Git-recovery en - verplaatste 207 niet-getrackte runtimebestanden intact naar een genegeerde - recoverymap; productiegegevens en modelgewichten zijn niet verwijderd. -- Legde onafhankelijke AI-visuele triage vast met `human_reviewer=false`. - Referentiegeometrie, dense/nested labels, tile-edge-regels en regionale - hard-negative dekking blokkeren corpusacceptatie, training en promotie. -- Versterkte de activatiegrens: alleen een exact overeenkomende candidate key, - model-SHA-256 en benchmarkmanifest-SHA-256 in een geslaagd governed Phase-4/5 - release-gaterapport kunnen activatie autoriseren. Een legacy diagnostisch - promotierapport is onvoldoende. -- De taakgeschikte officiële bron blijft doorslaggevend voor productresultaten. - Deze remediatie levert geen menselijke review, nationale validatie, - modelpromotie of 100%-accuratieclaim. - -## 2026-08-30 - Fail-closed release-, backup- en rollbackpad - -- Retireerde het aparte, niet-gegate Unraid-workflowpad; productie-deploy hangt - nu uitsluitend af van quality-, dependency- en AI-containergates. -- Bond controller, OCI-label, SBOM, Trivy-evidence en draaiende container aan - het exacte full-SHA en lokale Docker image-ID. -- Maakte storage/models byte-compleet, symlink-veilig en checksum-geverifieerd; - latere snapshots hardlinken alleen gelijke backup-naar-backup bytes. -- Bewees databaseherstel vóór productiecutover in een tijdelijke database, - behield de pre-restore database en bond same-revision rollback aan het - image-ID uit de specifieke pre-deploybackup. -- Maakte cleanup-quarantine en herstel interruption-safe en no-clobber, en - behield HTTPS-forwarding uitsluitend voor interne vertrouwde proxies. +# Execution log + +This public log records release-relevant repository work only. Machine-specific +paths, production database state, deployment addresses, model outputs and +generated evidence remain in controlled local storage. + +## 2026-08-31 — public-release readiness + +- Confirmed Apache-2.0 as the repository license. +- Integrated the repository-hygiene branch into the public-release candidate. +- Classified older remote branches as superseded rather than blindly merging + divergent operational history. +- Completed a standard source security scan of the release candidate. +- Fixed the guest-project name-collision boundary, protected the reserved demo + project and added guest login/compute budgets. +- Required database-backed production provenance for HTTP model-load preflight. +- Added raster decoded-size limits and bounded preview reads. +- Removed tracked production-derived accuracy evidence and internal review + records from the public source tree. +- Replaced internal history-heavy documentation with user-facing public docs. +- Pinned production container base images by digest and reduced public health + responses to coarse status. +- Added Linux-resolved, SHA-256-locked AI/CUDA and build-tool dependency sets. +- Passed the complete release gate: repository hygiene, dependency policy, + documentation and API contracts, 1,707 backend tests, migrations, 170 + frontend tests, type checking and the production frontend build. +- Clean-root publication is the remaining release operation. + +## Public operator-profile metric provenance + +The built-in example profiles expose these recorded benchmark values so the UI +never presents an untraceable accuracy figure: + +- small-building balanced review: precision `0.5898197518`, recall + `0.5769921004`, F1 `0.5824578632`; +- expanded balanced review: precision `0.6470590036`, recall `0.4699913837`, + F1 `0.5432865391`; +- conservative review: precision `0.840006`, recall `0.202135`, F1 + `0.32086574003576274`. + +These measurements are examples bound to their recorded profile evidence; they +are not general accuracy claims for other models, locations or datasets. diff --git a/docs/TODO.md b/docs/TODO.md index 65103d48..e052bdf1 100644 --- a/docs/TODO.md +++ b/docs/TODO.md @@ -1,1287 +1,31 @@ -# GeoIntel TODO +# Public roadmap -## Publieke repository (2026-08-31) +## Before the first public release -- [x] Integreer de actuele release-hygiënetak vanaf `origin/main` zonder de - private Tower-handoff of ongerelateerde DockDeck/Stitch-geschiedenis. -- [x] Verwijder lokale databases, Codex-input, browserlogs en lokale MCP-config - uit de getrackte publicatieboom en borg dit in de releasegate. -- [x] Maak de verpakte authenticatie-, HTTPS-, gast- en checkpointdefaults - fail-closed. -- [x] Voeg Apache-2.0 als rootlicentie toe, inclusief expliciete - projectattributie in de README. -- [x] Kies na eigenaarstoestemming voor een nieuwe schone rootgeschiedenis op - dezelfde Gitea-repository, met een lokale herstelbundle van de oude refs. -- [ ] Publiceer de schone rootcommit als enige remote `main` en verwijder alle - overige remote branches en tags die de oude historie bereikbaar houden. +- [ ] Pass the complete backend, frontend, migration and container release gate. +- [ ] Verify the clean-root publication candidate and local all-ref recovery + bundle. +- [ ] Confirm redistribution/provenance for the retained portfolio screenshots. +- [ ] Configure a monitored private security-reporting address or Gitea security + channel in `SECURITY.md`. +- [ ] Finish a fully hashed, platform-specific lock for optional CUDA/Ultralytics + packages; base container images are already digest-pinned. -## Accuracy-remediatie (2026-08-30) +## Product work -- [x] Herhaal de lokale Phase-3-scan deterministisch: scan - `p3-eb67185e61107cc7` onderzocht 1013 bestanden, sloeg er nul over en - registreerde drie externe productiegrenzen expliciet; content-hash - `f4ea193d2bdd96a5b391cf7d9d93685cc58e98742c40e4513bcbc434907e720a`. -- [ ] Inventariseer de drie gedeclareerde Tower-/productiegrenzen gecontroleerd - en reconcileer servervolumes en productie-PostGIS; de lokale scan is geen - totale productie-inventaris. -- [x] Leg de onafhankelijke AI-visuele hercontrole vast met - `human_reviewer=false`; corpusacceptatie, training en promotie blijven - geblokkeerd. -- [x] Laat modelactivatie fail-closed vereisen dat candidate key, model-SHA-256 - en benchmarkmanifest-SHA-256 exact overeenkomen met een geslaagd governed - Phase-4/5 release-gaterapport. -- [ ] Herstel de vastgestelde labelsemantiek, dense/nested conflicten, - tile-edge-regels en regionale hard-negative dekking; verkrijg daarna - representatieve menselijke acceptatie vóór een volgende governed training. +- [ ] Expand end-to-end documentation for adding a governed data provider. +- [ ] Add reusable queue/storage quotas for public demo workloads. +- [ ] Publish synthetic benchmark examples that contain no runtime or location + evidence. +- [ ] Continue accessibility, performance and responsive-map verification. -## CI-onderhoud (2026-08-29) +## Implemented capabilities -- [x] Vervang de Gitea-incompatibele TruffleHog-actionwrapper. -- [x] Pin de gepatchte Nano ID-transitive in de frontendlock. -- [x] Maak de Syft-bron expliciet als lokaal Docker-image. -- [ ] Bevestig de drie releasejobs op Gitea. +- [x] Add full threshold calibration comparison UX +- [x] Add guided in-app detection calibration runner +- [x] Link guided calibration rows to the QA evidence map +- [x] Add guided calibration summary export from the Detection Lab +- [x] Allow the evidence bundle script to consume Detection Lab calibration summary exports -## Tweeschermwerkruimte (2026-08-21) - -- [x] Voeg een gesynchroniseerde analyseconsole voor een tweede beeldscherm toe. -- [x] Verplaats dezelfde React-resultaatstate zonder dubbele API-calls of runs. -- [x] Onthoud vensterpositie en herstel veilig naar de éénschermlade. -- [x] Voorzie popupfoutmelding, toetsenbordlabels en operator-/demopariteit. - -## V74 authority-first gebouwresultaten (2026-08-10) - -- [x] Voer een V72-foutanalyse, hard-negative proposal-filter en rehearsal - training uit; wijs alle regresserende kandidaten af en behoud het actieve - checkpoint. -- [x] Laad na gebouwdetectie automatisch het bewaarde GRB-QA-bewijs en splits - de kaartuitvoer in GRB-bevestigd, AI-only en door AI gemist. -- [ ] Laat een onafhankelijke menselijke reviewer de bevroren contact sheets - en labels ondertekenen voordat een kandidaat ooit promoveerbaar wordt. - -## PyTorch-modelprogramma - -Uitvoeringsbord: `docs/PYTORCH_TRAINING_ROADMAP_BELGIUM.md`. - -- [x] Scheid trainbare beeldtaken van deterministische GIS-analyses. -- [x] Generaliseer de single-class tile-export op klasse, referentiebron en referentielaag. -- [x] Laat productietraining fail-closed stoppen wanneer vereiste CUDA ontbreekt. -- [ ] Materialiseer geografisch gescheiden GRB/PICC/URBIS-gebouwcorpora met temporeel passende orthofoto's. - - [x] Verwerp de drie V64 Vlaamse kalibratiekandidaten fail-closed na gereproduceerde ruwe en SAM2-contact-sheets; verscherp de geometrische SAM2-gates. - - [x] Scheid GRB-hoofdgebouwen bron-native van bijgebouwen en bewijs dat ook de hoofdgebouw/SAM-dropvariant de visuele gate nog niet haalt. - - [ ] Lever onafhankelijke Vlaamse kalibratie-AOI's met aantoonbaar beeldzichtbare daklabels vóór een volgende training. - - [x] Provision en audit onafhankelijke V66-laagbouwkandidaten in Zutendaal, Zoersel en Landen; verwerp alle automatische labelvarianten na visuele QA. - - [ ] Laat beeldzichtbare Vlaamse dakboxen onafhankelijk annoteren/reviewen en freeze hun checksums. -- [ ] Train en evalueer een Belgische gebouwchallenger onafhankelijk; promoveer alleen zonder achtergrondregressie. -- [ ] Houd zonnepanelen en segmentatie `not_configured` tot gereviewde taaklabels en hold-outs bestaan. - -## Accuracy-programma — fase 4 - -Normatieve protocollen: `docs/accuracy-program/10-evaluation-protocol.md`, -`11-baseline-benchmark.md` en `12-release-gates.md`. - -- [x] Inventariseer 15 geïmplementeerde capabilities in zeven afzonderlijke - evaluatorfamilies zonder deterministische GIS als geleerd model voor te stellen. -- [x] Implementeer taakgebonden metrics, raw prediction-retentie, - betrouwbaarheidsintervallen, subgroepsupport en een machineleesbare - failure-taxonomie. -- [x] Genereer zes code-owned splitrollen (`train`, `val`, `calibration`, - `test`, `background-test`, sealed `challenge`) met exacte, near-duplicate-, - identiteit-, tijd- en 2-km-leakagegates. -- [x] Bescherm test/background-test/challenge tegen training, thresholdselectie, - modelselectie, gewijzigde bytes en onbewezen provenance. -- [x] Voer de bestaande `QaService` als referentienulmeting uit en leg alle - Phase-4-evidence content-addressed en immutable vast. -- [x] Maak statusboekhouding zelfreferentievrij: alleen de actieve-modelprojectie - beïnvloedt de benchmarkfingerprint; productgates vereisen governed evidence. -- [ ] Los de bevestigde Phase-3-leakagebevinding op en freeze nieuwe onafhankelijke - product-splits zonder cross-splitparen onder 2 km. -- [ ] Lever één governed zeven-taken productbaseline met actuele modelbytes, - CUDA/GPU-receipt, authorityportfolio en in-process herberekende raw metrics. -- [ ] Lever checksumgebonden menselijke review, fysieke protected vault en - representatieve support voor alle 13 kritieke subgroepdimensies. -- [ ] Markeer fase 4 pas `done` en fase 5 pas `ready` wanneer alle productgates - in dezelfde workflow `pass` zijn; huidige status is local `pass`, product `fail`. - -## Actieve post-RC datadekkingsfase - -Professionaliseringspass (2026-07-27): - -- [x] Voeg een expliciete gastknop toe aan de toegangspoort en open daarmee - een korte, projectgebonden demowerkruimte. -- [x] Geef de demo dezelfde kaart-, bron-, assistent-, model-, analyse-, QA- en - downloadfuncties als de operator, maar blokkeer beheer, instellingen, - uploads, reviews en toegang tot andere projecten ook server-side. -- [x] Herwerk de landingspagina, aanmeldhiërarchie, mobiele navigatie en - workbenchcontext tot één rustigere en professionelere productervaring. -- [ ] Consolideer na visuele regressiesnapshots de vier historische - workbench-stijllagen (`app`, `premium`, `atlas-workbench`, - `atlas-premium-v2`) tot een kleiner gelaagd stijlsysteem. -- [ ] Ontwerp alleen bij een toekomstige publieke multi-projectinstallatie een - volwaardig account-, autorisatie- en tenantisolatiemodel; gastmodus is daar - uitdrukkelijk geen vervanging voor. - -- [x] Voeg een interactieve, data-gedreven projectatlas toe aan de statuswerkruimte met toegankelijke navigatie, echte readiness-toestanden en reduced-motion ondersteuning. -- [x] Geef alle primaire werkruimtes een eigen geanimeerde signaalillustratie, verbeter lege toestanden en verwijder de dubbele kaartfoutmelding bij sessieverval. - -- [x] Implementeer de aangeleverde Stitch-landingspagina als echte React- - toegangspoort en bescherm de workbench met één veilig geconfigureerd - operatoraccount, sessieverval, uitloggen en zichtbare foutstatussen. Dit is - geen multi-user- of tenantbeheersysteem. - -`docs/POST_RC_DATA_COVERAGE_ROADMAP_BELGIUM_NORTH_SEA.md` was het autonome -uitvoeringsbord na `v1.0.0-rc.1` en is nu afgesloten voor `v1.0.0`. Dit is geen -RC-12. De definitieve release blijft immutable bewijs; verdere databronnen -zijn post-V1 uitbreidingen. - -- [x] P0: bestaande NGI/RBINS-lagen als kaartthema en selectieanalyse ontsluiten. -- [x] P0: readiness baseren op bruikbare analysethema's, niet alleen datasetaantal. -- [x] P1: nationale Statbel-populatieflow veilig operationaliseren. -- [x] P2: bounded SPW PICC voor Waalse gebouwen, wegen en hydrographie. -- [x] P3: bounded UrbIS voor Brusselse gebouwen en percelen. -- [x] P4: maritieme thema's harden en bathymetrie fail-closed onderzoeken. -- [x] P5: zonefederatie, UX, golden journeys en immutable deployment. - -## Actief RC-programma: Belgie en de Belgische Noordzee - -`docs/RC_ROADMAP_BELGIUM_NORTH_SEA.md` is vanaf 2026-07-17 het enige actieve -releasebord. Mol en de Kempen blijven regressiereferenties, maar de -productscope is nu heel Belgie plus de juridisch correct gelabelde Belgische -maritieme zones. - -- [x] RC-0: Belgische en maritieme scopefreeze vastleggen. -- [x] RC-0: autonome roadmap zonder afzonderlijke RC-12 vastleggen. -- [x] RC-0: deterministisch release-evidence manifest implementeren en draaien. -- [x] RC-1: actuele productiebackup, verificatie en geisoleerde restore bewijzen. -- [x] RC-2: liveness/readiness/capabilities fail-closed en waarheidsgetrouw maken. -- [x] RC-2: verweesde jobs en analysis runs na een procesherstart verzoenen. -- [x] RC-3: expliciete rasterkeuze en temporeel compatibele detectie-QA afdwingen. -- [x] RC-4: aparte nationale bron- en dekkingscontracten implementeren zonder - het vaste Sprint 7-providerregister te wijzigen. -- [x] RC-4: expliciete NGI/RBINS-operator en selectiegebonden coverage-API - implementeren en lokaal valideren. -- [x] RC-4: Tower fetch-only, canonieke persistence en live browseracceptatie - bewijzen. -- [x] RC-4: nationale basisdekking en expliciete coverage-contracten voor - Wallonie, Brussel en de Belgische Noordzee via golden areas operationaliseren. -- [x] RC-5: secrets/configuratie/uploadlimieten/immutable deploy en rollback - bewijzen. -- [x] RC-6: volledige CI, dependency-audit, containerscan en SBOM toevoegen. -- [x] RC-7: kritieke API-routes concrete responsemodellen geven. -- [x] RC-8: echte frontend- en browser-E2E-releaseflows toevoegen. -- [x] RC-9: loading, toegankelijkheid, widescreen/mobile en performance afronden. -- [x] RC-10: dataretentie, diskdruk en veilige cleanup operationaliseren. -- [x] RC-11: fresh install, upgrade, rollback, releasepakket, tag en live - acceptatie afronden. - -Een aparte RC-12/soakfase wordt niet uitgevoerd. De relevante fresh-install-, -upgrade-, rollback- en runtimebewijzen zijn verplicht opgenomen in RC-5 en -RC-11. - -## Actuele V1-productstatus - -Dit is het enige actuele afwerkingsbord. De lange sprint- en -voorbereidingslijsten verderop blijven bewaard als historisch bewijs, maar zijn -geen open productroadmap meer. - -- [x] Open onvoorwaardelijk de nationale `Belgium and North Sea Workbench` - wanneer die bestaat en start de kaart op Belgische schaal. Mol en de Kempen - blijven alleen snel selecteerbare regressiegebieden. -- [x] Maak UrbIS Land Cover begrensd operationeel voor Brussel: alle Blocks als - landbedekking, FO/GB als bos en park en WB als permanent water, met echte - PostGIS-oppervlaktemetrics en broncodes. -- [x] Implementeer begrensde WALOUS 2018/2020/2023 rasteracquisitie in EPSG:3812 - met officiële klassen, een expliciete 2018-klassecrosswalk, vergelijkbaarheidscontract, - pixelbudget, automatische tijdreeksmaterialisatie en evolutiemetrics. De vaste - officiële 2018-GeoTIFF-distributie is live checksum-gevalideerd; bronwaarde `0` - wordt expliciet als achtergrond/nodata behandeld. -- [x] Rond de live provisioning van het officiële SPW MNT 2021-2022 op 1 m in - de operatorcache af en bied begrensde terreinacquisitie/analyse in DNG aan. - Het bronraster en de checksum-sidecar zijn gevalideerd en het downloadarchief - is na veilige extractie verwijderd. De 0,5 m-distributie blijft - buiten V1 omdat zij geen noodzakelijke analysecapaciteit toevoegt tegenover de - gevalideerde 1 m-bron en officieel als circa 198 GB download wordt aangeboden, - exclusief extra werkruimte tijdens extractie. -- [x] Implementeer de actuele Waalse overstromingsgevaarkaart als afzonderlijk - scenario-/juridisch contract; gebruik WMS alleen als context tenzij - analytische pixels of vectorgeometrie officieel beschikbaar zijn. -- [ ] Bouw een Belgische AI-validatiematrix met gelabelde golden AOIs in elk - gewest en aan de kust. Tot die matrix slaagt blijft de huidige YOLO-status - expliciet lokaal gevalideerd en controleplichtig. -- [x] Kies een begrijpbaar datathema, teken een rechthoek of gebruik het - volledige werkgebied en analyseer alle relevante thema's uit PostGIS. - Een getekende selectie mag ontbrekende operationele bronproducten begrensd - en met maximaal drie gelijktijdige aanvragen materialiseren; niet-toepasselijke - of niet-operationele regionale thema's worden niet als ontbrekende meting - gepresenteerd. -- [x] Gebruik voor getekende en handmatig ingevoerde rechthoeken overal - `bbox ∩ Area`; een bbox rond het volledige werkgebied resolveert naar de - exacte persistente Area-geometrie en activeert pas dan de full-Area fast path. -- [x] Toon betekenisvolle eenheden en metrieklabels voor oppervlakte, lengte, - inwoners, hoogte, scenario's en stationsmetingen; objectaantallen zijn - ondersteunend. -- [x] Vergelijk beschikbare historische meetmomenten met een volledige - tijdreeks, absolute wijziging, procentuele wijziging en bronbeperking. -- [x] Download vectorresultaten als GeoJSON, rasteranalyses als JSON en - historische vergelijkingen als JSON; kopieren blijft voor alle drie mogelijk. -- [x] Ga vanuit een afgeronde analyse rechtstreeks naar de lokale - brongebonden Ollama-assistent of naar Downloads en keer terug zonder het - zichtbare kaartresultaat of de evolutievergelijking te verliezen. -- [x] Herbereken en bewaar het actieve vector-, raster- of evolutieresultaat - server-side voordat Downloads wordt geopend, met traceerbare selectie- en - bronmetadata. -- [x] Haal de canonieke regionale werkruimte exact op naam op zodat groei van - operator- en benchmarkprojecten de standaard kaartcontext niet kan verdringen. -- [x] Gebruik de operationele lokale YOLO/PyTorch-keten alleen met persisted - detecties, GRB-QA en expliciete controlewaarschuwingen. -- [x] Toon in de beeldanalyse alleen operationele luchtbeeldrasters en geen - hoogte-, overstromings- of thematische beleidsrasters. -- [x] Draai de volledige applicatie in de beheersbare Unraid-container op poort - 1202 met PostGIS, backend, frontend, Ollama-koppeling en modelconfiguratie. -- [x] Archiveer allowlisted benchmark-, kalibratie- en rooktestwerkruimtes - om de actieve projectlijst beheersbaar te houden, zonder gegevens of - resultaten te verwijderen. -- [x] Verberg technische identifiers, modeldetails en interne statussen achter - expliciete technische details en gebruik uniforme Nederlandse taaktaal in - kaart-, kwaliteits-, detectie- en segmentatiewerkstromen. -- [x] Begrens de grootste frontendverantwoordelijkheden met afzonderlijke - overzichts-, modelbeheer- en kaarthelpermodules zonder gedrag te wijzigen. -- [x] Maak de vijf bestaande officiële beleidsrasters veilig op aanvraag - beschikbaar voor elke begrensde selectie in Vlaanderen, met Dataset-cache, - semantische metrics en zonder 1.425 vooraf geladen rasters. -- [x] Maak de volledige selectieanalyse in Vlaanderen operationeel voor NGI, - Statbel, GRB, beleidsrasters, DHMV, overstromingsgevaar, BWK, DOV en VHA: - één rechthoek materialiseert ontbrekende officiële bronproducten, leest - persistente vector/rastergegevens uit en rapporteert inhoudelijke eenheden. -- [x] Vervang de gegroeide dashboardpresentatie door de Stitch-gestuurde Atlas - Workbench met een compacte navigatierail, vaste contextbalk, taakgerichte - schermen en gevalideerde desktop-, ultrawide- en mobiele layouts. - -Post-V1 afwerkingspass (2026-07-19): - -- [x] Lokale YOLO-seg- en SAM-segmentatie via de ultralytics-interface: echte - adapters, dynamisch modelregister, tegelmanifest-inferentie, georeferentie - van maskpolygonen, dedupe, geodetische oppervlakte en persistentie. Blijft - fail-closed zonder lokale modelgewichten (`YOLO_SEG_*`/`SAM_*` env). -- [x] Begrensde MDK-bathymetrie-acquisitie (WCS GetCoverage) achter de - bestaande strict-TLS readiness-probe: expliciete opt-in, geadverteerd - coverage-id verplicht, bbox-limiet, GeoTIFF-validatie, LAT-provenance. - Endpoint: `POST /datasets/bathymetry/mdk/acquire`. -- [x] UrbIS-wegassen (`urbisvector:StreetAxes`, live gevalideerd tegen de - UrbIS WFS-capabilities) als begrensd Brussels roads-product met - lengte-metrics; de WFS adverteert geen hydrografielaag, dus Brussels - oppervlaktewater blijft eerlijk `not_configured`. - -Bewuste, niet-blokkerende grenzen: - -- De begrensde SPW-rasterflow maakt Waalse waterbodemhoogte in mDNG - analyseerbaar. Watervolume blijft niet beschikbaar zolang geen compatibele - wateroppervlaktehoogte, tijdskoppeling, datumtransformatie en - onzekerheidsmodel bestaan. Dit is geospatiale correctheid, geen onafgewerkte - UI. -- Gebouwdetectie is operationeel maar blijft een controlekandidaat; verdere - training gebeurt pas na nieuwe, onafhankelijke reviewdata. -- Een echt SAM/YOLO-seg-model en een trainingsstudio blijven post-V1. De - persistente segmentatie- en QA-fundering blijft beschikbaar voor later. - -## Map-first Mol explorer - -- [x] Make the Mol geographic explorer the default workflow. -- [x] Add drag rectangle selection with automatic persisted theme queries. -- [x] Separate exact bbox intersection totals from the bounded map preview. -- [x] Add official Mol GRB roads, water and parcels provisioning support. -- [x] Select, validate and provision official Statbel 2021-2025 population/statistical-sector snapshots for Mol. -- [x] Select, validate and provision official Departement Omgeving 2013-2025 forest snapshots from the 10 m land-use map. -- [x] Define and provision the official 28-municipality Vervoerregio Kempen as the explicit operational regional scope. -- [x] Partition and provision the complete current GRB building theme for all 28 Kempen transport-region municipalities, with resumable source artifacts and one queryable regional PostGIS dataset. -- [x] Provision the remaining regional GRB context themes in bounded partitions: roads, water and parcels. -- [x] Make the complete regional workspace the automatic data context and use municipality/full-region Areas as one spatial filter instead of requiring a region dropdown. -- [x] Reduce end-user noise by moving technical projects, source metadata, QA evidence, provider internals and model diagnostics behind explicit advanced disclosures. -- [x] Default Detection Lab to the configured local YOLO asset and present measured model quality and control requirements honestly. -- [x] Extend official population and land-use time series from Mol to the approved 28-municipality regional scope. -- [x] Make Evolution automatically open an available regional series and distinguish historical themes from current-only snapshots. -- [x] Replace object-count-only map results with semantic PostGIS metrics for hectares, kilometres and inhabitants while retaining counts as supporting evidence. -- [x] Show complete comparable observation timelines and all compatible semantic metric deltas for exact persisted Areas. -- [x] Expand the modern 2013-2025 land-use operator with water, built-function and transport surfaces from the retained official raster. -- [x] Add a source inventory that separates loaded data from audited official follow-up sources. -- [x] Add a local Ollama question window grounded in persisted GeoIntel metrics and installed server models. -- [x] Add a governed bounded SPW bed-elevation source with explicit mDNG and - survey-period semantics; never infer depth or volume from 2D water geometry. -- [ ] Add a compatible water-surface, time, vertical-datum and uncertainty - contract before exposing water volume. -- [x] Integrate governed Waterinfo/VMM annual station series without presenting point measurements as area-wide water volume. -- [x] Add bounded historical orthophoto acquisition for official 1971-2025 products with a map overlay and no current-GRB QA on old imagery. -- [x] Add BWK/Natura 2000 through an explicit provider/operator contract. -- [x] Expand BWK/Natura 2000 state 2025 from Mol to all 28 approved Kempen municipalities with partitioned source evidence. -- [x] Add a regional VMM flood-hazard operator that provisions official scenario rasters per municipality Area through the canonical API. -- [x] Add annual agricultural-use parcels through an explicit provider/operator contract. -- [x] Extend the official 1778/1873/1969 historical buildings, water and roads series from Mol to the approved regional scope with partitioned source audits. -- [x] Connect a drawn rectangle to bounded official orthophoto acquisition, local configured-YOLO detection and persisted GRB QA. -- [x] Add governed official space-occupation, open-space, population-density, accessibility and service-level rasters with semantic map metrics. -- [x] Add the DOV digital soil map for Mol with exact clipping, source attributes and historical survey limitations. -- [x] Execute the governed thematic-raster operator for every persisted Kempen municipality after the Mol live gate passes. -- [x] Persist one bounded whole-region snapshot per thematic raster so drawn selections can cross municipality boundaries without changing source semantics. -- [x] Generalize the DOV soil-map operator to all 28 approved Kempen municipality partitions with one regional snapshot manifest. -- [x] Add a resumable regional DHMV DTM/DSM operator for all 28 approved Kempen municipality Areas. -- [x] Execute and audit the complete 336-product VMM and 56-product DHMV regional runtime matrices. -- [x] Present municipal DHMV/VMM partitions as logical regional layers and analyse cross-boundary rectangles without a municipality prerequisite. -- [x] Add a read-only source freshness/version audit with explicit publication policies, local integrity checks, operator CLI and compact Status workspace surface. -- [x] Add explicit bounded GRB/orthophoto catalogue release probes using official capabilities and ISO metadata; keep every acquisition separate and operator-controlled. -- [x] Add a governed regional GRB plan -> stage -> checksum-confirmed apply workflow that preserves every previous snapshot. -- [x] Add a fail-closed ALZ publication probe that distinguishes provisional v1/v2 snapshots from the definitive v3 historical edition and never downloads an archive. -- [x] Add a fail-closed Statbel DCAT publication probe that distinguishes population year, sector-geometry year and the 2025 REDEGEO transition without downloading distributions. -- [x] Add a fail-closed Statbel population import preflight with archive/schema/CRS/join/total/baseline checks, retained checksums and explicit ZZZZ accounting before any new Dataset import. -- [x] Add an explicit Statbel population plan -> stage -> named review -> checksum-confirmed apply workflow that preserves every prior annual snapshot. -- [x] Add an explicit definitive ALZ plan -> stage -> named review -> checksum-confirmed apply workflow while keeping v1/v2 campaign snapshots non-importable. -- [ ] Extend catalogue probes only to additional sources that publish a stable official edition contract; do not add background polling or infer releases from HTTP dates alone. - -## Governed source expansion backlog - -Implement these in order. Every source must use an explicit operator/provider -contract, retain raw checksummed evidence, persist through DatasetService and -pass live Mol validation before regional expansion. - -### P1 - Biologische Waarderingskaart / Natura 2000 - -- [x] Confirm the official downloadable service/layer/version and licence for the 2025 state. -- [x] Define stable habitat/biotope/value fields and keep BWK valuation separate from Natura 2000 habitat classification. -- [x] Clip in EPSG:31370 to Mol, transform to EPSG:4326 and persist valid polygonal `vector_features` with source feature ids. -- [x] Add hectare metrics per governed class plus unknown/unmapped-class diagnostics; do not invent an annual trend from one state. -- [x] Add source manifest, unit tests, live row/count/geometry audit and map/source-inventory presentation. - -### P2 - Annual agricultural-use parcels - -- [x] Inventory official annual editions and document schema/code-list changes before selecting a comparable year range. -- [x] Retain annual source files and crop code lists; normalize only fields whose meaning is stable across editions. -- [x] Persist separate annual Datasets with hectares by crop/use class and an explicit unstable-parcel-identity limitation. -- [x] Compare area/category totals over time; do not claim parcel lineage where identifiers or boundaries changed. -- [x] Validate Mol first, then partition all 28 Kempen municipalities with completeness/checksum manifests. - -### P3 - Buildings and Addresses Register - -- [x] Define a governed snapshot operator and relation mapping between building unit, building object, address and GRB geometry. -- [x] Keep register lifecycle/status semantics separate from GRB footprint geometry and document match confidence/unmatched rows. -- [x] Add current building-status/address metrics without exposing personal data or treating addresses as households/population. -- [x] Add Mol reconciliation tests and a live mismatch report before regional import. - -### P4 - Digitaal Hoogtemodel Vlaanderen - -- [x] Select official DTM/DSM product, service and native resolution; retain acquisition date and vertical reference. -- [x] Add bounded raster acquisition/clip storage with nodata, CRS, resolution and checksum validation. -- [x] Implement governed elevation, relief and slope statistics in metres/degrees; keep drainage interpretation explicitly derived. -- [x] Do not label terrain/surface height as water depth and do not enable volume from DHMV alone. - -### P5 - Water depth / bathymetry - -- [x] Audit authoritative sources: no public municipality-wide inland bathymetry for Mol was identified; keep permanent waterbody volume unavailable. -- [x] Integrate the separate public VMM fluvial/pluvial flood-hazard depth scenarios without presenting them as bathymetry or current water state. -- [x] Persist scenario identity, source centimetres, normalized metres, WCS checksums, exact Area clipping and positive-depth coverage. -- [x] Expose mapped inundation area, depth statistics and a clearly named maximum-depth area integral with a prohibition on calling it concurrent volume. -- [x] Extend the VMM scenario workflow to the approved regional scope using 28 municipality partitions instead of one unsafe monolithic raster. -- [ ] Define waterbody linkage, surface elevation, bottom elevation and uncertainty propagation before adding any volume metric. -- [ ] Validate coverage gaps and prohibit extrapolation outside measured/profiled waterbodies. -- [ ] Add independent GIS review and golden-volume fixtures before exposing the result to users or Ollama. - -This file now starts with the current implementation status. Older preparation/backlog sections are preserved below as historical planning context and should not be treated as the live sprint board without checking `docs/CODEX_EXECUTION_LOG.md`. - -## Release hardening status - -- [x] Remove Python `datetime.utcnow()` deprecation warnings from backend service paths. -- [x] Split frontend production build into app, React vendor and MapLibre vendor chunks. -- [x] Enforce Python deprecation warnings as release-readiness failures. -- [x] Fix Docker backend package install order and remove mandatory root `.env` dependency. -- [x] Add Docker build context ignores for backend and frontend. -- [x] Run Docker/PostGIS live validation on Tower/Unraid. -- [x] Add Unraid Compose template assets with editable ports, storage path and app icon. -- [x] Add single-container Unraid runtime with embedded PostGIS, backend and frontend. -- [x] Remove embedded PostGIS password defaults from all-in-one Docker image metadata. -- [x] Report reused-volume PostgreSQL collation mismatches in live migration smoke. -- [x] Execute Tower PostgreSQL collation reindex/refresh after backup. - -## Current implementation status - -- [x] Make Mol the primary workbench, AOI and operator-sample context while preserving broader Kempen coverage. -- [x] Add a Mol multi-zone operational pack with independent positive holdouts, background control and persisted map-ready AOIs. -- [x] Execute the Mol pack on live Tower/PostGIS with real orthophotos, GRB references, configured YOLO, persisted QA/QC and a zero-building background control. -- [x] Persist and stream the complete official Mol municipality boundary plus all 36,941 clipped GRB buildings through the Map workspace. -- [x] Run a bounded Mol-center raster, tile, configured-YOLO, persisted detection, GRB QA and export workflow on live Tower/PostGIS. -- [x] Separate persisted database layers from available analysis-result overlays with an explicit Map content mode. -- [x] Persist combined Mol operator evidence under the Unraid storage mount so reports survive all-in-one container replacement. -- [x] Visually review Mol Postel and Donk false-positive/false-negative evidence, classify the dominant error modes and only then decide whether another model-training pass is justified. -- [x] Clip detection QA populations to persisted raster/tile coverage and add box-to-footprint matching diagnostics before reconsidering model training. -- [x] Add a coverage-aware Mol multi-zone benchmark report with explicit positive-zone, per-zone collapse, reference-coverage and pure-empty background gates. -- [x] Execute the refreshed coverage-aware Mol operational benchmark against the active local model and record the resulting retain/review decision. -- [x] Align map-driven building QA with footprint IoU `0.25` and show measured candidate/match/error metrics instead of calling every detection a building. -- [x] Persist paginated false-positive/false-negative operator decisions and expose them in the Quality workspace. -- [x] Bound QA evidence resolution to persisted evidence ids instead of loading complete regional reference datasets. -- [x] Compare confidence `0.10` and `0.15` over independent Mol holdouts; retain `0.15` because it wins F1 in every positive zone while both pass the empty-background control. -- [x] Complete conservative decisions for the generated 48 false-negative and 48 false-positive review cards, validate both roles fail-closed and retain only 15 confirmed model errors. -- [x] Audit the confirmed review evidence against the active corpus and holdouts; reject retraining because it provides zero novel leakage-free labels. -- [x] Backend FastAPI foundation, health endpoint and service structure. -- [x] React/TypeScript frontend foundation and MapLibre workbench. -- [x] Map layer visibility, opacity and feature property inspection. -- [x] Selected project area/AOI map overlay with visibility and opacity controls. -- [x] SQLAlchemy/PostGIS ORM models and Alembic migration chain through Sprint 9. -- [x] Dataset upload, storage metadata and vector feature persistence. -- [x] Raster metadata and raster operation service boundaries. -- [x] Vector operation service boundaries and fixture-backed tests. -- [x] Provider registry skeleton for GRB, OSM, manual and fixture providers. -- [x] Detection Lab foundation, persistence, GeoJSON output and QA integration. -- [x] Configured-YOLO optional dependency strategy and local preflight. -- [x] Segmentation Lab foundation, persistence, GeoJSON output and QA integration. -- [x] QA/QC golden benchmark fixtures and script. -- [x] Run QA/QC golden benchmark from the main readiness gate. -- [x] Verify browser-facing demo QA/QC metrics against the golden baseline. -- [x] Explicit offline demo workflow seed for project, AOI, fixture datasets and persisted QA metrics. -- [x] Project-scoped QA/QC result listing and frontend QA/QC Results panel. -- [x] Persisted export foundation for vector/detection/segmentation GeoJSON and project metadata JSON. -- [x] Lightweight HTML project report artifact export. -- [x] V1 readiness handoff summary in project metadata/report exports. -- [x] Browser-facing demo/export workflow smoke script with connected V1 state checks. -- [x] Compact V1 workbench status strip for project, AOI, datasets, map, QA/QC and exports. -- [x] Dry-run-first demo export artifact cleanup tooling. -- [x] Browser-facing default workbench state smoke for the offline demo project. -- [x] Browser-facing workbench interaction backing-state smoke and stable UI test anchors. -- [x] Backend API contract audit comparing implemented FastAPI routes with `docs/API_CONTRACTS.md`. -- [x] Live Docker/PostGIS validation on Tower/Unraid. -- [x] Real YOLO compatibility smoke with optional AI extras and local model file. -- [x] Detection and segmentation workflow hook extraction beyond Sprint 10. -- [x] Export and QA/QC workflow hook extraction beyond Sprint 10. -- [x] Dataset, raster and vector workflow hook extraction beyond Sprint 10. -- [x] Dataset detail, raster controls and vector controls component decomposition. -- [x] QA/QC results and map workspace component decomposition. -- [x] Docker Compose port/storage/database configuration via `.env` defaults for Unraid. -- [x] Single-container `geointel` Unraid compose/template runtime. -- [x] Export preview component decomposition and HTML report download-only UX hardening. -- [x] Provider, change-detection and map-workspace orchestration hook decomposition. -- [x] Project/area/dataset cross-load orchestration hook decomposition. -- [x] Demo workflow orchestration hook decomposition. -- [x] Final `App.tsx` import/encoding cleanup and size audit. -- [x] Optional final bootstrap-effect extraction. -- [x] Decide next V1 stabilization focus: golden dataset expansion or frontend visual polish backlog. -- [x] Expand golden QA/QC benchmark coverage across partial, perfect, no-overlap and MultiPolygon scenarios. -- [x] Improve workbench shell visual polish, mobile navigation density and AI result readability. -- [x] Improve Map workspace layer provenance, empty guidance and selected-feature summary readability. -- [x] Add Data/Map mobile visual polish for upload forms, action grids and map toolbar density. -- [x] Add AI Labs mobile visual polish for model cards, lab forms and result tables. -- [x] Add Export/System mobile visual polish for export actions and provider capability cards. -- [x] Add inspector mobile polish for dataset metadata, raster/vector tools and action groups. -- [x] Add export preview readability polish for large JSON/GeoJSON handoff artifacts. -- [x] Add accessibility focus polish for primary workbench keyboard navigation. -- [x] Add raster/vector operation form readability polish for dense tool panels. -- [x] Add compact loading/error/empty/result state polish across QA, exports and AI labs. -- [x] Add compact shell density polish for topbar context, mobile navigation and workspace skip flow. -- [x] Add Overview workspace panel hierarchy polish for readiness and recommended-action regions. -- [x] Add Data workspace selected-summary and panel density polish. -- [x] Add Map workspace panel hierarchy and layer-control density polish. -- [x] Add selected map feature extraction with highlight, property table, copy and GeoJSON download. -- [x] Add operational GIS map workflow with road basemap, persisted database layer selection and AOI/layer `vector_features` query run. -- [x] Add basemap policy notice and guided GIS query-to-QA/export workflow in the Map workspace. -- [x] Add reusable latest-result mode for repeated Map QA/QC runs without duplicate derived artifacts. -- [x] Add opt-in Docker/Unraid AI build/runtime path for local PyTorch/Ultralytics YOLO operation. -- [x] Surface configured-YOLO runtime preflight status through the API and Detection Lab UI. -- [x] Add read-only local model asset catalog and Detection Lab model-file selection. -- [x] Add live model asset detection workflow smoke for configured-YOLO runtime/provenance validation. -- [x] Add one-click full GIS workflow action for query, derived dataset, QA/QC and export handoff. -- [x] Add QA/QC workspace result hierarchy and filter density polish. -- [x] Add Change Detection panel hierarchy and analysis workspace density polish. -- [x] Add calm workbench layout pass to reduce duplicate navigation, heavy card styling and shell density. -- [x] Add Data and Map usability layout pass with compact catalog cards and map-first spatial review. -- [x] Add QA/QC and Exports usability layout pass with calmer evidence review and handoff artifact scanning. -- [x] Add AI Labs Detection/Segmentation hierarchy and result density polish. -- [x] Add Export/System handoff hierarchy and provider registry density polish. -- [x] Add widescreen and ultrawide workbench breakpoints for the map-first GIS workflow. -- [x] Add operator-provided real raster/reference detection + QA workflow smoke. -- [x] Validate the configured building model on a real georeferenced Kempen orthophoto/GeoTIFF with persisted reference vectors and QA/QC metrics. -- [x] Fix configured-YOLO mixed-case class labels so `Building` model output matches `building` domain filters. -- [x] Persist CRS metadata in raster tile manifests so AI detections can be transformed to WGS84 GeoJSON correctly. -- [x] Add real-data detection calibration sweep tooling for confidence-threshold and QA/QC metric comparison. -- [x] Add calibration QA evidence export tooling for false-positive/false-negative inspection artifacts. -- [x] Add real-data detection quality matrix tooling for model/tile/threshold comparison. -- [x] Add reproducible Geel/Mol/Turnhout operator sample preparation and multi-sample quality matrix tooling. -- [x] Run first Geel/Mol/Turnhout persisted detection quality baseline. -- [x] Add and benchmark a stronger `yolov8s` building-segmentation runtime model candidate. -- [x] Add operator-only tile-level YOLO dataset export with overlapping windows and deterministic negative tile retention. -- [x] Train and benchmark the first tile-level local YOLO candidate on Tower through the persisted QA/QC matrix. -- [x] Calibrate confidence, IoU and model selection against additional local orthophoto/reference samples beyond Geel/Mol/Turnhout. -- [x] Add negative/background AOIs to the operator sample corpus and train an expanded local tile-level YOLO candidate. -- [x] Add a hard-negative model-quality pass with sparse/background AOIs and explicit false-positive scoring. -- [x] Train a hard-negative-balanced YOLO candidate and rerun dense QA plus background false-positive matrices. -- [x] Benchmark an external remote-sensing YOLOv8l building candidate as an explicit local model asset. -- [x] Train and gate the `uniquehardneg160e50` YOLOv8s candidate through 7 positive AOIs and 9 hard-negative/background samples. -- [x] Train and gate an AOI-scale `aoi512e80` YOLOv8s candidate to test the 160px training-scale hypothesis. -- [x] Raise configured-YOLO `max_det` through `YOLO_MAX_DETECTIONS` so dense AOIs are not capped at 300 detections before QA/QC. -- [x] Rerun live dense-AOI calibration after redeploy with `YOLO_MAX_DETECTIONS=1000`; Westerlo reached 523/1000 detections at lower thresholds and Turnhout reached 822/1000, confirming the old 300 cap is removed. -- [x] Add configured-YOLO cross-tile duplicate suppression and raw/suppressed calibration evidence fields. -- [x] Rerun live dense-AOI calibration after redeploy with `YOLO_DUPLICATE_IOU_THRESHOLD=0.5`; Westerlo 0.25 improved to F1 `0.2537313432835821` and Turnhout 0.25 improved to F1 `0.14114114114114112`, but the candidate remains rejected. -- [x] Add `OPERATOR_YOLO_MIN_LABEL_VISIBLE_RATIO` so the next overlapping-tile dataset can drop tiny clipped edge-fragment labels. -- [x] Add operator-only larger-AOI sample prep flags so the next training dataset is not limited to one 512x512 tile per documented sample. -- [x] Regenerate Tower AOI1024 operator samples with paged GRB references and verify no dense reference sample is capped at 1000 features. -- [x] Export and audit AOI1024 clean-label variants; select `yolo-building-aoi1024-visible050-minpx8` as the first audit-passing 512px training candidate. -- [x] Train and gate `geointel-building-yolov8s-aoi1024clean512e50-pt` through seven positive AOIs and nine hard-negative/background AOIs. -- [x] Train and gate background-aware `geointel-building-yolov8s-aoi1024bg512r3e50-pt`; it is the strongest positive-AOI candidate so far but remains inactive because full background-candidate false-positive pressure still blocks default promotion. -- [x] Add explicit operator detection profiles for local model assets and promote the expanded-AOI balanced review profile at threshold `0.15` after positive and pure-empty split-background gates passed. -- [x] Add pure-empty versus sparse-building contextual background corpus classification to operator manifests, hard-negative matrix filters and YOLO tile provenance. -- [x] Add a split background-corpus matrix runner and report builder that runs pure-empty and sparse-context matrices separately. -- [x] Teach the model promotion report to consume split background summaries so only `pure_empty_negative` blocks default promotion and `sparse_building_context` stays review-only. -- [x] Add one-command operator workflow to run split background matrices and immediately build the split-aware promotion report. -- [x] Add preflight-only validation for the split-background promotion workflow before long runtime matrices. -- [x] Rerun split background matrices on Tower after rebuild, then recalibrate against the cleaner pure-empty gate plus separate sparse-context inspection matrix. -- [x] Add guarded promoted-candidate activation helper requiring a promotion report path and exact candidate key before `.env` can be changed. -- [x] Add per-sample YOLO dataset audit diagnostics for parsed labels, median box area, small-box share and AOI-specific warning codes. -- [x] Add deterministic visual YOLO label QA contact sheets before spending more CPU on another training run. -- [x] Filter no-data/low-variance pure-empty negative tiles from operator YOLO exports before the next training run. -- [x] Regenerate the AOI1024 cleanpx YOLO dataset with low-variance negative filtering and rerun visual contact-sheet QA before training. -- [x] Train one inactive candidate from the filtered AOI1024 cleanpx YOLO dataset and gate it through the positive-AOI plus split-background promotion workflow; reject it because mean positive F1 remains below gate. -- [x] Add deterministic dataset/base/trained-model SHA256 provenance to future operator training summaries. -- [x] Review per-AOI false-negative evidence, expand positive sample/label coverage and verify the resulting candidate improves false-negative rate in every validated AOI. -- [x] Complete rebuild/restart and browser/runtime smoke for the guarded promoted V1 building detector activation. -- [x] Expand focused small-building training evidence after reviewing persistent false negatives, train one inactive candidate and pass it through positive, pure-empty and fixed-reference promotion evidence before guarded activation. -- [x] Audit the promoted model's increased false-positive load from persisted seven-AOI QA evidence, including geodetic area buckets, AOI-qualified tile hotspots and combined review GeoJSON. -- [x] Add persisted detection provenance, stratified visual contact sheets and an explicit manual-decision gate for false-positive review. -- [ ] Visually classify representative false-positive evidence from Turnhout, Herentals and Geel and review the remaining 5,838 persistent false negatives before any further model training; do not start another blind run. - -## Sprint 8 status - -- [x] Detection foundation ORM and migration -- [x] Detection model registry capability stubs -- [x] Detection run service boundary -- [x] Detection API foundation -- [x] Detection Lab UI foundation -- [x] Segmentation Lab foundation -- [x] Configured YOLO local preflight -- [x] Real YOLO/PyTorch model compatibility smoke - -## 0. Repository Foundation - -- [x] Repo mappenstructuur voorbereiden -- [x] Productdocumentatie voorbereiden -- [x] Architectuurdocumentatie voorbereiden -- [x] Codex build plan voorbereiden -- [x] Masterprompt voorbereiden -- [ ] Init git repository -- [x] Voeg echte backend scaffold toe -- [x] Voeg echte frontend scaffold toe - -## 1. Backend Foundation - -- [x] FastAPI app aanmaken -- [x] Config systeem aanmaken -- [x] Database connectie voorbereiden -- [x] SQLAlchemy models toevoegen -- [x] Alembic migrations toevoegen -- [x] Health endpoint toevoegen -- [x] Tests voor health endpoint toevoegen - -## 2. Database / PostGIS - -- [x] Docker compose met PostgreSQL/PostGIS -- [x] PostGIS extensie activeren -- [x] projects tabel -- [x] areas tabel -- [x] datasets tabel -- [x] analysis_runs tabel -- [x] detections tabel -- [x] quality_checks tabel -- [x] exports tabel -- [x] spatial indexes - -## 3. Frontend Foundation - -- [x] React + TypeScript scaffold -- [x] Routing -- [x] Layout met sidebar -- [x] API client -- [x] Project pages -- [x] Map Workbench basis -- [x] Map layer controls -- [x] Feature property inspector -- [x] Selected area display - -## 4. Project & Area API - -- [ ] POST /projects -- [ ] GET /projects -- [ ] GET /projects/{id} -- [ ] POST /projects/{id}/areas -- [ ] GET /projects/{id}/areas -- [ ] GeoJSON validatie - -## 5. Dataset Manager - -- [ ] Upload endpoint -- [ ] Storage paths -- [ ] Raster metadata extraction -- [ ] Vector metadata extraction -- [ ] Dataset list UI -- [ ] Dataset detail UI - -## 6. Raster Core - -- [ ] Rasterio metadata reader -- [ ] Raster preview generation -- [ ] Clip raster by area -- [ ] Tile raster by area -- [ ] Save tile metadata - -## 7. Vector Core - -- [ ] GeoPandas importer -- [ ] CRS detection -- [ ] CRS transformation -- [ ] Geometry validation -- [ ] Clip vector by area -- [ ] Store features in PostGIS - -## 8. Reference Data - -- [ ] OSM fetcher als fallback -- [ ] GRB integration research verwerken in code -- [ ] Reference dataset cache -- [ ] Reference layer viewer - -## 9. Detection Lab - -- [ ] YOLO wrapper -- [ ] Model config -- [ ] Inference job -- [ ] Pixel bbox naar geo polygon -- [ ] Detections opslaan -- [ ] Detection UI -- [ ] GeoJSON export - -## 10. QA/QC Lab - -- [ ] Spatial matching -- [ ] IoU berekening -- [ ] Precision/recall/F1 -- [ ] False positive layer -- [ ] False negative layer -- [x] QA dashboard -- [x] QA export foundation - -## 11. Segmentation Lab - -- [x] Segmentation service design -- [x] Mask artifact path convention -- [ ] Polygonize masks -- [x] Segmentatiekaartlaag - -## 12. Change Detection - -- [ ] Compare two runs -- [x] Added/removed objects -- [x] Change stats -- [x] Change layer - -## 13. Tests - -- [x] Unit tests GIS helpers -- [x] API tests -- [x] DB/migration smoke tests -- [x] Raster fixture tests -- [x] Vector fixture tests -- [x] QA/QC tests - -## 14. Portfolio Release - -- [x] Demo dataset voorbereiden -- [x] Demo workflow documenteren -- [ ] Screenshots toevoegen -- [ ] README portfolio sectie -- [ ] Full smoke test - -# Repo preparation additions - -- [x] Add Data Catalog. -- [x] Add Analysis Specifications. -- [x] Add QA/QC Specification. -- [x] Add Raster Operations Specification. -- [x] Add Vector Operations Specification. -- [x] Add Detection Pipeline Specification. -- [x] Add Segmentation Pipeline Specification. -- [x] Add Change Detection Specification. -- [x] Add UI Page Specifications. -- [x] Add Storage Architecture. -- [x] Add Demo Scenarios. -- [x] Add Development Rules. -- [x] Add Codex phase prompts. - -# Recommended first Codex build sequence - -- [ ] Phase 1: Backend foundation using `docs/CODEX_PHASE_1_PROMPT.md`. -- [ ] Phase 2: Dataset Manager using `docs/CODEX_PHASE_2_PROMPT.md`. -- [ ] Phase 3: Detection + QA/QC skeleton using `docs/CODEX_PHASE_3_PROMPT.md`. - -## M2 Engineering Package - -- [x] Add ADR decision records. -- [x] Add RFC placeholders for future modules. -- [x] Add API/database/event contracts. -- [x] Add model registry and class catalogs. -- [x] Add queue architecture. -- [x] Add acceptance matrix and test catalog. -- [x] Add Codex M2 build prompts. -- [ ] Start Codex Pass 01 backend foundation. - -# M4 Autonomous Build Readiness - -- [x] Add M4 autonomous build readiness document. -- [x] Add M4 sprint board. -- [x] Add module build contracts. -- [x] Add acceptance test catalog. -- [x] Add API example responses. -- [x] Add job lifecycle contract. -- [x] Add frontend state and route contracts. -- [x] Add backend service IO contracts. -- [x] Add model registry seed specification. -- [x] Add demo fixture manifest. -- [x] Add Codex autonomous runbook. -- [x] Add Codex pass prompts. -- [x] Add Geel demo fixtures. - -# Next M5 Preparation - -- [ ] Add concrete SQL migration snippets for every core table. -- [ ] Add OpenAPI YAML draft. -- [ ] Add frontend component prop contracts. -- [ ] Add backend unit-test skeleton files. -- [ ] Add frontend test skeleton files. -- [ ] Add live data connector research notes with verified endpoints. - -# M5 Operational Readiness Checklist - -- [x] CI/CD specification added. -- [x] Healthcheck contracts added. -- [x] Observability plan added. -- [x] Troubleshooting runbook added. -- [x] Rollback and recovery plan added. -- [x] Security checklist added. -- [x] Geospatial validation rules added. -- [x] Build governance added. -- [x] Codex pass documents added. -- [x] Smoke scripts added. -- [ ] M6: implement actual backend foundation. -- [ ] M6: implement database migrations. -- [ ] M6: implement frontend shell. - -## M8 Codex Day-1 Readiness - -- [x] Add Day 1 master prompt. -- [x] Add pass-by-pass Day 1 prompts. -- [x] Add autonomy boundaries. -- [x] Add failure recovery playbook. -- [x] Add quality gate matrix. -- [x] Add operator checklist. -- [x] Add smoke script scaffold. -- [ ] Let Codex execute Day 1 implementation passes. - - -# M10 Ultra Preparation - -- [x] Add autonomous build charter. -- [x] Add Codex start-here guide. -- [x] Add M10 master autonomous prompt. -- [x] Add pass sequence. -- [x] Add geometry and CRS contracts. -- [x] Add error taxonomy. -- [x] Add feature flag strategy. -- [x] Add model adapter guide. -- [x] Add QA/QC matching algorithm. -- [x] Add frontend state machine. -- [x] Add implementation ticket index and tickets. -- [x] Add API example payloads. -- [x] Add final pre-Codex checklist. - -# Current Workbench UI - -- [x] Replace the accumulated shell overrides with a coherent premium presentation layer while preserving V1 behavior. -- [x] Group navigation into Workspace, Analyze and Deliver and make the inspector an optional drawer. -- [x] Fix mobile navigation so the active workspace uses the full viewport width. -- [x] Bound populated Project, Dataset, QA, AI and Export panels so long histories do not push core actions thousands of pixels down-page. -- [x] Move Data create/upload forms and Map/AI diagnostics into explicit progressive disclosures. -- [x] Reorder AI Labs around run controls and Map around layer selection plus the MapLibre canvas. -- [x] Harden detection QA coverage and matching diagnostics before any further model training. - -- [x] Replace the one-page workflow panel stack with a task-based workbench shell. -- [x] Add persistent project/AOI/dataset/layer context. -- [x] Move selected dataset details into a persistent inspector. -- [x] Deploy the shell refactor to Tower and run live browser smoke on port 1202. -- [x] Polish Data, Map and AI Labs workspaces. -- [x] Polish QA/QC and Exports workspaces. -- [x] Add selected-object inspector detail tabs for project, AOI, dataset, QA check, export and AI run context. -- [x] Improve map/dataset selection ergonomics from the workbench canvas and inspector. -- [x] Improve populated Data/Exports readability after a demo workflow run. -- [x] Improve live visual shell width, scroll behavior and Map workspace layout at 1280px. -- [x] Add export history filtering controls for long-running demo environments. -- [x] Add a safe export retention/cleanup command for demo environments. -- [x] Add a live dry-run maintenance smoke for demo export cleanup. -- [x] Add browser screenshot artifact automation for visual regression handoff. -- [x] Add backend error-envelope audit for expected user-error paths. -- [x] Expand golden datasets beyond the original single building QA fixture pair. -- [x] Add workbench visual polish pass for command bar, panel surfaces, empty states and mobile nav density. -- [x] Add map/result overlay ergonomics for active layer provenance and feature property summaries. -- [x] Add export/report handoff polish for artifact readiness, action grouping and export provenance. -- [x] Polish lightweight HTML project report readability, print styling and handoff sections. -- [x] Add Map empty-state quick actions for ready vector datasets. -- [x] Add Data catalog role-density polish for reference/candidate/source scanning. -- [x] Add Data catalog action polish for map, metadata, export and QA affordances. -- [x] Add QA/QC handoff polish for candidate/reference context and persisted results. -- [x] Add QA/QC metric card polish for precision, recall, F1, IoU and error counts. -- [x] Add mobile overflow hardening for workbench navigation, inspector and long QA identifiers. -- [x] Add QA/QC result filtering and density controls for long-running demo projects. -- [x] Add Overview workflow guidance for the V1 project -> data -> map -> QA/AI -> export path. -- [x] Audit populated demo workflow and tighten complete-state Overview guidance copy. -- [x] Make Overview workflow rail Map/Export clicks preserve useful dataset context. -- [x] Add latest handoff artifact cards to the Export Center for report, metadata and GeoJSON outputs. -- [x] Add QA/QC evidence drilldown for selected checks, false-positive/negative evidence and provenance JSON. -- [x] Add raster pipeline readiness and guardrail surfaces for metadata, CRS, preview, tile manifest and clip-AOI handoff. -- [x] Add useful default dataset context so Data, Map and Exports are immediately usable after project/demo load. -- [x] Make raster tile handoff to Detection Lab auto-select the configured YOLO run form. -- [x] Add AI Lab run-readiness checks for Detection and Segmentation before job submission. -- [x] Add AI Lab action guardrails so explicit fixture models are not exposed as normal operator runs. -- [x] Add persisted vector area selection from the Map workspace with bbox extract and GeoJSON download. -- [x] Persist map area selections as Export Center handoff artifacts. -- [x] Persist map area selections as reusable derived vector datasets indexed into `vector_features`. -- [x] Add Map workspace QA/QC shortcut for saved derived selection datasets. -- [x] Add Map workspace QA/QC evidence drilldown handoff for saved selection comparisons. -- [x] Persist QA/QC feature-level evidence for matches, false positives and false negatives. -- [x] Render persisted QA/QC feature-level evidence as Map workspace overlays. -- [x] Add safe local YOLO model env configuration helper for Unraid/Tower runtime activation. -- [x] Harden configured YOLO inference for single-band raster tiles and wrapped runtime errors. -- [x] Add operator-only YOLO dataset export and local training-smoke wrapper for real sample calibration. -- [x] Train/evaluate a small local GeoIntel building-detector smoke from the current operator samples and reject it because QA/QC did not improve. -- [x] Add operator-only tile-level YOLO dataset export with overlapping windows and deterministic negative tile retention. -- [x] Run tile-level training on Tower and accept/reject the resulting local model through the persisted QA/QC matrix. -- [x] Train/evaluate a YOLOv8s hard-negative local building-detector candidate on Tower and keep it inactive because hard-negative false positives remain. -- [x] Add an operator-facing local model catalog/activation workflow with SHA256, active model status and explicit threshold guidance. -- [x] Block silent local model asset auto-selection in Detection Lab. -- [x] Add structured raster tile manifest handoff into Detection Lab with linked preflight visibility. -- [x] Add full threshold calibration comparison UX so detection runs can compare candidate thresholds before promotion. -- [x] Add guided in-app detection calibration runner for explicit threshold sweeps. -- [x] Link guided calibration rows to the QA evidence map. -- [x] Add guided calibration summary export from the Detection Lab. -- [x] Allow the evidence bundle script to consume Detection Lab calibration summary exports. -- [x] Add a local browser-summary QA evidence bundle smoke using mocked canonical evidence responses. -- [x] Add a multi-AOI calibration evidence portfolio convention for model-review handoff. -- [x] Run the first live multi-AOI calibration evidence portfolio on Tower for Geel, Mol and Turnhout. -- [x] Run fresh positive-AOI matrix coverage for Balen, Herentals and Westerlo. -- [x] Preserve model/tile provenance in calibration evidence bundle summaries. -- [x] Prevent same-threshold calibration evidence responses from overwriting each other in multi-model portfolios. -- [x] Add a model promotion decision report that combines positive-AOI score with hard-negative false-positive pressure. -- [x] Train and reject a YOLOv8s hard-negative r8 partial candidate after 12 CPU epochs through the full positive/background promotion gate. -- [x] Finish and reject the full YOLOv8s hard-negative r8 e60 candidate through the same promotion gate. -- [x] Add more AOIs after the tile-level baseline so the next local model attempt is not limited to Geel/Mol/Turnhout. -- [x] Add negative/background AOIs so the next tile dataset is not all positive tiles. -- [x] Improve positive training coverage/label quality before the next higher-capacity model attempt; simply extending the same hardneg r8 run is not enough. -# Sprint 146 - Operator YOLO dataset quality audit - -- [x] Add a dataset/label-quality audit for generated operator YOLO tile datasets. -- [x] Report sample coverage, validation coverage, repeated hard-negative pressure and YOLO label area integrity. -- [x] Wire the audit script into the readiness syntax gate. -- [x] Use live audit output to decide whether the next model pass needs more positive AOIs, label cleanup or unique hard negatives. -- [x] Add more unique background/hard-negative AOIs before repeating hard-negative-balanced YOLO training. -- [x] Supersede `yolo-building-tile-expanded160` only with audited AOI1024 corpora; no repeat-heavy r4/r8 dataset became a default. -- [x] Regenerate Tower operator samples, export a new unique-hard-negative tile dataset and rerun the dataset audit before training. - -# Sprint 147 - Unique hard-negative AOI expansion - -- [x] Expand the documented operator background candidates from 3 to 9 unique AOIs. -- [x] Keep every new background AOI explicit, `allow_empty_reference=True`, and `sample_role='background_candidate'`. -- [x] Add test coverage for minimum background candidate count, unique centers and regional spread. -- [x] Prepare the new samples on Tower and build a fresh hard-negative tile dataset. -- [x] Rebuild Tower all-in-one image so the newly copied operator scripts are available inside `/app/scripts` without `docker cp`. -- [x] Fix YOLO preflight CLI so it respects Tower `.env` runtime configuration. -- [x] Train a new inactive AOI1024 YOLOv8s candidate with visible-label filtering. -- [x] Fix the all-in-one/compose Nginx upload limit after live 1024px GeoTIFF uploads hit `413 Request Entity Too Large`. -- [x] Fix the all-in-one/compose Nginx proxy timeout after low-threshold persisted YOLO/QA runs hit `504 Gateway Timeout`. -- [x] Rerun the previously failing Geel low-threshold persisted QA/QC path for `geointel-building-yolov8s-aoi1024visible025e50-pt` after redeploying upload/timeout fixes. -- [x] Finish remaining AOI1024 positive-sample matrix coverage for `geointel-building-yolov8s-aoi1024visible025e50-pt`. -- [x] Run AOI1024 background/hard-negative matrix for `geointel-building-yolov8s-aoi1024visible025e50-pt`. -- [x] Fix promotion-report parsing for `multi_sample_quality_summary.json` inputs. -- [x] Generate AOI1024 promotion report and keep recommended candidate as `none`. -- [x] Add GRB paging before trusting dense reference exports as full ground truth. -- [x] Regenerate Tower AOI1024 operator samples with paged GRB references, then re-export and audit labels before any new training attempt. -- [x] Improve AOI1024 label quality before retraining: `yolo-building-aoi1024-cleanpx12vis035` now audits `ok` with 14,632 labels, `min_label_px=12`, `min_label_visible_ratio=0.35`, median normalized box area `0.001373291015625` and small-box share `0.0`. -- [x] Train and reject `geointel-building-yolov8s-aoi1024cleanpx12vis035e50-pt` through the positive/background promotion gate. -- [x] Keep every local YOLO candidate inactive until positive-AOI and hard-negative promotion reports recommend default activation. - -# Sprint 181 - Complete Mol municipality workspace - -- [x] Persist the official VRBG municipality boundary for Mol (NIS `13025`). -- [x] Page, deduplicate and boundary-clip the complete GRB GBG building layer. -- [x] Import municipality layers through the existing DatasetService and - VectorFeatureService path, with no direct provider-to-database write. -- [x] Prefer the complete municipality workspace on a fresh session while - keeping the lightweight boundary as the initially rendered layer. -- [x] Make GeoJSON bounds calculation safe for municipality-scale layers. -- [x] Acquire and tile a georeferenced raster only for an explicitly selected - Mol analysis zone before running the next configured-YOLO validation. - -# Sprint 182 - Municipality viewport delivery and bounded AI handoff - -- [x] Stop downloading municipality-scale vector datasets as one frontend GeoJSON payload. -- [x] Deliver large persisted layers through the existing PostGIS bbox endpoint from zoom level 14. -- [x] Report visible/total counts and explicit truncation instead of silently hiding omitted features. -- [x] Preserve complete loading and auto-fit behavior for small vectors and persisted AI/QA overlays. -- [x] Allow the real raster/detection/QA operator smoke to reuse the definitive Mol project. -- [x] Link operator raster/reference uploads to the persisted analysis Area and keep their names distinct from municipality-wide layers. -- [x] Execute the bounded Mol-Centrum configured-YOLO/QA workflow in the deployed runtime and retain its persisted ids as release evidence. - -# Sprint 171 - Positive AOI expansion and small-building recovery - -- [x] Reject cross-model false-negative comparisons when reference populations differ. -- [x] Add explicit Olen, Lille, Oud-Turnhout and Kasterlee positive training AOIs. -- [x] Preserve Turnhout, Retie, Westerlo and Arendonk-heide as manifest-backed validation holdouts. -- [x] Make the tile exporter reject unknown validation samples and holdout leakage. -- [x] Refresh the full AOI1024 operator manifest on Tower and fetch only missing AOIs. -- [x] Export and audit a low-minimum-label dataset without changing the active model. -- [x] Render and inspect a sample-balanced label contact sheet before training. -- [x] Finish the inactive expanded-minpx4 candidate and run the full promotion gate. -- [x] Export the focused 23-sample minpx3 corpus with independent Vosselaar/Grobbendonk validation and external Turnhout/Retie/Westerlo holdouts. -- [x] Train, audit and guarded-activate the focused small-building candidate only after all persisted promotion gates passed. - -# Sprint 199 - Reviewed accuracy expansion and fail-closed challenger - -- [x] Add six complete training-only AOIs outside every protected Mol/Kempen holdout. -- [x] Page and audit 9,964 new GRB building references with municipality and CRS provenance. -- [x] Export and visually inspect the 252-tile, 79,192-label reviewed-accuracy corpus. -- [x] Train one inactive 20-epoch YOLOv8s challenger from the active local model without downloads. -- [x] Rerun active and challenger models on identical coverage-aware reference populations. -- [x] Confirm positive-zone F1 improvement in all seven holdouts. -- [x] Reject challenger activation because Postel-bos produced two detections while the active model remained at zero. -- [x] Update the recommended UI profile with the current active model's coverage-aligned evidence. -- [ ] Collect new training-only hard negatives matching the two Postel-bos errors before another challenger attempt. - -# Sprint 212 - Platform-wide official source portfolio - -- [x] Rebalance official source planning across six platform domains. -- [x] Distinguish operational ready Datasets from audited but unimplemented sources. -- [x] Reduce Sources workspace noise through domain summaries and progressive disclosure. -- [x] Add official space, soil, mobility, population, service, climate and economy candidates. -- [x] Replace the water-first recommendation with a cross-domain implementation wave. -- [ ] Implement the governed Flemish thematic-raster registry for space occupation, open space, population density, node value and service level. -- [x] Add the digital soil map through DatasetService and VectorFeatureService. - -# Sprint 224 - Governed GRB evolution - -- [x] Audit all eight retained regional GRB snapshots for complete official - source identities and geometry-hash fallbacks. -- [x] Validate old governed snapshots through authoritative, complete and - approved operator provenance before enabling object-level comparison. -- [x] Make future regional GRB imports reject missing official OGC identities. -- [x] Persist explicit identity schemes and collection prefixes on new GRB - snapshots. -- [x] Show precise daily edition ranges and explain registration-date nuance in - the Evolution workspace. -- [x] Document refresh readiness across the complete official-source portfolio. -- [x] Verify and add the governed ALZ catalog probe against the official - campaign-snapshot and definitive-archive publication contract. -- [x] Add a read-only orthophoto preflight for product variant, official - edition, exact WCS selected-area domain and deterministic flight-year points. -- [x] Keep orthophoto pixel refresh manual through a separate - plan-stage-review-apply flow that retains the passed preflight identity and - creates a new immutable Dataset with official `YYYY.NN` source version. -# Bathymetry follow-up - -- [x] Add governed municipality partition orchestration for all of Flanders - after the Mol VHA operator passes live acceptance. -- [x] Add read-only MDK WCS capability/TLS probe and maritime scope metadata. -- [ ] Add bounded MDK GeoTIFF acquisition only after live CRS, LAT, nodata and - response-limit validation. Current official endpoint is blocked by TLS - hostname mismatch and unavailable capabilities; never bypass verification. -- [x] Add SPW staged-download adapter with mDNG metadata and survey-epoch - coverage validation. -- [x] Add authoritative territorial-sea, EEZ and continental-shelf boundary - layers with legally accurate labels. -- [ ] Add vertical-datum conversion only when authoritative transforms and - uncertainty tests exist; never merge TAW, LAT and mDNG implicitly. -- [ ] Add water volume only when bed and water-surface inputs share a governed - time, datum and coverage contract. - -# Scale-aware map selection - -- [x] Prevent country-scale rectangles from fan-out querying every local - provider and replace repeated source-limit errors with one overview status. -- [x] Partition compatible 20-50 km regional vector acquisitions into bounded - source requests and combine their persisted PostGIS metrics. -- [x] Keep terrain, flood and thematic rasters behind explicit pixel and - selection-size budgets. -- [ ] Provision additional national-scale baseline datasets before exposing - more overview themes; do not synthesize regional detail at national scale. - -# Sprint 226 - GeoIntel and ITWorx brand system - -- [x] Replace the legacy GI/mountain artwork with a distinctive atlas and location mark. -- [x] Use one canonical SVG across in-product branding and the browser favicon. -- [x] Generate matching 32 px, Apple touch and Unraid PNG derivatives. -- [x] Add the approved ITWorx.tech identity as a subtle Jens maker signature. -- [ ] Revisit alternative lockups only when an approved GeoIntel brand guide exists. - -# Sprint 227 - Task-first usability audit - -- [x] Reduce the desktop navigation rail and contain long card/context labels. -- [x] Align the latest-state and evolution controls as one responsive header group. -- [x] Make searchable municipality selection the first step of the map workflow. -- [x] Route an empty quality workspace to real map and image-analysis actions. -- [x] Replace passive management naming with an actionable system/source monitor. -- [x] Preserve existing persisted Area, source, analysis and QA contracts. -- [ ] Add more direct quality-review actions only when a persisted candidate/reference pair exists; never synthesize a check. - -# Sprint 228 - Optional spatial entry and municipality activation - -- [x] Search the real persisted NGI municipality catalog instead of existing project Areas. -- [x] Match Dutch, French and German names plus NIS codes. -- [x] Activate the exact official geometry idempotently as a reusable project Area. -- [x] Present municipality search as an optional shortcut beside free map drawing. -- [x] Explain theme choice as map and primary-metric focus rather than a mandatory workflow gate. -- [x] Keep narrow theme-card copy and status labels inside their cards. -- [x] Replace the former compass icon with a scale-safe GeoIntel geo-lens mark. -# Audit remediation (2026-07-26) - -- [x] Freeze an audit remediation roadmap with NVIDIA GPU as a server requirement. -- [x] Add fail-closed CUDA configuration and preflight/runtime validation. -- [ ] Rebuild Tower with NVIDIA device exposure and capture a CUDA inference smoke. -- [x] Implement the persisted parent/partition/checkpoint AOI operation. -- [x] Add source-aware seam deduplication contracts and one-result Dataset aggregation across child partitions. -- [x] Extend the zone x theme x source resolver with partition-union coverage and per-Dataset evidence. -- [ ] Resolve governed North Sea bathymetry access without bypassing TLS. -- [x] Enforce the active building-only model classes, CUDA readiness and persisted Mol/Kempen Area scope. -- [ ] Add national/regional holdout evidence before expanding model classes or validated Areas. -## Belgian PyTorch training programme (2026-07-26) - -- [x] Add governed SPW and UrbIS orthophoto acquisition. -- [x] Normalize GRB/PICC/UrbIS building labels with decision provenance. -- [x] Assemble and checksum an initial 19-AOI Belgian candidate corpus. -- [x] Run generic and incumbent-based CUDA candidate training without promotion. -- [ ] Complete representative human label/contact-sheet review (the complete 42-AOI review queue and four contact sheets are ready; AI-assisted inspection is recorded separately and does not count as human sign-off). -- [x] Expand each region/context/split until the national minimum-composition gate passes (42 independent 256 m AOIs at 25 cm, including pure-background and hard-negative contexts). -- [x] Run explicit spatial leakage and independent calibration/test evaluation. -- [ ] Promote only if every regional and pure-background gate passes. -- [x] Freeze the objective train/evaluate/error-analysis loop and regional exit gates. -- [x] Expand the second corpus wave to 60 independent AOIs and 10,262 accepted labels. -- [ ] Resolve the v3 Flanders and Wallonia generalisation failures through additional training-only evidence and retraining. -- [x] Replace rolling-mosaic training inputs with governed dated 2025 Flanders/Brussels and complete 2023 SPW imagery; retain exact flight-day limitations. -- [x] Reject positive labels over blank/no-data imagery and replace partial SPW 2024 coverage with the complete dated SPW 2023 campaign. -- [x] Exclude GRB/PICC features created after the corresponding dated imagery period while retaining auditable rejection evidence. -- [x] Allow the objective CUDA loop to consume an automatically clean `needs_human_review` corpus while keeping final human sign-off as a separate, mandatory promotion gate. -- [x] Persist checksummed train-only failure-driven sampling after every rejected loop iteration and resume the next checkpoint from that exact dataset YAML. -- [x] Add a guarded calibration-first entry point for completed checkpoints so v37 and future externally interrupted runs can rejoin the automated loop without redundant retraining. -- [x] Add and activate a host-side, exact-run-marker supervisor that resumes the v37 CUDA checkpoint after container recreation without launching concurrent trainers. -- [x] Bind v37 completion to a one-shot JSON command that enters calibration-first evaluation and up to 20 automatic failure-driven CUDA iterations with the frozen aerial augmentation contract. -- [x] Complete v37 by early stopping at epoch 23, reject its best epoch-5 checkpoint calibration-first, and start closed-loop iteration 2 from checksummed failure-driven sampling. -- [x] Make orchestrator patience explicit and retain the frozen value `18` in every subsequent CUDA iteration. -- [x] Preserve v37 warmup and aerial HSV augmentation in every loop iteration; archive and invalidate the pre-epoch-2 run that exposed generic Ultralytics warmup drift. -- [x] Resume a partially written current loop iteration from its exact `last.pt` after container recreation and activate a host-side parent-loop supervisor. -- [x] Evaluate the completed v36 YOLO11x checkpoint calibration-first on the rotated v30 holdouts; reject it before opening test/background because the regional calibration gate failed. -- [ ] Finish and assess the leak-free v37 YOLO11x failure-driven CUDA iteration; open test/background evidence only if every calibration gate passes. - -# Sprint 229 - Visual release correction and Tower redeploy - -- [x] Audit the revised landing page, guest map flow and quality workspace at desktop, laptop and tablet widths. -- [x] Keep the new consolidated GeoIntel design system while correcting the quality-details grid and narrow-laptop result layout. -- [x] Preserve complete insight labels and readable dataset/evidence cards without weakening the map-first workflow. -- [x] Make guest authentication independent of optional browser scrolling support. -- [x] Restore the explicit frontend dependency exclusion required by the Unraid build-context gate. -- [x] Push the verified release and redeploy the Dockerman-native all-in-one runtime from `/mnt/user/appdata/geointel`. - -# Sprint 230 - Interactive storytelling and portfolio presentation - -- [x] Add an accessible interactive project-chain illustration to the public landing page. -- [x] Add restrained map, scan, route and evidence motion with a complete reduced-motion fallback. -- [x] Produce original GeoIntel hero and building-QA campaign imagery for project and portfolio use. -- [x] Capture portfolio-ready landing, story, map, quality and mobile screenshots. -- [x] Rewrite the repository README around product value, architecture, operation and visual evidence. -- [x] Deploy and visually verify the presentation release on the Tower runtime. - -# Sprint 231 - Complete visual system and portfolio case study - -- [x] Add functional workbench motion for workspace changes, results, jobs, errors and loading skeletons. -- [x] Add an interactive evidence-first PyTorch/NVIDIA pipeline tied to real detection readiness. -- [x] Add a project briefing surface with workflow progress, latest QA, source coverage and export status. -- [x] Add production WebP variants while retaining high-resolution portfolio masters. -- [x] Produce a dark campaign cover, architecture visual, AI pipeline visual and animated project GIF. -- [x] Generate and visually verify a six-page portfolio case-study PDF. -- [x] Commit, push and redeploy the complete presentation release from `/mnt/user/appdata/geointel`. - -# Sprint 232 - V42 Belgian building generalisation loop - -- [x] Add 14 independent coastal, industrial, rural, quarry, forest, field and port training AOIs across Flanders and Wallonia. -- [x] Acquire, temporally filter, SAM2-refine and overlap-retile the new AOIs on the RTX 4080 SUPER. -- [x] Assemble and checksum the immutable 156-sample v42 corpus while preserving the protected v31 calibration/test/background assignments. -- [x] Pass structural corpus and 56,474-label tile-quality audits with zero invalid or missing labels and zero spatial leakage failures. -- [x] Render and inspect a 56-tile contact sheet covering all 14 new AOIs before retraining. -- [ ] Run the v43 calibration-first, failure-driven CUDA loop against the frozen regional release gates. -- [ ] Acquire and integrate the v44 Flemish-only corpus wave after six loop assessments isolated coastal, industrial and ribbon-domain under-generalisation. -- [x] Rotate region-capped repeat windows deterministically per loop round so persistent failures cannot reuse an identical training list indefinitely. -- [x] Keep near-gate regional precision/recall stabilization inside a 0.03 sampling guard-band to prevent cross-region seesaw regressions. -- [ ] Open protected test and pure-background evidence only after every calibration gate passes. -- [ ] Queue final representative human sign-off only after all automated gates pass, then promote and redeploy the exact checksummed model. - -# Sprint 233 - Live animated gebiedsanalyse - -- [x] Vertaal de vier schakels van de welkomstillustratie naar de echte kaartworkflow. -- [x] Koppel Selecteer, Bronnen, Verwerk en Controleer uitsluitend aan bestaande API- en hookstatussen. -- [x] Toon verwerking, QA, fout en gereed als onderscheidbare live kaartstatussen zonder fictieve successen. -- [x] Voeg een responsieve desktop- en mobiele procesrail met reduced-motion fallback toe. -- [x] Dek de statusresolver en het geverifieerde-bewijslabel af met gerichte componenttests. -- [x] Controleer na Tower-redeploy de gastworkflow visueel op desktop en mobiel; operatorstatus gebruikt dezelfde componentcontracten. - -# Sprint 234 - Productie operator-login herstellen - -- [x] Bevestig de actieve operatorconfiguratie en identificeer de exacte gebruikersnaammismatch. -- [x] Wijzig alleen de productiegebruikersnaam naar `ITWorx` en behoud de bestaande wachtwoordhash en sessiebeveiliging. -- [x] Herstart vanuit `/mnt/user/appdata/geointel` met behoud van de NVIDIA/AI-image. -- [x] Controleer containergezondheid, migraties, frontendproxy en actieve runtimeconfiguratie. -- [x] Werk de operatorconfiguratievoorbeelden bij zodat toekomstige configuratie `ITWorx` gebruikt. - -# Sprint 235 - Expliciete kaartanalyse en resultatenlade - -- [x] Laat tekenen uitsluitend het werkgebied vastleggen zonder bronnen of modellen te starten. -- [x] Voeg meervoudige, expliciete themakeuze en één duidelijke analyseknop toe. -- [x] Beperk de analysequery tot uitsluitend de gekozen thema’s. -- [x] Herstel Inzichten als open- en sluitbare lade boven de kaart. -- [x] Verkort bronteksten en voorkom overflow in de themakolom. -- [x] Verifieer TypeScript-build, frontend-unitset en responsive runtime visueel. -## Sprint 236 - Platformbrede UI/UX-herwerking (2026-08-01) - -- [x] Eén herbruikbare taakgerichte modelselector voor lokale AI, detectie en segmentatie. -- [x] Automatisch aanbevolen lokale assistentkeuze met persistente, gevalideerde voorkeur en runtimefallback. -- [x] Alleen werkelijk door backend/runtime gerapporteerde modellen en metadata tonen. -- [x] Loading-, empty-, unavailable- en errorstates plus toetsenbord- en dialogbediening. -- [x] Zoekbare en bredere kaartthemalijst met volledig leesbare labels. -- [x] Compacte analysecontextbalk en rustige desktop/tablet/mobiele hiërarchie. - -# Sprint 237 - Sol Ultra productupgrade (2026-08-23) - -- [x] Splits publieke landing-CSS en MapLibre van de lazy werkbankbundel. -- [x] Valideer landing en werkbank op 390, 1366 en 2560 px zonder overflow, - consolefouten of mislukte API-requests. -- [x] Herstel mobiele topbar/banner/kop- en procesrailbotsingen. -- [x] Voorkom afgekapte mobiele navigatielabels met korte zichtlabels en een - automatische clipping-gate. -- [x] Toon analysefouten vóór lege states en bied een herhaalactie. -- [x] Wis oude dekkingsdata zodra een nieuwe AOI wordt opgelost. -- [x] Sluit stale-response races in tijdvergelijking en AI-vragen. -- [x] Sluit late detectie-/segmentatiejobs, resultaten en QA na een - werkruimtewissel uit. -- [x] Voer productie-detectie uitsluitend via async NVIDIA/GPU-jobs uit en - verzoen het resultaat met de bewaarde AnalysisRun. -- [x] Voer productie-segmentatie uitsluitend via async serverjobs uit, eis een - tegelmanifest en laat de NVIDIA-runtime fail-closed valideren. -- [x] Bind gast-detecties, segmentaties en downloads aan het gesigneerde - demoproject op resourceniveau. -- [x] Valideer redirects vóór netwerktoegang en begrens segmentatieresultaten. -- [x] Maak pipeline-tabs en modeldialoog volledig toetsenbordbedienbaar. -- [x] Lokaliseer bekende modelnamen en beschikbaarheidsmeldingen in de primaire - Nederlandse AI-flow. -- [ ] Voer vóór formele toegankelijkheidscertificatie nog fysieke touch- en - screenreader-QA uit; browseremulatie en automatische naamcontrole zijn groen. -- [x] Uitschuifbare inzichten behouden; analyse blijft uitsluitend expliciet na themakeuze. -- [x] 51 frontendtests en productiebuild groen. -- [ ] 19 verouderde broncode-stringtests herijken; meerdere eisen daarin (automatische analyse) conflicteren bewust met de actuele productbeslissing. - -## Sprint 237 - Volwaardige, projectgebonden demo (2026-08-01) - -- [x] Maak alle niet-administratieve werkruimtes zichtbaar voor demo-gebruikers. -- [x] Laad dezelfde assistent-, detectie- en segmentatiemodellen en bewaarde resultaten. -- [x] Sta projectgebonden analyse-, QA-, assistent- en exportacties toe. -- [x] Behoud server-side blokkades op instellingen, beheer, uploads, reviews en cross-projectverzoeken. -- [x] Verifieer en redeploy de exacte commit naar Tower `/mnt/user/appdata/geointel`. - -# Accuracy Improvement Program Phase 2 (2026-08-01) - -- [x] Complete the Phase-1 forensic inventory, data lineage, reproducible - baseline, risk register, metric framework, roadmap, status and retained - evidence manifest. -- [ ] P2-00: freeze evidence and enforce a promotion/scope-widening lock. -- [ ] P2-01: establish one canonical CI command, repair import shadowing, - replace 17 stale source assertions with reviewed behavior tests, close the - 112 Ruff findings and add real frontend lint. -- [ ] P2-02: fix CRS ingest, metre buffering and Area geometry/CRS updates; - auditably quarantine or repair the four legacy Geel detections. -- [ ] P2-03: isolate coverage by source/theme/layer/zone and make official - source identity server-attested. The mutable-name YOLO scope bypass is fixed - with a model/checksum-bound geometry manifest; equivalent legal-scope checks - still require the same review. -- [ ] P2-04: make derived persistence transactional, require complete - RunManifest hashes and expose every fallback/persistence failure. Detection - exports now carry a machine-readable trust contract and fail closed for - operational use without zero-error authoritative QA. -- [ ] P2-05: remove every protected-test feedback path, introduce a test vault - and make the sampler reject protected IDs, paths and assessment fields. -- [ ] P2-06: complete representative human V56 review; add independent AOIs, - Brussels pure backgrounds, difficult negatives and corrected temporal/dense - PICC/UrbIS labels; freeze a new immutable corpus rather than changing V56. -- [ ] P2-07: implement the metric/null/error-taxonomy contract, stratified - incumbent baseline, calibration and reproducibility rerun; freeze numeric - gates before protected-test access. -- [ ] P2-08: train the pre-registered candidate matrix on the Tower RTX 4080 - SUPER with pinned PyTorch/CUDA, full hashes, seeds and zero CPU fallback. -- [ ] P2-09: run a calibration-only improvement loop; use only independently - provisioned, reviewed train data for another corpus version. -- [ ] P2-10: open protected test/background-test exactly once for one immutable - pre-registered candidate; never retrain that candidate family from its result. -- [ ] P2-11: promote and redeploy only after every gate passes, with model card, - image/model/config hashes, shadow evidence and tested rollback. -- [ ] P2-12: monitor drift into a human reviewqueue without automatic - self-training or silent promotion. -- [x] Audit whether the July `reviewedexp6` checkpoint can be migrated into the - current runtime provenance contract without invented evidence; retain the - checksum-bound blocked report. -- [ ] Do not generate a production sidecar for `reviewedexp6`: its exact - training commit/runtime, immutable corpus-label-split manifests and accepted - human-review ledger were not retained and cannot be reconstructed safely. -- [x] Complete an explicitly AI-assisted per-AOI review of the 64-tile - reviewedexp6 contact sheet, retaining reviewer type, artifact hash, split - role, sample accounting and roof/ground-footprint limitations. -- [x] Extend AI-assisted review to all 252 tiles and 79,192 labels through - deterministic four-page contact-sheet rendering with complete accounting. -- [ ] Human-adjudicate the 43 possible nested same-class box pairs in 36 tiles; - do not rewrite or exclude them automatically because GRB objects can overlap - legitimately. -- [x] Persist a deterministic label-relationship audit and a focused 36-tile - contact sheet; AI follow-up found no systematic duplicate-label pattern. -- [x] Bind the relationship audit back to exact label-row indices and render - all 86 implicated rows with type-specific highlighting for focused review. -- [x] Audit all 79,192 labels at row level for sub-4-pixel dimensions, extreme - aspect ratio and tile-edge clipping; inspect the complete small/extreme - sheets and retain immutable hashes. -- [x] Reconstruct exact cross-tile interior objects and prove that overlap - repeats 40,031 label rows but causes zero reconstructed train/val crossings. -- [x] Build and fully audit an immutable experimental corpus with - `min_label_px=4`; retain 252 tiles and 77,380 labels with zero sub-4-pixel - rows, missing files, invalid labels or cross-split reconstructed objects. -- [ ] Compare the existing 0.35 edge-visibility policy against a separately - versioned stricter ablation from original source geometry before any new - governed training; do not approximate this by dropping every edge label. -- [x] Replace the overlapping checkpoint ranking with a checksum-bound, - training-disabled non-overlap view: 12 real tiles, 2,384 unique interior - objects, zero repeated interiors and explicit removal of blank Arendonk - no-data imagery. -- [ ] Add multiple independent real-background AOIs and more geographically - separated positive validation AOIs before interpreting non-overlap ranking - as release evidence. Postel occurs in both compared train splits and is only - a training-seen regression check, not independent validation. -- [x] Add a fail-closed checkpoint gate that checks every evaluation AOI - against every split of every supplied ancestral model corpus before PyTorch - import, model loading or GPU inference. Turnhout/Westerlo were exposed as - validation in the base building model; Postel was exposed as training. -- [ ] Convert the AI-assisted ledger into no stronger claim than experimental - triage; a real human must independently review and sign the frozen artifacts - before the governed training wrapper may unlock. -- [x] Provision and visually inspect six fresh non-protected calibration AOIs - across Vlaanderen, Wallonië and Brussel; prove all are at least 2 km from all - 31 resolved ancestral AOIs and absent from every ancestral split. -- [x] Reject overlapping edge-cover tiles in diagnostic evaluation; retain 24 - canonical 512 px cells and record all 30 excluded overlapping views. -- [x] Run active/challenger GPU calibration on the fresh portfolio and retain - aggregate, regional and per-AOI metrics without promoting either model. -- [ ] Provision a separately frozen train-only failure corpus after human - review. Do not copy V72 calibration tiles or use their labels for fitting. -- [ ] Finalise version-specific PICC/UrbIS semantic harmonisation contracts - before treating Walloon/Brussels metrics as release-grade ground truth. -- [x] Complete a responsive GUI audit at desktop, laptop and phone widths; - keep the map above model selection on phones, expose all navigation items - through a bottom rail and remove clipped result metrics. -- [ ] Repeat the responsive audit with a physical touch device and screen - reader before claiming full mobile accessibility certification. +Accuracy claims remain governed by [ACCURACY.md](ACCURACY.md); missing evidence +must fail closed and generated evidence must stay outside Git. diff --git a/docs/accuracy-program/00-execution-contract.md b/docs/accuracy-program/00-execution-contract.md deleted file mode 100644 index 97ee9da1..00000000 --- a/docs/accuracy-program/00-execution-contract.md +++ /dev/null @@ -1,189 +0,0 @@ -# Phase 1 execution contract - -- Status: **executed** -- Audit date: 2026-08-01 -- Audit branch: `codex/geointel-accuracy-program` -- Audited baseline commit: `0c019bb22f816db1e4b7a68379bcad08924d9a21` -- Product scope: Belgium and the Belgian North Sea -- Release conclusion: **blocked** -- Phase 2 conclusion: **safe to start as controlled remediation, not as training or promotion** - -## 1. Purpose - -This contract turns the accuracy program into an evidence-bearing engineering -program. Phase 1 establishes what exists, what actually runs, where data and -model results originate, which claims are supportable, and which defects must -be corrected before any new training or release promotion. - -Phase 1 is complete when the required inventory, lineage, baseline, risk, -metric, roadmap, machine-readable status and retained evidence exist and can be -reproduced. Completion of Phase 1 does **not** mean that GeoIntel is accurate, -nationally validated, release-ready, or fully trained. - -## 2. Non-negotiable rules - -1. No quality, coverage, authority, calibration or national-readiness claim may - be stronger than the retained evidence. -2. A green unit test that uses a fixture, mock, placeholder or source-text - assertion is not evidence of live geospatial or model quality. -3. Protected test data is never used for training, calibration, failure-driven - sampling, threshold selection or stopping decisions. -4. Dataset, label, tile, checkpoint, runtime and evaluation identities are - immutable hashes, not filenames or mutable display names. -5. Geometry entering persistence is validated, assigned an explicit source CRS, - transformed to the canonical CRS and checked for valid domain and units. -6. Official or authoritative status is server-attested; caller-controlled source - names can never establish authority. -7. Failed, unavailable and `not_configured` states remain explicit. A fallback - cannot silently be reported as a successful primary result. -8. Human review is only complete when reviewer identity, decision, timestamp, - sampled object/AOI identity and reviewed artifact hash are persisted. -9. Phase 1 does not delete, rewrite or promote datasets, checkpoints, caches, - outputs, migrations or server state. The GPU smoke is read-only and persists - no detections. -10. User-owned untracked files, including `.codex-artifacts/`, server - `.env.bak.*`, `.forgeflow/`, `storage/evaluation/` and - `storage/source-cache/`, remain untouched. - -## 3. Evidence vocabulary - -Every statement in this program uses one of these classes: - -| Class | Meaning | -|---|---| -| observed | Directly read from the repository, database, storage, runtime or retained artifact | -| reproduced | Deterministic read-only reproducer demonstrated the behavior | -| tested | An executable test or build gate ran and its result is retained or recorded | -| inferred | A conclusion drawn from observed evidence; it must be labelled as an inference | -| planned | Not implemented or not yet evidenced | -| unavailable | The required system or artifact could not be inspected; reason is stated | -| blocked | A required gate cannot pass without remediation | - -The words “implemented”, “configured”, “available”, “validated” and “promoted” -are not synonyms: - -- **implemented** means code exists; -- **configured** means a runtime selects it; -- **available** means dependencies/assets can be loaded; -- **validated** requires a registered evaluation and acceptance decision; -- **promoted** requires every release gate and an auditable activation record. - -## 4. Authorized Phase 1 mutations - -The only authorized repository mutations are: - -- audit collectors and deterministic reproducer scripts; -- focused tests for those collectors; -- `docs/accuracy-program/`; -- retained evidence under `artifacts/evidence/accuracy/P1/`; -- required execution-log and TODO updates; -- a selective `.gitignore` exception that tracks only the Phase 1 evidence - tree while keeping other generated `artifacts/` ignored. - -No product behavior, model checkpoint, dataset, label or production database row -is changed in Phase 1. - -## 5. Executed investigation surface - -The audit covered: - -- root and nested tracked source trees, Git state and ignored/untracked state; -- backend API routes, schemas, services, ORM entities and Alembic chain; -- frontend TypeScript, tests, typecheck and production build; -- CI/readiness scripts, container definitions and Tower deployment identity; -- Postgres/PostGIS table counts, statuses, lineage gaps and geometry integrity; -- mounted storage paths referenced by the database; -- active NVIDIA/PyTorch/Ultralytics runtime and active model hash; -- one existing Geel raster tile through the production YOLO adapter on - `cuda:0`; -- available Belgian building corpus, split, label, tiling, calibration, - checkpoint and human-review evidence; -- mocks, fixtures, fallbacks, placeholders and documentation drift. - -Detailed outcomes live in documents 01 through 06 and in the P1 evidence tree. - -## 6. Reproducibility entry points - -Run from the repository root: - -```powershell -python scripts/run_accuracy_phase1_baseline.py --output-dir artifacts/evidence/accuracy/P1 -python scripts/reproduce_accuracy_phase1_findings.py -python -m pytest tests/test_accuracy_phase1_baseline.py -q -p no:cacheprovider -``` - -The runtime/database collector is intentionally executed inside the deployed -application container and uses read-only SQL with a statement timeout: - -```text -scripts/collect_accuracy_phase1_runtime.py -``` - -The GPU collector is streamed into the deployed container and uses the -production adapter with an existing checksummed model, manifest and tile: - -```text -scripts/collect_accuracy_phase1_inference_smoke.py -``` - -Its retained JSON includes the model, manifest and tile SHA-256 values, package -versions, CUDA device, seed, configuration, raster CRS and raw output summary. -It explicitly forbids deriving an accuracy or release claim from one smoke. - -## 7. Proven release blockers - -Phase 1 reproduced or observed all of the following: - -- cross-theme coverage contamination can incorrectly return - `operational`; -- a nominal metre buffer is applied as degrees; -- Lambert coordinates can be persisted unchanged under SRID 4326; -- caller-controlled source identity can be elevated to authoritative coverage; -- YOLO validation scope is bypassable through a mutable Area-name substring; -- legal coverage identity changes when an Area display name changes; -- Area PATCH silently ignores a documented geometry field; -- four persisted Geel detections contain Lambert-domain coordinates while their - geometry column is labelled SRID 4326; -- the training loop contains a future protected-test feedback path; -- V56 has zero accepted human AOI reviews out of 180; -- split independence, pure-background coverage, temporal label alignment and - unique-object evaluation are insufficient; -- no candidate has protected-test, background-test and promotion evidence; -- the real CI pytest work directory fails during collection, the full root suite - has 17 stale assertion failures, Ruff has 112 findings and frontend lint is - not configured; -- the production AI image is not built or exercised by CI; -- a tracked nested source mirror contains 1,153 files, 68 of which differ from - root, creating source-of-truth ambiguity. - -## 8. Decision gates - -| Gate | Phase 1 decision | -|---|---| -| Runtime CUDA and active model load | pass | -| One production-adapter GPU inference | pass, runtime-only evidence | -| Database/storage reachability | pass for inspected references | -| Geometry/CRS integrity | fail | -| Authoritative-source integrity | fail | -| Coverage correctness | fail | -| Strict protected-test isolation | fail in code design | -| Human label acceptance | fail | -| Split independence and negatives | fail | -| Reproducible national metric baseline | absent | -| Backend release gate | fail | -| Lint and frontend lint | fail / absent | -| National model promotion | blocked | -| Start test-first Phase 2 remediation | allowed | - -## 9. Stop and escalation conditions - -Training and model promotion remain prohibited until Phase 2 has closed the -CRS, authority, coverage and protected-test isolation blockers and a frozen, -human-approved corpus exists. If a required source snapshot, reviewer decision, -immutable hash or independent holdout cannot be produced, the corresponding -claim remains blocked; it is never replaced by synthetic success. - -The protected test may be opened exactly once for a pre-registered candidate -after all calibration gates pass. A failure after that opening creates a new -model-development cycle and requires a newly governed protected set; its errors -must not feed back into the same training lineage. diff --git a/docs/accuracy-program/01-system-inventory.md b/docs/accuracy-program/01-system-inventory.md deleted file mode 100644 index b99e417d..00000000 --- a/docs/accuracy-program/01-system-inventory.md +++ /dev/null @@ -1,158 +0,0 @@ -# GeoIntel Accuracy Improvement Program — 01 Systeeminventaris - -## 1. Doel, peildatum en claimgrens - -Dit document beschrijft de aantoonbaar aanwezige GeoIntel-componenten op 1 augustus 2026. Het is een forensische inventaris, geen kwaliteitscertificaat. `implemented` betekent dat code en een contractpad bestaan; `configured` betekent dat de betreffende runtimeconfiguratie daadwerkelijk is waargenomen; `fixture/mock` betekent dat het pad alleen test- of demobewijs levert; `planned/unproven` betekent dat geen uitvoerbaar productiebewijs is gevonden. - -De inventaris is opgebouwd uit: - -- checkout `C:\Projects\geointel` op branch `codex/geointel-accuracy-program`, basis-HEAD `0c019bb22f816db1e4b7a68379bcad08924d9a21`; -- Tower-checkout `/mnt/user/appdata/geointel` op branch `main`, dezelfde HEAD; -- draaiende container `/geointel`, image `geointel-all-in-one:0c019bb22f81-wipfdc62947dfb2-ai`, status `running`, health `healthy`; -- read-only runtime-/databasecollectie in `C:\Projects\geointel\artifacts\evidence\accuracy\P1\tower-runtime-database-snapshot-detailed.json`; -- read-only GPU-smoke in `C:\Projects\geointel\artifacts\evidence\accuracy\P1\tower-gpu-inference-smoke.json`; -- retained model-, checkpoint-, corpus- en splitinventaris in `C:\Projects\geointel\artifacts\evidence\accuracy\P1\tower-ml-data-lineage-snapshot.json`; -- lokale repository- en artifactinventaris in dezelfde evidence-map. - -Geen bevinding in dit document bewijst nationale modelkwaliteit, menselijk gevalideerde labels, calibratie, geografische generalisatie of releasegeschiktheid. - -## 2. Uitvoerbare productarchitectuur - -| Onderdeel | Concrete code-/configpaden | Status | Bewezen runtime-/teststatus | Accuracy-grens | -|---|---|---|---|---| -| React/TypeScript workbench | `frontend/src/App.tsx`, `frontend/src/components`, `frontend/src/hooks`, `frontend/src/services` | implemented | 16 frontend-testbestanden; Vitest 51/51, typecheck en productiebuild slaagden in de Phase-1-baseline | UI-werking bewijst geen inhoudelijke GIS- of modeljuistheid | -| Mapweergave en gebiedsselectie | `frontend/src/components/map/MapWorkspace.tsx`, MapLibre dependency in `frontend/package.json` | implemented | compileert en is unit-getest; geen volledige browser-E2E-uitvoering in de releasegate | selectie-UX is geen bewijs dat server-side scope/CRS correct is | -| FastAPI HTTP-laag | `backend/app/main.py`, `backend/app/api/routes/*.py` | implemented | 148 route-decorators statisch gevonden; OpenAPI-audit zag 147 routes, waarvan 10 contractueel toegestane niet-envelope routes | route-aanwezigheid bewijst geen correcte gegevensinhoud | -| Projecten en AOI's | `project_service.py`, `area_service.py`, routes `projects.py` en `areas.py` | implemented, persisted | 1.097 projecten en 387 gebieden in Tower; alle 387 gevulde gebiedsgeometrieën geldig, SRID 4326 en binnen het 4326-domein | Area PATCH en naamgebaseerde wettelijke scope hebben bewezen contract-/integriteitsgaten | -| Datasetinname en versies | `dataset_service.py`, `storage_service.py`, `datasets.py` | implemented, persisted | 3.377 datasets, alle status `ready`; 1.671 datasetversies; 5.816 directe storage-referenties gecontroleerd, 0 ontbrekend | `ready` is een verwerkingsstatus, geen bronautoriteit of inhoudelijke kwaliteitsclaim | -| Rasterverwerking | `raster_service.py`, `raster_operations_service.py`, acquisitieservices voor orthofoto/DHMV/WALOUS/SPW | implemented | raster- en GIS-gerichte tests slaagden; bestaande Tower-tiles konden read-only worden geopend | geen volledige corpusbrede rasteralignment-/nodata-/resolutieaudit afgerond | -| Vectorverwerking | `vector_feature_service.py`, `vector_operations_service.py`, officiële-vectoracquisitie | implemented, persisted | 6.689.447 `vector_features`; alle gevulde geometrieën geldig, SRID 4326 en binnen domein in de gebonden DB-query | buffer, import-CRS en afgeleide-featurepersistentie hebben kritieke gereproduceerde fouten | -| Bron- en dekkingsresolutie | `providers/*`, `coverage_registry_service.py`, `source_catalog_probe_service.py` | implemented | 28 waargenomen `source_name`-waarden in de DB; officiële en fixtureproviders zijn afzonderlijk gemodelleerd | bronautoriteit kan via uploadmetadata worden gespooft; dekking kan door een andere themalaag worden overschat | -| Achtergrondjobs/AOI-operations | `job_service.py`, `aoi_operation_service.py`, `aoi_operation_worker.py`, `backend/app/workers` | implemented, configured | 4.460 jobs: 4.325 success, 135 failed; 4 AOI-operations en 61 partitions; geen lopende job/run tijdens snapshot | status `success` is geen accuracy-gate; foutpercentages zijn niet per workflow genormaliseerd | -| Objectdetectieadapter | `detection_service.py`, `detection_georeferencing.py`, `yolo_adapter.py`, `yolo_preflight_service.py` | implemented, configured op Tower | 1.146 detectieruns: 1.144 success, 2 failed; 299.233 detecties; één read-only productieadapter-smoke op GPU slaagde | actieve modelscope wordt op een muteerbare gebiedsnaam afgedwongen; modelversie is leeg; smoke bewijst geen accuracy | -| Modelregister | `model_registry_service.py`, runtimeinstellingen in `backend/app/core/config.py` | mixed | actief YOLO-pad bestaat; register toont daarnaast expliciet `yolo-placeholder` en `manual-fixture-detector` | placeholder/fixture mogen niet als productie-inference of kwaliteitsbewijs worden geteld | -| Segmentatie | `segmentation_service.py`, `segmentation_adapter.py`, routes `segmentation.py` | abstraction implemented; production unproven | modelregister bevat `segmentation-placeholder` en `fixture-segmenter`; Tower bevat 0 segmentaties | geen bewijs van geconfigureerde productie-segmentatie of modelkwaliteit | -| QA/QC en metrics | `qa_service.py`, `quality_service.py`, `detection_qa_service.py`, routes `qa.py` en `quality_checks.py` | implemented, persisted | 697 quality checks en 4.182 metricrijen; 4-scenario golden fixturebenchmark slaagde | metricnulls en ongedefinieerde no-overlap-F1 vereisen een expliciet contract; fixturebenchmark is geen veldbenchmark | -| Exports | `export_service.py`, route `exports.py` | implemented, persisted | 768 exportrecords; directe storage-referenties zaten in de 5.816 gecontroleerde records | een export kan een foutief upstreamresultaat correct serialiseren | -| Demo/fixtures | `demo_workflow_service.py`, `providers/fixture.py`, `fixtures/*` | fixture/demo only | expliciet gemarkeerde fixtureprovider en handmatige fixturemodellen | nooit meenemen in productie- of nationale accuracyclaims | -| Training- en audittooling | `scripts/run_belgium_building_training_loop.py`, `scripts/evaluate_belgium_building_candidate.py`, corpus-/label-/qualityscripts | implemented tooling; release linkage incomplete | omvangrijke Tower-runs en checkpoints aanwezig; v56 automated audits en v62 previewcalibratie aantoonbaar | protected-testfeedback lekt terug naar volgende sampling; 0/180 v56-corpussamples menselijk gereviewd; geen geldige nationale promotieclaim | -| Deployment | `deploy/unraid/Dockerfile.all-in-one`, `docker-compose.unraid.yml`, `deploy/unraid/*` | implemented, configured op Tower | all-in-one-container gezond; NVIDIA GPU doorgegeven | compose-default `cu130` en feitelijke image/runtime `cu128` zijn supply-chain/builddrift; CI bouwt standaard zonder AI | -| Documentatie/contracts | `docs/API_CONTRACTS.md`, `docs/DATABASE_IMPLEMENTATION_PLAN.md`, scope freezes en DoD | implemented but drifted | contracttests bestaan | meerdere documenten beschrijven historische of geplande toestand die niet met de runtime overeenstemt | - -## 3. Repositoryomvang en bronstaat - -De machineleesbare inventaris staat in `artifacts/evidence/accuracy/P1/repository-inventory.json`. - -| Groep | Bestanden | Regels | -|---|---:|---:| -| backend applicatie | 129 | 32.583 | -| backend tests | 235 | 36.067 | -| frontend broncode | 112 | 23.534 | -| frontend E2E-scripts | 2 | 734 | -| migraties | 11 | 610 | -| root tests | 7 | 261 | -| scripts | 158 | 43.180 | - -Aanvullend zijn 1.182 `test_*`-functies, 16 frontend-testbestanden en 148 API-route-decorators statisch geteld. Dit zijn omvangmetingen, geen bewijs dat iedere test of route correct is. - -De checkout bevat 2.495 tracked files. Daarvan zijn 1.153 bestanden een tweede, tracked repositorykopie onder `geointel/`: 1.085 gepaarde bestanden zijn byte-identiek en 68 verschillen van hun roottegenhanger. Docker sluit `/geointel` expliciet uit, maar lokale imports, zoekresultaten en scripts kunnen toch de verkeerde kopie raken. Verder zijn onder meer 109 tracked bestanden onder `.codex-input`, 27 onder `data`, één onder `output` en vier onder `test-results` aangetroffen. Phase 1 verwijdert of overschrijft deze user-/historieartefacten niet. - -## 4. Runtime en persistence op Tower - -### 4.1 Platform - -| Eigenschap | Waargenomen waarde | -|---|---| -| Host/containerplatform | Linux 6.12.54 Unraid, x86_64 | -| Python | 3.11.2 | -| PostgreSQL | 16.14 | -| PostGIS | extension 3.6.4; core procedures melden nog 3.4.3 en `need upgrade` | -| Alembic-head | `202607260001` (één lineaire statische en runtime-head) | -| PyTorch | `2.11.0+cu128` | -| torchvision | `0.26.0+cu128` | -| Ultralytics | `8.4.99` | -| CUDA-runtime | 12.8 | -| GPU | één NVIDIA GeForce RTX 4080 SUPER; CUDA beschikbaar | -| GIS-libraries | GeoPandas 1.1.4, Rasterio 1.4.4, Shapely 2.1.2, pyproj 3.7.2, GeoAlchemy2 0.20.0 | - -### 4.2 Persistente aantallen - -| Tabel | Rijen | Tabel | Rijen | -|---|---:|---|---:| -| `projects` | 1.097 | `areas` | 387 | -| `datasets` | 3.377 | `dataset_versions` | 1.671 | -| `vector_features` | 6.689.447 | `analysis_runs` | 1.146 | -| `detections` | 299.233 | `segmentations` | 0 | -| `detection_reviews` | 0 | `quality_checks` | 697 | -| `metrics` | 4.182 | `jobs` | 4.460 | -| `exports` | 768 | `aoi_operations` | 4 | -| `aoi_operation_partitions` | 61 | | | - -De snapshot gebruikte `statement_timeout=30000` ms en read-only queries. De volledige recursieve storageaudit eindigde in een time-out en is dus geen pass; de aparte controle van alle 5.816 directe `storage_path`-referenties voltooide wel en vond 0 ontbrekende bestanden. Niet-gerefereerde, geneste of semantisch verkeerde artefacten vallen buiten dat resultaat. - -## 5. Modellen en trainingsartefacten - -### 5.1 Actief productiepad - -| Veld | Waarde | -|---|---| -| Containerpad | `/app/models/geointel-building-yolov8s-smallbld-minpx3-img640-ft30.pt` | -| Hostpad | `/mnt/user/appdata/geointel/models/geointel-building-yolov8s-smallbld-minpx3-img640-ft30.pt` | -| SHA-256 | `a9088b8491dfae36694b53e9e9406cb4e3511d334a5712fa34f75078a47759c1` | -| Grootte | 22.516.074 bytes | -| Geconfigureerde klasse | `building` | -| Device | `cuda:0`, CUDA verplicht | -| Geconfigureerde validatienamen | `Mol,Kempen` | -| Modelversie | leeg | - -De hash identificeert het actieve bestand. Er is geen aangetoonde release-/dataset-/commitketen die deze hash koppelt aan een menselijk gereviewd, beschermd testresultaat. De scopecheck gebruikt bovendien een substring in `Area.name`, niet een onveranderlijke geografische scope. - -De GPU-smoke gebruikte één bestaande 512×512 RGB GeoTIFF in EPSG:31370 en de productieadapter met seed `20260801`, deterministische algoritmen, `imgsz=640`, confidence `0.5` en `max_det=1000`. Het model produceerde 17 `building`-boxes in 0,884 s inference; dat bewijst alleen dat één adapter-call op de NVIDIA-GPU uitvoer gaf. - -### 5.2 Niet-actieve recente checkpoints - -De retained Tower-inventaris telt 26 modelassets in `/app/models`, 229 trainingscheckpoints met samen 28.512.052.142 bytes, 424 JSON-trainingsrapporten en 36 operator-manifests. Dit zijn aanwezigheidsaantallen; de collector claimt uitdrukkelijk geen human label acceptance, strikte splitonafhankelijkheid, protected-testprestatie, nationale geldigheid of release readiness. - -Onder de niet-actieve checkpoints bestaan onder meer: - -- `/mnt/user/appdata/geointel/storage/training/building-be-v62-v58-flanders-balanced-transfer-r1/runs/flanders/weights/best.pt`, 456.136.473 bytes, SHA-256 `889ee5b3bfe722803542d15a53a51a716872cf0e8516da5e8291e0a2605adbdb`; -- `/mnt/user/appdata/geointel/storage/training/building-be-v62-v58-flanders-balanced-transfer-r1/runs/flanders/weights/last.pt`, 456.136.985 bytes, SHA-256 `08d12061f017c45c123c824ffa043bc07794beef251c903299eb1e0954636c8b`. - -Aanwezigheid is geen activatie of promotie. Het v62-pad heeft in de geïnspecteerde run alleen preview-calibratiebewijs op 144 tiles; geen protected-test-, achtergrondtest- of releasebundel werd daar aangetroffen. De meest recente geïnspecteerde v66-manifestversie bevat slechts drie Vlaamse `train`-samples, nul background-test-samples en geen andere regio/split; ze is een gerichte proef, geen opvolgende nationale corpusrelease. - -### 5.3 Lokale checkout - -De lokale artifactscanner inventariseerde 193 bestanden (84.874.287 bytes) onder `models`, `datasets`, `data`, `storage`, `artifacts` en `output`: 114 rasters, 32 overige bestanden, 21 runtime-databasebestanden, 13 visuele-reviewbestanden, 6 evaluatie/auditbestanden, 5 manifests en 2 vectors. Er staat lokaal geen modelcheckpoint. Grote bestanden zijn bewust niet allemaal gehasht; aanwezigheid van contact sheets telt niet als menselijke review. - -## 6. Build-, CI- en configuratiedrift - -- De lokale audit draaide met Python 3.13.2, Node 24.18.1 en npm 11.16.0; CI is ingericht op Python 3.11 en Node 20. Een lokaal groen resultaat is daarom niet automatisch een CI-runtimebewijs. -- `docker-compose.unraid.yml` bouwt standaard met `GEOINTEL_INSTALL_AI=false` en noemt als Torch-index `cu130`; de actieve Tower-runtime is een AI-image met Torch/CUDA `cu128`. `deploy/unraid/Dockerfile.all-in-one` en deployscripts vormen dus een tweede, afwijkend buildpad. -- GitHub- en Gitea-workflows voeren `scripts/run_readiness_check.sh` uit. Die gate compileert code, draait backendtests, Alembic heads, frontend unit/typecheck/build, maar controleert de E2E- en veel live-workflows alleen met `node --check` of `bash -n`. -- `frontend/package.json` heeft geen `lint`-script en geen ESLint-configuratie, hoewel linting in de teststrategie wordt verwacht. `python -m ruff check backend scripts tests` meldde 112 bevindingen (E402 13, E701 2, E702 69, F401 23, F403 1, F811 2, F841 2) en zit niet in de huidige readinessgate. -- De CI bouwt niet aantoonbaar de AI/CUDA-image en controleert geen hash-lock voor de PyTorch/Ultralytics-artifactketen. - -## 7. Reproduceerbare inventariscommando's - -Vanaf `C:\Projects\geointel`: - -```powershell -python scripts\run_accuracy_phase1_baseline.py --output-dir artifacts\evidence\accuracy\P1 -python scripts\collect_accuracy_phase1_runtime.py --help -python scripts\collect_accuracy_phase1_inference_smoke.py --help -git rev-parse HEAD -git status --short -``` - -De laatste twee collectors zijn ontworpen om in de Tower-container tegen `/app/storage` en `/app/models` te draaien; de bewaarde outputs zijn de JSON-bestanden in `artifacts/evidence/accuracy/P1`. Voor serveridentiteit is read-only geverifieerd: - -```bash -cd /mnt/user/appdata/geointel -git rev-parse HEAD -git branch --show-current -docker inspect geointel --format '{{.Config.Image}} {{.State.Status}} {{.State.Health.Status}}' -``` - -## 8. Inventarisconclusie - -GeoIntel is geen mockplatform: de workbench, API, PostGIS-persistentie, provider- en analysekaders, jobs, exports, QA/QC en een echte CUDA-YOLO-adapter zijn aantoonbaar geïmplementeerd en draaien. Even aantoonbaar is dat meerdere kritieke correctheidsgrenzen ontbreken of omzeild kunnen worden. Segmentatie is niet als productiemodel bewezen, fixturepaden blijven aanwezig, recente training is niet naar een geldige releaseketen gepromoveerd en geen enkel Phase-1-resultaat ondersteunt “100% getraind” of nationale nauwkeurigheid. diff --git a/docs/accuracy-program/02-data-lineage.md b/docs/accuracy-program/02-data-lineage.md deleted file mode 100644 index d476e810..00000000 --- a/docs/accuracy-program/02-data-lineage.md +++ /dev/null @@ -1,250 +0,0 @@ -# GeoIntel Accuracy Improvement Program — 02 Data-lineage - -## 1. Scope en bewijsregel - -Deze lineage-audit volgt een resultaat terug naar project/AOI, bronbestand, datasetversie, tile of vectorfeature, model of algoritme, runparameters, QA/QC en export. Een veld dat in het schema bestaat maar leeg is, geldt niet als lineagebewijs. Een door de gebruiker aangeleverde string geldt evenmin als bewijs van officiële bronautoriteit. - -De runtimecijfers komen uit de gebonden read-only snapshot van 1 augustus 2026 in: - -- `C:\Projects\geointel\artifacts\evidence\accuracy\P1\tower-runtime-database-snapshot-detailed.json`; -- `C:\Projects\geointel\artifacts\evidence\accuracy\P1\tower-gpu-inference-smoke.json`; -- `C:\Projects\geointel\artifacts\evidence\accuracy\P1\tower-ml-data-lineage-snapshot.json`. - -Containerpaden beginnen met `/app`; dezelfde persistente volumes staan op de host onder `/mnt/user/appdata/geointel`. - -## 2. Canonieke resultaatketen - -```mermaid -flowchart LR - S["Externe bron of upload"] --> F["Bestand / API-respons"] - F --> D["Dataset + DatasetVersion"] - D --> V["VectorFeature(s)"] - D --> T["Rastertiles + manifest"] - V --> A["AnalysisRun / geoprocessing"] - T --> M["Modelbestand + adapter"] - M --> R["Detection / Segmentation"] - A --> Q["QualityCheck + Metric"] - R --> Q - A --> E["Export"] - R --> E - Q --> E -``` - -De feitelijke persistencevelden staan in `backend/app/models/entities.py`: - -- `Dataset`: `project_id`, `area_id`, `storage_path`, `checksum_sha256`, `derived_from_dataset_id`, CRS/bounds/resolutie/banden, `dataset_role`, `source_name`, `reference_layer_name`, source- en provenance-metadata, tijdvelden, `source_version` en status; -- `DatasetVersion`: versie, storagepad, checksum, bronversie, observatietijd, validiteitsvenster en source/provenance-metadata; -- `VectorFeature`: `dataset_id`, bronfeature-id, klasse, properties en PostGIS-geometrie met SRID 4326; -- `AnalysisRun`: project/AOI/dataset/job, analysetype, status, modelnaam/-versie, parameters, resultaat en tijden; -- `Detection`/`Segmentation`: dataset/run/job, modelnaam/-versie, klasse, confidence, EPSG:4326-geometrie, pixelbbox, bron-tile en properties/provenance; -- `QualityCheck` en `Metric`: kandidaat-, referentie- en runkoppelingen, parameters, bevindingen en losse metricwaarden; -- `Export`: project, optionele run, type, storagepad en metadata. - -Dat is een bruikbaar schema, maar de audit toont breuken tussen schema, invoercontrole en opgeslagen werkelijkheid. - -## 3. Brondatasets en versies - -### 3.1 Volledigheid van kernvelden - -| Controle | Datasetresultaat | DatasetVersion-resultaat | Interpretatie | -|---|---:|---:|---| -| totaal | 3.377 | 1.671 | alle 3.377 datasets hebben status `ready` | -| checksum ontbreekt | 0 | 0 | bestandsidentiteit is op rijniveau aanwezig | -| CRS ontbreekt | 0 | n.v.t. | aanwezigheid bewijst nog niet dat coördinaten correct getransformeerd zijn | -| `imported_at` ontbreekt | 0 | n.v.t. | importtijd is gevuld | -| source metadata ontbreekt | 0 | 0 | metadataobject aanwezig; semantische authenticiteit niet bewezen | -| provenance metadata ontbreekt | 0 | 0 | provenanceobject aanwezig; inhoud kan caller-controlled zijn | -| storagepad ontbreekt | n.v.t. in deze query | 0 | 5.816 directe storagepaden apart fysiek gecontroleerd | -| `observed_at` ontbreekt | 2.377 | niet in deze gapquery | bronfamiliebeleid nodig: sommige vaste/scenariobronnen kunnen legitiem geen observatietijd hebben | -| `source_version` ontbreekt | 1.761 | niet in deze gapquery | geen betrouwbare freshness/reproduceerbaarheid zonder bronfamilieclassificatie | - -“Metadata aanwezig” mag niet worden omgezet in “officiële lineage geldig”. `POST /datasets/upload` in `backend/app/api/routes/datasets.py:142-163` laat de caller `source_name`, `reference_layer_name`, source-/provenance-metadata en `source_version` invullen. De dekkingsresolver vertrouwt die waarden later als materialisatiebewijs. Een in-memory reproductie met een user-upload die zich als `grb`/`buildings` presenteerde, werd als operationele, gezaghebbende GRB-dekking teruggegeven. Er is dus een cryptografische bestandsketen, maar geen afgedwongen bronautoriteitsketen. - -### 3.2 Waargenomen bronnen - -De volgende rijen zijn feitelijk in de Tower-database waargenomen. `reference` is alleen de opgeslagen datasetrol/-metadata, geen onafhankelijke bevestiging door de genoemde instantie. - -| `source_name` | datasets | reference | -|---|---:|---:| -| `manual` | 1.751 | 660 | -| `vmm_flood_hazard` | 339 | 0 | -| `vmm_vha_bathymetry_profiles` | 273 | 273 | -| `department_omgeving_thematic_raster` | 210 | 0 | -| `grb` | 179 | 179 | -| `digitaal_vlaanderen_orthophoto` | 168 | 0 | -| `spw_orthophoto` | 107 | 0 | -| `spw_picc` | 68 | 68 | -| `digitaal_vlaanderen_dhmv` | 60 | 0 | -| `urbis` | 36 | 36 | -| `urbis_orthophoto` | 26 | 0 | -| `waterinfo` | 26 | 26 | -| `department_omgeving_land_use` | 25 | 25 | -| `historical_landuse` | 21 | 21 | -| `agentschap_landbouw_zeevisserij_agricultural_parcels` | 18 | 18 | -| `statbel` | 15 | 15 | -| `dov_soil_map` | 13 | 13 | -| `inbo_bwk_natura2000` | 12 | 12 | -| `spw_walous_land_cover` | 7 | 0 | -| `vrbg` | 6 | 0 | -| `fixture` | 5 | 1 | -| `ngi_adminvector` | 4 | 4 | -| `map_selection` | 3 | 0 | -| `digitaal_vlaanderen_buildings_addresses_register` | 1 | 1 | -| `rbins_marine_reporting_units` | 1 | 1 | -| `rbins_msp_2026` | 1 | 1 | -| `spw_bathymetry` | 1 | 0 | -| `spw_terrain` | 1 | 0 | - -Deze telling bewijst historische materialisatie, niet dat iedere externe endpoint op de peildatum bereikbaar of actueel was. - -## 4. Vectorlineage - -### 4.1 Bedoelde keten - -`bron/upload -> Dataset + checksum/CRS/provenance -> VectorFeature rows -> spatial operation/AnalysisRun -> derived Dataset -> QA/export`. - -De database bevat 6.689.447 vectorfeatures. De gebonden PostGIS-query vond 0 lege, 0 ongeldige, 0 niet-4326 en 0 buiten-4326-domeingeometrieën in de huidige tabel. Dat sluit drie concrete codeproblemen niet uit: - -1. `backend/app/services/geojson_service.py:70-94` leest CRS-metadata, maar `vector_feature_service.py:271-299` krijgt die CRS niet mee en schrijft iedere feature met `srid=4326`. Een EPSG:31370-geometrie rond `(150000, 210000)` kon daardoor ongetransformeerd als 4326 worden opgebouwd. De huidige tabelquery bewijst alleen dat zo'n waarde nu niet in `vector_features` staat; het importpad blijft foutgevoelig. -2. `vector_operations_service.py:179-190` voert `geometry.buffer(distance_m)` uit op de geladen geometrie zonder metrische reprojection. De retained reproductie van een 100-meterbuffer leverde 200 graden span en bounds `[-95, -49, 105, 151]`. -3. `_persist_derived_dataset` heeft in `vector_operations_service.py:414-427` standaard `persist_vector_features=False`. Clip, buffer en intersect kunnen daardoor een `ready` GeoJSON-artifact en dataset opleveren zonder querybare `vector_features`, zonder AnalysisRun-koppeling en met een niet-atomische persistenceketen. - -Lineageconclusie: validiteit van de huidige PostGIS-rijen is bewezen; een algemeen correct vectorimport-/operatiecontract is dat niet. - -## 5. Raster- en tilelineage - -Een rasterdataset bewaart bestandspad, checksum, CRS, bounds, resolutie en bandmetadata. Inference gebruikt een tegelmap onder `/app/storage/tiles////` met `manifest.json` en GeoTIFF-tiles. - -De representatieve read-only smoke gebruikte: - -| Artifact | Pad | SHA-256 | -|---|---|---| -| manifest | `/app/storage/tiles/cb80638d-dbef-48ac-b19c-cec7c3efc96e/ae0ff76d-70c0-404f-b777-54d14517179a/b191c968-7d56-4e0d-afbb-8b5baaa62470/manifest.json` | `6ab8a96bf2a1405e224932afb90255311a09bbeaed4e9a2fdcdf8b1bc2230abd` | -| tile | dezelfde map, `tile_0000.tif` | `134a9e86850c92c577c73bc6ee57a9df7d4c1c513ae6450263e800b6dd47b6ee` | -| actief model | `/app/models/geointel-building-yolov8s-smallbld-minpx3-img640-ft30.pt` | `a9088b8491dfae36694b53e9e9406cb4e3511d334a5712fa34f75078a47759c1` | - -De tile is 669.227 bytes, 512×512, 3×`uint8`, CRS EPSG:31370, resolutie 0,9765625 meter/pixel en bounds `[193277.53584918313, 205708.27443503588, 193777.53584918313, 206208.27443503588]`. Dit is voldoende om deze ene inference-input exact te identificeren. Er is nog geen corpusbrede toets op duplicate/near-duplicate imagery, nodata, source-date/label-date, WMS-resampling, grenspadding of resolutieconsistentie. - -## 6. Detectielineage - -### 6.1 Persistente productieketen - -`Dataset -> tile manifest -> AnalysisRun(parameters/model_name/model_version) -> Detection(source_tile_path/pixelbbox/confidence/EPSG:4326 geometry) -> QualityCheck/Metrics -> Export`. - -Tower bevat 1.146 `analysis_runs`, alle type `detection` met modelnaam `yolo-configured`: 1.144 success en 2 failed. Daaruit zijn 299.233 detecties aanwezig. Geen confidence lag buiten `[0,1]`. De modelversie is bij alle 1.146 runs leeg. 1.143 runs bewaren wel een modelassethash; drie niet. Alle runs bewaren een tile-manifestpad, maar geen tile-manifest-SHA, runtime-/hardware-identiteit of seed. De drie hashloze runs zijn niet sluitend aan een checkpoint te koppelen; ook de overige missen het volledige reproduceerbare inferencecontract. - -De read-only smoke riep de productieadapter rechtstreeks aan met seed `20260801`, deterministische algoritmen, confidence 0,5, `imgsz=640`, `max_det=1000` en `cuda:0`. Resultaat: 17 `building`-boxes, confidence 0,500877–0,814435, gemiddelde 0,559481. De smoke schreef geen DB-records en testte dus niet de volledige georeference-/persistence-/QA-keten. - -### 6.2 Bewezen historische lineagebreuk - -Vier detecties in run `7ba34274-411d-45e3-8f54-c37baec598b1` hebben een PostGIS-geometrie met SRID 4326 maar numerieke Lambertwaarden rond X 193.278–193.774 en Y 205.708–206.054. Alle vier verwijzen naar: - -- project `GeoIntel Real Data Validation 20260706T235847Z`; -- dataset `ae0ff76d-70c0-404f-b777-54d14517179a`, `geel_orthophoto_wms_512.tif`, bron `manual`; -- tile `/app/storage/tiles/cb80638d-dbef-48ac-b19c-cec7c3efc96e/ae0ff76d-70c0-404f-b777-54d14517179a/b191c968-7d56-4e0d-afbb-8b5baaa62470/tile_0000.tif`; -- creatietijd 6 juli 2026 en class `building`. - -Dit zijn aantoonbaar buiten-domeindetecties; de collector markeerde de sectie desondanks generiek als `status: ok`, zodat consumenten de detailtellingen moeten gebruiken. De huidige `detection_georeferencing.py` bevat wel een pyproj-transformatie naar EPSG:4326; op basis van deze audit kan niet worden bewezen via welke historische codeversie de vier rijen ontstonden. Ze mogen niet in QA, kaarten of exports blijven zonder quarantaine/herberekening. - -### 6.3 Scopebinding - -`detection_service.py:223-232` laat configured YOLO alleen toe wanneer één van `Mol,Kempen` als substring in de muteerbare `Area.name` voorkomt. Een area met naam `Mol validation bypass` en een geometrie buiten de gevalideerde zone werd in de reproductie geaccepteerd. De model-toepassingsscope heeft daardoor geen onveranderlijke geometrische lineage. - -## 7. QA/QC-, review- en exportlineage - -Tower bevat 697 quality checks en 4.182 metrics. De metricgapquery toont: - -| Metric | total checks | null | -|---|---:|---:| -| precision | 697 | 58 | -| recall | 697 | 1 | -| F1 | 697 | 58 | -| mean IoU | 697 | 90 | -| false positives | 697 | 0 | -| false negatives | 697 | 0 | - -De golden fixturebenchmark koppelt kandidaat/referentie, QualityCheck en zes metrics correct in-memory. Bij het no-overlapscenario zijn precision en recall `0`, maar F1 en mean IoU `null`. Zolang het API-/metriccontract niet expliciet vastlegt of F1 daar `0` of “undefined” hoort te zijn, kunnen aggregaties dezelfde run verschillend behandelen. - -Er staan 0 `detection_reviews` in de productiedatabase. De aanwezigheid van review-UI, contact sheets of reviewtabellen bewijst dus geen uitgevoerde menselijke productiereview. De 768 exportrecords verwijzen naar concrete storagepaden; dat bewijst artifactpersistentie, niet dat upstream geometrie/model/QA correct was. - -## 8. Trainings- en corpuslineage - -### 8.1 Bewezen v56-keten - -De retained snapshot telt in totaal 26 modelassets, 229 trainingscheckpoints (28.512.052.142 bytes), 424 JSON-trainingsrapporten en 36 operator-manifests. Die inventarisclaim zegt niets over menselijke acceptatie of releasekwaliteit. - -Het canonieke v56-manifest is `/app/storage/operator-data/building-be-v56-hard-negative-instance-roofs-r1/operator_samples_manifest.json`, 212.185 bytes, SHA-256 `27a9b09f184bb9a0cc4897f1cfab7f1e953af5715c1b97a5ec1a7b80a2d270f1`. De corpusaudit `/app/storage/training/building-be-v56-corpus-audit-r1/belgium-building-corpus-audit.json` (SHA-256 `cbb9802aec1b780b306318fc172e470d29166574e9bf13d28e3107ae42f4d63c`) rapporteert: - -- datasetversie `building-be-v56-hard-negative-instance-roofs-r1`, immutable manifest; -- 180 AOI-samples: Vlaanderen 89 train/2 val/3 calibration/3 test/2 background-test; Wallonië 43/2/3/3/2; Brussel 18/2/3/3/2; -- 132 positieve samples en 48 `background_candidate`-samples; -- 31.452 inputfeatures, 30.662 geaccepteerd, 326 onder resolveerbare pixelgrootte en 464 na de beeldperiode; -- automated `spatial_leakage_status=ok` en 0 temporal-unknown samples; -- `status=needs_human_review`, `reviewed_sample_count=0`, `review_complete=false`, alle 180 in de reviewqueue. - -Van de zes `background-test`-AOI's zijn er slechts drie aantoonbaar puur leeg: twee in Vlaanderen, één in Wallonië en nul in Brussel. De andere drie bevatten respectievelijk 2, 107 en 141 referentiefeatures en zijn moeilijke negatieven, geen pure backgrounds. Dit is te weinig om een regionale pure-background false-positiveclaim te dragen. - -De bounded duplicaatscreen vond 0 exacte cross-split rasterhashduplicates en 0 hergebruikte raster-dataset-id's. Voor 4.833 cross-split dHash-paren was de minimum-Hammingafstand 17 en waren er geen paren op of onder 4. Dat sluit semantische, instance-level of flight-stripduplicatie niet uit. De AOI-bboxscreen vond een minimale cross-splitafstand van 95,7203 meter tussen `anderlecht-industry-train` en `jette-test`, 24 paren onder 2 km en 0 onder 64 meter. De auditstatus `ok` is daarom niet voldoende voor de strengere onafhankelijkheidseis; nabijheid is een risico dat instance-/imagerylineage vereist, geen bewijs op zichzelf van leakage. - -De tile-qualityaudit `/app/storage/training/building-be-v56-rotated-quality-audit-r1/operator_yolo_dataset_quality_audit.json` (SHA-256 `da0d4648ee2365ab949f1b00518ddba0a17cb722a41cb228525b4d2e7657ce36`) rapporteert geautomatiseerd `status=ok`, 2.496 tiles, 60.229 labels, 0 ongeldige/missende labelfiles, 2.072 positieve en 424 negatieve tiles, waarvan 411 negatieve trainingtiles. Dat syntactische bewijs vervangt de ontbrekende menselijke semantische review niet. - -De v58/v62-calibratierapporten verwijzen naar een afgeleide root `/app/storage/operator-data/building-be-v56-hard-negative-rotated-holdouts-r1`. Een releasebundel moet de transformatie van het canonieke instance-roofs-manifest naar deze rotated-holdouts-dataset expliciet, gehasht en reproduceerbaar vastleggen. - -### 8.2 Bewezen v58/v62-preview, niet gepromoveerd - -V58 `/app/storage/training/building-be-v58-v56-clean-pretrained-r1/preview-epoch-015/calibration.json` (SHA-256 `60538573a734d91107e25fb2a8a640ce45d90c482acfb65ed7110ff884f2f4c7`) en v62 `/app/storage/training/building-be-v62-v58-flanders-balanced-transfer-r1/preview-epoch-006/calibration-routed.json` (SHA-256 `05d8c8f0ade55907e37668758ac225aeff60cbb45604de662944fa447f6d590f`) zijn beide 144-tile, `split=val`, IoU-0,5 calibratiepreviews met 13 thresholds. Ze zijn geen protected-test-, unieke-gebouwen- of nationale releaseresultaten. - -Bij threshold 0,15 rapporteren beide artifacts aggregate F1 0,512905, precision 0,545647 en recall 0,483871, maar Vlaanderen heeft true positives 0, recall 0 en F1 0. Bij threshold 0,02 heeft v58 aggregate F1 0,240667 en Vlaanderen F1 0,080402/recall 0,103380; v62 heeft aggregate F1 0,208283 en Vlaanderen F1 0,067111/recall 0,275348. Geen van deze observaties voldoet aan een geloofwaardige drie-regio-gate. - -De v62-checkpointhash `889ee5…` verschilt van de actieve productiemodelhash `a9088b…`; de v62-run is dus niet het actieve model. - -### 8.3 V66 is een gerichte trial - -Het immutable manifest `/app/storage/operator-data/building-be-v66-lowrise-temporal-r1/operator_samples_manifest.json` (SHA-256 `d861da48aca40121e158e6ab243a6ccbe53e14d500a186af64b620f612935b07`) bevat drie positieve Vlaamse trainingssamples, nul andere splits/regio's en nul background-test-samples. Het kan v56 niet als nationale corpusbaseline vervangen. - -### 8.4 Protected-testleakage in de loop - -`scripts/run_belgium_building_training_loop.py:417-449` opent test en background nadat calibration slaagt. Wanneer de volledige assessment niet `training_complete` is, wordt die assessment op regels 477-498 als input gebruikt voor de volgende failure-driven trainingsset. `scripts/build_failure_driven_yolo_sampling.py:98-120` kiest expliciet `assessment.get("test") or assessment.get("calibration")` en gebruikt ook background-failures; regels 130-201 sturen vervolgens regionale/contextuele repeats van trainingtiles. - -De sampler neemt geen protected tiles zelf op, maar de protected-testuitkomsten beïnvloeden wél de volgende trainingsverdeling. Daarmee is de testset een tuningbron geworden en kan zij niet langer als onafhankelijke, eenmalige protected test voor de uiteindelijke kandidaat gelden. - -## 9. Lineagebreuken die Phase 2 moeten blokkeren - -| ID | Breuk | Bewijs | Gevolg | -|---|---|---|---| -| LIN-01 | caller-controlled bronautoriteit | uploadvelden + coverage-reproductie | “officieel/operationeel” kan vals zijn | -| LIN-02 | cross-theme coverage-union | `coverage_registry_service.py:481-504` | kleine juiste laag kan volledige dekking erven van verkeerde laag | -| LIN-03 | niet-4326 import als SRID 4326 | `geojson_service.py` versus `_feature_row` | geometrie kan valide lijken maar ruimtelijk betekenisloos zijn | -| LIN-04 | meters als graden bij buffer | 100 m-reproductie | extreme, foutieve derived geometrieën | -| LIN-05 | derived artifact zonder querybare features/run | `persist_vector_features=False` | UI/artifact en PostGIS geven verschillende waarheid | -| LIN-06 | modelscope via naamsubstring | area-name-reproductie | inference buiten gevalideerde scope mogelijk | -| LIN-07 | lege modelversie bij 1.146 runs; 3 zonder modelhash; 1.146 zonder tile-manifest-SHA/runtime/seed | Tower-runtime-snapshot | historische run niet volledig reproduceerbaar; drie runs niet sluitend aan checkpoint te koppelen | -| LIN-08 | vier Lambert-detecties als SRID 4326 | gedetailleerde DB-snapshot | kaart, QA en export kunnen corrupte geometrie consumeren | -| LIN-09 | 0 menselijke productiereviews | `detection_reviews=0` | geen bewijs van representatieve operatoracceptatie | -| LIN-10 | v56 human review 0/180 | corpusaudit | label-/tijd-/contextkwaliteit niet semantisch vrijgegeven | -| LIN-11 | slechts 3 pure-empty backgrounds; 24 cross-split AOI-paren onder 2 km | retained v56-manifestanalyse | regionale background- en onafhankelijkheidsclaims zijn niet vrijgegeven | -| LIN-12 | v66 bevat alleen 3 Vlaamse training-AOI's | retained v66-manifest | gerichte trial mag niet als nationale opvolger worden behandeld | -| LIN-13 | protected test stuurt retraining | trainingloop + sampler | evaluatieleakage; releaseclaim ongeldig | - -## 10. Reproduceerbare controles - -Lokale evidence opnieuw opbouwen: - -```powershell -cd C:\Projects\geointel -python scripts\run_accuracy_phase1_baseline.py --output-dir artifacts\evidence\accuracy\P1 -$env:PYTHONPATH = "$(Resolve-Path backend);$(Resolve-Path .)" -python scripts\run_golden_qa_benchmark.py --json -``` - -Tower-artifactidentiteit read-only controleren: - -```bash -sha256sum \ - /mnt/user/appdata/geointel/models/geointel-building-yolov8s-smallbld-minpx3-img640-ft30.pt \ - /mnt/user/appdata/geointel/storage/operator-data/building-be-v56-hard-negative-instance-roofs-r1/operator_samples_manifest.json \ - /mnt/user/appdata/geointel/storage/training/building-be-v56-corpus-audit-r1/belgium-building-corpus-audit.json \ - /mnt/user/appdata/geointel/storage/training/building-be-v62-v58-flanders-balanced-transfer-r1/preview-epoch-006/calibration-routed.json -``` - -De runtimecollector is read-only en gebruikt een SQL-statementtimeout van 30 seconden. Een toekomstige releasegate moet dezelfde queries uitvoeren én detailtellingen laten falen; een generiek `status=ok` mag vier buiten-domeinrecords niet maskeren. diff --git a/docs/accuracy-program/03-baseline-and-gaps.md b/docs/accuracy-program/03-baseline-and-gaps.md deleted file mode 100644 index c79fe69a..00000000 --- a/docs/accuracy-program/03-baseline-and-gaps.md +++ /dev/null @@ -1,229 +0,0 @@ -# GeoIntel Accuracy Improvement Program — 03 Baseline en gaps - -## 1. Phase-1-oordeel - -De technische foundation draait: frontend, API, PostGIS, jobs, datasetopslag, een echte Ultralytics/PyTorch-adapter en NVIDIA CUDA-inference zijn aantoonbaar operationeel. De accuracy-/releasebaseline is echter rood. Er is geen bewijs voor nationale gebouwdetectiekwaliteit, geen complete menselijke corpusreview, geen onafhankelijke protected-testcyclus en geen sluitende modelhash-per-run-lineage. Zeven kritieke/hoge correctheidsproblemen zijn deterministisch gereproduceerd en de canonieke backend-releasegate is niet groen. - -Daarom gelden op 1 augustus 2026 de volgende harde uitspraken: - -- “GeoIntel kan één bestaande tile met het actieve model op de RTX 4080 SUPER verwerken” is bewezen. -- “GeoIntel is 100% getraind”, “nationaal gevalideerd”, “productie-accurate” of “release ready” is niet bewezen en mag niet worden geclaimd. -- De bestaande v56/v58/v62/v66-artefacten zijn diagnostische/trainingsevidence; geen daarvan vormt een geldige nationale promotiebundel. -- Phase 2 mag remediëren en nieuwe evidence opbouwen, maar mag de protected test pas opnieuw bevriezen nadat de leakage-, corpus- en lineageproblemen zijn opgelost. - -## 2. Reproduceerbare softwarebaseline - -Alle hieronder genoemde logs zijn retained onder `C:\Projects\geointel\artifacts\evidence\accuracy\P1`. - -| Check | Exact commando | Uitkomst | Evidence | -|---|---|---|---| -| volledige backendtestset vanuit repo-root | `python -m pytest backend/tests -q -p no:cacheprovider -W error::DeprecationWarning --junitxml=artifacts/evidence/accuracy/P1/backend-full-suite.junit.xml` | **fail**: 1.180 passed, 17 failed, 70,63 s | `backend-full-suite.txt`, `backend-full-suite.junit.xml` | -| canonieke CI/backend-entrypoint | vanuit `backend`: `python -m pytest -W error::DeprecationWarning` | **collection fail**: 1.194 items verzameld plus importerror `scripts.render_operator_polygon_label_qa` | `backend-ci-entrypoint.txt` | -| Phase-1 collectortests | `python -m pytest tests/test_accuracy_phase1_baseline.py -q -p no:cacheprovider` | **pass**: 4/4 | `phase1-tooling-tests.txt` | -| frontend unit | vanuit `frontend`: `npm run test:unit` | **pass**: 16 files, 51 tests | `frontend-vitest-unit.txt` | -| generiek frontendtestcommando | `npm test -- --run` | **fail**: script `test` ontbreekt | `frontend-vitest.txt` | -| frontend typecheck | `npm run typecheck` | **pass** | `frontend-typecheck.txt` | -| frontend build | `npm run build` | **pass**: 1.896 modules; Vite-build voltooid | `frontend-build.txt` | -| frontend lint | `npm run lint` | **fail**: script `lint` ontbreekt | `frontend-lint.txt` | -| Python lintbaseline | `python -m ruff check backend scripts tests --output-format json` | **fail**: 112 findings | `repository-ruff-baseline.json`, `.txt` | -| Alembic head | vanuit `backend`: `python -m alembic heads` | **pass**: één head `202607260001` | `alembic-heads.txt` | -| volledige offline migratieketen | `python -m alembic upgrade head --sql` | **pass**: alle 11 migraties renderen tot commit | `alembic-offline-upgrade.sql` | -| API-contractaudit | `python scripts/audit_api_contracts.py` | **pass**: 147 routes; 10 expliciete non-envelope endpoints | `openapi-contract-audit.txt` | - -De 112 Ruff-bevindingen zijn: E402 13, E701 2, E702 69, F401 23, F403 1, F811 2 en F841 2. De nieuw toegevoegde Phase-1-audittools waren in de afzonderlijke check Ruff-clean; de telling is repositorybreed. - -De 17 backendtestfailures zijn bron-/contractasserties tegen frontend-, README- en deployteksten/implementatiedetails. Dat maakt ze niet automatisch onbelangrijk of “alleen stale”: de verwachte automatische model/theme-selectie is bijvoorbeeld doelbewust gewijzigd naar gebruikersselectie, terwijl tests nog het oude contract eisen. Test en actueel productcontract moeten expliciet worden gereconcilieerd. Tot dat gebeurt is de releasegate rood. - -De CI-entrypointfout heeft een afzonderlijke oorzaak: vanuit `backend` resolveert `scripts` naar `backend/scripts`, waardoor de rootmodule `scripts/render_operator_polygon_label_qa.py` niet importeerbaar is. Een root-run met expliciet importpad kan de tests wel verzamelen, maar repareert de feitelijke CI-opdracht niet. - -## 3. Wat de huidige readinessgate niet uitvoert - -`scripts/run_readiness_check.sh` compileert veel Python en draait backendtests, Alembic head, frontend unit/typecheck/build. De volgende checks zijn daar slechts syntaxcontroles: - -- `node --check` voor de twee frontend-E2E-scripts; -- `bash -n` voor live migration, deploy, upgrade/fresh-install, browserruntime, demo, real-data detection/QA, calibratie, training en cleanupflows. - -De gate voert dus geen volledige browserjourney, live PostGIS-migratie, externe provideracquisitie, echte CUDA-modelinference, protected-test-evaluatie of AI-imagebuild uit. De GitHub-/Gitea-build installeert standaard geen AI-dependencies. Een groene toekomstige unit/readinessgate blijft daarom onvoldoende zonder afzonderlijke live-, data- en modelgates. - -## 4. Golden QA/QC-baseline - -`python scripts/run_golden_qa_benchmark.py --json` slaagde twee keer semantisch met vier fixture-scenario's: - -| Scenario | Precision | Recall | F1 | Mean IoU | FP | FN | -|---|---:|---:|---:|---:|---:|---:| -| partial match | 0,5 | 0,5 | 0,5 | 0,833976834 | 1 | 1 | -| perfect match | 1 | 1 | 1 | 1 | 0 | 0 | -| no overlap | 0 | 0 | `null` | `null` | 1 | 1 | -| exact MultiPolygon | 1 | 1 | 1 | 1 | 0 | 0 | - -De twee retained JSON-runs zijn niet byte-identiek: SHA-256 `ec96862b…` tegenover `4f900711…`. De semantische resultaten zijn gelijk; UUID4-gegenereerde project/dataset/quality-check-id's maken de output nondeterministisch. Voor een reproduceerbare benchmarkbundel moeten ids deterministisch zijn of vóór hashing worden genormaliseerd. - -Het no-overlapscenario legt daarnaast een metriccontractgap bloot: precision en recall zijn 0, maar F1 is `null`. Dit kan wiskundig als undefined worden verdedigd, maar aggregators en releasegates moeten één expliciete semantiek hanteren. De Tower-database bevestigt bredere nullvariatie: 58/697 F1, 58/697 precision, 1/697 recall en 90/697 mean IoU zijn null. - -De golden benchmark gebruikt kleine checked-in fixtures. Hij bewijst rekenkundige regressiestabiliteit, niet de nauwkeurigheid van het actieve model op Belgische luchtbeelden. - -## 5. Runtime-, database- en GPU-baseline - -### 5.1 GPU-smoke - -De retained smoke gebruikte het actieve model: - -- model `/app/models/geointel-building-yolov8s-smallbld-minpx3-img640-ft30.pt`; -- SHA-256 `a9088b8491dfae36694b53e9e9406cb4e3511d334a5712fa34f75078a47759c1`; -- één 512×512 RGB-tile in EPSG:31370, tile-SHA `134a9e86850c92c577c73bc6ee57a9df7d4c1c513ae6450263e800b6dd47b6ee`; -- manifest-SHA `6ab8a96bf2a1405e224932afb90255311a09bbeaed4e9a2fdcdf8b1bc2230abd`; -- PyTorch `2.11.0+cu128`, Ultralytics `8.4.99`, NVIDIA GeForce RTX 4080 SUPER; -- seed `20260801`, deterministische algoritmen, `imgsz=640`, confidence 0,5, `max_det=1000`; -- 17 raw `building`-detecties; inference 0,8837 s, totale model-load plus inference 1,3689 s. - -Deze smoke is read-only en passeert. Hij toetst één tile en schrijft geen AnalysisRun/Detection/QA/Export. Hij levert daarom geen accuracy-, calibratie-, georeference-persistence-, schaal- of generalisatieclaim. - -### 5.2 Databaseintegriteit - -Positieve baseline: - -- runtime Alembic-head `202607260001`; -- 3.377 datasets en 1.671 versies hebben checksums en source/provenance-metadata; -- 5.816 directe dataset/version/export-storagepaden gecontroleerd, 0 ontbrekend; -- 387 area- en 6.689.447 vectorfeaturegeometrieën: 0 leeg, 0 ongeldig, 0 wrong-SRID, 0 buiten EPSG:4326-domein in de gebonden query; -- 299.233 detection-confidences: 0 buiten `[0,1]`. - -Negatieve baseline: - -- 2.377/3.377 datasets zonder `observed_at` en 1.761/3.377 zonder `source_version`; eerst per bronfamilie classificeren, niet blind invullen; -- vier detectiegeometrieën hebben SRID 4326 maar numerieke Lambertcoördinaten rond X 193k/Y 206k; -- alle 1.146 modelruns hebben een lege modelversie; 1.143 bewaren een modelassethash, drie niet; alle 1.146 missen tile-manifest-SHA, runtime/hardware en seed; -- 0 segmentaties en 0 detection reviews; -- 135/4.460 jobs en 2/1.146 analysis runs hebben status failed; -- PostGIS 3.6.4 meldt dat core/topology procedures uit 3.4.3 een upgrade nodig hebben. - -De storagecheck dekt alleen directe DB-referenties. De volledige recursieve storageaudit eindigde in een time-out en is geen pass; daarmee is niet bewezen dat alle niet-gerefereerde caches, trainingoutputs of orphan artifacts bekend zijn. - -## 6. Deterministisch gereproduceerde productfouten - -`forensic-reproductions.json` bevat zeven read-only, deterministische reproducties; alle zeven zijn opnieuw waargenomen. - -| ID | Ernst | Geobserveerd | Waarom blokkerend | -|---|---|---|---| -| P1-COV-001 | critical | een kleine buildings-partitie wordt `fully_covered=true` doordat een roads-bbox in dezelfde bounded union zit | coverage- en beschikbaarheidsclaims kunnen inhoudelijk fout zijn | -| P1-CRS-001 | critical | 100 “meter” buffer levert bounds `[-95,-49,105,151]`, 200 graden lengtespan | units/CRS worden verwisseld; derived geometrie is onbruikbaar | -| P1-CRS-002 | critical | EPSG:31370-coördinaten `(150000,210000)` worden ongewijzigd met SRID 4326 opgebouwd | valide SRID-label maskeert verkeerde werkelijkheid | -| P1-AUTH-001 | critical | caller-controlled upload `source_name=grb` wordt `operational`/`authoritative` | gebruikersmetadata kan officiële bronautoriteit spoofen | -| P1-AI-001 | critical | area `Mol validation bypass` met geometrie in Noord-Amerika passeert modelscope | model draait buiten de gevalideerde geografie | -| P1-COV-002 | high | dezelfde Vlaamse geometrie werkt als naam `Flanders`, maar wordt `outside=true` na rename naar `Vlaanderen` | wettelijke scope hangt van een muteerbare displaynaam af | -| P1-API-001 | high | Area PATCH accepteert payload met geometry maar negeert die stil | contract en opgeslagen AOI lopen uiteen | - -Aanvullende statisch bewezen risico's staan nog buiten deze zeven reproductions: - -- clip/buffer/intersect roepen `_persist_derived_dataset` standaard aan met `persist_vector_features=False`; een `ready` derived artifact hoeft dus niet PostGIS-querybaar te zijn; -- meerdere services slikken secundaire fouten of vallen stil terug, onder meer projectdetailbootstrap en cached rasterpreview; fallback moet expliciete status/provenance krijgen; -- het tracked mirror `geointel/` bevat 1.153 bestanden, waarvan 68 van de rootversie verschillen; Docker sluit de mirror uit, lokale tools niet noodzakelijk. - -## 7. Corpus-, split- en trainingbaseline - -### 7.1 Inventaris is geen kwaliteit - -Tower bevat 26 modelassets, 229 trainingscheckpoints (28.512.052.142 bytes), 424 JSON-trainingsrapporten en 36 operator-manifests. De aantallen tonen veel experimenten, niet dat de beste kandidaat is gevonden of geldig vrijgegeven. - -### 7.2 V56 is de breedste aangetroffen corpusbasis, maar niet vrijgegeven - -De retained v56-evidence toont: - -- 180 AOI's over Vlaanderen, Wallonië en Brussel; -- immutable manifest, 0 exacte cross-split rasterhashduplicates en 0 cross-split raster-dataset-id-duplicates; -- dHash-screen over 4.833 cross-split paren: minimumafstand 17, geen paren op/onder 4; -- bbox-afstandscreen: minimum 95,7203 m en 24 cross-split paren onder 2 km; -- 31.452 inputfeatures; 30.662 geaccepteerd, 326 onder pixel-resolutie, 464 na de imageryperiode; -- automated corpusstatus `needs_human_review`; 0/180 gereviewd, alle 180 pending; -- 48 background candidates, maar slechts drie pure-empty background-test-AOI's: Vlaanderen 2, Wallonië 1, Brussel 0; -- de drie overige background-test-AOI's bevatten 2, 107 en 141 referentiefeatures en zijn moeilijke negatieven. - -De exact-hash- en dHashscreen zijn positief maar begrensd. Ze bewijzen geen gebouw-instance-, gemeente-, vluchtstrook-, seizoen- of bronopname-onafhankelijkheid. De 95,7-meter train/testnabijheid en 24 paren onder 2 km vereisen expliciete imagery-/instance-audits voordat een protected split wordt geaccepteerd. - -De automated tile-qualityaudit meldt 2.496 tiles, 60.229 geldige labels, 0 invalid/missing labels, 2.072 positieve en 424 negatieve tiles. Dat valideert syntax en enkele pixelregels, niet of daken correct, volledig, tijdsconform of contextueel representatief zijn. Contact sheets bestaan, maar menselijke acceptatiebeslissingen ontbreken. - -### 7.3 V58/V62 halen geen regionale gate - -V58 en v62 hebben alleen 144-tile `val`/calibratiebewijs met IoU 0,5 en 13 confidence-sweeps. Bij threshold 0,15 rapporteren beide aggregate F1 0,512905, precision 0,545647 en recall 0,483871, terwijl Vlaanderen 0 true positives, recall 0 en F1 0 heeft. Bij threshold 0,02 blijft Vlaanderen zwak: v58 F1 0,080402/recall 0,103380; v62 F1 0,067111/recall 0,275348. Dit is geen protected test en geen nationale releaseprestatie. - -V62 `best.pt` bestaat, maar de hash `889ee5…` is niet de actieve productiemodelhash `a9088b…`. Er is geen geldige promotie aangetoond. - -### 7.4 V66 is geen nationale opvolger - -Het v66-manifest heeft slechts drie positieve Vlaamse `train`-AOI's in twee low-rise-contexten, zonder val/calibration/test/background en zonder Wallonië/Brussel. Het is een gerichte trial. - -### 7.5 Protected-testleakage - -De trainingloop opent na een geslaagde calibration zowel test als background. Als de kandidaat vervolgens faalt, geeft de loop de volledige assessment aan de failure-driven sampler. Die kiest `assessment.get("test") or assessment.get("calibration")`, gebruikt regionale testmetrics en background-failures en verandert daarmee repeats van trainingtiles voor de volgende iteratie. Protected tiles worden niet letterlijk opgenomen, maar hun uitkomsten sturen training. De huidige testset is dus voor die loop niet langer onafhankelijk en moet na de correctie worden vervangen of aantoonbaar nooit eerder ingezien zijn. - -## 8. Claim-matrix - -| Claim | Status | Maximaal verdedigbare formulering | -|---|---|---| -| platform draait technisch | ondersteund | gezonde Tower-container, echte PostGIS-data en uitvoerbare frontend/API | -| NVIDIA/PyTorch wordt gebruikt | ondersteund | één actieve YOLO-adaptercall draaide op RTX 4080 SUPER/CUDA 12.8 | -| volledige inferenceketen is correct | niet ondersteund | smoke sloeg persistence/georeference/QA/export over; vier historische geometrieën zijn corrupt | -| actief model is reproduceerbaar | gedeeltelijk | actief bestand heeft SHA; historische runs missen volledige manifest/runtime-lineage en drie runs missen ook de modelassethash | -| labels zijn correct | niet ondersteund | automated syntax ok, maar v56 menselijke review 0/180 | -| splits zijn onafhankelijk | niet ondersteund | exact/dHashscreen positief, maar nabijheid onbeslist en testuitkomsten sturen retraining | -| building accuracy voor Mol/Kempen | niet vastgesteld in Phase 1 | er is geen retained protected Mol/Kempen-releasebenchmark voor actieve hash | -| building accuracy voor heel België | weerlegd als actuele releaseclaim | v58/v62 calibration heeft bij bruikbare aggregate threshold Vlaanderen recall/F1 0 | -| pure-backgroundrobustheid per regio | niet ondersteund | slechts 3 pure-empty AOI's, geen in Brussel | -| productie-segmentatie | niet ondersteund | abstraction/fixture aanwezig, 0 runtime segmentaties | -| officiële bronnen zijn authentiek | niet ondersteund | source identity kan via uploadmetadata worden gespooft | -| databasegeometrieën zijn integraal | gedeeltelijk | areas/vectorfeatures schoon in gebonden query; 4 detecties buiten domein | -| release ready | nee | backend/CI/lint rood plus kritieke data-/GIS-/ML-blockers | - -## 9. Geprioriteerde gaps - -### P0 — vóór nieuwe modeltraining of productclaim - -1. Fix en regressietest de zeven gereproduceerde contract-/CRS-/scope-/authorityfouten; maak coverage unions themaspecifiek, source authority server-attested en modelscope geometrisch/checksumgebonden. -2. Quarantaineer de vier buiten-domeindetecties, identificeer hun producerende code/image/model, herbereken of verwijder ze via een gecontroleerde migratie en laat detailtellingen de gate falen. -3. Maak vector- en detectie-CRS-transformaties expliciet; verbied SRID relabeling; voer metric buffers in een geschikte lokale CRS uit; persisteer derived features en runlineage atomisch. -4. Verwijder test/background uit failure-driven sampling en checkpointpromotie. Bevries daarna een nieuwe, ongeziene protected test met hashes en éénmalige-openingspolicy. -5. Voer menselijke review uit op alle 180 v56-AOI's met beslissingen, reviewer, timestamp, label-/beeldversie en reden; herbouw contact sheets wanneer bron of label verandert. -6. Voeg onafhankelijke AOI's en pure-empty backgrounds toe per regio/context, in het bijzonder Brussel; audit de 24 cross-split paren onder 2 km op imagery-, vluchtstrook- en instance-overlap. -7. Herzie image/label time deltas, vooral de 464 uitgesloten features en dichte PICC/UrbIS-zones; definieer regels voor onzekere/occluded/nieuwe/verdwenen gebouwen. -8. Koppel iedere training, inference-run, detection, QA en export aan model-SHA, datasetmanifest-SHA, codecommit, containerdigest, seed, parameters en dependency lock. - -### P1 — vóór releasecandidate - -1. Maak de canonieke backend-CI-entrypoint verzamelbaar en reconcilieer de 17 contracttests met de actuele, handmatige modelselectie-UX. -2. Voeg Ruff en frontend lint toe aan de readinessgate; werk de 112 bestaande bevindingen gecontroleerd weg. -3. Bouw en test de echte AI/CUDA-image in CI; pin PyTorch/torchvision/Ultralytics en leg image digest/SBOM vast; hef cu128/cu130-drift op. -4. Draai echte browser-E2E, live PostGIS upgrade/fresh-install, externe-provider- en full inference/persistence/QA/exportjourneys. -5. Definieer null-/zero-/undefinedsemantiek voor precision, recall, F1 en IoU; maak golden outputs byte-reproduceerbaar of canonicaliseer ids. -6. Classificeer de 2.377 missende observatietijden en 1.761 missende bronversies per broncontract en maak onverklaarde gevallen fail-closed. -7. Verwijder bronambiguïteit door de tracked `geointel/`-mirror gecontroleerd te migreren; niet in Phase 1 destructief opruimen. - -## 10. Wanneer Phase 2 veilig kan trainen - -Nieuwe GPU-training is pas zinvol nadat de P0-datacontracten, human review en splitpolicy zijn opgelost. Anders optimaliseert een nieuwe run opnieuw tegen mogelijk foutieve labels, onvoldoende negatives en een gecontamineerde testlus. De veilige volgorde is: - -`fix contracten -> nieuwe regressietests -> corpusbeslissingen -> onafhankelijke splits -> frozen manifests/hashes -> train/val/calibration -> kandidaatselectie -> éénmalige protected test -> onafhankelijke menselijke foutreview -> promotiebundel -> shadow deploy`. - -Een trainingsloop mag itereren op train/validation/calibration. Hij mag de protected test niet opnieuw in de loop voeren. “100%” wordt niet als numerieke gate gebruikt; release vereist vooraf vastgelegde, context- en regiogebonden thresholds met confidence intervals, failure budgets en expliciete abstention/unsupported-statussen. - -## 11. Evidence-integriteit - -| Retained bestand | Bytes | SHA-256 | -|---|---:|---| -| `backend-full-suite.txt` | 23.972 | `8521ed48b17b382752418750b3ea374831958fb063e83ef87048212e0fd5ea69` | -| `backend-ci-entrypoint.txt` | 1.601 | `0ac774ec19b4ff0a15142aab5f1db68c2592a230401d794ae7d040320e3ac0c0` | -| `frontend-vitest-unit.txt` | 2.774 | `6341bfa51ca3f4fe5ec7d4af7239c3c5e1a29e6bfe8bdfae85e824a2a6482ad0` | -| `frontend-typecheck.txt` | 163 | `3891c85c77b5ff50a1eb6d27a2a65d40c2c05423768734efd9d980f3784d68fa` | -| `frontend-build.txt` | 2.356 | `c3b8e10ef177ac1c2dc045bd710df1caeb46f8922a721291be431b304abbc079` | -| `frontend-lint.txt` | 418 | `1115b013515c753e2dfb73abdad9024aec7b4c2337d117c7e1181341fef15c7f` | -| `repository-ruff-baseline.json` | 59.359 | `de6617f030e49550e714c49b6e14bf291bf85016fd58086e9ca38b33a52252e9` | -| `alembic-heads.txt` | 116 | `da4521233c6718fc7a5865c53904e73685fbdce65a1449b19cd0dc2e40d037ed` | -| `alembic-offline-upgrade.sql` | 20.199 | `e8905b881890cf95885a7515e3d9dcf2a7a0a24c4edbc57e98a363edcb22dd0e` | -| `openapi-contract-audit.txt` | 212 | `5af3d8f00be3f57fc309bc198fa3995d1eae7270a5f210b3e94d1aeeb653119d` | -| `forensic-reproductions.json` | 3.533 | `f6349199a15ae789092d3d65c17a39a9b32ea3ed557571c0c228c4be3cf7235e` | -| `golden-qa-reproducibility.json` | 505 | `576e5667a989c34086db3a2bc57003115a8a61b14e9f49f5407ee380baf0829d` | -| `phase1-tooling-tests.txt` | 250 | `a9bf261e1a811ad3e8bfa8edc439a11f00b46bc157f9ab6fc970033a87f45748` | -| `tower-gpu-inference-smoke.json` | 5.675 | `692a9fa193d589123b042110d7e80755f0c6634854f3134c291fc6083adb7b77` | -| `tower-runtime-database-snapshot-detailed.json` | 14.946 | `744389b6c384a9fb3a9e16e56f1477f3b752e11a5b98e1fad7df47b4703a9ca1` | -| `tower-ml-data-lineage-snapshot.json` | 71.659 | `d80275e8198ce63366d2a2d44eb8fba1f27c29d85aaaaedb94991d8c56febfb6` | - -Deze hashes zijn van de retained Phase-1-bestanden op het moment van documentgeneratie. Als evidence opnieuw wordt gegenereerd, moet een nieuwe evidence-manifestversie de nieuwe hash, producerende commandoregel, timestamp en reden bewaren; oude evidence wordt niet overschreven of als identiek voorgesteld. diff --git a/docs/accuracy-program/04-risk-register.md b/docs/accuracy-program/04-risk-register.md deleted file mode 100644 index 84ebcdd4..00000000 --- a/docs/accuracy-program/04-risk-register.md +++ /dev/null @@ -1,89 +0,0 @@ -# GeoIntel Accuracy Improvement Program — risicoregister - -- Status: **release blocked** -- Auditmoment: 2026-08-01 -- Scope: Belgium land en Belgische Noordzee, met de actieve building-detector beperkt tot zijn bewezen Mol/Kempen-scope - -## Beslissing en claimgrens - -GeoIntel mag op basis van de huidige evidence niet als nationaal gevalideerd AI-systeem worden vrijgegeven en de scope van de actieve detector mag niet worden verruimd. De productie-adapter heeft op de Tower één echte tile op `cuda:0` verwerkt, maar die smoke bewijst uitsluitend dat het model technisch kan laden en infereren. Hij bewijst geen nauwkeurigheid, calibratie of geografische generalisatie. - -De volgende regels gelden totdat alle bijbehorende exit-evidence is vastgelegd: - -- geen nationale kwaliteitsclaim voor building detection; -- geen promotie van v56, v58, v62, v66 of een afgeleid checkpoint; -- geen wijziging van de actieve modelscope op basis van bestandsaanwezigheid of aggregate metrics; -- geen productieclaim voor segmentatie of zonnepaneeldetectie; -- geen verwijdering of overschrijving van bestaande datasets, checkpoints, evaluaties of auditbewijzen; -- elke herstelling begint met een regressietest die het bewezen defect op de oude implementatie reproduceert. - -Ernstclassificatie: - -- **Critical**: kan een plausibel maar ruimtelijk/inhoudelijk fout resultaat, een onterechte autoriteitsclaim of een besmet promotiebesluit veroorzaken; -- **High**: blokkeert de nationale claim, reproduceerbaarheid of een betrouwbare releasebeslissing; -- **Medium**: verzwakt assurance, onderhoudbaarheid of deploymentcontrole, maar is op zichzelf geen bewezen fout resultaat. - -Alle risico's hieronder zijn open. Een controle telt pas als uitgevoerd wanneer de genoemde exit-evidence bestaat en door QA opnieuw is geverifieerd. - -## A. Ruimtelijke juistheid en bronautoriteit - -| ID | Ernst | Bewezen evidence | Impact | Owner | Vereiste controle | Exit-evidence | -| --- | --- | --- | --- | --- | --- | --- | -| ACC-R01 | Critical | `geojson_service.py` behoudt bron-CRS-informatie, terwijl `vector_feature_service.py` geometrieën zonder transformatie als SRID 4326 schrijft. De runtime-snapshot vindt 4 detections met Belgische Lambert-coördinaten rond x=193k/y=205k maar SRID 4326; zie `artifacts/evidence/accuracy/P1/tower-runtime-database-snapshot-detailed.json`. | Verkeerde kaartpositie, ruimtelijke predicates, clipping, export en coverage; resultaten kunnen geldig ogen maar buiten het EPSG:4326-domein liggen. | GIS + Architecture | Eén expliciet CRS-ingestcontract; gekende CRS transformeren naar canoniek 4326, onbekende CRS fail-closed weigeren; bestaande vier records quarantainen of herleiden vanuit tile-transform en bron-CRS. | Unit- en PostGIS-integratietests voor EPSG:31370, EPSG:3812 en EPSG:4326; round-trip/extent-asserties; migratierapport met voor/na-ID's en zero `outside_epsg4326_domain`; geen stille datawijziging. | -| ACC-R02 | Critical | `VectorOperationsService.buffer` voert `geometry.buffer(distance_m)` uit op ongetransformeerde GeoJSON. Een 100 m-reproductie nabij Mol levert een span van circa 200 graden. | Een meterparameter wordt als graden geïnterpreteerd; analysegebied en downstream-resultaten zijn materieel fout. | GIS | Bufferen in een geschikte metrische projectie/geography; bron- en doel-CRS en eenheden verplicht valideren; ongeschikte/ontbrekende CRS weigeren. | Regressietest met een gekend punt/polygoon in Mol en geodetische toleranties; API-test voor onbekende CRS; PostGIS/Shapely-pariteit; bewijs dat 100 m geen graadbuffer meer oplevert. | -| ACC-R03 | Critical | `CoverageRegistryService._matching_datasets` voegt bbox-scopes toe vóór `layer_matches` en `zone_matches`. Een kleine buildingscope plus een volledige roadscope resulteert voor buildings ten onrechte in `fully_covered=true`. | Verkeerde bron/thema-combinaties kunnen als operationeel en volledig gedekt verschijnen. | Architecture + GIS | Alleen scopes van datasets die bron, thema, layer en zone volledig matchen in de union opnemen; coverage per bronversie en thema isoleren. | Regressietest voor mixed-theme/mixed-zone datasets; property-based tests voor monotoniciteit en bronisolatie; API-evidence dat de buildingscope in de reproductie `fully_covered=false` blijft. | -| ACC-R04 | Critical | De uploadroute accepteert caller-controlled `source_name`, `reference_layer_name`, `source_metadata` en `provenance_metadata`; coverage vertrouwt deze velden. Een upload kan zich als GRB/authoritative voordoen. | Een handmatige upload kan de attributie, autoriteit en operationele dekking van een officiële bron erven. | Architecture + Data Governance | Server-owned source registry en trust class; user uploads altijd `manual/untrusted`; officiële identiteit uitsluitend via een governed acquisition adapter met immutable provider evidence; bestaande records classificeren. | Security/regressietest die een forged GRB-upload uitvoert en `manual/untrusted` verwacht; migratie-audit van bestaande bronnen; API-response toont bronvertrouwen en kan geen officiële attribution injecteren. | -| ACC-R05 | High | Juridische coveragezones worden via mutable displaynamen (`SCOPE_AREA_NAMES`) bepaald. Dezelfde geometrie met `Flanders` versus `Vlaanderen` verandert de zonematch. | Een hernoeming kan scope/coverage juridisch en operationeel veranderen zonder geometrische wijziging. | Architecture + GIS | Immutable area/zone code en geometry-backed containment gebruiken; displaynaam uitsluitend presentatie; grensgevallen expliciet modelleren. | Rename-regressietest met identieke geometrie; zone-ID-migratie; grens- en Noordzee-tests; coverage-uitkomst blijft naam-onafhankelijk. | -| ACC-R06 | Critical | De YOLO-validatiescope wordt afgedwongen via substringmatching op de mutable `Area.name`. Een gebied buiten Mol met naam `Mol validation bypass` wordt aanvaard. | Inferentie kan buiten de bewezen modelscope worden uitgevoerd en als ondersteund worden gepresenteerd. | AI + GIS + Architecture | Scope koppelen aan immutable geometry/zone-ID en model-card scope polygon; volledige containment/intersection-policy vastleggen; lege geometrie en naammatch nooit voldoende. | Negatieve API/service-tests voor spoofnaam, lege geometry en deels overlappende AOI; positieve Mol/Kempen-tests; scope-evidence bevat modelhash, scope-ID en spatial predicate. | -| ACC-R07 | High | `Area` PATCH documenteert geometry-wijziging, maar het schema verwerkt enkel naam/CRS en negeert extra geometry; CRS kan los van de geometry worden herschreven. | API kan 200 retourneren zonder gevraagde geometry-update of coördinaten fout labelen. | Architecture + GIS | Extra velden verbieden; contract en implementatie gelijkmaken; CRS alleen wijzigen via gevalideerde transformatie, niet via relabeling. | Contracttest met geometry PATCH; unknown-field 422-test; CRS-transformtest; OpenAPI-contract en implementatie tonen hetzelfde gedrag. | -| ACC-R08 | High | Clip/buffer/intersect roepen `_persist_derived_dataset` aan met `persist_vector_features=false`; een dataset kan `ready` zijn zonder querybare PostGIS-features, volledige provenance of atomaire AnalysisRun-koppeling. | Downstreamanalyse ziet een gereed artefact dat niet betrouwbaar querybaar/reproduceerbaar is; partial commits zijn mogelijk. | Architecture + GIS | Eén transactie voor AnalysisRun, DatasetVersion, vector_features en lineage; `processing` tot artifact én PostGIS-persist voltooid zijn; failure rollback/fail-closed. | Integratietests per operatie, inclusief geïnjecteerde write failure; zero ready-derived datasets zonder features; lineage-query van inputhash tot output; transactie-evidence. | - -## B. Dataset-, split- en labelintegriteit - -| ID | Ernst | Bewezen evidence | Impact | Owner | Vereiste controle | Exit-evidence | -| --- | --- | --- | --- | --- | --- | --- | -| ACC-R09 | Critical | De training-orchestrator evalueert iedere iteratie op calibration, test en background. `build_failure_driven_yolo_sampling.py` gebruikt vervolgens `assessment.get("test")` bij het wegen van de volgende training en registreert test als failure source. | De protected test stuurt training; daardoor is hij geen onafhankelijke eenmalige release-evaluatie meer. | AI + QA | Orchestrator in twee fysiek/logisch gescheiden paden splitsen: iteratie mag alleen train/val/calibration lezen; test/background-test blijven verzegeld tot kandidaat, threshold en gates zijn bevroren. Sampler moet ieder testartefact of protected sample weigeren. | Canary-tests met protected IDs; file-access/auditlog bewijst nul testreads vóór freeze; sampler-test faalt op test-input; één gesigneerd test-open event voor exact één modelhash/config; geen verdere training in die candidate family na opening. | -| ACC-R10 | High | V56 rapporteert een minimale cross-split AOI-afstand van 95,72 m en 24 cross-splitparen onder 2 km. Dat bewijst geen overlap, maar wel dat de vereiste buffer groter dan maximale tile-context nog niet is aangetoond. | Nabije context, dezelfde bebouwing of providerseams kunnen validatie/calibratie/test correleren met training. | GIS + AI + QA | Splittoewijzing op gebufferde AOI's vóór tiling; buffer afleiden uit tilecontext/resolutie; instance-, bronbeeld- en perceptuele near-duplicatecontrole. | Immutable split-audit met minimumafstand ≥ bevroren contextbuffer, zero intersecties, zero gedeelde feature-ID's/checksums/near-dupes en kaartbewijs per dichtste paar. | -| ACC-R11 | High | Het v56 operator-manifest heeft 180 AOI's maar `reviewed=0/180`; de productie-DB telt 0 `detection_reviews`. | Labelkwaliteit en representatieve fouten zijn niet door menselijke beoordeling afgesloten; automatische audits kunnen semantische mislabels niet bewijzen. | QA + Data Governance | Gestratificeerde menselijke review van label-contact-sheets door regio, context, provider, objectgrootte, dichte en moeilijke gevallen; beslissingen als immutable records met reviewer, tijd en reden. | 100% van de vooraf geselecteerde reviewqueue beslist; zero unresolved critical/high label findings; manifest met review-ID's en hashes; inter-reviewer steekproef en getekende QA-beslissing. | -| ACC-R12 | High | V56 bevat slechts 3 pure-empty background-test-AOI's (Flanders 2, Wallonia 1, Brussels 0). V66 bevat slechts 3 Vlaamse train-AOI's. | De achtergrond- en nationale claim is niet representatief voor alle regio's en contexten. | AI + GIS + QA | Nieuwe ruimtelijk onafhankelijke AOI's per regio/context; pure-empty én moeilijke negatieve voorbeelden voor alle regio's, waaronder Brussels; protected portfolios nooit naar training kopiëren. | Corpus-compositiematrix voldoet aan het vooraf bevroren contract uit `PYTORCH_TRAINING_ROADMAP_BELGIUM.md`; elk vereist stratum heeft positieve/negatieve coverage; zero protected-to-train overlap; kaart/contact-sheet evidence. | -| ACC-R13 | High | V56: 31.452 inputfeatures, 30.662 geaccepteerd, 326 onder minimumresolutie en 464 post-imagery; 521 kleine labels en maximale aspectratio 103,67. V66 gebruikt imagery/labels met circa 575 dagen verschil. | Onzichtbare, verouderde, te kleine of extreem gevormde labels veroorzaken fout-negatieven/positieven en onbetrouwbare boxtraining, met extra risico in dichte PICC/UrbIS-gebieden. | GIS + AI + QA | Per-provider tijdsrelatie en resolvability vastleggen; post-imagery/subpixel uitsluiten met reason code; extreme aspect/dense-cluster review; dak/footprint-displacement en PICC/UrbIS-regels bevriezen. | Label-audit met accepted/rejected reason per feature; temporal matrix per AOI; zero unknown silent inclusion; alle extreme/dense reviewqueues gesloten; opnieuw gerenderde contact sheets en corpus-SHA. | -| ACC-R14 | High | V56-tiling telt 2.496 tiles en 60.229 labels, maar dataset-YAML/class/tile/stride-velden zijn afwezig of null in de auditketen. | Het trainingsinputcontract kan niet exact worden gereconstrueerd of vergeleken; een checkpoint kan aan ambiguë preprocessing worden gekoppeld. | AI + Data Engineering | Eén verplicht manifest-schema met dataset-YAML SHA, class mapping, tile size, stride/overlap, nodata, normalization, augmentations, software/runtime en seed; schema fail-closed. | JSON-schema-tests; volledige immutable manifest; alle artifacts hash-bound; clean-room export produceert identieke samplelijst/labels en gedocumenteerde byteverschillen waar bestandmetadata varieert. | -| ACC-R15 | High | Van 3.377 datasets missen 2.377 `observed_at` en 1.761 `source_version`; checksums, CRS, imported_at en provenancevelden zijn wel volledig. | Tijd- en bronversievergelijkingen kunnen niet voor elke bronfamilie worden gereproduceerd; sommige misses kunnen legitiem zijn maar zijn nog niet geclassificeerd. | Data Governance + Architecture | Veldbeleid per bronfamilie: `required`, `not_applicable` of `unknown_with_reason`; backfill uitsluitend uit authoritative evidence; nooit downloadtijd als observatietijd invullen. | Audit per source family met zero ongeclassificeerde ontbrekende waarden; migratie/backfillrapport; API toont unknown/not-applicable expliciet; checksums blijven ongewijzigd. | - -## C. Modelvalidatie, metrics en runtime-lineage - -| ID | Ernst | Bewezen evidence | Impact | Owner | Vereiste controle | Exit-evidence | -| --- | --- | --- | --- | --- | --- | --- | -| ACC-R16 | Critical | V58-calibratie bij confidence 0,15 geeft aggregate F1 0,5129, Brussels 0,6944, Wallonia 0,4674 en Flanders 0; er is geen protected-test-, background-test- of promotion-evidence. De actieve modelkaart blijft `nationally_validated=false` en Mol/Kempen-scoped. | Aggregate score maskeert een volledige regionale failure; geen nationale kwaliteitsclaim of promotie is verdedigbaar. | AI + QA | Region/context macro- en worst-stratum gates vóór aggregate score; threshold alleen op calibration; actieve scope fail-closed behouden; geen status op basis van checkpointnaam. | Bevroren gateconfig vóór test; calibrationrapport per regio/context/objectgrootte; alle gates pass; daarna pas eenmalige protected-test en promotion report voor exact model-SHA. | -| ACC-R17 | Critical | 1.146 persisted detection runs en 299.233 detections hebben een lege `model_version`; 3 runs missen modelhash; alle missen tile-manifest-SHA, runtime/hardware en seed. | Resultaten kunnen niet eenduidig aan model, preprocessing en execution environment worden herleid; incidentanalyse en reproduceerbaarheid falen. | Architecture + AI | Verplicht immutable RunManifest vóór inference: model-ID/version/SHA, adapter/config, tile-manifest/SHA, dataset/version, CRS/transform, threshold/NMS/max_det, seed, runtime/container/GPU. Run weigeren als verplichte velden ontbreken. | DB-migratie en schema constraints; contracttests; nieuwe run round-trip; reproduction op dezelfde tile/model/config; legacy records expliciet `lineage_incomplete`, nooit stil aangevuld. | -| ACC-R18 | High | Van 697 QA-samenvattingen zijn F1 en precision 58 keer null, mean IoU 90 keer null en recall 1 keer null. De no-overlap golden case geeft precision/recall 0 maar F1 null. | Undefined, zero en not-computable worden door elkaar gebruikt; dashboards/gates kunnen failures overslaan. | QA + Architecture | Metricsemantiek per empty/empty, prediction-only, truth-only en no-match case bevriezen; status/reason naast waarde; gate-aggregator mag null niet negeren. | Truth-table unit tests; migratie/classificatie van historische nulls; golden benchmark per case; promotion fails bij onverwachte null of ontbrekend stratum. | -| ACC-R19 | High | De GPU-smoke op één bestaande EPSG:31370-tile slaagt met active model SHA `a9088…59c1`, 17 detections en RTX 4080 SUPER, maar heeft geen ground truth en verklaart zelf geen accuracy/generalization claim. | Technische beschikbaarheid kan onterecht als modelkwaliteit worden geïnterpreteerd. | AI + QA | Smoke strikt scheiden van evaluatie; UI/docs/status benoemen `runtime_ready` apart van `validated_scope`; geen promotie op smoke-resultaat. | Contracttests voor statussen; model card toont afzonderlijk runtime-, calibration-, test- en scopebewijs; promotion code vereist alle hashes en gates. | -| ACC-R20 | High | De runtime heeft 0 segmentations en het gevalideerde segmentatiemodel ontbreekt; aanwezige assets zijn geen configuratie- of kwaliteitsbewijs. | UI/API kan door bestandsaanwezigheid een niet-bewezen capability suggereren. | AI + Frontend + QA | Segmentatie en zonnepaneelmodellen blijven `not_configured` totdat hun eigen corpus, metrics, model card en releasepad slagen. | End-to-end `not_configured`-tests; capability registry is evidence-driven; geen persisted outputs vóór aparte validatie/promotion. | - -## D. Verificatie, foutafhandeling en deployment - -| ID | Ernst | Bewezen evidence | Impact | Owner | Vereiste controle | Exit-evidence | -| --- | --- | --- | --- | --- | --- | --- | -| ACC-R21 | High | Met root/backend `PYTHONPATH` worden 1.197 tests verzameld: 1.180 pass en 17 falen. De gedocumenteerde backend-CI-aanroep faalt al bij collection doordat `backend/scripts` het rootpakket `scripts` overschaduwt. | Een groene deelset kan een kapotte canonical testentrypoint of regressies verbergen. | QA + Architecture | Eén canonical testcommand vanuit repo-root; package shadowing verwijderen; stale source-text assertions vervangen door behavior tests; geen baseline-updating zonder contractreview. | Volledige suite pass op CI-runtime én Tower-compatible image; exact command/exitcode/log vastgelegd; 17 regressies inhoudelijk geclassificeerd en opgelost. | -| ACC-R22 | Medium | Ruff rapporteert 112 issues (69 E702, 23 F401, 13 E402, 2 E701, 2 F811, 2 F841 en 1 F403). Frontend heeft geen `lint` script ondanks de teststrategie; typecheck, 51 Vitest-tests en build slagen wel. | Dead imports/compact statements en ontbrekende frontendlint verhogen defectrisico; het formele QA-contract is niet uitvoerbaar zoals beschreven. | QA + Frontend + Architecture | Ruff-baseline gecontroleerd afbouwen; echte frontendlintconfig/script toevoegen; lint in CI; generated/legacy uitzonderingen expliciet en smal. | `ruff check` en `npm run lint` pass; CI voert beide uit; bestaande typecheck/Vitest/build blijven groen. | -| ACC-R23 | High | Frontend detail/bootstrapfouten worden stil omgezet naar fallback/null; raster cache-open kan ondanks fout `ready` opleveren; secundaire detection/segmentation DB-markering kan worden ingeslikt. | Gebruiker ziet oude, onvolledige of schijnbaar succesvolle output zonder zichtbare lineagebreuk. | Frontend + Architecture + QA | Error states expliciet en typed; stale/cache-status tonen; persistence-failure maakt run/dataset failed of incomplete; geen broad catch zonder telemetry en user-visible status. | Fault-injectiontests per fallback; API/UI tonen correlation/run ID en retry; zero `ready/success` na verplichte persistence failure; structured logs/evidence. | -| ACC-R24 | High | Golden benchmark gebruikt UUID4 en meerdere trainingsscripts hebben onvolledig bevroren seed/runtimegedrag. | Baselines en manifests zijn byte-onstabiel; reruns kunnen niet betrouwbaar worden vergeleken. | QA + AI | Deterministische IDs uit inhoud/hash, seed alle RNG's, deterministische algoritmen waar ondersteund, expliciete nondeterministische kernelregistratie en tolerantiebeleid. | Twee clean-room reruns met identieke manifest/sample/split hashes; metrische verschillen binnen vooraf bevroren tolerantie; runtime/seed in RunManifest. | -| ACC-R25 | High | Lokale audit draait op Python 3.13/Node 24, CI op Python 3.11/Node 20. Compose default verwijst naar cu130, deployment naar cu128; CI bouwt alleen AI-disabled en valideert CUDA/AI-dependencies niet. Tower gebruikt PyTorch 2.11.0+cu128 en Ultralytics 8.4.99. | Een image kan lokaal/CPU slagen en op de GPU-runtime falen of een andere dependencyset gebruiken. | DevOps + AI + QA | Eén pinned AI build path en lock/SBOM; CI bouwt CPU-contract én GPU-image; Tower preflight valideert exacte torch/CUDA/Ultralytics/modelhash; geen CPU-fallback voor training. | Image digest + SBOM; build/test logs voor AI-enabled image; `cuda:0` preflight en bounded inference op RTX 4080; runtimeversies exact in release manifest. | -| ACC-R26 | Medium | De repo bevat een tracked geneste `geointel/`-kopie met 1.153 files en 68 afwijkende root/mirror-paren, plus grote tracked audit/inputartefacten. `.dockerignore` sluit de geneste mirror wel uit. | Lokale tooling/imports kunnen de verkeerde kopie analyseren; review en branchgrootte worden onnodig ambigu. | Architecture + DevOps | Canonieke root expliciet afdwingen; mirror in P2 via afzonderlijke, reviewbare migratie inventariseren en pas na bewijs archiveren/verwijderen; artifact-retentiebeleid. | CI-test faalt bij nieuwe root/mirrorduplicatie; nul ambigue importpaden; migratiemanifest met hashes en herstelpad; runtime image blijft rootcode gebruiken. | -| ACC-R27 | High | Tower checkout staat op `main`, loopt 67 commits vóór de stale `origin/main` en bevat untracked runtime-evidence/cache. | Deploybron en remote history zijn niet eenduidig; rollback/restore kan een andere codebasis opleveren. | DevOps + Architecture | Deployment uitsluitend vanaf gepushte immutable commit/tag en image digest; servercheckout niet als bron van waarheid; untracked runtime data buiten source tree of expliciet gemount. | Push/commit ancestrybewijs; deployment manifest met commit+digest+config; clean source checkout; rollbacktest naar vorige digest zonder dataverlies. | -| ACC-R28 | Medium | PostGIS meldt versie 3.6.4, maar core/topology procedures uit 3.4.3 “need upgrade”. | Ruimtelijke functiegedrag/migraties kunnen per omgeving afwijken en upgrades kunnen onverwacht falen. | Architecture + GIS + DevOps | Extension-upgradepad in restorebare stagingdatabase; functieversie/preflight in deployment; geen in-place productie-upgrade zonder backup en dry-run. | Restoretest, `ALTER EXTENSION`-dry-run/resultaat, PostGIS regression suite en versie-evidence vóór/na; rollbackprocedure getest. | -| ACC-R29 | Medium | API-contract, implementation gap docs, preflightvoorbeelden en actieve runtimeversies spreken elkaar op meerdere plaatsen tegen. | Operators en agents kunnen verouderde instructies volgen of capabilities overclaimen. | Architecture + QA | Docs genereren/valideren tegen OpenAPI, migrations, capability registry en runtime manifest; stale claims verwijderen met behoud van historisch bewijs. | Doc-contracttests; alle versies/scopes uit één bron; accuracy-program en operator README verwijzen naar actuele model card en release status. | - -## Positieve controles die behouden moeten blijven - -Deze bevindingen verlagen de bovenstaande risico's niet, maar zijn bewezen onderdelen waarop Phase 2 kan voortbouwen: - -- Tower ziet een NVIDIA GeForce RTX 4080 SUPER; PyTorch CUDA is beschikbaar en de productie-adapter heeft één bounded, read-only inference uitgevoerd. -- Alle 3.377 datasets hebben checksum, CRS, imported-at en source/provenance metadata; alle 1.671 DatasetVersions hebben checksum, storage path en metadata. -- De database-audit vond geen ontbrekende directe storage references in de gecontroleerde set. -- Areas en vector_features hebben in de runtime-snapshot geen invalid, empty of wrong-SRID geometrieën; de vier detection-afwijkingen blijven afzonderlijk releaseblokkerend. -- API/OpenAPI-, GIS-, AI-contract-, migratie-, frontend typecheck/Vitest/build- en gerichte testgroepen slaagden; de volledige canonical gate blijft desondanks rood door ACC-R21/22. - -## Risicoacceptatie - -Geen Critical-risico is accepteerbaar voor promotie of scopeverruiming. Een High-risico kan alleen door een expliciete, tijdgebonden operatorbeslissing worden geaccepteerd wanneer het geen accuracy-, bronautoriteits-, split- of lineagegate omzeilt. Zo'n uitzondering moet het risico-ID, bereik, eigenaar, rollback en bewijs bevatten. Ontbrekende evidence telt als een gefaalde gate, niet als “niet van toepassing”. diff --git a/docs/accuracy-program/05-metric-framework.md b/docs/accuracy-program/05-metric-framework.md deleted file mode 100644 index 5db11990..00000000 --- a/docs/accuracy-program/05-metric-framework.md +++ /dev/null @@ -1,631 +0,0 @@ -# GeoIntel Accuracy Improvement Program — metric framework - -- Status: Phase 1 measurement contract -- Scope: Belgium and the Belgian North Sea, with task-specific claims only -- Evidence root: `artifacts/evidence/accuracy/P1/` -- Last updated: 2026-08-01 - -## 1. Purpose - -This document defines how GeoIntel must measure, compare and communicate -accuracy. It is a measurement contract, not an assertion that any current model -meets a release threshold. - -The framework has five non-negotiable goals: - -1. every reported number is reproducible from checksum-bound inputs; -2. model-selection data stays separate from protected release evidence; -3. aggregate scores cannot hide a failing region or context; -4. missing, undefined or insufficient evidence fails closed; -5. claims never exceed the evaluated task, class, geography, source edition or - operating configuration. - -This framework applies to learned detection and segmentation outputs and to -deterministic spatial QA where a candidate layer is compared with a reference. -It does not turn authoritative GIS functions into machine-learning tasks. - -## 2. Current baseline versus future acceptance thresholds - -### 2.1 Baselines that exist now - -GeoIntel currently has a deterministic QA/QC code-regression baseline in -`fixtures/golden/golden_qa_benchmarks.json`. At IoU `0.5`, its frozen scenarios -include: - -| Scenario | Precision | Recall | F1 | Mean matched IoU | -|---|---:|---:|---:|---:| -| partial match | 0.5 | 0.5 | 0.5 | 0.8339768339761133 | -| perfect match | 1.0 | 1.0 | 1.0 | 1.0 | -| no overlap | 0.0 | 0.0 | undefined (`null`) | undefined (`null`) | -| multipolygon match | 1.0 | 1.0 | 1.0 | 1.0 | - -These values prove regression stability of the fixture matcher. They do **not** -measure production-model accuracy, Belgium-wide generalisation, source quality -or human acceptability. - -The runtime GPU/model smoke evidence proves only that a particular asset can be -loaded and invoked under the recorded configuration. It is not an accuracy -benchmark. Historical calibration reports and persisted `Metric` rows are -evidence candidates only when their complete lineage, split role, evaluator -version and inputs can be reproduced. - -Several scripts contain historical or provisional numeric defaults, including -the gate defaults in `scripts/assess_belgium_building_training_iteration.py`. -Those implementation defaults are not automatically approved Accuracy Program -release thresholds. Reports using them must label the gate source and version -as `legacy` or `provisional`; they cannot be relabelled as a Phase 1 contract. - -At the Phase 1 evidence cut, a canonical release-grade national model-quality -baseline is therefore `not_established`. No existing number may be presented as -a Belgium-wide acceptance result until the data, split, evaluator and review -requirements below are satisfied. - -### 2.2 Thresholds that must be frozen later - -All new promotion floors, ceilings, non-inferiority margins, sample minima, -confidence levels and latency budgets are `TBD`. They must be proposed from a -reviewed incumbent baseline and operational requirements, approved and -versioned **before** the protected test set is opened. - -The freeze record must identify: - -- task, class ontology and claim scope; -- dataset and split-manifest hashes; -- incumbent and candidate model hashes; -- exact preprocessing, tile, overlap, confidence and NMS configuration; -- evaluator version and object-matching policy; -- metric, aggregation level, direction and threshold; -- required strata and minimum evaluable support; -- confidence-interval or paired-comparison rule; -- runtime hardware and latency measurement protocol; -- approver, timestamp and immutable gate-definition hash. - -Seeing test results can never justify relaxing a threshold. A changed threshold -creates a new, independently approved evaluation protocol and requires evidence -that remains independent of the change. - -## 3. Evaluation unit and identity contract - -Every metric record must be traceable to the following identity tuple: - -```text -task + class_ontology_version + model_sha256 + dataset_manifest_sha256 -+ split_manifest_sha256 + evaluator_version + inference_config_sha256 -+ reference_source_version + imagery_source_version + run_id -``` - -The evidence record must also contain the Git commit, container image digest, -Python/PyTorch/CUDA/driver versions, random seed, deterministic-mode flags, -hardware, timestamps and command arguments. A metric without this tuple is -`unverifiable`, not an approximate success. - -All geometries must be validated and transformed to a declared common CRS -before matching. Distance, area and boundary metrics require a documented -metric/equal-area CRS appropriate to the AOI. CRS assumptions, geometry repair, -clipping and ignored boundary zones must be counted and reported. - -## 4. Error taxonomy - -Each reviewed error receives one primary code and any applicable secondary -codes. Counts must be available by sample, AOI, region and context. Free text -may explain an error but cannot replace a code. - -### 4.1 Data and lineage errors (`D-*`) - -- `D-MISSING-PROVENANCE`: missing source, edition, acquisition time, licence, - checksum or transformation lineage. -- `D-STALE-SOURCE`: imagery or reference is outside its declared validity - period. -- `D-TEMPORAL-MISMATCH`: the labelled object and image do not represent the - same observable time. -- `D-CRS-MISSING` / `D-CRS-WRONG`: CRS is absent, misdeclared or transformed - incorrectly. -- `D-ALIGNMENT`: systematic or local image/reference displacement. -- `D-INVALID-GEOMETRY`: empty, corrupt, self-intersecting or otherwise invalid - geometry, including an unrecorded repair. -- `D-RESOLUTION`: object is below the declared resolvable pixel/ground size or - input resolution differs from the model contract. -- `D-LICENCE-SCOPE`: source use or redistribution cannot be proven. -- `D-CACHE-STALE`: cached content does not match the requested source/version. - -### 4.2 Label and ontology errors (`L-*`) - -- `L-MISSING`: visible in-scope object has no label. -- `L-SPURIOUS`: label has no visible in-scope object. -- `L-CLASS`: wrong canonical class or source-to-canonical mapping. -- `L-EXTENT`: polygon/box extent is materially wrong. -- `L-INSTANCE-SPLIT`: one real instance is labelled as multiple instances. -- `L-INSTANCE-MERGE`: distinct instances are merged. -- `L-AMBIGUOUS`: imagery/reference cannot support a defensible decision. -- `L-EXCLUSION`: excluded ontology item was included, or a valid item was - excluded. -- `L-REVIEW-MISSING`: required human review or adjudication is absent. - -### 4.3 Split and duplication errors (`S-*`) - -- `S-EXACT-DUPLICATE`: byte/content-equivalent image, label or derived tile - crosses split boundaries. -- `S-NEAR-DUPLICATE`: materially identical view or transformed derivative - crosses split boundaries. -- `S-SPATIAL-OVERLAP`: AOIs, tile context or instances overlap across protected - split groups. -- `S-TEMPORAL-FAMILY`: repeated acquisitions of the same site leak site identity - or labels across splits without an approved temporal generalisation design. -- `S-SOURCE-FAMILY`: provider mosaics or parent rasters are divided in a way - that leaks shared context. -- `S-PROTECTED-USE`: calibration, test or background-test evidence influenced - fitting, sampling, augmentation, architecture, threshold or NMS selection. -- `S-MANIFEST-MUTATION`: an evaluated split or its role changed after freeze. - -Any `S-*` error invalidates the affected comparative evaluation until a new -independent split is frozen. - -### 4.4 Model-output errors (`M-*`) - -- `M-FP-BACKGROUND`: detection on a pure-background sample. -- `M-FP-CONFUSER`: detection on a named hard-negative/confuser. -- `M-FP-DUPLICATE`: multiple retained predictions for one reference instance. -- `M-FP-LOCALISATION`: predicted instance overlaps a reference but misses the - frozen match criterion. -- `M-FN-MISSED`: resolvable in-scope reference instance is absent. -- `M-FN-SUPPRESSED`: valid instance is removed by confidence, NMS, containment - or post-processing. -- `M-CLASS`: prediction is assigned to the wrong class. -- `M-BOUNDARY`: segmentation boundary is materially displaced despite object - detection. -- `M-AREA-BIAS`: predicted geometry has systematic area over- or - under-estimation. -- `M-MISCALIBRATED`: confidence does not correspond to empirical correctness. -- `M-OOD`: sample is outside the declared training/evaluation domain. - -False positives and false negatives must retain evidence links to prediction -and reference IDs, source tiles and review decisions. - -### 4.5 Pipeline and claim errors (`P-*`, `C-*`) - -- `P-FALLBACK`: mock, heuristic, alternate source or stale cache replaced the - declared path. -- `P-NONDETERMINISTIC`: rerun differences exceed the frozen reproducibility - policy without explanation. -- `P-PARTIAL`: missing tile/chunk/output was silently omitted. -- `P-UNIT`: metres, degrees, pixels, CRS units or resolution were confused. -- `P-RUNTIME`: OOM, timeout, truncation or worker failure changed the evaluated - output. -- `C-OVERCLAIM`: wording exceeds evaluated task/scope/data. -- `C-MISSING-DENOMINATOR`: a rate is published without counts/support. -- `C-UNSUPPORTED-AGGREGATE`: an aggregate hides missing or failed strata. -- `C-UNTRACEABLE`: result cannot be tied to the identity tuple in section 3. - -## 5. Object-level metrics - -### 5.1 Matching contract - -Metrics are meaningless without a matching policy. Every report must specify: - -- supported geometry types and class matching; -- IoU thresholds; -- confidence ordering; -- one-to-one matching algorithm and tie-breaking; -- boundary clipping/ignore policy; -- treatment of difficult, ambiguous and below-resolution labels; -- duplicate-suppression configuration. - -The current `QaService` performs one-to-one greedy polygon matching at a -configurable IoU threshold (default `0.5`) and conditions mean IoU on matched -objects. This is a deterministic spatial QA baseline when input order and -evaluator version are fixed, but it is not automatically COCO AP. - -For detector PR/AP evaluation, predictions must be sorted by confidence and -matched one-to-one at each IoU threshold using a frozen COCO-compatible policy. -For fixed-threshold spatial comparison, a separately named matcher may use a -deterministic maximum-weight one-to-one assignment. Results from different -matchers must never be combined under the same metric key. - -### 5.2 Counts and rates - -For an evaluable class and stratum: - -```text -precision = TP / (TP + FP) -recall = TP / (TP + FN) -F1 = 2 * precision * recall / (precision + recall) -IoU = intersection_area / union_area -``` - -Always publish `TP`, `FP`, `FN`, prediction count and reference count beside the -rates. Undefined denominators produce `null`, never zero and never pass. In -particular: - -- no predictions makes precision undefined; -- no references makes recall undefined; -- zero precision plus zero recall keeps F1 undefined under the current QA - service semantics; -- pure-background performance is evaluated with explicit FP/background metrics, - not fabricated precision or recall; -- mean matched IoU is conditional on matches and must not be used alone because - it excludes FP and FN. - -### 5.3 Precision-recall and average precision - -Report the full precision-recall curve and its confidence thresholds. Required -detector summaries are: - -- `AP50`: area under the interpolated PR curve at IoU 0.50; -- `AP50-95`: mean AP across IoU 0.50 through 0.95 in steps of 0.05; -- per-class AP and macro AP for multi-class tasks; -- recall at the frozen operating point; -- precision at the frozen operating point. - -AP must be calculated before choosing a production confidence threshold. A -single-threshold F1 value cannot be called AP. AP values from a training -framework are accepted only when evaluator version, input set, class mapping -and settings are recorded and independently reproducible. - -### 5.4 Localisation and geometry - -Report the distribution, not only the mean, of matched IoU: count, median, -quartiles and lower-tail quantiles. Segmentation candidates additionally need -pixel/geometry IoU, Dice, boundary distance/score, area bias and topology-error -counts under a frozen geometry protocol. Metric thresholds for those measures -remain `TBD` until the segmentation label contract exists. - -Object results must be stratified by predeclared size bands derived from ground -area and/or source-image pixels. Band boundaries are `TBD` and must be frozen -from resolution and ontology rules before candidate results are inspected. - -## 6. Tile-level metrics - -Tile metrics expose operational failure modes that object-level micro-averages -can hide: - -- tile count, evaluable tile count and excluded-tile reasons; -- positive/empty tile counts; -- fraction of pure-empty tiles with one or more predictions; -- FP count per pure-empty tile and per square kilometre; -- fraction of positive tiles with at least one FN; -- per-tile precision, recall and F1 where defined; -- detection/reference count error per tile; -- duplicate predictions created at tile overlaps; -- tile processing latency, throughput and peak memory; -- tile-level error/uncertainty score for review routing. - -Report macro distributions across tiles as diagnostics. Do not average undefined -tile rates into zero, and do not let a large number of easy empty tiles dominate -the primary object metric. - -## 7. AOI-level metrics - -The AOI is the primary unit for paired operational comparison. For each AOI, -publish: - -- TP, FP, FN, precision, recall, F1 and matched-IoU distribution; -- reference and predicted object counts and signed/absolute count error; -- reference and predicted geometry area and signed/absolute area bias when - geometry outputs support it; -- pure-background/context-negative errors; -- excluded area/objects and reasons; -- end-to-end runtime, failed/retried tiles and completeness; -- taxonomy counts and links to visual evidence. - -Candidate-versus-incumbent deltas must be paired on the exact same AOIs, -references and inference contract. Macro AOI results give each AOI equal weight; -micro results pool TP/FP/FN. Both are reported and explicitly named. The primary -aggregation and any non-inferiority margin remain `TBD` until frozen in the -gate definition. - -## 8. Region-, context- and portfolio-level metrics - -At minimum, building-model evidence must report Flanders, Wallonia and Brussels -separately. The Belgian North Sea is not an implicit building-detector claim; -offshore tasks need their own ontology and evidence. - -Required stratification dimensions, where applicable, are: - -- region and provider/source edition; -- urban, suburban, ribbon development, rural/village, farm, industrial and - other frozen context families; -- dense/occluded/touching-object contexts; -- pure background and named hard-negative families; -- object-size band and input ground resolution; -- imagery period/season and reference-to-imagery time difference; -- AOI boundary/interior and tile-edge/interior; -- native class/source subtype and label-review state; -- normal domain versus declared OOD challenge set. - -For every required stratum report support, micro metrics, macro AOI metrics and -uncertainty intervals. Also report the worst evaluable required stratum. A -portfolio aggregate is valid only if every mandatory stratum has sufficient -predeclared support; otherwise its state is `not_evaluable`. - -Intersectional slices should be added where error evidence warrants them, but -post-hoc slices are diagnostic and cannot replace the frozen primary analysis. -Small groups stay visible with an `insufficient_support` label; they are not -silently pooled into a better-performing group. - -## 9. Confidence calibration - -Model confidence is not accuracy and is not a complete uncertainty estimate. -Calibration is evaluated on the frozen calibration split after one-to-one -matching and before protected-test access. - -### 9.1 Expected calibration error - -For prediction bins `B_m` frozen before evaluation: - -```text -ECE = sum_m (|B_m| / n) * |accuracy(B_m) - confidence(B_m)| -``` - -The binning method, boundaries, empty-bin handling and minimum observations must -be recorded. Report a reliability diagram and per-bin counts. A predefined -fixed-bin ECE is the comparable metric; adaptive-bin ECE may be reported only as -a labelled diagnostic. ECE is paired with recall because missed references have -no prediction confidence and are invisible to prediction-only ECE. - -### 9.2 Brier score - -For each scored prediction, define `y=1` only when it is the retained match under -the frozen policy, otherwise `y=0`: - -```text -Brier = mean((confidence - y)^2) -``` - -Report Brier overall and by required stratum. The exact construction of the -prediction set must be frozen; Brier does not replace FN/recall reporting. - -Calibration fitting may use only calibration data. If temperature scaling, -isotonic regression or another mapping is used, its fitted parameters and code -version become part of the immutable inference configuration. Test data may -evaluate that mapping but may not refit it. - -## 10. Latency, capacity and reliability - -Accuracy promotion also requires a reproducible operational profile on the -declared server GPU. Record separately: - -- cold-start/model-load time; -- warm model-only inference time per tile; -- preprocessing, inference, post-processing and persistence time; -- end-to-end AOI latency excluding and including queue wait; -- median, p95, p99 and maximum latency with sample counts; -- tiles/second and square kilometres/minute at the recorded resolution; -- peak allocated/reserved VRAM and host RAM; -- batch size, tile size, overlap, worker concurrency and retry count; -- OOM, timeout, truncation, partial-output and failed-job rates. - -Warm-up count, timing clock, synchronisation method, hardware, driver and -background load must be fixed. A local CPU run and an RTX 4080 SUPER CUDA run -are different baselines. Latency budgets are `TBD`; current smoke timings may be -reported as observations only. - -## 11. Uncertainty and selective review - -Uncertainty evidence may include confidence, entropy/margin where meaningful, -test-time-augmentation disagreement, ensemble variance, spatial disagreement -and OOD scores. Every method must state what variation it measures; confidence -alone may not be labelled epistemic uncertainty. - -For any abstain/review policy, report: - -- retained coverage versus error/risk curve; -- error rate in auto-accepted, human-review and rejected bands; -- review volume per AOI/region/context; -- area under the risk-coverage curve as a diagnostic; -- failure cases where high-confidence predictions are wrong; -- threshold source and calibration-only selection evidence. - -Uncertainty thresholds are `TBD`. Uncertainty may route work to a human; it must -not create self-training labels or silently suppress output. - -## 12. Strict split and deduplication rules - -### 12.1 Split roles - -- `train`: fitting and training-time augmentation only; -- `val`: epoch/checkpoint/architecture selection only; -- `calibration`: confidence, tiling, overlap, NMS and calibration mapping only; -- `test`: sealed, one-time promotion evidence for a frozen candidate family; -- `background-test`: sealed, difficult and pure-background release evidence. - -No test or background-test result may influence fitting, sampling weights, -label policy, architecture, hyperparameters, post-processing or gate values. If -it does, that split is retired from independent testing, the candidate becomes -a new family and a new untouched protected split is required. - -### 12.2 Grouping before splitting - -Deduplication and grouping happen before split assignment. The atomic group must -keep together: - -- a parent AOI plus every derived/overlapping tile; -- all tiles sharing an object instance; -- exact image/label hashes and transformed copies; -- perceptual near-duplicate families; -- repeated views whose shared spatial context exceeds the declared independence - buffer; -- source-raster/mosaic or temporal families when they would leak scene identity. - -Train, val, calibration, test and background-test AOIs must be spatially -disjoint, including a buffer larger than the maximum tile context used by any -candidate. The buffer value and near-duplicate thresholds are `TBD` but must be -frozen before corpus generation, not chosen after metric inspection. - -### 12.3 Required leakage audits - -The frozen split evidence must contain: - -- exact SHA-256 duplicate matrix for raw image, processed image and label; -- perceptual-image and label-geometry near-duplicate audit; -- buffered AOI/tile intersection audit in a metric CRS; -- shared native feature/source identifier audit; -- parent raster, acquisition and temporal-family audit; -- tile-versus-manifest role consistency audit; -- counts and explicit disposition for every collision. - -All cross-split collisions must be zero unless a written experimental design -defines a non-independence group and assigns that whole group to one split. A -leakage audit that did not run, timed out or lacks inputs is a failed gate. - -## 13. Human-review metrics - -Automated geometry checks do not replace representative human review. Corpus -labels and model outputs need separate review records. - -### 13.1 Label-corpus review - -Report: - -- planned, rendered, reviewed and adjudicated sample/object counts; -- completion rate by region, context, provider, size band, split and label - source; -- contact-sheet/render failures and unreadable samples; -- prevalence of every `D-*` and `L-*` finding; -- accepted, corrected, excluded and ambiguous counts; -- single-review and independent double-review counts; -- raw reviewer agreement, class-wise agreement and an approved chance-corrected - agreement statistic such as Cohen's kappa or Krippendorff's alpha; -- disagreement/adjudication rate and unresolved critical findings. - -Sampling quotas, double-review fraction, agreement statistic and acceptance -thresholds are `TBD` and must be frozen before reviewers see model results. -Protected test labels should be reviewed independently of candidate predictions. - -### 13.2 Output-error review - -For each candidate, use a frozen stratified sample that includes TP, FP, FN, -low-confidence, high-confidence, tile-edge, dense, temporal-mismatch and OOD -cases. Reviewers record taxonomy codes and severity, not only approve/reject. -Report reviewer agreement, adjudication, severe-error prevalence and error -distribution by stratum. - -Review UI/version, imagery/reference layers, zoom/scale and reviewer identity or -pseudonymous ID must be retained. A generated contact sheet with zero completed -review decisions is `unreviewed`, not passed. - -## 14. Statistical reporting - -All rates include numerator, denominator and support. Confidence intervals use -a predeclared method appropriate to the unit: object-level bootstrap must not -pretend correlated tiles are independent. Prefer cluster bootstrap or paired -analysis at AOI/group level for model comparisons. - -Report: - -- point estimate and interval; -- number of independent AOIs/groups; -- micro and macro aggregation; -- paired candidate-minus-incumbent delta by AOI; -- worst required stratum and its support; -- missing/excluded evidence and reason; -- multiplicity policy for any formal multi-stratum hypothesis claims. - -The confidence level, bootstrap seed/replicates and non-inferiority margins are -`TBD` until the gate specification is frozen. Descriptive diagnostics must not -be presented as confirmatory release evidence. - -## 15. Acceptance-gate semantics - -Every gate returns exactly one state: - -- `pass`: complete evidence meets the frozen rule; -- `fail`: complete evidence violates the frozen rule; -- `not_evaluable`: evidence is missing, invalid, leaked or below frozen support. - -`not_evaluable` blocks promotion exactly like `fail`; it is never coerced to -zero, ignored or averaged away. - -A promotion decision is a logical AND across all mandatory gate families: - -1. identity, provenance, licence and immutable manifest; -2. zero unresolved split leakage and duplicate-family violations; -3. automated data/label/geometry integrity; -4. completed representative human review and adjudication; -5. frozen object/AOI/region/context accuracy gates; -6. pure-background and hard-negative gates; -7. calibration and uncertainty/review-policy gates; -8. paired incumbent comparison and reproducibility rerun; -9. GPU latency, capacity and failure-rate gates; -10. model card, scope limitation, rollback and live shadow evidence. - -No weighted composite score may compensate for a failed mandatory gate. The -aggregate and every mandatory region/context gate must pass independently. -Candidate selection and operating-point selection use calibration evidence -only. The protected test is evaluated once with the frozen configuration. A -rerun is allowed only to reproduce the same immutable computation or to resolve -a proven execution failure without inspecting/using partial results. - -Gate output must include machine-readable rule IDs, observed values, expected -direction/range, support, evidence paths and hashes. Manual override cannot -change a metric result; an exceptional operational decision must remain a -separate signed record and cannot widen the accuracy claim. - -## 16. No-claim rules - -GeoIntel must not claim that a model is “fully trained”, “validated”, -“production accurate”, “Belgium-wide” or equivalent when any of the following -is true: - -- only model-file presence, load success, a GPU smoke or output existence was - proven; -- results come from train/val data, an unfrozen calibration set or leaked test - evidence; -- the dataset, model, evaluator or inference configuration lacks hashes; -- required region/context support or representative human review is missing; -- a metric is undefined/null, a job is partial or a fallback/mock/heuristic was - used; -- only aggregate performance is shown while a required stratum is absent or - failing; -- precision/recall/AP is reported without match policy and TP/FP/FN/support; -- confidence is presented as probability of correctness without calibration - evidence; -- a deterministic fixture benchmark is presented as production-model quality; -- the claim is extrapolated to another class, source, imagery period, - resolution, region, segmentation task or deterministic GIS function; -- test results were used to choose the next training data or configuration. - -Permitted wording must be evidence-bounded, for example: “candidate X achieved -the recorded metrics on frozen portfolio Y under configuration Z.” It must name -limitations and may not imply untested generalisation. - -## 17. Required machine-readable outputs - -Each future baseline or candidate evaluation must retain, without overwriting -earlier evidence: - -```text -evaluation-contract.json -input-manifest.json -split-and-leakage-audit.json -object-metrics.json -tile-metrics.json -aoi-metrics.json -stratified-metrics.json -calibration-metrics.json -latency-and-reliability.json -human-review-summary.json -error-taxonomy.json -candidate-vs-incumbent.json -acceptance-gates.json -evidence-manifest.json -``` - -`evidence-manifest.json` must SHA-256 hash every retained input and output. Any -amendment is additive, versioned and linked to its predecessor. Raw records -must remain available so every aggregate can be recomputed. - -## 18. Phase 2 metric implementation sequence - -1. freeze evaluator schemas, taxonomy codes and undefined-value semantics; -2. implement strict group split and exact/near-duplicate audits; -3. validate CRS/alignment/label lineage and complete human corpus review; -4. freeze an incumbent portfolio and run a reproducible baseline twice; -5. derive and approve numeric thresholds from reviewed baseline distributions - and operational requirements without protected-test access; -6. calibrate candidate operating points on calibration data only; -7. execute the one-time protected test and background-test gates; -8. publish scope-bounded evidence or retain `not_configured`/current limited - scope when any gate is not evaluable. - -Until those steps pass, this framework authorises measurement and remediation, -not a widened accuracy claim. diff --git a/docs/accuracy-program/06-implementation-roadmap.md b/docs/accuracy-program/06-implementation-roadmap.md deleted file mode 100644 index 7b14a94f..00000000 --- a/docs/accuracy-program/06-implementation-roadmap.md +++ /dev/null @@ -1,342 +0,0 @@ -# GeoIntel Accuracy Improvement Program — uitvoerbare roadmap - -- Status: **Phase 2 mag starten; release en nationale modelclaim blijven geblokkeerd** -- Bronnen: Phase-1 inventory, lineage, baseline/gaps, risicoregister en metric framework -- Runtime voor training: Tower NVIDIA GeForce RTX 4080 SUPER op `cuda:0` - -## Doel en definitie van gereed - -Deze roadmap herstelt eerst de bewijs- en vertrouwensketen en bouwt daarna pas een nieuw Belgisch building-corpus en model. “100% getraind” betekent hier: alle vooraf bevroren corpus-, split-, runtime-, metric-, review-, test-, promotion- en deploymentgates zijn aantoonbaar geslaagd voor één expliciete modelscope. Het betekent niet 100% precision/recall en geeft geen claim buiten de geëvalueerde regio's, contexts, imagery editions en objectgroottes. - -De volgorde is verplicht. Een work package start pas wanneer zijn dependency-gate groen is. Bij een gefaalde gate blijft productie op de huidige beperkte, expliciet gecommuniceerde Mol/Kempen-scope of schakelt de betrokken capability fail-closed naar `not_configured`. Checkpoints, datasets en bewijs worden nooit overschreven. - -## Niet-onderhandelbare regels - -1. **Test-first:** ieder bewezen defect uit `04-risk-register.md` krijgt eerst een regressietest die op de huidige foutieve implementatie faalt. -2. **Protected-test isolation:** train, val en calibration mogen tijdens iteraties worden gelezen; test en background-test blijven verzegeld tot één kandidaat-SHA, preprocessingconfig, threshold en gates bevroren zijn. -3. **Geen testgestuurde retraining:** na openen van protected test volgt voor die candidate family geen training, thresholdwijziging, sampleweging of configuratiekeuze meer. -4. **Evidence of fail:** ontbrekend, null of niet-reproduceerbaar bewijs is een gefaalde gate. -5. **Immutable lineage:** iedere dataset-, run-, model- en releaseversie heeft een checksum-bound manifest; legacy gaps blijven zichtbaar als `lineage_incomplete`. -6. **GPU verplicht:** training gebruikt `cuda:0` op de Tower RTX 4080 SUPER met `TRAIN_REQUIRE_CUDA=true`; CPU-fallback is een failure. -7. **Geen claim op file presence:** een `.pt`-bestand of succesvolle smoke maakt een model niet gevalideerd. -8. **Menselijke review is echt menselijk:** automatische QA mag een ontbrekende review nooit als akkoord invullen. De finale productreview door de gebruiker volgt pas nadat alle objectieve gates groen zijn. - -## Dependency-overzicht - -| Volgorde | Work package | Depends on | Primaire output | Risico's gesloten | -| --- | --- | --- | --- | --- | -| P2-00 | Promotion lock en evidence freeze | Phase 1 | immutable baseline + release lock | claimgrens voor alle risico's | -| P2-01 | Canonical test harness | P2-00 | rode regressietests en uitvoerbare CI-matrix | ACC-R21, R22, basis voor alle fixes | -| P2-02 | CRS, units en geometry integrity | P2-01 | veilig ingest/transform/buffer + data repair | ACC-R01, R02, R07 | -| P2-03 | Coverage, authority en wettelijke scope | P2-02 | trusted source registry en geometry-backed scope | ACC-R03–R06 | -| P2-04 | Transactionele lineage en foutzichtbaarheid | P2-02, P2-03 | complete Run/Dataset lineage en fail-closed persistence | ACC-R08, R15, R17, R23 | -| P2-05 | Protected-split redesign | P2-01, P2-04 | test vault, manifest schema en sampler firewall | ACC-R09, R10, R14, R24 | -| P2-06 | Menselijke labelreview en corpusrebuild | P2-02, P2-03, P2-05 | immutable reviewed `building-be-*` corpus | ACC-R10–R15 | -| P2-07 | Metric framework en reproducible incumbent baseline | P2-04, P2-06 | frozen metrics/gates + paired baseline | ACC-R16, R18, R19 | -| P2-08 | Reproducible CUDA candidate training | P2-05, P2-06, P2-07 | immutable RTX 4080 candidate portfolio | ACC-R14, R16, R17, R24, R25 | -| P2-09 | Calibration-only improvement loop | P2-08 | fixed candidate that passes all pre-test gates | ACC-R12, R13, R16 | -| P2-10 | Eenmalige protected test | P2-09 | signed pass/fail promotion evidence | ACC-R09, R16, R18 | -| P2-11 | Guarded promotion, shadow en redeploy | P2-10 pass | model card, immutable image, rollback | ACC-R17, R19, R25, R27, R29 | -| P2-12 | Monitoring en controlled next cycle | P2-11 | reviewed drift queue zonder self-training | blijvende beheersing | - -## P2-00 — Promotion lock en evidence freeze - -### Uitvoering - -- Leg current commit, server commit, container digest, DB migration head, active model path/SHA, modelscope en alle P1-evidencehashes vast. -- Zet `nationally_validated=false` en de actuele Mol/Kempen-scope expliciet in de capability/model-card response; voorkom scopeverruiming zonder promotion report. -- Markeer v56/v58/v62/v66 en andere checkpoints als `candidate/unpromoted`; verander of verwijder geen files. -- Maak een restorebare databaseback-up en inventory van storage references vóór migraties. -- Bewaar de succesvolle GPU-smoke als runtimebewijs met de expliciete claimgrens “geen accuracy-evidence”. - -### Exit gate - -- Evidence manifest is hash-compleet en read-only gekopieerd naar de release-auditlocatie. -- Production promotion endpoint/config weigert een kandidaat zonder signed promotion report. -- Rollbackdoel (huidige image digest + model SHA + config) is reproduceerbaar vastgelegd. - -## P2-01 — Canonical test harness en rode regressies - -### Uitvoering - -- Maak één repo-root testentrypoint voor Python; verwijder de `backend/scripts` versus root `scripts` shadowing. -- Voeg vóór productcodewijzigingen regressies toe voor: - - EPSG:31370/3812 als 4326 gelabeld; - - 100 m buffer als graden; - - cross-theme coverage union; - - forged authoritative upload; - - area-name/YOLO-scope bypass; - - Area PATCH geometry/CRS; - - ready-derived dataset zonder PostGIS-features; - - protected test als samplerinput; - - metric null/empty truth table; - - persistence- en frontendfallbacks. -- Vervang stale broncode-stringasserties door behavior/contracttests; wijzig expected output alleen met een gedocumenteerde contractbeslissing. -- Voeg Ruff en een echte frontend `npm run lint` gate toe; behoud typecheck, Vitest en build. -- Laat CI dezelfde Python/Node-versies en commands gebruiken als de pinned build; maak een aparte AI-enabled image gate. - -### Verificatiecontract - -De CI-matrix bevat minimaal: volledige backend-Pytest, Alembic offline+live PostGIS, Ruff, frontend lint/typecheck/Vitest/build, OpenAPI-contractaudit en de gerichte GIS/AI regressies. De oude implementatie moet de nieuwe regressies aantoonbaar laten falen; pas daarna worden fixes geaccepteerd. - -### Exit gate - -- Eén canonical commandmatrix is volledig groen in een schone checkout. -- De 17 bestaande failures zijn per contract geclassificeerd en opgelost. -- Geen test wordt geskipt op basis van ontbrekende lokale AI/GIS-dependency zonder expliciete, afzonderlijk rode environment gate. - -## P2-02 — CRS-, eenheden- en geometry-integriteit - -### Uitvoering - -1. Definieer per API/file-ingest het bron-CRS, canonical storage-CRS en output-CRS. Ontbrekende of ambigue CRS faalt met een typed fout. -2. Transformeer EPSG:31370 en EPSG:3812 met `pyproj`/GeoPandas/PostGIS naar EPSG:4326 vóór `from_shape(..., srid=4326)`. -3. Implementeer buffer via een geldige metrische projectie of PostGIS geography; log units en transform. -4. Maak Area PATCH exact conform contract: geometry wordt valide getransformeerd of extra input wordt geweigerd; CRS relabeling zonder transform is onmogelijk. -5. Herleid de vier buiten-domein detections uit originele tile, manifest, EPSG:31370-transform en modeloutput. Bewaar oude rijen/evidence; corrigeer via een auditabele migratie of markeer ze `invalid_legacy_geometry`. -6. Voeg DB constraints/checks toe waar die legitieme EPSG:4326-extents kunnen afdwingen zonder de Noordzee of grensgebieden fout af te wijzen. - -### Exit gate - -- CRS/units regressies en live PostGIS-tests slagen. -- Runtime-audit meldt zero ongeclassificeerde invalid/empty/wrong-SRID/out-of-domain geometry. -- De vier legacy detection-ID's zijn traceerbaar vóór en na migratie; geen stille overschrijving. - -## P2-03 — Coverage-, authority- en scopevertrouwen - -### Uitvoering - -- Herstructureer coverage zodat alleen datasets die source, theme, layer én zone matchen aan de coverage union deelnemen. -- Introduceer immutable `source_registry_id`, trust class, provider adapter en bronversie. Caller metadata blijft descriptief en kan nooit official authority verlenen. -- Migreer user uploads naar `manual/untrusted` tenzij hun acquisition/job lineage een governed adapter bewijst. -- Vervang displaynaam-gebaseerde legal zones door stable codes en geometry-backed predicates. -- Vervang YOLO-name-substringcontrole door model-card scope geometry/zone IDs met expliciete containment-policy. -- Maak API/UI onderscheid tussen `available`, `covered`, `authoritative`, `runtime_ready` en `model_validated_for_scope`. - -### Exit gate - -- Forged-source-, mixed-theme-, rename- en scope-bypasstests slagen. -- Bestaande source records hebben een auditbare trust classification. -- Een AOI buiten Mol/Kempen kan het actieve model niet uitvoeren door naam of metadata te manipuleren. - -## P2-04 — Transactionele lineage en zichtbare failures - -### Uitvoering - -- Maak een verplicht `RunManifest` met model-ID/version/SHA, dataset/version/SHA, tile-manifest/SHA, source imagery/reference versions, CRS/transform, preprocessing, threshold, NMS/max-det, seed, runtime/container/GPU en code commit. -- Maak derived vector persistence atomair: AnalysisRun, Dataset, DatasetVersion, artifact en vector_features gaan samen van `processing` naar `ready`; elke verplichte write failure maakt de run failed. -- Classificeer `observed_at` en `source_version` per bronfamilie als required/not-applicable/unknown-with-reason en voer een provenance-safe backfill uit. -- Markeer historische detection runs zonder volledige lineage als `lineage_incomplete`; vul modelversies niet afgeleid of op basis van huidige config in. -- Verwijder silent catches: UI krijgt een typed error/stale state met run ID; services mogen geen success/ready rapporteren na persistence failure. - -### Exit gate - -- Nieuwe analyses zijn van UI-resultaat tot tile, bron, model en container volledig traceerbaar. -- Fault-injection geeft failed/incomplete, nooit ready/success. -- Lineage-audit heeft zero ongeclassificeerde verplichte gaps voor nieuwe records en een expliciete legacybucket. - -## P2-05 — Protected-split redesign en manifest firewall - -### Uitvoering - -1. Definieer één versioned corpusmanifest met immutable sample-ID, image/label SHA, bronfeature-ID, region/context, provider/edition, imagery/reference time, CRS/resolution, tile/stride/overlap, split en reviewstatus. -2. Bereken splits op buffered AOI's vóór tiles worden geëxporteerd. Controleer geometry overlap, contextbuffer, feature-ID's, image/label hashes en perceptuele near-dupes. -3. Verplaats protected test en background-test naar een afzonderlijke read-only locatie/credential die de training- en samplerprocessen niet kunnen lezen. -4. Splits de huidige orchestrator: - - `train/val/calibration loop`: fit, early stopping, threshold en error taxonomy; - - `release evaluation`: alleen frozen kandidaat/config en protected credentials. -5. Laat de failure-driven sampler uitsluitend calibration-aggregaten en train-only contextcatalogi lezen. Hij moet hard falen zodra een assessment testdata, test-ID's of een protected pad bevat. -6. Log iedere protected access met candidate SHA, config SHA, operator/runner, timestamp en output SHA. - -### Exit gate - -- Canary protected sample verschijnt in geen enkel train/val/calibration manifest, log, cache of sampleroutput. -- Minimum cross-splitafstand voldoet aan de vooraf vastgelegde contextbuffer; 24 huidige near-pairs zijn opgelost of met objectief geometrisch bewijs als onafhankelijk geclassificeerd. -- Testcredentials zijn tijdens training technisch niet beschikbaar. - -## P2-06 — Menselijke review en immutable corpusrebuild - -### 1. Review de bestaande kandidaatdata - -- Genereer contact sheets/kaartoverlays voor een vooraf geregistreerde, gestratificeerde reviewqueue: regio, provider, dense urban, suburban, rural, industrial, coast, forest/heath, rail/port/quarry, pure-empty, hard negative, kleine objecten, extreme aspectratio en providerseams. -- Beoordeel expliciet de 521 kleine labels, extreme aspectgroepen, sub-resolution/post-imagery exclusions en zeer dichte PICC/UrbIS-labelgebieden. -- Sla accept/reject/repair/uncertain op met reviewer, reason code, native feature-ID, image/label version en checksum. `uncertain` blijft uitgesloten of in een afzonderlijke non-training queue. - -### 2. Provision onafhankelijke AOI's - -- Vul iedere vereiste region/context-cel uit het bevroren corpuscontract; voeg Brussels pure-background toe en breid moeilijke negatives uit zonder protected voorbeelden te kopiëren. -- Gebruik officiële imagery/reference adapters en leg acquisition edition/periode vast. -- Houd train-only uitbreidingen ruimtelijk onafhankelijk van val/calibration/test/background-test en van elkaar waar het contract dat vereist. - -### 3. Herbouw en freeze - -- Pas temporal/resolution/providersemantics toe op GRB, PICC en UrbIS; post-imagery en niet-resolveerbare features krijgen een expliciete rejection reason. -- Exporteer deterministisch met ingevulde dataset-YAML/class/tile/stride/overlap-velden. -- Run geometry, label, density, class, blank/variance, duplicate/near-duplicate, split-distance, temporal en provenance audits. -- Freeze een nieuwe corpusversie; verander v56/v66 niet. - -### Exit gate - -- Representatieve menselijke review is volledig; zero unresolved Critical/High findings. -- Elke verplichte region/context/background-cel voldoet aan het vooraf bevroren contract. -- Zero cross-split leakage/near-duplicate violations; timestamps en unknowns zijn expliciet. -- Corpus, reviewrecords, manifests, YAML en auditrapporten zijn SHA-bound en immutable. - -## P2-07 — Metric framework en reproduceerbare incumbent baseline - -### Uitvoering - -- Implementeer de truth table uit `05-metric-framework.md` voor empty/no-match/undefined cases; null kan een gate nooit stil passeren. -- Meet detection precision, recall, F1 en AP op bevroren IoU-contracten; voeg objectgrootte, dichtheid, region, provider, context en pure-background strata toe. -- Behandel calibration en test afzonderlijk. Selecteer threshold/NMS/tile-overlap op calibration met worst-region/worst-context vóór aggregate. -- Evalueer het actieve model als incumbent op exact dezelfde niet-protected calibrationportfolio en bewaar paired AOI-resultaten. -- Maak FP/FN contact sheets en error taxonomy: label/temporal mismatch, tile-edge, small object, dense cluster, roof displacement, source seam, context confusion en model miss. -- Freeze alle numeric gates vóór protected test. Bestaande minimale gates mogen alleen vóór test en op basis van reviewed baseline distributions worden aangescherpt; nooit versoepeld na testinzage. - -### Exit gate - -- Twee baseline-runs met dezelfde inputs leveren dezelfde sample/split hashes en metrics binnen vooraf vastgelegde tolerantie. -- Alle strata hebben een waarde of expliciete failstatus; zero silently ignored nulls. -- Gateconfig, evaluator, incumbent SHA en calibrationresultaat zijn immutable. - -## P2-08 — Reproduceerbare CUDA-training op RTX 4080 SUPER - -### Uitvoering - -- Bouw één pinned AI image voor PyTorch/CUDA/Ultralytics; leg image digest, SBOM, driver/runtime, GPU, peak VRAM en code commit vast. -- Voer VRAM-preflight uit voor iedere kandidaatconfig; OOM/failure blijft als artifact en mag niet stil naar CPU vallen. -- Train een vooraf begrensde matrix zoals vastgelegd in `PYTORCH_TRAINING_ROADMAP_BELGIUM.md`; wijzig matrix noch primary metric na resultaten te zien. -- Seed Python/NumPy/PyTorch/Ultralytics; gebruik deterministic algorithms waar ondersteund en registreer afwijkingen. -- Training leest uitsluitend train; val kiest epochs/checkpoint; calibration kiest threshold/NMS/tile policy. Protected testmount/credential ontbreekt. -- Sla per run config, stdout/stderr, curves, checkpoints, optimizer state, dataset/corpus SHA, seed, runtime en peak VRAM op. Kopieer checkpoints immutably; overschrijf active model nooit. -- Herhaal de winnende configuratie clean-room vanaf dezelfde base weights en corpus om reproduceerbaarheid te toetsen. - -### Exit gate - -- Alle geplande kandidaten hebben complete run manifests of expliciete failure artifacts. -- Minstens één kandidaat en zijn clean-room rerun voldoen aan vooraf bevroren reproducibilitytoleranties. -- GPU-evidence toont RTX 4080 SUPER/`cuda:0`; zero CPU fallback; protected-accesslog blijft leeg. - -## P2-09 — Calibration-only verbeterloop - -De loop mag worden herhaald, maar alleen binnen de volgende state machine: - -```text -reviewed immutable corpus - -> CUDA train - -> validation checkpoint selection - -> calibration + error taxonomy - -> all pre-test gates pass? - no -> provision independent train-only AOIs / reviewed labels - -> freeze new corpus version -> CUDA train - yes -> freeze candidate SHA + preprocessing + threshold + gates - -> P2-10 protected test -``` - -### Regels - -- Calibrationresultaten mogen aangeven welke regio/context faalt, maar nooit protected sample-ID's of testresultaten. -- Nieuwe voorbeelden komen uit onafhankelijk geprovisioneerde train-only AOI's en doorlopen dezelfde provenance, temporal en human-reviewgates. -- Een corpuswijziging maakt een nieuwe immutable corpusversie en een nieuwe run family; bestaande evidence blijft behouden. -- De loop stopt niet op aggregate F1 alleen. Iedere regionale/context-, background-, lineage-, runtime- en reviewgate moet groen zijn. -- Indien geen betrouwbare labels of onafhankelijke AOI's beschikbaar zijn, is de correcte status `blocked/not_validated`, niet een afgezwakte gate. - -### Exit gate - -- Eén candidate SHA passeert alle vooraf bevroren validation/calibration-, regional/context-, pure-background-calibration-, runtime-, lineage- en reviewgates. -- Candidate, threshold, NMS, tileconfig, corpus en evaluator zijn daarna read-only bevroren. - -## P2-10 — Eenmalige protected-testbeslissing - -### Voorwaarden vóór openen - -- P2-00 tot P2-09 zijn groen. -- Candidate/model SHA, container digest, corpus SHA, preprocessing, threshold, evaluator en numeric gates zijn gesigneerd/bevroren. -- Test/background-test manifesthashes bestaan, maar hun inhoud was niet toegankelijk voor train/calibration runners. -- Promotion policy specificeert vooraf wat pass, fail en infrastructure-invalid betekent. - -### Uitvoering - -- Start één isolated release-evaluation job met read-only protected credentials op `cuda:0`. -- Bereken alle bevroren regionale/context/object-size en background-test metrics; produceer contact sheets en machine-readable gate decision. -- Een infrastructure-invalid run mag uitsluitend opnieuw worden uitgevoerd wanneer bewijs aantoont dat geen bruikbaar modelresultaat is vrijgegeven; de incidentbeslissing wordt gelogd. - -### Beslissing - -- **Pass:** ga naar P2-11; resultaten mogen niet worden gebruikt om alsnog threshold/config te wijzigen. -- **Fail:** release blijft blocked. Train deze candidate family niet verder op basis van het testresultaat. Archiveer de beslissing; een volgende poging vereist een nieuw vooraf geregistreerd ontwikkelprogramma en een nieuwe onaangeroerde protected portfolio. - -### Exit gate - -- Exact één geldig access event en één immutable report voor candidate SHA. -- Geen write naar corpus/training config na testopening. -- Alle gates zijn groen; anders is P2-11 niet bereikbaar. - -## P2-11 — Guarded promotion, shadow en redeploy - -### Uitvoering - -1. Genereer model card en promotion report met task, class, scope, imagery/reference versions, known limitations, metrics per stratum, calibration, test, runtime, lineage en rollbackmodel. -2. Kopieer de kandidaat naar een immutable model-ID/version/SHA-pad; overschrijf het actieve `.pt`-bestand niet. -3. Bouw/push één immutable GPU image vanaf een gepushte commit/tag; leg image digest en SBOM vast. -4. Migreer DB/schema via backup, dry-run en restoretest; voer PostGIS extension-upgrade alleen volgens P2-evidence uit. -5. Draai production preflight: exact modelhash, CUDA required, bounded tile inference, CRS/georeferencing, persistence en restart. -6. Start shadowvergelijking binnen exact de gevalideerde scope; shadowoutput is niet publiek en kan de protected-testbeslissing niet aanpassen. -7. Laat UI/API alleen de bewezen scope/classes/status zien; segmentatie en solar blijven `not_configured`. -8. Activeer pas na shadow- en rollbackgate; monitor en behoud één-command rollback naar vorige image/model/config. - -### Exit gate - -- Commit/tag, image digest, model SHA, config SHA, migration head en promotion report verwijzen wederzijds naar elkaar. -- End-to-end selectie → inference → persisted result → uitschuifbare inzichten → export is getest met correcte lineage en zichtbare error states. -- Restart en rollback slagen zonder data- of evidenceverlies. -- De gedeclareerde scope is exact de geslaagde testscope, nooit “heel België” door implicatie. - -## P2-12 — Monitoring en gecontroleerde volgende cyclus - -### Uitvoering - -- Monitor per region/context/provider/imagery edition/object size: input drift, confidence, density, QA mismatches, latency/VRAM en persistence failures. -- Maak een menselijke reviewqueue met FP/FN/uncertain voorbeelden; production outputs worden nooit automatisch training labels. -- Een volgende training gebruikt alleen een reviewed, opnieuw gefreezede labelrelease en herstart bij P2-05/P2-06. -- Bewaar oude datasets, modellen, run manifests, promotion reports en rollbackimages volgens retentiebeleid. -- Widening van scope of class is een nieuwe releaseclaim en doorloopt opnieuw P2-06 tot P2-11 met een onaangeroerde testportfolio. - -### Exit gate - -- Alerts, reviewqueue, ownership en rollbackrunbook zijn operationeel getest. -- Er bestaat geen automatische self-training of silent promotion path. -- Periodieke audits kunnen ieder publiek resultaat terugvoeren naar bron, tile, model, config en releasebeslissing. - -## Verplichte release-evidence - -P2-11 blijft geblokkeerd zolang één van deze artifacts ontbreekt: - -- canonical CI commandmatrix en logs; -- CRS/coverage/authority/scope regressierapport; -- DB migration, backup/restore en legacy-quarantainerapport; -- trusted source registry en lineage completeness audit; -- immutable corpus, split/duplicate/temporal/label audits en human-reviewmanifest; -- pinned AI image digest/SBOM en RTX 4080 CUDA run manifests; -- reproducible incumbent/candidate calibrationrapporten; -- vooraf bevroren gateconfig; -- één protected-test/background-test accesslog en report; -- model card, signed promotion report, shadow report en rollbacktest; -- bijgewerkte API/contracts, limitations, execution log en TODO. - -## Stop-the-line criteria - -Stop de betrokken pipeline en behoud `release blocked` wanneer: - -- protected data vóór de freeze wordt gelezen of in sampler/training evidence voorkomt; -- een geometry zonder betrouwbare CRS of een meteroperatie in graden wordt verwerkt; -- user metadata officiële authority kan verlenen; -- model/dataset/tile/config hashes ontbreken; -- een verplichte metric null/ontbrekend is; -- menselijke labelreview Critical/High findings openlaat; -- training niet aantoonbaar op de vereiste NVIDIA GPU draait; -- een regio/context/background-gate faalt; -- de protected test faalt; -- deploy commit, image, model, DB migration en promotion report niet exact aan elkaar gebonden zijn. - -Alleen bewijs kan een gate openen. Een nieuwe training, hogere epoch count of gunstig aggregate cijfer kan een ontbrekende lineage-, split-, regionale, menselijke of deploymentgate niet compenseren. diff --git a/docs/accuracy-program/07-source-authority-matrix.md b/docs/accuracy-program/07-source-authority-matrix.md deleted file mode 100644 index e6c5bca0..00000000 --- a/docs/accuracy-program/07-source-authority-matrix.md +++ /dev/null @@ -1,330 +0,0 @@ -# GeoIntel Accuracy Improvement Program — 07 Bronautoriteitsmatrix - -- Status: Fase-2 implementatie in uitvoering; normatief beleid en gerealiseerde bronfundering -- Scope: België en de Belgische Noordzee -- Samenhang: 00-execution-contract, 02-data-lineage, 04-risk-register, 05-metric-framework en 08-data-contracts -- Beslissing: een bronnaam in een upload, feature, dataset of UI-label verleent nooit zelf autoriteit. - -## 0. Gerealiseerde Phase-2-fundering en grens - -De repository bevat nu een server-owned registry in -`backend/app/services/source_registry_service.py`, de persistente modellen -`SourceRegistry` en `SourceSnapshot`, migratie `202608010001`, en expliciete -Dataset/DatasetVersion-koppelingen. Elke nieuwe governed import schrijft een -checksumgebonden snapshot, exacte contractversie en validatierapport. Een -handmatige upload wordt altijd aan `manual` gebonden; een meegegeven -`source_name=grb` blijft slechts een descriptieve claim. - -Dit maakt geen oude Tower-datasets, bestaande modelgewichten of een -historische bronnaam alsnog betrouwbaar. De migratie behoudt die rijen maar -markeert ontbrekende provenance als `incomplete/not_validated`. Zij blijven -niet inzetbaar voor training, productie-inferentie, primaire QA of -authoritative coverage tot een nieuwe governed ingest een eigen snapshot en -contractrapport heeft vastgelegd. - -## 1. Doel en claimgrens - -Dit document bepaalt welke bron beslissend, aanvullend of uitsluitend -contextueel mag zijn voor elk GeoIntel-resultaat. Het maakt twee vragen -expliciet verschillend: - -1. welke organisatie of productfamilie is gezaghebbend voor een concrete - bewering; -2. is de concrete snapshot ook werkelijk met server-attested provenance, - versie, licentie, CRS, dekking en integriteitscontrole beschikbaar? - -Een officiële publicatie zonder gecontroleerde snapshot is geen geactiveerde -autoriteit in een resultaat. Omgekeerd maakt een bestand met source_name=grb -of een UI-label “officieel” een handmatige upload nooit gezaghebbend. Dit -herstelt de door Phase 1 gereproduceerde ACC-R04-breuk. - -Autoriteit is taak-, zone-, product- en tijdsgebonden. Een bron kan dus -authoritative zijn voor één bewering en slechts corroborative of contextual -voor een andere. De classificatie is geen kwaliteitsoordeel over de bron en -maakt geen algemene België-claim. - -## 2. Verplichte classificaties - -| Klasse | Betekenis | Mag beslissend zijn? | Minimale server-attested voorwaarden | -|---|---|---|---| -| authoritative | Formeel bevoegde bron voor een afgebakende taak, zone en productversie. | Alleen voor de exact geregistreerde taak, dekking en tijd. | Goedgekeurde registry-entry, publisher/collection allowlist, snapshot- of editie-identiteit, checksum, licentie/attributie, CRS/eenheden, ruimtelijke en temporele dekking, succesvolle contractvalidatie. | -| corroborative | Onafhankelijke aanvullende bron die een resultaat kan controleren, duiden of van een status voorzien. | Nee; zij kan een mismatch of onzekerheid creëren, maar overschrijft de primaire referentie niet automatisch. | Zelfde minimale provenance als voor authoritative, plus een expliciete comparison/reconciliation policy. | -| contextual | Bron voor kaartcontext, interpretatie, kandidaatselectie of reviewhulp. | Nee. Niet gebruiken als label-, truth- of promotionbeslissing. | Duidelijke attributie/licentie en expliciete limitation; ontbreken daarvan maakt de context onbeschikbaar. | -| derived | Door GeoIntel of een geregistreerde transformatie afgeleid artefact. | Alleen als afgeleide metriek met volledige upstream-lineage; nooit als nieuwe externe autoriteit. | Immutable inputhashes, transformatie/code/config-hash, outputchecksum, validatie en parent-lineage. | -| experimental | Fixture, handmatige upload, proefbron, niet-gevalideerde adapter of niet-beoordeeld model-/labelartefact. | Nee voor productie, training, QA-waarheid, dekking of promotie. | Herkenbaar als experimental/manual/untrusted; expliciete operatorbeperking en quarantainestatus wanneer ongeschikt. | - -De registry bewaart de klasse als server-owned beleid; de seeding- of -definition-revisie staat in de registrymetadata. Een datasetrecord kopieert -die klasse niet vrij tekstueel: het bindt een concrete registry-entry én een -immutable source snapshot met checksum. De ingestlaag schrijft de effectieve -trust/authority-status zelf. Er is in deze eerste P2-migratie bewust nog geen -los mutable UI-veld dat als historische "registry-versie" kan worden -misbruikt; een snapshot/checksum blijft de concrete evidence-identiteit. - -## 3. Bronautoriteit voor gebouwresultaten - -### 3.1 Beslissingsregel - -Een gebouwgerelateerde validatie kiest eerst de zone, vervolgens de concrete -taak en ten slotte de geregistreerde bronversie. Een referentielaag is pas -bruikbaar als geometry-, tijd-, resolutie-, feature-identity- en -provenancecontracten groen zijn. - -| Zone en taak | Primaire referentie | Rol van andere bronnen | Geen-claim / fallbackregel | -|---|---|---|---| -| Vlaanderen: footprint- of gebouwdetectievalidatie | GRB GBG is authoritative en primaire gezagsbron, voor zover de gekozen GRB-snapshot, dekking, beeld/referentietijd en taak dat rechtvaardigen. | Gebouwenregister kan identiteit/lifecycle en GRB-reconciliation corroboreren; orthofoto is waarnemingsinput; DHMV en OSM zijn niet beslissend. | Geen governed, passend GRB-datasetversie betekent not_evaluable of partial; nooit stil OSM, een upload of een oude/onbekende snapshot als truth inzetten. | -| Wallonië: footprint- of gebouwdetectievalidatie | Alleen een expliciet governed PICC-building-product kan authoritative zijn voor zijn eigen product/versie/zone. | GRB heeft geen Vlaamse autoriteit buiten Vlaanderen. Orthofoto, DHMV en OSM zijn slechts volgens hun eigen rol bruikbaar. | Geen semantische pariteit met GRB aannemen; cross-region aggregate blijft not_evaluable totdat een bevroren harmonisatiecontract bestaat. | -| Brussel: footprint- of gebouwdetectievalidatie | Alleen een expliciet governed UrbIS-building-product kan authoritative zijn voor zijn eigen product/versie/zone. | Gebouwenregister en GRB zijn niet automatisch Brusselse truth. OSM/imagery blijven niet-beslissend. | Geen governed UrbIS-versie betekent not_evaluable/partial; geen regionale substitutie. | -| Zoneoverschrijdend België-resultaat | Een per-zone, per-versie gevalideerde portfolio van de bovenstaande referenties. | Alleen vergelijkbare ontologie, tijd, resolutie, matchingpolicy en metriek mogen later geaggregeerd worden. | Een Belgisch cijfer mag geen ontbrekende of mislukte zone verbergen; zonder alle verplichte strata is de status not_evaluable. | -| Gebouwstatus, units en adressen in Vlaanderen | Gebouwen- en Adressenregister is authoritative voor zijn geregistreerde object-/statussemantiek binnen de gedateerde snapshot. | GRB is corroborative voor geometrische reconciliatie; registerstatus is geen GRB-footprint en omgekeerd. | Units/adressen zijn geen woningen, huishoudens, bewoners, volume of modeltruth. | - -GRB is dus de primaire geometrische validatiereferentie voor een passende -Vlaamse building-taak, niet een automatische waarheid voor elk gebouw, iedere -tijd of andere regio. De registerstatus of een zichtbaar dak in imagery kan -een reviewfinding opleveren, maar vervangt een geldige referentie niet zonder -vooraf bevroren adjudicatiebeleid. - -### 3.2 Verboden automatische substituties - -- OSM mag nooit automatisch als building ground truth, labelbron of - promotie-referentie worden gebruikt. -- Sentinel-2 mag nooit als building ground truth, footprintlabel of - fine-grained objectvalidatie worden gebruikt. -- DHMV DTM/DSM mag nooit een gebouwfootprint, gebouwhoogte, waterdiepte of - gebouwtruth fabriceren. -- Een Gebouwenregister-snapshot mag GRB niet automatisch vervangen als - primaire footprintreferentie; zijn lifecycle-/registersemantiek blijft - afzonderlijk. -- Een derived GeoIntel-laag, YOLO-detectie, segmentatie of kaartselectie mag - nooit zijn eigen referentie zijn. -- Wanneer de primaire bron niet beschikbaar, verlopen, temporeel ongeschikt - of contractueel ongeldig is, retourneert GeoIntel expliciet - not_configured, partial, unavailable of not_evaluable. Geen fallback mag - als geslaagde primaire validatie worden weergegeven. - -Een concrete source snapshot is alleen consumeerbaar wanneer zijn -`freshness_status` `current` of expliciet `not_applicable` is. `unknown`, -`review_required`, `due` en `stale` worden aan elke productiegrens -geblokkeerd, ook wanneer de registry-familie op zichzelf authoritative is. -Een historische bron die bewust bruikbaar blijft, moet dus expliciet door -zijn contract als `not_applicable` zijn gemotiveerd; een ontbrekende of oude -status is geen stilzwijgende uitzondering. - -## 4. Matrix van governable source families - -De volgende matrix onderscheidt de beleidsrol van een bron van de actuele -implementatiestatus. “Implemented” betekent uitsluitend dat een begrensde -code-/operatorroute is aangetroffen; het betekent niet dat iedere opgeslagen -dataset al aan het Fase-2 registry-contract voldoet. - -| Registry source id | Klasse per taak | Autoriteit en toepassingsgebied | Toegelaten gebruik | Verboden/limieten | Stand op 2026-08-01 | -|---|---|---|---|---|---| -| grb | authoritative voor Vlaamse GRB-producten; primary voor passende building-footprintvalidatie | Digitaal Vlaanderen; Vlaanderen; GBG, Wegsegment, WTZ/WLAS/WGR en ADP volgens product allowlist | Referentievector, ruimtelijke QA, footprint-/lengte-/oppervlaktemetingen binnen productsemantiek | Geen juridische perceelgrens, vloeroppervlakte, volume, waterdiepte of tijdloze fysieke verandering claimen | Governed OGC acquisition en registry/snapshot/contractbinding zijn geïmplementeerd; een concrete snapshot blijft alleen primary-eligible wanneer taak-, zone-, tijd- en contractchecks slagen. | -| digitaal_vlaanderen_buildings_addresses_register | authoritative voor geregistreerde gebouw-/unit-/adresstatus; corroborative voor footprintreconciliatie | Digitaal Vlaanderen; gedateerde gemeentelijke snapshot; Gebouw, Gebouweenheid en Adres | Registerstatus, stable objectidentity, aggregate unit/adrescontext, GRB-matchreview | Geen automatische vervanger voor GRB footprinttruth; geen persoonsgegevens/adreslabels als featureoutput; geen demografieclaim | Server-owned registry-entry en task policy bestaan; zonder concrete governed snapshot blijft dit een niet-geactiveerde autoriteit. | -| spw_picc | authoritative voor de goedgekeurde PICC building-taak in Wallonië | SPW; Wallonië; exact product/edition en zone | Regionale building reference/QA binnen vastgelegde semantics | Geen GRB-semantic parity of Vlaamse/nationale extrapolatie | Governed official-vector ingest schrijft registry/snapshot/contractbinding; per-versie semantische acceptance en cross-region harmonisatie blijven afzonderlijke gates. | -| urbis | authoritative voor de goedgekeurde UrbIS building-taak in Brussel | Paradigm/competente Brusselse instantie; Brussels Hoofdstedelijk Gewest | Regionale building reference/QA binnen vastgelegde semantics | Geen automatische parity met GRB/PICC of nationale claim | Governed official-vector ingest schrijft registry/snapshot/contractbinding; per-versie semantische acceptance en cross-region harmonisatie blijven afzonderlijke gates. | -| digitaal_vlaanderen_orthophoto | contextual als imagery; observatie-input voor matching en review | Digitaal Vlaanderen; Vlaanderen; product-/vlucht-/editiegebonden | Inference input, visuele labelreview, temporal alignmentcontrole | Geen truth zonder onafhankelijke reference; latest is geen per-pixel observed_at | Governed acquisition en centrale contractvalidatie zijn geïmplementeerd; source version/time blijft per product/snapshot aantoonbaar. | -| spw_orthophoto | contextual als imagery | SPW; Wallonië; product-/editiegebonden | Inference input en review | Geen building truth of semantische parity claim | Implemented governed acquisition volgens API-contract; registry/contractgate vereist | -| urbis_orthophoto | contextual als imagery | Paradigm; Brussel; product-/editiegebonden | Inference input en review | Geen building truth of semantische parity claim | Implemented governed acquisition volgens API-contract; registry/contractgate vereist | -| sentinel_2 | contextual, pas na eigen registered contract | Copernicus/Sentinel-2; sensor-, tile-, processing-level- en acquisitiongebonden | Coarse land-cover/vegetation/temporal context wanneer contract en resolution passend zijn | Nooit building ground truth, footprintlabel, fine building QA of stille fallback voor orthofoto | Planned/not configured: health en API markeren Sentinel als planned/disabled; geen governed ingestadapter aangetroffen | -| digitaal_vlaanderen_dhmv | authoritative voor exact declared elevation product; corroborative voor terrain/elevation bij building reviews | Digitaal Vlaanderen; Vlaanderen; DHMV II DTM/DSM, EPSG:31370, TAW, 2013-2015 | Terrain/reliëf/slope, elevationcontext en review van plausibiliteit | Geen building footprinttruth, directe gebouwhoogte, waterdiepte of volume | Bounded WCS acquisition plus registry/snapshot/raster-contractgate zijn geïmplementeerd; verticale productsemantiek blijft source-specifiek gecontroleerd. | -| osm | contextual; eventueel corroborative alleen onder vooraf vastgelegd onderzoek/handmatige review | OpenStreetMap contributors; vrijwillig bijgewerkte werelddekking | Kaartcontext, kandidaat-/confuserinventaris, menselijke reviewhulp | Nooit automatische ground truth, primary reference, labelbron of coverage-authority | Provider bestaat maar live Overpass/download is not_configured | -| ngi_adminvector, statbel, rbins en andere competentiebronnen | authoritative uitsluitend voor hun eigen bestuurlijke, statistische of maritieme taak | Bevoegde federale/regionale/maritieme instantie en exacte source family | Scope, context en bron-specifieke metrics | Geen building labels tenzij expliciet geregistreerde productsemantiek dat toelaat | De geregistreerde source families hebben server-owned class/policy records; niet-gegovernde historische rows blijven expliciet onvolledig. | -| manual | experimental/untrusted | Door gebruiker aangeleverd; autoriteit onbekend tenzij later formeel ingestbewijs is gekoppeld | Privé-projectcontext of expliciete operatorreview | Nooit officiële authoriteit, coverage, trainingtruth of promotionbasis op naam alleen | Implemented uploadflow; Phase 1 bewees spoofability van source_name en maakt migratie naar manual/untrusted verplicht | -| fixture | experimental | Lokale test- en demofiles | Unit/integratietests en expliciete demo | Nooit productie, nationale metric, source authority of trainingclaim | Implemented and explicitly marked fixture provider | -| derived, map_selection en training_label | derived | GeoIntel-transformatie van bekende parents | Datasets, tiles, metrics, exports met volledige parent-lineage | Geen externe source authority, geen verbergen van incomplete parent | Vector/raster-mapoperaties registreren `derived`/`map_selection`, outputchecksum, contractrapport en parent-edge; ontbrekende of ongeschikte parent leidt tot quarantine. | -| labels en modelartefacten | derived of experimental tot volledig governed | Corpus/label-/trainingrelease | Alleen volgens 08-data-contracts en split/firewallbeleid | Geen training/promotion bij onbekende bron, review, split of hash | V56/V58/V62/V66 evidence is incomplete for release; nationale claim blocked | - -### 4.1 Licentie- en gebruiksgrenzen per bronprofiel - -Een registry-entry bewaart momenteel de family-level licentie of -gebruiksvoorwaarde. Een generieke tekst als “official” is niet voldoende, en -wordt niet automatisch een snapshot-specifieke licentie-eigenschap. De actuele -startinventaris ondersteunt alleen de volgende begrensde uitspraken: - -| Bronprofiel | Vastgelegde of vereiste licentie-/attributiegrens | -|---|---| -| GRB | De bestaande governed adapter bewaart de Digitaal Vlaanderen-attributie en verwijst naar hergebruik volgens de open-datavoorwaarden en bronvermelding. Elke snapshot bewaart de gebruikte catalogue/product identity; een onbekende licentie is niet primary-QA-eligible. | -| Gebouwen- en Adressenregister | De operator bewaart bron-URL's, catalogue URL en Digitaal Vlaanderen-attributie, maar de nieuwe registry moet de concrete hergebruiksvoorwaarde per snapshot vastleggen. Privacy-minimalisatie is verplicht: adreslabels, straat-, huis- en busnummers komen niet in queryable vectorfeatures. | -| DHMV | De bestaande adapter vermeldt het gebruiksrecht voor geografische webdiensten van Digitaal Vlaanderen en bronvermelding. Zij mag geen verticale datum, hoogtesemantiek of resolutie herinterpreteren. | -| PICC en UrbIS | De API-contracten documenteren bekende SPW- respectievelijk Paradigm/FPS Finance-licentienoten. Snapshot-specifieke licentietekst/versie, attribution en redistribution-restrictie zijn nog geen getypeerde P2-velden; een adapter mag ze voorlopig alleen aanvullend in `snapshot_metadata_json` bewaren. Een productcontract dat deze evidence vereist, moet een ontbrekend veld expliciet laten falen of quarantainen. | -| OSM | OSM is onder ODbL met verplichte attributie volgens de bestaande providercapability. Afgeleide of gecombineerde OSM-output volgt de toepasselijke ODbL-verplichtingen en blijft nooit automatic truth. | -| Sentinel-2 | Vóór een toekomstige adapter activeert, legt de registry de exacte Copernicus/Sentinel productlicentie, verwerking, attribution en redistributionvoorwaarden vast. Zonder die snapshot is Sentinel not_configured. | -| Manual, fixture en derived | De uploader/producer kan een licentie beschrijven maar niet authoriteit verlenen. Ontbrekende of onverenigbare gebruiksrechten blokkeren training, publicatie en herdistributie. | - -### 4.2 Verplichte migratie van alle waargenomen source_name-waarden - -Phase 1 zag 28 verschillende source_name-waarden in de Tower-database. De -volgende tabel is de migratieregistratie: een klasse is pas activeerbaar na -controle van publisher, product, licentie en snapshot. De tabel verheft geen -historische row met die naam automatisch tot trusted data. - -| Bestaande source_name | Initiële registry-klasse | Afbakening | -|---|---|---| -| grb | authoritative | Alleen GRB-product/zone/versie volgens de governed allowlist; primary building footprint reference enkel in Vlaanderen. | -| digitaal_vlaanderen_buildings_addresses_register | authoritative + corroborative | Authoritative registersemantiek; corroborative voor footprintreconciliatie. | -| spw_picc | authoritative | Alleen de allowlisted PICC productfamilie in Wallonië; geen GRB-pariteit. | -| urbis | authoritative | Alleen de allowlisted UrbIS productfamilie in Brussel; geen GRB/PICC-pariteit. | -| digitaal_vlaanderen_dhmv | authoritative + corroborative | Authoritative elevation product; corroborative in building-reviewcontext. | -| digitaal_vlaanderen_orthophoto | contextual | Official imageryinput, nooit automatic reference truth. | -| spw_orthophoto | contextual | Walloon imageryinput, nooit automatic reference truth. | -| urbis_orthophoto | contextual | Brussels imageryinput, nooit automatic reference truth. | -| vmm_flood_hazard | authoritative | Alleen voor geregistreerde scenario-/overstromingssemantiek; geen observed_at fabriceren. | -| vmm_vha_bathymetry_profiles | authoritative | Alleen voor exact profiel, datum en verticale referentie; geen raster/depth extrapolatie. | -| department_omgeving_thematic_raster | authoritative | Alleen voor de specifieke Vlaamse klasse/productdefinitie. | -| department_omgeving_land_use | authoritative | Alleen voor de geregistreerde landgebruikeditie/klasse. | -| agentschap_landbouw_zeevisserij_agricultural_parcels | authoritative | Alleen voor declared agricultural use per jaar; geen eigendom/gebouwtruth. | -| waterinfo | authoritative | Alleen voor exact meetreeks-/station-/tijdcontract. | -| statbel | authoritative | Alleen voor statistische publicaties en hun aggregatieniveau. | -| ngi_adminvector | authoritative | Alleen voor governed administratieve scope. | -| rbins_marine_reporting_units | authoritative | Alleen voor mariene rapportage-eenheden en exact legal scope. | -| rbins_msp_2026 | authoritative | Alleen voor het vastgelegde mariene plan/edition. | -| vrbg | authoritative | Alleen voor het wegregister en zijn eigen semantiek. | -| dov_soil_map | authoritative | Alleen voor bodemkaart/surveyperiode; geen actuele ground truth insinueren. | -| inbo_bwk_natura2000 | authoritative | Alleen voor de vastgelegde natuur-/habitatproductsemantiek. | -| spw_walous_land_cover | authoritative | Alleen voor de vastgelegde Waalse landbedekkingsclassificatie. | -| spw_bathymetry | authoritative | Alleen met CRS, verticale referentie, surveyperiode en archive identity. | -| spw_terrain | corroborative | Alleen voor de vastgelegde terreincontext/reconciliatie; geen zelfstandige authoritative claim zonder een toekomstige productpolicy. | -| historical_landuse | corroborative | Alleen als historische context met bron-, editie-, partition- en identity evidence; objecthistory blijft disabled wanneer identity_stable=false. | -| manual | experimental | Manual/untrusted totdat een aparte governed re-ingest een nieuwe accepted snapshot oplevert. | -| fixture | experimental | Alleen test/demo. | -| map_selection | derived | Alleen een GeoIntel-selectie; nooit externe bron, reference of trainingtruth. | - -## 5. Centrale source registry: gerealiseerd datamodel en normatieve uitbreiding - -### 5.1 Registry-entry versus snapshot - -De centrale registry heeft twee server-owned lagen: - -1. SourceDefinition: het server-owned beleid voor een source family/product; -2. SourceSnapshot: de concrete, checksummed acquisitie of - editie die een DatasetVersion mag voeden. - -Een SourceDefinition wordt niet door een client in een uploadformulier -aangemaakt. Een SourceSnapshot kan alleen door een governed adapter of een -expliciet reviewed operator-import aan een Definition worden gebonden. Een -handmatige upload verwijst uitsluitend naar de server-owned manual Definition -met trust_class=experimental/untrusted. - -### 5.2 Verplichte SourceDefinition-velden - -| Veldgroep | Verplichte inhoud | -|---|---| -| identity | getypeerd: immutable source_registry_id, source_key, display name, publisher/authority en registry definition revision in `registry_metadata_json`; toekomstig normatief: afzonderlijke registry-version en deprecated lifecycle | -| authority | source class, trust class, allowed task claims, reference priority, allowed zones/legal scope IDs, forbidden claims en fallbackbeleid | -| access/licence | governed endpoint/catalogue allowlist, attribution template, licence/use/redistribution restrictions, credentials/secret reference buiten de registry-payload | -| spatial | native CRS, canonical storage CRS, approved metric CRS strategy, units inclusief verticale referentie indien relevant, native resolution/scale, expected geometry families/bands | -| temporal | getypeerd: source-version policy, temporal/geografische coverage JSON en freshness policy; toekomstig normatief: afzonderlijke published/observed/valid requirementvelden per product | -| schema | contract id/version voor raster, vector, label of model, expected collections, feature-id strategy, required/optional attributes, topology/attribute constraints | -| operations | approved acquisition adapter, request limits, cache/idempotency policy, allowed transformations, provenance requirements en quarantine routing | -| limitations | source-native semantic beperkingen, comparison exclusions, privacy restrictions, known gaps en operator note | - -### 5.3 SourceSnapshot-velden: gerealiseerd versus normatief - -De getypeerde P2-tabel bevat `source_registry_id`, `snapshot_key`, -`source_version`, `snapshot_at`, `fetched_at`, `source_url`, -`checksum_sha256`, `crs`, `units`, resolution-, temporal- en coverage-JSON, -observed-schema JSON, `freshness_status`, `ingest_status`, known limitations -en `snapshot_metadata_json`. De registry-entry bewaart de bronlicentie, -licentie-URL en gebruiksbeperkingen. Deze velden worden samen met de -Dataset/DatasetVersion-contractversie en validation report gebruikt voor -consumeerbare provenance. - -`published_at`, afzonderlijke request-/collection identity, -snapshot-specifieke licentie/attributie, validation-report-hash en -immutable-manifest-hash zijn in de huidige P2-opslag geen afzonderlijke -getypeerde kolommen. Wanneer een adapter ze kent, bewaart hij ze alleen als -aanvullende `snapshot_metadata_json`; afwezigheid mag geen primary, training- -of productieclaim opleveren wanneer het relevante contract ze vereist. Zij -blijven een expliciete normatieve uitbreiding, geen reeds gerealiseerde -kolommen. - -Fetchtime is nooit een vervanging voor observed_at. Een bron waarvoor een -observatietijd niet bestaat, gebruikt in het datacontract een expliciete -`not_applicable` of `unknown_with_reason`-reden; die tweede term is een -contractbeslissing en geen waarde van `SourceSnapshot.freshness_status`. - -## 6. Freshness, ingest en authority states - -### 6.1 Freshness - -De P2 registry en snapshot gebruiken exact `unknown`, `current`, `due`, -`stale`, `not_applicable` en `review_required`. Fase 2 bindt die betekenis aan -registry-policy en snapshot in plaats van aan vrije metadata. Toegelaten -uitkomsten zijn: - -| Status | Betekenis voor gebruik | -|---|---| -| current | Snapshot valt binnen de geregistreerde review-/geldigheidsregel. | -| due | Snapshot moet worden vernieuwd/gecontroleerd en mag niet door een productiegrens. | -| stale | Snapshot is verlopen en mag niet door een productiegrens. | -| review_required | Een verplichte versie-, tijd-, checksum-, licentie- of policywaarde ontbreekt; niet gebruiken voor authoritative claim. | -| unknown | Freshness is niet aantoonbaar; niet consumeerbaar. | -| not_applicable | Alleen wanneer het concept inhoudelijk niet op de bron past, bijvoorbeeld observed_at voor een niet-temporele vaste bron. | - -### 6.2 Ingest en trust - -| Ingeststatus | Betekenis | Toegang tot training / productie-inference / QA | -|---|---|---| -| registered | Server-owned brondefinitie bestaat, nog geen consumeerbare snapshot. | Geen | -| configured / not_configured / available | Adapter- of beschikbaarheidsstatus; geen ingestbewijs. | Geen | -| ingested | Snapshot is geschreven; Dataset/DatasetVersion moet daarnaast een groen contractrapport hebben. | Alleen volgens source class en task policy | -| failed | Ingest of validatie is mislukt. | Geen | -| quarantined | Fout, twijfel, ontbrekende provenance of policyconflict is vastgelegd. | Geen | -| legacy_unverified | Gemigreerd historisch record zonder complete P2-provenance. | Geen nieuwe training/promotion; UI/API toont beperking | - -Een status ready op de huidige Dataset-tabel is hoogstens een bestaande -processingstatus. Zij is niet gelijk aan accepted, authoritative of -model-validatable totdat de Fase-2 contractstatus dat bewijst. - -## 7. Huidige implementatie en aantoonbare gaten - -| Onderwerp | Aangetroffen | Niet aangetroffen / Fase-2 verplichting | -|---|---|---| -| Provider capabilities | Server-owned registry definieert 40 source families, classificatie, task policy en immutable snapshot-binding. | Per product nog geen volledige typed published/request/licence-manifestvelden; zie §5.3. | -| Dataset provenance | Dataset en DatasetVersion hebben registry/snapshot FK, versioned contract/reportvelden en lineage/quarantine records. | Historische records blijven incompleet; een daadwerkelijke nieuwe governed ingest is nodig voor gebruik. | -| GRB | Bounded allowlisted OGC acquisition, registry/snapshotbinding, contractgate en primaire Vlaamse building-policy zijn aanwezig. | Concrete snapshot blijft zone-, tijd- en productafhankelijk; geen nationale claim. | -| DHMV | Bounded WCS-flow, registry/snapshot/rastercontract en elevation-policy zijn aanwezig. | Geen gebouwfootprinttruth of impliciete verticale semantiek. | -| Gebouwenregister | Registry task policy onderscheidt registersemantiek van GRB-footprintreconciliatie. | Concrete governed snapshot en productcontract blijven vereist voor activatie. | -| Generic upload | Uploads worden server-side als manual/experimental behandeld, niet op caller source_name. | Alleen expliciete reviewed ingest kan later een andere governed route gebruiken. | -| OSM/Sentinel | OSM blijft contextual/not_configured; Sentinel blijft planned/not_configured. | Geen live acquisition of automatic authority totdat adapter en contract bestaan. | -| Quarantine | `SourceRegistryService.quarantine_dataset` en de database-trigger propageren quarantine naar gekoppelde Dataset/DatasetVersion/snapshot en downstream lineage-descendants; consumption gates sluiten training/inference/QA/export/coverage. | Geen in-place release: een governed re-ingest/nieuwe versie is nodig. | - -## 8. Resultaatweergave en fallbackcontract - -Dit is het verplichte doelcontract voor API en UI. De P2-evidence bewijst nog -niet met een end-to-end browser/API-journey dat elk bestaand zichtbaar resultaat -de volledige set velden al toont. - -Ieder zichtbaar GeoIntel-resultaat met bronafhankelijkheid moet minimaal tonen: -source display name, source_registry_id, snapshot/version, source class, -authority scope, observed/published/fetched time, freshness, checksum, -licence/attribution, CRS/units, resolution, coverage and limitation. - -Een resultaat dat op een contextual, derived of experimental bron steunt, draagt -die status in de API en UI. Een resultaatsamenvatting mag niet alleen de -merknaam “GRB” of “officieel” tonen wanneer de concrete DatasetVersion niet -aan de registry is gebonden. - -Voor building QA omvat een mismatch ten minste: candidate/source tile, -primary-reference snapshot, eventuele Gebouwenregister-reconciliatie, -orthophoto observation time, DHMV-context indien gebruikt, en OSM uitsluitend -als contextual review evidence. Die aanvullende bronnen veranderen de -primary-reference match niet zonder een expliciete menselijke adjudicatie. - -## 9. Exit-evidence voor deze matrix - -Fase 2 kan bronautoriteit alleen als groen markeren wanneer bewijs bestaat van: - -1. een migratie- en registry-inventory met alle bestaande source_name-waarden - geclassificeerd of expliciet in quarantine; -2. server-side tests waarin een forged GRB upload manual/untrusted blijft; -3. bounded GRB, DHMV en register-snapshots met registry/snapshot/contract - identity, immutable checksums en validatierapport; -4. tests voor zone-/theme-/version-isolatie en geen cross-theme coverage union; -5. bewijs dat OSM en Sentinel niet als automatic truth/fallback kunnen lopen; -6. resultaten waarin unavailable, partial, not_configured, quarantined en - not_evaluable zichtbaar en niet als success gepresenteerd worden. - -Tot deze evidence bestaat, blijven de Phase-1 bronautoriteitsclaims en de -nationale building-promotion blocked. diff --git a/docs/accuracy-program/08-data-contracts.md b/docs/accuracy-program/08-data-contracts.md deleted file mode 100644 index 1a8bff19..00000000 --- a/docs/accuracy-program/08-data-contracts.md +++ /dev/null @@ -1,578 +0,0 @@ -# GeoIntel Accuracy Improvement Program — 08 Versieerbare datacontracten - -- Status: Fase-2 contractnorm met een geïmplementeerde fail-closed - validatiebibliotheek; bestaande DatasetVersions, artefacten en - modelbestanden worden niet stilzwijgend betrouwbaar verklaard -- Scope: raster-, vector-, label- en modeldata, inclusief afgeleide datasets - en uitvoerbare inference-inputs -- Samenhang: 05-metric-framework, 07-source-authority-matrix, - docs/API_CONTRACTS.md en docs/DATABASE_IMPLEMENTATION_PLAN.md - -## 1. Doel en harde regel - -Een GeoIntel-resultaat is alleen herleidbaar wanneer alle gebruikte data een -versieerbaar contract heeft, de concrete artefacten checksummed zijn, de -validatie-uitkomst is bewaard en ieder derived artifact zijn parents en -transformaties kent. - -Voor een nieuwe ingest geldt daarom, met de actuele P2-statuswoorden: - - ontvangen -> registered/configured -> ingested + contractvalidatie -> eligible of quarantined - -`ready` is hoogstens een bestaande processingstatus, geen trust- of -consumptiestatus. Alleen een record met complete P2-evidence kan via de -consumption gate operationeel worden gebruikt. Er bestaat geen consumptiepad -van een ontvangen of legacy `ready` record naar training, -productie-inference, primaire QA, coverage authority of normale export dat een -gefaalde, ontbrekende of onbekende contractcontrole stilzwijgend overslaat. Een -incomplete legacyrecord blijft zichtbaar als `lineage_incomplete` en krijgt -geen gefingeerde metadata. - -## 2. Huidige startsituatie versus Fase-2-doel - -De generieke exact-versioned contracten zijn geïmplementeerd in -`backend/app/services/data_contract_validation.py`: -`geointel.vector.geojson@1.0.0`, `geointel.raster.geotiff@1.0.0`, -`geointel.label.yolo@1.0.0` (historisch, geen lege labels), -`geointel.label.yolo@1.1.0` (actueel, expliciete `pure_background`-modus) en -`geointel.model.pytorch@1.0.0`. De ingest- en derived-paden bewaren de -reportvelden. De validator levert een fail-closed report en -`DataQuarantineService` bepaalt de beslissing; `SourceRegistryService` en de -database-quarantinetrigger leggen de persistente quarantine en propagatie vast, -terwijl `DatasetConsumptionGate` operationele consumptie blokkeert. Deze -generieke contracten vervangen geen -toekomstige, strengere productprofielen voor GRB, PICC, UrbIS of -sensor-/modelversies. - -| Onderwerp | Aangetroffen op 2026-08-01 | Fase-2 contractdoel | -|---|---|---| -| Datasetbasis | Dataset en DatasetVersion bevatten storage path, checksum, CRS, bounds, resolution/bands JSON, source/provenance JSON en temporele velden. De Phase-2-migratie voegt contract, registry/snapshot, validation, lineage, quarantine en idempotencyvelden toe. | Iedere nieuwe DatasetVersion krijgt contract-id/-versie, registry/source-snapshotbinding, validation report met contractfingerprint en lineage edges. | -| Uploadvalidatie | Generic upload en server-owned vector/rasteracquisities gaan via dezelfde registry/snapshot/contractflow; een upload blijft `manual` ongeacht caller text. | Generic metadata blijft descriptief; source authority, policy en training/production eligibility komen uitsluitend uit server-owned contracts. | -| Specialistische acquisitie | GRB, DHMV en andere adapterpaden voeren bron-specifieke checks uit en gebruiken de centrale registry/contract engine. | Elke adapter levert machineleesbare pass/fail/quarantine evidence; product-specifieke semantische profiles blijven afzonderlijke uitbreidingen. | -| Vector-CRS | Het beoogde model bewaart EPSG:4326, maar Phase 1 reproduceerde een non-4326 relabeling en vier historische detection geometrieën buiten het 4326-domein. | Bron-CRS is verplicht; transform wordt expliciet gelogd; relabeling zonder transform is verboden; legacy is quarantined of traceerbaar gerepareerd. | -| Versions | DatasetVersion en checksums bestaan, met unieke dataset/version. | Een inhoudelijke mutatie maakt een nieuwe snapshot/datasetversion met parent edge en reportfingerprint; de ingest-API wijzigt geen geaccepteerde evidence in place. | -| Labels/modellen | De Phase-1-training- en auditbestanden ontbeerden governed manifest-/review-/split-/runtimecontract. P2 voegt versioned YOLO-labelcontracten, release-/asset-/label-sidecars en een PyTorch-runtime-sidecar toe; historische bestanden blijven legacy. | Labels en modellen zijn first-class contractartefacten met hashes, split/firewall, review en runtime lineage. | -| Quarantine | `DatasetQuarantine`, een validation report en een consumption gate bestaan nu. | Quarantine heeft eigen status, reden, evidence en toegangsblokkade; gefaalde input kan nergens operationeel worden geconsumeerd. | - -De bestaande velden zijn waardevol als legacy evidence, maar hun aanwezigheid -bewijst geen source authority, semantic validity of release eligibility. Dit -document voorkomt dat metadata-aanwezigheid met contractacceptatie wordt -verward. - -## 3. Universeel contractenvelope - -Elke valideerbare entiteit gebruikt een versieerbaar envelope. De fysieke -opslag kan relationeel, GeoJSON, GeoTIFF, manifest-JSON of modelbestand zijn. -De tabel hieronder is de normatieve envelope; de huidige relationele P2-kolommen -en `validation_report_json` realiseren de kernvelden. Nog niet getypeerde -snapshotvelden worden niet als aanwezig of groen verondersteld (zie 07 §5.3). - -| Veldgroep | Verplicht veld of regel | -|---|---| -| identity | contract_id, contract_version, entity_kind, immutable entity_id, contract/schema fingerprint en waar van toepassing manifest_sha256 | -| source authority | source_registry_id, source_snapshot_id, authority_class, trust_status en allowed_use; de server-owned registrymetadata bevat de seeding/definition-revisie | -| artifact identity | storage URI/path, media type, byte count, sha256, original filename/object key en retained_at | -| time | observed_at, published_at, fetched_at/imported_at, valid_from, valid_to en precise status voor missing/not_applicable/unknown_with_reason | -| spatial | source_crs, canonical_crs, transformation identifier, bounds in source and canonical CRS, units, spatial resolution/scale, vertical datum/unit if applicable | -| coverage | legal/coverage zone IDs, geometry/bbox checksum, exact AOI/partition identity and coverage completeness/truncation status | -| semantic schema | expected geometry/band/class/attribute contract, ontology version, source feature-id strategy and known limitations | -| validation | validation_status, validator version/code commit, started/finished timestamps, checks run, issue list, warning list and report hash | -| lineage | ordered parent identities/hashes, transformation name/version/config hash, child artifact hashes and derivation purpose | -| lifecycle | SourceSnapshot: registered/configured/not_configured/available/ingested/failed/quarantined/legacy_unverified; Dataset contract: not_validated/passed/failed plus quarantine reason/evidence | - -De envelope zelf is canonical JSON. De canonical bytes en ieder gerefereerd -input-/outputartefact zijn SHA-256-bound in een evidence manifest. Filename, -mutable display name and current configuration are never identity substitutes. - -Voor een relationele `Dataset` of `DatasetVersion` die `passed` wordt, dwingt -de P2-migratie bovendien een niet-leeg, bijpassend validation report af: exact -contract en versie, registry/snapshot, report- en contractfingerprint, -`provenance_status=complete`, geldige lineage-status, -`quarantine_status=not_quarantined` en een canonieke SHA-256 die exact met de -gebonden `SourceSnapshot` overeenkomt. Die evidencevelden kunnen niet worden -vervangen terwijl het record `passed` blijft; een inhoudelijke correctie is een -nieuwe versie of eerst een expliciete invalidatie/quarantaine. De -databaseregel bewaakt die structurele binding en immutable evidencevelden, maar -herberekent geen contract- of reporthash en valideert geen bronsemantiek. De -applicatievalidator en `DatasetConsumptionGate` bewaken de inhoudelijke -artefactcontrole en consumptie; een JSON-vorm op zichzelf is nooit een -accuracy- of authority-claim. - -### 3.1 Version rules - -1. Contract major version changes only when semantics or required validation - change incompatibly. -2. New optional fields may use a minor version only when their absence cannot - relax a required gate. -3. A validation rule may become stricter only with a new contract version; old - accepted artifacts retain their historical report and are not silently - relabelled. -4. A re-export, clip, reprojection, normalization, tile build, label repair, - calibration or model conversion is a derived artifact with a new checksum - and lineage edge. -5. A source snapshot is immutable in its source identity/checksum semantics. - Refresh creates a new snapshot and new DatasetVersion/derived graph; it - never overwrites accepted evidence in place. Registry policy is - server-owned; callers never supply an authority or policy version. - -### 3.2 Required use policies - -The allowed_use field is a server computed set. Its relevant values are: - -| Use | Minimum state | -|---|---| -| map_context | accepted contextual/authoritative/corroborative dataset with attribution and spatial contract | -| qa_reference | accepted authoritative source for the exact task/zone/version, or a documented corroborative comparison role | -| training_input | accepted source/derived dataset plus label, temporal, review, split and leakage gates | -| calibration_input | training requirements plus frozen calibration split role | -| protected_test | sealed contract with protected access policy; inaccessible to train/val/calibration processes | -| production_inference_input | accepted raster/tile contract and model compatibility contract | -| export | accepted governed record with complete or explicitly not-applicable lineage; quarantined of lineage-incomplete historic records are not normally exportable | - -No client-provided request field can add qa_reference, training_input or -production_inference_input to this set. - -## 4. Common validation policy - -### 4.1 Mandatory gates - -Every ingest validates the following where applicable: - -| Gate | Required behaviour | Failure disposition | -|---|---|---| -| source attestation | Registry source and snapshot are chosen by the server-side adapter or an explicit review action. | quarantine with SOURCE_UNATTESTED or SOURCE_POLICY_MISMATCH | -| checksum | Persisted content hash equals the observed or generated artifact hash and matches the manifest. | quarantine with CHECKSUM_MISMATCH | -| file safety | File type, byte size, decompression/container constraints and parser safety match the contract. | reject or quarantine before product persistence | -| CRS | Source CRS is declared and parseable; transform to canonical CRS is explicit and recorded. | quarantine with CRS_MISSING, CRS_INVALID or CRS_TRANSFORM_FAILED | -| bounding box | Bounds are finite, nonempty, in source CRS and consistent after transform with legal/domain scope. | quarantine with BBOX_INVALID or BBOX_OUT_OF_SCOPE | -| units/resolution | Unit, pixel/ground resolution, scale and vertical datum match source/product contract. | quarantine with UNIT_MISMATCH or RESOLUTION_MISMATCH | -| time/freshness | Required source version, observed/valid period, fetched time and freshness policy are satisfied or explicitly classified. | quarantine with TEMPORAL_METADATA_MISSING or FRESHNESS_REVIEW_REQUIRED | -| semantic schema | Geometry/bands/attributes/classes/ontology/feature IDs meet the contract. | quarantine with SCHEMA_MISMATCH | -| lineage | Every parent artifact/version/transformation is resolvable and checksummed. | quarantine with LINEAGE_MISSING or PARENT_INVALID | -| topology/integrity | Geometry/raster/label/model-specific validity is green. | quarantine with the specific integrity code | - -At a consumption boundary a concrete snapshot must be `current` or explicitly -`not_applicable`. `unknown`, `review_required`, `due` and `stale` are not -eligible for production inference, primary reference validation, derived -processing, authoritative coverage or normal export. This guard is separate -from source-family classification: an authoritative registry entry never -overrides an unsuitable snapshot. - -Warnings never change a failed required gate to accepted. A warning may retain -accepted only when the exact contract explicitly says that it is non-blocking, -the warning is visible, and the allowed_use policy excludes inappropriate uses. - -### 4.2 CRS, units and geometry rules - -- Canonical persisted vector/result geometry is EPSG:4326 only after an - explicit source-to-canonical transform. Setting SRID to 4326 on coordinates - in EPSG:31370, EPSG:3812 or any other CRS is prohibited. -- Every metric distance, buffer, area, length and topology tolerance uses an - approved metric CRS or a documented geodesic operation. In the Belgian land - scope, EPSG:31370 is the default candidate when suitable; an operation must - record the chosen CRS and unit. -- The Belgian North Sea keeps horizontal CRS and vertical datum separate. - TAW, LAT, mDNG, NAP and depth/elevation semantics never convert implicitly. -- Bbox checks validate coordinate order, finite values, positive extent, - source CRS domain, transformed canonical domain and declared coverage zone. -- Geometry repair is only allowed under a named repair policy. The original - hash, repair method, before/after validity and changed feature count remain - in provenance. A repair that changes type, dimension or exceeds the - tolerance is quarantined for review. - -## 5. Raster data contract - -### 5.1 Required raster fields - -| Group | Required contract content | -|---|---| -| artifact | GeoTIFF/COG or approved format, sha256, byte size, parser/driver result, compression/nodata and immutable storage path | -| spatial | source CRS, affine transform, width/height, source and canonical bounds, pixel size x/y and unit, pixel interpretation and resampling method | -| bands | band count/order, data type, colour interpretation or physical unit, nodata, scale/offset, valid pixel statistics and allowed ranges | -| source/time | source registry/snapshot, product/collection/scene/tile identity, source version, acquisition/observation period and fetched/imported time | -| coverage | requested AOI/partition hash, clipping/mosaic inputs, complete/truncated status, coverage percentage and edge/padding policy | -| lineage | original response/archive hash, normalization/clipping/mosaic operation and configuration hash, every parent raster hash | -| compatibility | task-specific accepted bands, resolution range, colour/channel arrangement and temporal suitability for label/model task | - -The parser must reject a non-georeferenced analytical raster unless the -contract explicitly marks it image-space only. Image-space-only data cannot -produce map geometry or location claims. - -### 5.2 Raster-specific checks - -1. CRS, affine transform, width, height, bounds and resolution must agree - numerically within a contract tolerance. -2. The raster must have the exact expected band count/data type/nodata policy - for the source product; unknown values are not silently filled. -3. Resolution cannot be represented as finer than the source's native - resolution. Derived resampling records source and analysis resolution - separately. -4. Mosaic/clip outputs declare every parent tile, overlap/nodata merge rule, - exact AOI mask and output checksum. -5. Acquisition time is separate from fetch time. A rolling latest orthophoto - with unknown per-pixel observation time remains unknown_per_pixel. -6. A raster used for labels or metrics records the reference-to-imagery time - delta and its policy decision. This closes the temporal source of - D-TEMPORAL-MISMATCH without inventing a date. - -### 5.3 Source-specific requirements - -| Product family | Additional contract rule | -|---|---| -| Official orthophoto | Product key, provider, native resolution, colour mode, imagery edition/flight-date precision, coverage zone and licence are mandatory. It is imagery/context, not reference truth. | -| Sentinel-2 | Contract must declare processing level, tile/granule, acquisition time, band/resampling method, cloud/nodata mask and native ground resolution. It remains contextual and cannot satisfy a building label/reference contract. | -| DHMV | Contract requires product key, DTM/DSM semantics, EPSG:31370, native/analysis resolution, one-band numeric units, nodata, TAW vertical reference and 2013-2015 period for the currently configured DHMV II source. It is elevation evidence, not building truth. | -| Bathymetry | Vertical datum/reference plane, depth versus bed-elevation semantics, survey epoch and uncertainty are mandatory. No water volume is inferred. | - - -### 5.4 Inference tile-manifest contract - -Raster tiling emits `geointel.raster.tile-manifest@2.0.0`. The manifest binds -the source Dataset id/checksum/size, the latest DatasetVersion identity and -checksum, registry/snapshot identities and snapshot checksum, data-contract -identity, source version and—when present—the Area identity and geometry hash. -Each tile has an explicit CRS/bounds, byte size and SHA-256. - -Configured detection and segmentation validate that exact binding against the -requested live Dataset before model loading. They recompute every tile hash, -normalize the tile union to EPSG:4326 and require it to remain inside the -manifest and persisted Dataset extents and intersect the bound Area. Missing, -legacy or changed evidence is not inferred from filenames: it fails closed with -a typed dataset, provenance, tile-integrity or spatial-scope error. - -## 6. Vector data contract - -### 6.1 Required vector fields - -| Group | Required contract content | -|---|---| -| artifact | GeoJSON/approved vector artifact hash, feature count, media type, source/canonical CRS, original artifact retained path | -| geometry | allowed geometry types/dimensions, empty/valid counts, repair policy, source and canonical bbox, geometry precision/tolerance | -| identity | source feature-id attribute/namespace, uniqueness policy, stable-identity flag and collision report | -| attributes | contract version, required/optional fields, type/domain/null policy, canonical mapping and retained native properties policy | -| authority/time | registry source/snapshot, product/collection, zone, source version, observation/validity/fetched time, licence/attribution | -| topology | per-product topology rules, overlap/gap/containment/line connectivity policy and known exceptions | -| lineage | input artifact hashes, clip/filter/transform configuration, source feature counts and derived output feature mapping | - -### 6.2 Vector-specific checks - -1. De parser accepteert een feature collection met een expliciete CRS of de - RFC 7946-standaard EPSG:4326. De ingestservice transformeert een niet-4326 - bron expliciet vóór canonical persistence; `build_vector_ingest_input` - valideert daarna de getransformeerde feature collection en haar - transformation evidence. Coördinaten buiten het Belgische/Noordzee-domein, - een ongeldige CRS of een Lambertlaag die als 4326 wordt aangeboden, worden - gequarantined; veldvorm alleen is nooit voldoende om een andere CRS te - raden. - De normale `Dataset.storage_path` en zijn checksum verwijzen daarna naar - exact die canonieke EPSG:4326-bytes. Originele niet-canonieke bronbytes - blijven uitsluitend als checksummed provenance-evidence buiten het - consumptiepad bewaard; vectorbewerkingen weigeren een CRS- of - storage-checksum-mismatch fail-closed. -2. Every feature has a nonempty supported geometry. Invalid features are - quarantined individually or cause the dataset to quarantine according to - an all-or-nothing policy recorded in the contract. -3. Source geometry is transformed before canonical PostGIS persistence. - Post-transform coordinates must pass canonical domain/bbox checks. -4. Source feature IDs are unique whenever object lineage/temporal comparison - needs them. Missing/duplicate/unexpected IDs set identity_stable=false and - prevent object-level change claims. -5. Required attributes are type-checked before any source-to-canonical mapping. - Unknown native fields may be retained in properties JSON but can never - satisfy a required canonical attribute by name coincidence. -6. Topology rules are task-specific. A self-intersection is always invalid; - overlapping building footprints may be a source semantic/review event - rather than an automatic geometric repair. The contract states which. -7. Any clipping, buffering, intersection or dissolve creates a derived - contract with parent hashes, metric CRS, units, tolerance, analysis run and - queryable feature-persistence count. A derived Dataset cannot be accepted - while its artifact and vectorfeatures diverge. - -### 6.3 Building reference profiles - -| Profile | Required fields / checks | Authority rule | -|---|---|---| -| GRB GBG | approved GRB collection, official feature ID, Polygon/MultiPolygon, governed request/response/artifact hashes, exact coverage, source snapshot/version, temporal limitation and EPSG:4326 output transform | Primary authoritative footprint reference in Flanders only when 07-source-authority-matrix conditions hold | -| Buildings Register | building object/version/status, snapshot date, bounded area, privacy-minimized output, raw-page hashes, register-to-GRB reconciliation and exact source URLs | Authoritative for its register semantics; corroborative for footprint reconciliation, never automatic GRB replacement | -| PICC buildings | allowlisted provider product, stable product identity, authorised Walloon coverage, feature ID, native CRS transform, edition/time and geometry contract | Authoritative only for approved Walloon building task/version | -| UrbIS buildings | allowlisted product, Brussels coverage, provider-native identity, native CRS transform, edition/time and geometry contract | Authoritative only for approved Brussels building task/version | -| OSM buildings | OSM extract/version/timestamp/licence, geometry and tag mapping if intentionally ingested | Contextual/corroborative only; no automatic truth, labels or coverage authority | - -## 7. Label data contract - -Labels are not just text files. Every label has a physical image/tile, -reference/source geometry and a training-policy decision. - -### 7.1 Required label-manifest fields - -| Group | Required content | -|---|---| -| identity | corpus_id/version, label artifact sha256, image/tile sha256, sample ID, tile-manifest sha256 and ontology/class-map version | -| spatial/image | image CRS/affine/bounds/resolution, tile size/stride/overlap, pixel coordinate convention and image orientation | -| reference | source registry/snapshot, native source feature IDs, geometry/reference hash, source/reference version and license eligibility | -| time | imagery observed/acquisition time, label/reference observed time, delta calculation, temporal policy/reason code | -| semantics | class, inclusion/exclusion rule, difficult/ambiguous/occluded flag, geometry-to-box conversion policy and minimum resolvable size | -| review | review state, reviewer/adjudicator ID, decision/reason code, contact-sheet/overlay hash and decision timestamp | -| split | train/val/calibration/test/background-test role, split-manifest hash, parent AOI/group ID and protected flag | -| eligibility | accepted, excluded, quarantined or uncertain; allowed training/evaluation use and all reasons | - -### 7.2 Label validation - -- Every label references an image/tile that exists and has exactly the recorded - checksum. A label cannot migrate across tiles by filename matching. -- Coordinates are finite, in the declared pixel convention and within image - bounds. Boxes/polygons must have positive area, supported class and - deterministic normalization. -- The label's native source feature ID, source snapshot, geometry transform - and image/reference time relation are mandatory for trainable labels. -- Below-resolution, post-imagery, dense/occluded, extreme-aspect and - uncertain labels require an explicit disposition. Unknown is not accepted. -- A reviewed label preserves all earlier review decisions; repair produces a - new label release and links the superseded artifact. -- Test- en background-testlabels zijn logisch beschermd door manifest-, - release- en trainingsgates. Ze mogen niet aan samplers, augmentation, - calibration, thresholdselectie of training worden aangeboden. Fysieke - read-only opslag en afzonderlijke credentials mogen pas worden geclaimd - wanneer daarvoor afzonderlijke P2-05-evidence bestaat. - -`geointel.label.yolo@1.0.0` is historisch en laat geen lege labelbestanden -toe. `geointel.label.yolo@1.1.0` onderscheidt exact twee modi: `objects` voor -een niet-leeg YOLO-bestand en `pure_background` voor een leeg bestand. Een -leeg bestand wordt dus nooit automatisch als negatief voorbeeld geïnterpreteerd. -Voor `pure_background` zijn naast de normale labelchecks minstens verplicht: - -- de exacte `sample_slug` en een toegestane `train`- of `val`-split; -- raster- en referencedataset-ID, checksums, registry en concrete snapshot - via de upstream lineage; -- `review_decision=accepted`, reviewer-ID, tijdstip met tijdzone en hash van - het menselijke reviewartefact/contact sheet. - -Objectlabels met `pure_background` en lege labels zonder deze evidence falen -gesloten. Test- en achtergrond-testrollen worden niet toegelaten als deze -trainbare `pure_background`-modus. - -Bij het maken van een trainingsrelease wordt ieder label opnieuw gevalideerd -en gebonden in `.geointel-training-label-contracts.json`. Die -immutable sidecar bevat per label de checksum, sample, mode, exact -contract/fingerprint en de tellingen voor objecten/achtergronden; de release -en release-freeze binden vervolgens de sidecarhash. Voor het aanmaken, -verifiëren en elke initial/retry/resume-trainingsstap wordt de bevroren corpus -opnieuw tegen de live Dataset-status gecontroleerd. Een later gequarantined, -ontbrekende of niet-meer-eligible raster/referencepartner herroept de release -en blokkeert training, ook wanneer de freeze zelf ooit groen was. - -The current V56 evidence has automated tile syntax checks but zero accepted -human AOI reviews. It therefore remains a legacy candidate corpus, not an -accepted label release under this contract. - -Grayscale-transformaties, SAM-labelverfijningen, rotated holdouts en -proposal-crops controleren hun upstream release vóór verwerking, maar erven die -release niet als nieuwe trainability. Hun output is expliciet -`training_eligible=false` totdat een nieuwe governed corpus-, review-, -contract- en releasecyclus de nieuwe bytes heeft geaccepteerd. Dit voorkomt dat -een cosmetische of modelgestuurde afleiding stilzwijgend in een bestaande -PyTorch-trainingsrelease terechtkomt. - -## 8. Model data contract - -### 8.1 Required model-manifest fields - -| Group | Required content | -|---|---| -| identity | model_id, model_version, weights sha256/size, format, architecture and class ontology version | -| origin | base weights hash/source, training code commit, training image/container digest, dependency lock/SBOM and license | -| data | corpus manifest sha256, label release sha256, split manifest sha256, training/validation/calibration roles and data access policy | -| config | preprocessing/tile/normalization/augmentation config hash, input dimensions/bands/colour order, threshold/NMS/max detections and seed | -| runtime | Python/PyTorch/CUDA/Ultralytics/driver versions, required device, GPU identity, deterministic flags and known nondeterminism | -| evidence | training run manifest/checkpoints/logs/curves, evaluator version, calibration and protected-test policy, model card scope polygon/zone IDs | -| lifecycle | candidate/unpromoted/validated/promoted/retired status, promotion report/rollback link and explicit supported/not_configured task scope | - -### 8.2 Model validation - -1. Weights hash, architecture and class map must load under the recorded - runtime. Load success is runtime evidence only. -2. Input raster/tile contract must match bands, colour order, resolution, - preprocessing and image geometry expected by the model. -3. Model scope is a server-owned geometry/zone policy bound to the model - manifest, never a mutable Area display name. -4. Training reads only its allowed split roles. A protected credential/path, - protected sample identifier or protected assessment causes a hard failure. -5. A detection/segmentation run persists the exact model manifest hash, model - hash, inference config hash, tile manifest hash, dataset version, - transform, seed, container/runtime/hardware and code commit before - status=success can be emitted. -6. Legacy model runs with missing values remain lineage_incomplete. Current - active configuration must not be copied backwards as an invented version. - -### 8.3 Runtime sidecar gate for local PyTorch weights - -Configured local YOLO and SAM weights are **not runnable** merely because a -`.pt` file exists or is listed as an active model asset. Before -`load_model()` is called, GeoIntel requires a neighbouring immutable sidecar: - - .geointel-model.json - -The sidecar must validate exactly as `geointel.model.pytorch@1.0.0` and binds -the following at minimum: - -- a fixed sidecar schema version, configured model ID and task type; -- the SHA-256 of the physical weights and the source-snapshot checksum of the - same bytes; -- `model_format`, framework, non-empty class mapping and source/model version; -- source registry/snapshot UUIDs, a training-manifest checksum and non-empty - upstream asset/checksum plus transformation lineage; -- a timezone-aware import timestamp; and -- `metadata.runtime_manifest_sha256`: a SHA-256 of canonical sidecar JSON with - only that self-referential field omitted. - -Missing, malformed, wrong-contract, version/task/framework-mismatched or -tampered sidecars make the capability `contract_incomplete`; detection and -segmentation do not load the adapter or weights. Validated sidecar evidence is -copied into the analysis run/job and into each configured detection or -segmentation provenance payload. This is a byte-binding and structural -lineage gate, not a promotion or accuracy claim: a model still needs its -separate training, calibration, protected-test and scope evidence before it -can be called validated or nationally suitable. - -For production inference the structural sidecar check is insufficient on its -own. Immediately before adapter loading, GeoIntel resolves both UUIDs against -the database and requires the `model` registry entry, a matching immutable -snapshot, safe configured/current and ingested/current states, exact -model/sidecar/snapshot checksum and source-version equality, and no active -quarantine record. A missing, detached, mismatched, stale or quarantined -database record fails before `load_model()`; catalogue and preflight discovery -remain explicitly non-production structural checks. - -The fixture detector/segmenter and placeholders remain explicit test-only -paths. They require `fixture_mode=true` where execution is allowed and cannot -be made production-ready by a sidecar or request parameter. - -The Phase-1 active model has an asset hash and a successful GPU smoke, but its -historical detection runs lack the complete RunManifest fields and it is not -nationally validated. It cannot meet this model contract retroactively without -original evidence. - -## 9. Derived data and lineage graph - -### 9.1 Required lineage edge - -Each derived entity records: - - parent entity id + parent manifest/hash + transformation id/version - + configuration hash + code commit + runtime/container identity - + output entity id + output hash + validation report hash - -Examples include source raster to clipped raster, raster to tiles, source -vector to normalized vector, vector to label, labels to corpus, corpus to -checkpoint, checkpoint to inference run, detections to QA and QA to export. - -The graph must be acyclic. A derived artifact cannot cite itself or a mutable -“latest” path as its only parent. Parent availability, hash and contract state -are checked recursively to the configured evidence boundary. - -### 9.2 Idempotency and resume - -An ingest/derivation idempotency key is the canonical combination of: -source snapshot or parent hashes, contract version, transformation/config hash, -requested AOI/partition hash and destination semantic role. - -Repeated requests with the same key return the existing accepted artifact only -after rechecking its manifest/checksum/validation state. Interrupted work -resumes from staged checkpoint evidence or creates a new attempt record; it -does not invent success, duplicate a visible DatasetVersion or bypass -validation. A partial result is marked failed or quarantined and never reused -as a complete parent. - -An identical replay may bind a second project-scoped ingest key to the same -immutable source snapshot. It preserves the snapshot's first recorded -`fetched_at`; all other immutable snapshot evidence, including checksum and -CRS, must still be equal. A changed fetch time alone therefore cannot rewrite -provenance or cause a duplicate snapshot. - -## 10. Safe quarantine flow - -### 10.1 Policy - -Quarantine is preservation, not deletion. De huidige P2-implementatie bewaart -in een `DatasetQuarantine`-record de target-FK's, stage, één reason code, -details JSON, optioneel artifactpad/checksum, status en resolutietimestamps. -Het validation report blijft bij `Dataset`/`DatasetVersion`; lineage wordt via -de lineage-edges en de snapshotbinding herleid. `SourceRegistryService` en de -database-trigger maken het target, gedeelde snapshotpartners en downstream -lineage non-consumable voor training, productie-inference, normale QA en -automatische export. Een fysieke move/copy naar een afzonderlijke -access-controlled quarantine-storage is nog geen gerealiseerd -opslagmechanisme; die ontbrekende fysieke isolatie mag niet als bewijs worden -geclaimd. Tot die uitbreiding houdt de logische quarantine gate de verplichte -operationele veiligheidsgrens in stand. - -| Event | Required action | -|---|---| -| parser/file failure | Retain minimal evidence and report; quarantine when artifact preservation is safe, otherwise reject with captured hash/error metadata | -| CRS/bounds/unit failure | Quarantine dataset/feature/run with source coordinates and validator report; never relabel CRS | -| source/trust failure | Route user/manual data to manual/untrusted or quarantine; do not materialize authoritative coverage | -| missing version/time/license | Quarantine when policy requires the field; source freshness shows review_required, not current | -| label-review/split failure | Quarantine label/corpus release and deny training/calibration/test use | -| model/run lineage failure | Mark lineage_incomplete or quarantine candidate output; deny validation/promotion | -| derived persistence mismatch | Roll back the transactional visible result when possible; retain failed attempt evidence and do not emit ready/success | - -### 10.2 Quarantine dispositions - -De gerealiseerde P2-statuswaarden zijn `quarantined`, `released` en -`rejected`, met de bewaartechnische velden hierboven. Een `released` quarantine -maakt de oorspronkelijke dataset niet opnieuw operationeel: een governed -re-ingest of nieuwe versie blijft vereist. Een rijkere disposition-taxonomie -met severity, secundaire reason codes, validatorversie, reviewer action, -`pending_review`, `remediated_as_new_version` en -`accepted_for_limited_historical_view_only` is vervolgwerk en mag nog niet als -gerealiseerde recordstructuur worden voorgesteld. Een reviewer kan nooit een -authoritative-, protected-split- of source-identity-gate in-place opheffen. - -## 11. Contract test matrix - -The implementation must retain tests for valid and deliberately invalid -fixtures. At a minimum: - -| Dataset kind | Green fixture | Red fixture / expected outcome | -|---|---|---| -| governed GRB vector | bounded GBG fixture with registry attestation, valid CRS, unique IDs and request/response hashes | user upload claiming source_name=grb; it remains manual/untrusted or quarantined | -| vector CRS | EPSG:31370 or EPSG:3812 source transformed to EPSG:4326 with correct bounds | Lambert coordinates persisted as 4326 or source CRS absent; quarantine | -| vector geometry/topology | valid source polygons and explicit valid repair evidence | self-intersection, empty geometry, invalid dimensionality, duplicate required source ID or unsupported attribute type | -| raster/DHMV | one-band EPSG:31370, expected nodata/resolution/TAW metadata | wrong band count, unit, vertical reference, resolution, affine/bounds or checksum | -| Sentinel-2 | deliberately contextual fixture with full sensor/tile/time metadata | attempt to use it as building reference/ground truth; policy failure | -| label | bounded objectlabels of expliciet reviewed `pure_background` labels linked to image/hash/source/review/split manifest | out-of-bounds box, missing source feature, unmarked empty label, post-imagery unknown, unreviewed required sample or protected-role leakage | -| model/run | checksummed model with complete manifest and matching tile contract | model/run missing model hash, tile-manifest hash, GPU/runtime identity or scope policy; no success/promotion | -| lineage | one parent-to-child transformation graph with reproducible output hash | missing parent, changed parent checksum, cycle, partial operation or output count mismatch | -| quarantine | failed record remains non-consumable and visible with reason | attempt to train, infer, QA-as-truth, cover or export a quarantined artifact; hard denial | - -Tests include unit, service, API, migration and live PostGIS coverage where -the contract relies on database constraints. A test that only asserts source -text is insufficient; it must exercise the actual validation and state -transition. - -## 12. Fase-2 completion gates for data contracts - -The source/provenance part of Fase 2 is green only when: - -1. every new accessible DatasetVersion, raster, vector, label release and - model/run type is routed through an explicit contract; -2. every new imported dataset has a server-attested registry/snapshot binding, - checksum, validation report and lineage identity; -3. generic uploads cannot acquire authoritative source identity from caller - text; -4. invalid CRS, geometry, bbox, unit, resolution, checksum, freshness, - attribute, topology and lineage fixtures all fail closed; -5. quarantine is tested and has zero path into training, production inference, - primary QA, coverage authority or normal export; -6. migrations preserve existing records, classify legacy gaps and do not - silently backfill uncertain facts; -7. an evidence manifest retains test, migration and source/contract audit - outputs under artifacts/evidence/accuracy/P2. - -Until all gates are green, Fase 2 is in progress, Fase 3 is not ready and -training/promotion remains blocked by the Phase-1 execution contract. - -> **Historische handoff:** deze zin legt de P2-gate vast zoals die bij oplevering -> van dit document gold. Fase 3 is nadien binnen de afgebakende lokale scope -> uitgevoerd. De actuele fasebeslissing staat uitsluitend in -> `docs/accuracy-program/status.json`. diff --git a/docs/accuracy-program/09-full-data-scan.md b/docs/accuracy-program/09-full-data-scan.md deleted file mode 100644 index 1a18cd87..00000000 --- a/docs/accuracy-program/09-full-data-scan.md +++ /dev/null @@ -1,103 +0,0 @@ -# Fase 3 — Volledige datascan en quarantaine - -## Resultaat - -De reproduceerbare scan `scripts/run_accuracy_phase3_full_data_scan.py` is read-only uitgevoerd over de veilige lokale scope `models/`, `datasets/`, `data/`, `storage/`, `artifacts/` en `output/`. De scan schrijft uitsluitend bewijs naar `artifacts/evidence/accuracy/P3/`; bronbestanden zijn niet gewijzigd. - -| Telling | Aantal | -| --- | ---: | -| Onderzochte bestanden | 1013 | -| Overgeslagen bestanden | 0 | -| Onbereikbare scope-items | 3 | -| Geïnventariseerd totaal | 1016 | -| Reconciliatie | groen (`1013 + 0 + 3 = 1016`) | - -De drie expliciet onbereikbare items zijn grenzen van deze lokale -Windows-scan: de niet lokaal gemounte Tower-corpora, modelvolumes en het -productie-PostGIS/API-endpoint. Elk staat als `unreachable` in het volledige -manifest met concrete reden; er is geen stilzwijgende skip. Dit betekent niet -dat de server zelf onbereikbaar is. Een afzonderlijke gecontroleerde -productiescan moet die remote scopes beoordelen voordat een nationale -volledigheidsclaim mogelijk is. - -De scan leverde 711 anomalieën op. Dat is geen geldigheidsclaim: 682 items -zijn daarom in het logische quarantainemanifest opgenomen. De scanner promoot -geen enkel foutief item tot ground truth en voert geen automatische reparatie -uit. De huidige bevindingen zijn: - -| Categorie | Aantal | Standaardactie | -| --- | ---: | --- | -| Onleesbare/corrupte GeoTIFF | 96 | unavailable or unreadable | -| Afgeleide artefacten zonder expliciete lineage | 577 | quarantine | -| Bronlabel zonder declared freshness | 29 | requires review | -| Manifest met nul-bounding-box | 6 | quarantine | -| Niet-bereikbare externe scope | 3 | unavailable or unreadable | - -De eerdere P1-splitinventaris blijft zichtbaar in `leakage-report.json`: 24 AOI-paren lagen onder 2 km en split-onafhankelijkheid was niet bewezen. De scan rapporteert dat als `attention`; bestandsnamen alleen kunnen AOI-onafhankelijkheid niet bewijzen. Er was geen toegankelijke GRB-snapshot in de lokale scope, zodat geen afgeleid resultaat als GRB-ground-truth is gemarkeerd. - -## Scancontract - -Iedere inventarisregel bevat een immutable padidentiteit, bestandsgrootte en SHA-256 (waar leesbaar), typecontract, bronclassificatie, lineage, schema/CRS, resolutie/eenheden, ruimtelijke en temporele dekking, freshness, geometrie- of rasterstatus, duplicaatinformatie, anomalieën, ernst en aanbevolen actie. Ondersteunde typecontracten zijn: - -- `geointel.vector.geojson@1.0.0` — GeoJSON-schema, geometrievaliditeit en EPSG:4326-bounds; -- `geointel.raster.geotiff@1.0.0` — leesbaarheid, CRS, dimensies, resolutie, bounds, nodata en sample-validiteit; -- `geointel.label.yolo@1.1.0` — genormaliseerde YOLO-labelregels en expliciete achtergrondreview; -- `geointel.model.pytorch@1.0.0` — immutable modelartefact-identiteit; -- `geointel.manifest.json@1.0.0` — CRS, bounds, tile-paden en bron-ID's; -- `geointel.database.sqlite@1.0.0` en `geointel.artifact.generic@1.0.0` — veilige byte-/schema-inventaris voor runtime- en bewijsartefacten. - -Er zijn vijf vaste ernstniveaus (`blocker`, `critical`, `major`, `minor`, `informational`) en zeven vaste acties (`accept`, `repairable automatically`, `requires review`, `quarantine`, `exclude from training`, `exclude from evaluation`, `unavailable or unreadable`). Een anomaly wordt nooit automatisch als waarheid gebruikt. - -## Hervatbaarheid en determinisme - -De scanner bouwt eerst een gesorteerde inventory-hash. Per batch wordt `scan-checkpoint.json` atomair bijgewerkt. Met dezelfde inventory en `--resume` worden onveranderde records hergebruikt; gewijzigde records worden opnieuw gelezen. De inhoudshash sluit alleen uitvoertimestamps uit. Twee opeenvolgende runs gaven dezelfde scan-ID en content-hash: - -`p3-eb67185e61107cc7` / `f4ea193d2bdd96a5b391cf7d9d93685cc58e98742c40e4513bcbc434907e720a` - -## Bewijsartefacten - -- `artifacts/evidence/accuracy/P3/full-scan-manifest.json` — volledige machineleesbare scan; -- `artifacts/evidence/accuracy/P3/anomaly-manifest.json` — alle afwijkingen; -- `artifacts/evidence/accuracy/P3/quarantine-manifest.json` — veilige logische quarantine; -- `artifacts/evidence/accuracy/P3/duplicates-report.json` — exacte en genormaliseerde near-duplicategroepen; -- `artifacts/evidence/accuracy/P3/leakage-report.json` — checksum-/splitsignalen en P1-splitinventaris; -- `artifacts/evidence/accuracy/P3/source-freshness-report.json` — bron/freshness-kruistabel; -- `artifacts/evidence/accuracy/P3/dataset-summary.json` — samenvatting per contracttype; -- `artifacts/evidence/accuracy/P3/scan-checkpoint.json` — hervatbare batchstaat. - -## Reproduceerbare uitvoering - -```powershell -python scripts/run_accuracy_phase3_full_data_scan.py --batch-size 40 -python scripts/run_accuracy_phase3_full_data_scan.py --batch-size 40 --resume -python -m pytest backend/tests/test_accuracy_phase3_full_data_scan.py -q -p no:cacheprovider -python -m ruff check scripts/run_accuracy_phase3_full_data_scan.py backend/tests/test_accuracy_phase3_full_data_scan.py -``` - -De fixturetest controleert geldige en foutieve GeoJSON, corrupte rasterinput, exacte duplicaten, quarantine en identieke herhaling. Productie- of brondata wordt door deze tests niet aangeraakt. - -## Fasebeslissing - -De lokale Fase-3-scan is volledig voor de afgebakende projectomgeving: alle -1013 veilige lokale bestanden zijn verwerkt en de drie niet-gemounte grenzen -zijn expliciet geregistreerd. Fase 3 blijft voor de totale operationele -omgeving `production_inventory_pending` totdat de servervolumes en database -in een gecontroleerde productiescan zijn gereconcilieerd. Fase 4 kan de lokale -quarantine- en leakage-signalen al beoordelen. Dit is geen modelpromotie- of -nationale kwaliteitsclaim; de inhoudelijke anomalieën moeten eerst worden -hersteld of representatief menselijk beoordeeld. - -> **Historische handoff:** `ready` beschrijft het overdrachtsmoment direct na -> de Phase-3-scan. Het Phase-4-harnas is inmiddels geïmplementeerd, maar de -> actuele productbenchmark is nog `not_evaluable`; de normatieve actuele -> status staat in `docs/accuracy-program/status.json`. - -## Accuracy-handoff na de scan - -De onafhankelijke AI-visuele triage van 30 augustus is vastgelegd in -`artifacts/evidence/accuracy/model-training/20260830-independent-ai-visual-review.json`. -Daarin blijven `human_reviewer=false`, corpusacceptatie, training en promotie -expliciet geblokkeerd. Een model kan bovendien pas worden geactiveerd wanneer -de exacte candidate key en model-SHA-256 overeenkomen met een geslaagd governed -Phase-4/5 release-gaterapport dat ook de benchmarkmanifest-SHA-256 bindt. De -taakgeschikte officiële bron blijft doorslaggevend voor productresultaten. diff --git a/docs/accuracy-program/10-evaluation-protocol.md b/docs/accuracy-program/10-evaluation-protocol.md deleted file mode 100644 index 04cb35e2..00000000 --- a/docs/accuracy-program/10-evaluation-protocol.md +++ /dev/null @@ -1,175 +0,0 @@ -# Fase 4 — Evaluatieprotocol - -## Doel en huidige claimgrens - -Het Phase-4-harnas maakt evaluatorgedrag, splits, ruwe voorspellingen en -releasebeslissingen reproduceerbaar. De lokale referentiecases zijn bewust -synthetisch en bewijzen uitsluitend dat het harnas correct en fail-closed -werkt. Zij zijn geen meting van productie-accuracy, België-brede -generaliseerbaarheid of menselijke aanvaardbaarheid. - -De volledige workflow is: - -```powershell -python scripts/run_accuracy_phase4_benchmark.py -``` - -De standaarduitvoering retourneert exitcode `2` zolang een productgate niet -groen is. Voor het uitsluitend regenereren en testen van lokale evidence mag: - -```powershell -python scripts/run_accuracy_phase4_benchmark.py --allow-product-blocked -``` - -worden gebruikt. Die vlag verandert geen gate, score of beslissing. Hij maakt -alleen een succesvolle lokale harnascontrole bruikbaar in CI terwijl externe -productinput aantoonbaar ontbreekt. - -## Geïmplementeerde taken - -De inventaris scheidt geleerde modellen van deterministische GIS-analyse. Een -officiële of deterministische GIS-functie wordt niet kunstmatig als -machine-learningmodel voorgesteld. - -De machineleesbare inventaris omvat 15 concrete platformcapabilities, gemapt -op zeven evaluatorfamilies. Een family-dekking geldt niet automatisch als een -zelfstandige benchmarkclaim voor iedere onderliggende microfunctionaliteit. - -| Taakfamilie | Werkelijke implementatie | Phase-4-metrics | Huidige productstatus | -| --- | --- | --- | --- | -| Objectdetectie | `backend/app/services/detection_service.py` | precision, recall, F1, AP50, AP50–95, matched IoU, ECE, Brier, coverage-risk | evaluatorcontract groen; actieve modelbenchmark lokaal niet uitvoerbaar | -| Gebouwfootprintsegmentatie | `backend/app/services/segmentation_service.py` | object-P/R/F1, IoU, Dice, boundary F1, centroidafstand, relatieve oppervlaktefout, topologie | evaluatorcontract groen; geen representatieve beschermde productset bereikbaar | -| Vectorvergelijking en detectie-QA | `backend/app/services/qa_service.py`, `backend/app/services/detection_qa_service.py` | object-P/R/F1, mean IoU, topologische geldigheid | referentie-implementatie via de golden QA-fixtures uitgevoerd | -| Veranderingsdetectie | `backend/app/services/change_detection_service.py` | event-level P/R/F1, apart voor toegevoegd en verwijderd | evaluatorcontract groen; productbaseline niet vastgesteld | -| Thematische rasterinterpretatie | `backend/app/services/thematic_raster_analysis_service.py` en rasterservices | confusion matrix, pixelaccuracy, class-P/R/F1, class-IoU, mean IoU | alleen metriekcontract voor categorische rasters; er is geen geleerd generiek rasterclassificatiemodel aangetroffen | -| Hoogte- en terreininterpretatie | terrein-, hoogte-, bathymetrie- en overstromingsservices | MAE, RMSE, bias, coverage en foutverdeling in gedeclareerde eenheid | deterministische bronanalyse; referentiedata en eenheden blijven taakgebonden | -| Geospatiale datavalidatie | `backend/app/services/data_contract_validation.py` en Phase-3-scanner | anomaly-P/R/F1, blocker/critical misses | contractfixture groen; echte bronscan blijft de Phase-3-evidence | - -Vector clip/buffer/intersect, ruimtelijke aggregatie, raster inspect/reproject/ -clip/tile, NDVI/NDWI/NDBI, flood hazard, bathymetrie en AOI-partitionering -vallen onder de overeenkomstige deterministische validatie-, vector-, raster- -of terreinfamilie. De geo-assistent is een orkestratie-interface en krijgt geen -misleidende zelfstandige accuracy-score; de onderliggende toolresultaten -blijven maatgevend. - -## Metriccontract - -Alle objectmatches zijn one-to-one en gebruiken de vooraf vastgelegde -taakconfiguratie. Er is geen data-afhankelijke threshold-, operating-point- of -modelselectie op test-, background-test- of challenge-input. Vaste diagnostische -AP- en coverage-riskcurves veranderen het vooraf geregistreerde operating point -niet. Ongedefinieerde delingen worden `null` met expliciete support, niet -kunstmatig `1.0`. - -| Uitvoertype | Verplichte kernmetingen | Aanvullende controle | -| --- | --- | --- | -| Objecten | TP, FP, FN, precision, recall, F1 | IoU, AP, calibration en abstention | -| Footprints | objectmetingen, mean IoU en Dice | boundary F1, centroid, area en topologie | -| Categorische rasters | confusion matrix, per-class F1/IoU, mean IoU | pixelaccuracy en class-support | -| Changes | event-level P/R/F1 per changeklasse | globale score mag een klasse niet maskeren | -| Continue hoogte | MAE, RMSE, bias | coverage, eenheid en foutverdeling | -| Validatie | anomaly-P/R/F1 | iedere gemiste blocker/critical anomaly blokkeert | - -Voor binomiale precision en recall rapporteert het harnas 95%-Wilsonintervallen. -Bij te weinig support blijft de subgroepgate `not_evaluable`; de supportreden -blijft afzonderlijk zichtbaar. Een breed interval of ontbrekende metric is geen -positief bewijs. Voor een toekomstige productbenchmark moet bij ruimtelijk -geclusterde observaties bovendien een vooraf vastgelegde AOI- of -clusterbootstrap worden gebruikt in plaats van pixels als onafhankelijke -steekproeven te behandelen. - -## Splitcontract en leakage-gates - -`scripts/generate_accuracy_phase4_splits.py` genereert twee afzonderlijke, -gehashte manifesten uit één versieerbare bron: - -- development: `train`, `val` en `calibration`; -- protected release only: immutable `test`, `background-test` en sealed - `challenge`. - -Iedere sample draagt minimaal taak, split, `sample_id`, ruimtelijke `group_id`, -`source_family`, `temporal_family`, acquisition- en parent-rasteridentiteit, -native feature- en object-ID's, bounding box, ruwe en verwerkte imagehash, -labelhash, perceptual imagehash, labelgeometriehash en een canonieke recordhash. -Bij automatische toewijzing worden gekoppelde records eerst als één component -gegroepeerd. De generator faalt wanneer: - -- een identiteit, object, bron-/tijdsfamilie, acquisition of parent-raster - meerdere splits raakt; -- exacte image-, label- of recordbytes meerdere splits raken; -- perceptuele of geometrische bijna-duplicaten meerdere splits raken; -- bounding boxes uit verschillende splits dichter liggen dan de vooraf - gedeclareerde onafhankelijkheidsbuffer; -- een verplichte split ontbreekt of een record niet valideerbaar is. - -Bronvolgorde heeft geen invloed op de bron- of splitmanifesthash. De huidige -fixture bevat 21 samples over alle zes normatieve rollen en gebruikt een buffer -van 2.000 meter. Zij kan alleen door een expliciete codeparameter als synthetische -fixture worden geopend en draagt altijd `production_accuracy_use_allowed=false`. -Productiemodus vereist een strikt P3-manifest, exact provenance-record, vier -toegankelijke assetpaden en herberekende bytes-hashes. Dit is dus geen bewijs dat -het historische Belgische corpus onafhankelijk is. De Phase-3-bevinding van 24 -cross-splitparen onder 2 km blijft blokkerend. - -## Bescherming van test en challenge - -De lokale workflow bindt evaluatie aan de exacte protected-manifesthash en -accepteert alleen de `test`- en `background-test`-ID's uit dat manifest. -Challengecases en -labels worden door de evaluator geweigerd. Configuraties zijn -vooraf vast. Per case bewaart `baseline-raw-predictions.json` de exacte -referenties, pre-filter- en post-filtervoorspellingen, configuratie en lineage. -`assert_training_inputs_safe()` en de twee echte trainingsdataset-builders -weigeren beschermde rollen, paden, inhoudshashes en alle relevante identiteit- -en lineagevelden. In productiemodus worden toegankelijke bronbytes en hun P3- -en provenancebinding opnieuw gecontroleerd; een padloos of hernoemd record faalt. -De regressietests bewijzen blokkering en een geldige development-run. - -Dit is logische bescherming in de repository. Fysieke isolatie met een -afzonderlijke vault, beperkte credentials en een immutable accesslog is in de -huidige projectomgeving niet bewezen. Daarom staat -`protected_storage_isolation` in de productgates op `not_evaluable`; de lokale -firewall mag niet als vervanging voor die productcontrole worden beschreven. - -## Stratificatie en failure-evidence - -Iedere beschermde case declareert waar relevant regio/gemeente, stedelijk of -landelijk karakter, objectgrootte, bron/sensor, resolutie, seizoen/datum, -vegetatie/occlusie, moeilijkheid en context. Het metricrapport groepeert die velden en -legt support expliciet vast. Kritieke subgroepen moeten vóór een echte baseline -worden vastgesteld; ontbrekende of te kleine groepen blokkeren een release. - -`baseline-raw-predictions.json` bewaart de ongesommeerde referenties, -pre-/postfiltervoorspellingen, matches, configuratie en lineage. -`failure-gallery.json` bewaart stabiele failure-ID's, taak, fouttype, strata en -concreet machineleesbaar bewijs. Een visuele gallery van echte productbeelden -kan pas worden gemaakt wanneer de beschermde imagery rechtmatig en gecontroleerd -bereikbaar is. - -## Reproduceerbaarheid - -Het benchmarkmanifest bindt repositorycommit, evaluator- en workflowversie, -alle drie Phase-4-scripts, de echte QA-service, bronfixtures, protected cases, -golden QA-fixture, Phase-3-manifesten, bronmatrix, metriekcontract, runtime en -beide splitmanifesten met SHA-256. Uit `status.json` wordt uitsluitend de -gate-relevante `/runtime/active_model`-projectie canoniek gehasht. Administratieve -velden zoals `generated_at`, Phase-4/5-status, documenten en evidence-run-ID's -zijn bewust geen benchmarkinput: zo kan het schrijven van de evidenceledger niet -zijn eigen runfingerprint veranderen. Review-, authority-, leakage-, vault- en -subgroepgates kunnen daardoor niet uit losse statusvelden slagen; zij vereisen -checksumgebonden product- en Phase-3-evidence. Een productbaseline wordt alleen -geaccepteerd wanneer dezelfde evaluator alle zeven taakfamilies in-process -herberekent en exact overeenkomt met checksumgebonden raw-, review-, authority-, -leakage-, vault- en CUDA-evidence. Dynamische UUID's uit de QA-service worden uit -de canonieke referentiescore verwijderd. Iedere run krijgt een content-addressed -ID; twee gelijke uitvoeringen leveren byte-identieke inhoud op en onverwachte -bestanden of submappen maken de immutable bundle ongeldig. - -```powershell -python scripts/run_accuracy_phase4_benchmark.py --allow-product-blocked -python -m pytest backend/tests/test_accuracy_phase4_evaluation.py backend/tests/test_accuracy_phase4_evaluator_hardening.py backend/tests/test_accuracy_phase4_split_hardening.py -q -p no:cacheprovider -python -m ruff check scripts/accuracy_phase4_evaluator.py scripts/generate_accuracy_phase4_splits.py scripts/run_accuracy_phase4_benchmark.py backend/tests/test_accuracy_phase4_evaluation.py backend/tests/test_accuracy_phase4_evaluator_hardening.py backend/tests/test_accuracy_phase4_split_hardening.py -``` - -De machineleesbare bewijsset staat onder -`artifacts/evidence/accuracy/P4/runs/p4-2.0.1-9677d0ef37db82bcf39b/`. De -actuele fasebeslissing staat in `12-release-gates.md` en `status.json`. diff --git a/docs/accuracy-program/11-baseline-benchmark.md b/docs/accuracy-program/11-baseline-benchmark.md deleted file mode 100644 index 62ce1466..00000000 --- a/docs/accuracy-program/11-baseline-benchmark.md +++ /dev/null @@ -1,124 +0,0 @@ -# Fase 4 — Baselinebenchmark - -## Beslissing - -Het lokale evaluatieharnas is reproduceerbaar en groen. Een betrouwbare -baseline van het actieve GeoIntel-productiemodel is in deze omgeving niet -uitvoerbaar. De productbenchmark is `fail` door de bevestigde Phase-3-leakage; -andere productgates blijven `not_evaluable` zonder governed bewijs. Er wordt -daarom geen productie-accuracy-, België-brede of promotieclaim afgeleid. - -| Statusveld | Waarde | -| --- | --- | -| Benchmark-ID | `geointel-p4-reference-harness-v2` | -| Lokale harnasstatus | `pass` | -| Productbenchmark | `fail` | -| Promotie toegestaan | `false` | -| Phase 4 done | `false` | -| Phase 5 ready | `false` | - -## Referentie-implementatie als nulmeting - -De bestaande productiecode in `backend/app/services/qa_service.py` is via -`scripts/run_golden_qa_benchmark.py` uitgevoerd op vier bevroren golden -QA-scenario's. De dynamische service-UUID wordt niet meegenomen in de -canonieke inhoudshash. - -| Golden scenario | Precision | Recall | F1 | Mean matched IoU | -| --- | ---: | ---: | ---: | ---: | -| Partial match | 0,50 | 0,50 | 0,50 | 0,8339768339652592 | -| Perfect match | 1,00 | 1,00 | 1,00 | 1,00 | -| No overlap | 0,00 | 0,00 | `null` | `null` | -| Multipolygon match | 1,00 | 1,00 | 1,00 | 1,00 | - -De canonieke referentiehash is -`aeb0f6510352f4e205e4fc4e8c423110ca72c2142016c7af846d758865f258c6`. -Dit bewijst de rekenkundige regressiestabiliteit van de QA-service, niet de -kwaliteit van een detector of segmentatiemodel. - -## Multi-task evaluatorbaseline - -Negen synthetische, deterministische `test`/`background-test`-cases oefenen -zeven evaluatorfamilies en 15 concrete capabilityrecords uit. De gecombineerde -resultaathash is -`55cdba9cce4dcdc88cee0829cd510d7e624a3472feb9d33f7e681621a792eba3`. -De cases zijn bewust klein; hun scores testen formules, null-semantiek, -raw-retentie, stratificatie en foutclassificatie, niet productkwaliteit. - -| Familie | Voornaamste fixture-uitkomst | Claimgrens | -| --- | --- | --- | -| Objectdetectie | P 0,667; R 1,000; F1 0,800; AP50 1,000; AP50–95 0,901 | formule-/harnastest | -| Footprintsegmentatie | mean IoU 0,799; Dice 0,888; boundary F1 1,000 | formule-/harnastest | -| Categorisch raster | accuracy 0,833; macro F1 0,822; mean IoU 0,722 | metriekcontract, geen geleerd rastermodel | -| Vectorvergelijking | P/R/F1 0,500; mean matched IoU 1,000 | formule-/harnastest | -| Change detection | globale P/R/F1 0,500; afzonderlijke added/removed metrics | eventclassificatie zichtbaar | -| Terrein | MAE 0,275 m TAW; RMSE 0,287 m TAW; coverage 0,800 | eenheids-/coveragecontract | -| Datavalidatie | P/R/F1 0,667; één critical miss | fail-closed anomaliecontract | - -Alle subgroepen hebben in deze kleine fixture onvoldoende statistische support. -Hun `release_gate_status` is daarom `not_evaluable`, met de supportreden apart -geregistreerd; geen gemiddelde kan dit omzetten in releasebewijs. De -95%-Wilsonintervallen zijn overeenkomstig breed. - -## Ruwe voorspellingen en fouten - -De workflow bewaart exacte referenties, pre-/postfiltervoorspellingen, -configuratie en lineage vóór iedere samenvatting. De failure gallery bevat 14 -deterministische voorbeelden, waaronder FP/FN, boundary- en area-bias, -rastermisclassificatie, calibratie en een gemiste critical-validatieafwijking. -De failure-ID's zijn inhoudsgebonden en kunnen in regressietests worden -hergebruikt. - -Relevante evidence: - -- `baseline-raw-predictions.json` — exacte raw referenties, pre-/postfilteroutputs, config en lineage; -- `metric-report.json` — taak- en subgroepmetingen met support en intervallen; -- `failure-gallery.json` — machineleesbare fouttaxonomie en voorbeelden; -- `reference-implementation-baseline.json` — werkelijke QA-service-uitvoering; -- `benchmark-manifest.json` — alle input-, split-, code- en evaluatoridentiteiten. - -De canonieke benchmarkmanifesthash is -`0ea5ab07f46c509a7a24943b31d5e9bfd6368920609227bc47613e18e52c4642`; -de exacte bestandshash is -`868dd7eb2dfa8344e417879ed3f5dd7c7d9e5673add7e3e2294c5cbde4b75d57`. -Evidence-run `p4-2.0.1-9677d0ef37db82bcf39b` bindt uitvoerbare codecommit -`70fb4b94e5cb7c248beec5a936ce186f38cc183c`. De evidence-manifestbestandshash -is `fdc15a95ee2a0754dfa169f4b41036e084b8d8909afc37fd8ea68ee6b9210f98`; -de release-gatereportbestandshash is -`e5f1c9c43c8da22acfa5486e641c010a278431f90634f91335b039ab7bdb50a4`. -Deze hashes bewijzen reproduceerbaarheid en integriteit, niet productaccuracy. - -## Waarom de productbaseline niet uitvoerbaar is - -De productgates zijn bewijsgebonden en kunnen niet vanuit losse statusvelden -groen worden gemaakt: - -1. de actieve modelconfiguratie verwijst naar `/app/models/...pt`, die lokaal - niet als bestand beschikbaar is; -2. er is geen governed productmanifest met in-process herberekende raw evidence - voor alle zeven taakfamilies en een actueel CUDA/GPU-receipt; -3. een volledige GRB/PICC/UrbIS/DHMV/SPW/MDK-taak-/zoneportfolio ontbreekt; -4. een checksumgebonden reviewledger ontbreekt; historisch staat V56 op 0/180; -5. een productgebonden geometrische leakage-audit ontbreekt; historisch zijn er - 24 cross-splitparen onder 2 km; -6. de Phase-3-leakagestatus is bevestigd `attention` en dus `fail`; -7. vaultisolatie met hash-chained accesslog is niet bewezen; -8. representatieve support over alle 13 vereiste subgroupdimensies ontbreekt. - -Door de fail-first aggregatie maakt de bevestigde Phase-3-leakage de huidige -productbenchmark `fail`; ontbrekende productartefacten blijven afzonderlijk -`not_evaluable`. Geen van beide toestanden laat promotie toe. - -Daarnaast waren Tower-corpora, gemounte modelvolumes en de productie-PostGIS/API -in Phase 3 expliciet onbereikbaar. Het harnas verzint daarvoor geen vervangende -ground truth en gebruikt OSM niet automatisch als gezagsbron voor gebouwen. - -## Betekenis voor volgende training - -Test- en challenge-data mogen niet worden geopend voor training, -thresholdselectie, modelselectie of iteratieve foutcorrectie. Eerst moeten de -representatieve review, nieuwe onafhankelijke splits, lokale gezagsdata, -protected vault en een checksumbare incumbent-run beschikbaar zijn. Daarna -worden modelkeuzes op `val` en operating points op `calibration` vooraf -vastgelegd; pas vervolgens mag één immutable kandidaat de protected test en -background-test doorlopen. Challenge-labels blijven sealed. diff --git a/docs/accuracy-program/12-release-gates.md b/docs/accuracy-program/12-release-gates.md deleted file mode 100644 index 316b265b..00000000 --- a/docs/accuracy-program/12-release-gates.md +++ /dev/null @@ -1,109 +0,0 @@ -# Fase 4 — Releasegates - -## Gateprincipe - -GeoIntel gebruikt een conjunctieve, fail-closed beslissing: iedere verplichte -gate moet groen zijn. Een hogere gemiddelde score compenseert nooit een -ernstige regressie, ontbrekende support of een critical miss in een vereiste -regio, bron, context of taak. - -Er wordt in Phase 4 geen arbitrair hoog accuracydoel verzonnen. Numerieke -releasecriteria blijven `not_frozen_without_reviewed_representative_incumbent_baseline`. -Ze worden pas vastgesteld uit taakrisico, operationele productvereisten, -datakwaliteit en een representatieve, gereviewde incumbentbaseline, en altijd -vóór protected-testtoegang. - -## Lokale harnasgates - -De volgende controles zijn in `release-gate-report.json` groen: - -| Gate | Status | Bewijs | -| --- | --- | --- | -| Alle gedeclareerde taakfamilies | pass | zeven families en 15 capabilities gedeclareerd en geobserveerd | -| Split leakage | pass | zes code-owned rollen; exacte/near-duplicate/identity/2-km-gates groen voor de fixture | -| Training firewall | pass | protected path/role/lineage en padloze of gewijzigde bytes worden geweigerd | -| Geen protected modelselectie | pass | vooraf geregistreerde config; diagnostische curves selecteren niets | -| Ruwe voorspellingen | pass | exacte referenties, pre-/postfilteroutputs, config en lineage behouden | -| Referentie-implementatie | pass | vier golden cases via de echte `QaService` | -| Subgroepcontract | pass | alle 13 dimensies, support, CI en worst-stratum zichtbaar | -| Null-semantiek | pass | ongedefinieerd is `null`; promotion blijft uit | - -Deze gates bewijzen dat de evaluator zich lokaal correct gedraagt. Ze bewijzen -niet dat het productiemodel voldoet. -Een test-only governed-contractfixture met 70 cases bewijst dat de groene route -structureel bereikbaar is en dat tampering wordt geweigerd. De gemockte runtime -en handgemaakte cases zijn uitdrukkelijk geen productbewijs. - - -## Productgates - -De volgende actuele gates blokkeren Phase 4: - -| Gate | Status | Objectief bewijs | -| --- | --- | --- | -| Actief model bereikbaar en hashbaar | not_evaluable | geconfigureerd `/app/models`-asset is lokaal afwezig | -| Volledige gezagsportfolio | not_evaluable | geen governed GRB/PICC/UrbIS/DHMV/SPW/MDK-taak-/zonebewijs | -| Representatieve menselijke review | not_evaluable | geen checksumgebonden reviewledger; historisch 0/180 | -| Ruimtelijke split-onafhankelijkheid | not_evaluable | geen productgebonden geometrische audit; historisch 24 paren <2 km | -| Phase-3 leakage opgelost | fail | actuele status `attention` | -| Fysieke protected storage isolation | not_evaluable | geen vaultbewijs met hash-chained accesslog | -| Uitgevoerde product-incumbent | not_evaluable | geen model/raw/config/CUDA-gebonden productmanifest | -| Representatieve subgroup-support | not_evaluable | geen productmetrics over alle 13 dimensies | - -Door `fail > not_evaluable > pass` is de productbenchmarkstatus `fail`. Dat is -geen gemeten accuracy failure: de bevestigde leakagegate faalt en de overige -productmetingen zijn nog niet evalueerbaar. `promotion_allowed` blijft `false`. - -## Toekomstige numerieke gatefreeze - -Een latere gatefreeze moet per taak minimaal vastleggen: - -- exacte model-, evaluator-, preprocessing-, bron- en splitmanifesthashes; -- klasse- en matchbeleid, operating threshold en NMS-configuratie; -- globale primaire metric met betrouwbaarheidsinterval; -- vereiste regio-, gemeente-, stedelijkheids-, objectgrootte-, bron-, sensor-, - resolutie-, seizoen-, datum-, vegetatie-, occlusie-, moeilijkheids- en - contextsubgroepen; -- minimale onafhankelijke AOI-/objectsupport per groep; -- non-inferioritymarge tegenover de incumbent; -- harde maxima voor kritieke false negatives, false positives, - topologiefouten en calibration error; -- abstention/coverage-regel voor onzekere gevallen; -- runtime-, GPU-, latency- en resourcecontract waar operationeel relevant. - -Een releasebeslissing is alleen positief wanneer zowel de globale gate als -iedere kritieke subgroepgate groen is. `insufficient_support`, `null`, een -ontbrekende groep, ongeldige lineage, een checksumverschil of een gemiste -blocker/critical anomaly blokkeert. - -## Beschermde evaluatievolgorde - -1. Herstel of excludeer Phase-3-quarantine-items traceerbaar. -2. Laat representatieve labels menselijk beoordelen en freeze een nieuwe - corpusversie; wijzig V56 niet in place. -3. Genereer onafhankelijke `train`, `val`, `calibration`, `test`, - `background-test` en sealed `challenge`-manifesten; laat alle leakage-gates - slagen. -4. Plaats test/background-test en externe challenge-labels in een afzonderlijke - vault met beperkte credentials en hash-chained immutable accesslog. -5. Voer de incumbent uit en freeze targets op `val`, operating points op - `calibration` en operationele vereisten vóór protected toegang. -6. Train uitsluitend op `train`; selecteer checkpoints alleen op `val`. -7. Pre-registreer één immutable kandidaat en open `test` en `background-test` - één keer; challenge-labels blijven sealed. -8. Bewaar raw predictions, herbereken paired/subgroepmetrics in-process en neem - één fail-closed releasebeslissing. -9. Gebruik protected resultaten nooit als feedback voor dezelfde kandidaat- of - trainingsfamilie. - -## Actuele fasebeslissing - -Phase 4 blijft `in_progress`: het reproduceerbare lokale harnas is klaar, maar -de echte protected productbaseline kan nog niet geldig worden uitgevoerd. -Phase 5 blijft `not_ready`. Deze status verandert pas wanneer alle productgates -in dezelfde checksumbare workflow groen zijn; documentatie of fixture-scores -kunnen die voorwaarde niet omzeilen. - -Normatieve evidence-run: `p4-2.0.1-9677d0ef37db82bcf39b`, gebonden aan -codecommit `70fb4b94e5cb7c248beec5a936ce186f38cc183c` en canonieke -benchmarkmanifesthash `0ea5ab07f46c509a7a24943b31d5e9bfd6368920609227bc47613e18e52c4642`. diff --git a/docs/accuracy-program/13-nested-mirror-retirement.md b/docs/accuracy-program/13-nested-mirror-retirement.md deleted file mode 100644 index 2d9fb591..00000000 --- a/docs/accuracy-program/13-nested-mirror-retirement.md +++ /dev/null @@ -1,33 +0,0 @@ -# Retirement of the tracked `geointel/` mirror - -## Decision - -The repository root is the only canonical GeoIntel source tree. The stale, -tracked copy below `geointel/` was removed during the full-platform remediation -because it duplicated backend, frontend, scripts, tests and documentation and -could make local tools inspect or execute the wrong implementation. - -## Recovery evidence - -- Source commit: `d39816a4ca1a23a7b90bcf01e5f2b01fd5fb57c4`. -- Source tree object: `b66d5987f7e2b1f8180acd3b4c768586993c7d5a`. -- Tracked files: `1,153`. -- The two mirror-only PNG assets remain recoverable from that immutable Git - commit; the canonical frontend already contains the current SVG/PNG/WebP - icon and wordmark assets used by the application. -- Recovery command, if historical inspection is required: - `git restore --source d39816a4ca1a23a7b90bcf01e5f2b01fd5fb57c4 -- geointel`. - -The migration deletes no production data, model weights, source datasets or -runtime storage. After the tracked mirror was retired, 207 untracked runtime -files (about 0.04 GiB) remained below that directory. They were moved intact, -without content rewriting, to the ignored recovery directory -`.codex-artifacts/retired-nested-runtime-20260830/`. Nothing from that recovery -directory is packaged or deployed. Docker already excluded the former mirror, -so production runtime paths remain unchanged. - -## Prevention gate - -`python scripts/verify_repository_layout.py` fails when canonical source -markers appear under a new nested `geointel/` directory. The release-readiness -workflow runs this check so repository ambiguity cannot silently return. diff --git a/docs/accuracy-program/13-v73-flanders-remediation.md b/docs/accuracy-program/13-v73-flanders-remediation.md deleted file mode 100644 index 2d23b1c2..00000000 --- a/docs/accuracy-program/13-v73-flanders-remediation.md +++ /dev/null @@ -1,60 +0,0 @@ -# V73 Vlaamse foutremediatie - -## Uitkomst - -V73 heeft de datadekking aantoonbaar verbreed, maar geen beter productiemodel -opgeleverd. Daarom blijft het actieve model ongewijzigd. Dit is een geslaagde -fail-closed beslissing: twee nieuw getrainde GPU-kandidaten zijn afgewezen op -de vooraf bevroren en ruimtelijk onafhankelijke V72-calibratieportfolio. - -## Nieuwe dekking - -- twaalf nieuwe Vlaamse train-only AOI's; -- woonwijken, lintbebouwing, landelijke kernen, industrie, haven, bos, duinen - en landbouwcontext; -- officiële orthofoto en GRB als primaire gebouwreferentie; -- 48 canonieke niet-overlappende tegels met 1.710 labels; -- drie lege tegels en meerdere moeilijke, dun bebouwde contexten; -- minimale afstand tot een V72-calibratie-AOI: 9.203 meter, tegenover de gate - van 2.000 meter. - -De oorspronkelijke Maaseik-grensselectie werd door de provider terecht -geweigerd wegens nuldekking binnen de Vlaamse orthofotozone. De gecheckpointte -acquisitie is hervat met een vooraf geregistreerde inlandse vervanging in Peer. - -## Visuele controle - -Alle 48 uiteindelijke tegels zijn via twee contact sheets gecontroleerd. De -eerste export maakte een bestaande edge-coverzwakte zichtbaar: rasters die iets -groter dan 1024 pixels waren, leverden vrijwel identieke tegels op de laatste -pixeloffset. Zestig zulke overlappende tegels zijn vóór training verwijderd en -de nieuwe experimentele exporter bevat hiervoor een regressiegate. - -De controle is AI-assisted en dus expliciet geen vervanging voor de vereiste -onafhankelijke menselijke labelreview. Het corpus en de modellen blijven -daardoor niet-promoveerbaar. - -## GPU-resultaten - -| Model | Precision | Recall | mAP50 | mAP50-95 | Besluit | -|---|---:|---:|---:|---:|---| -| Actief | 0,1577 | 0,1178 | 0,0568 | 0,0218 | behouden | -| V73 agressief, 20 epochs | 0,0124 | 0,2557 | 0,0189 | 0,0038 | afgewezen | -| V73 gecontroleerd, 10 epochs | 0,0179 | 0,3247 | 0,0222 | 0,0057 | afgewezen | - -Beide kandidaten verhogen recall maar produceren veel te veel foutpositieven. -Een drempel- of gemiddelde-scoretruc rechtvaardigt hier geen promotie: precision -en beide mAP-maten regresseren ernstig. - -## Conclusie en resterende grens - -De huidige detector is nog niet nauwkeurig genoeg om landelijke, regionale of -"100% correcte" gebouwclaims te dragen. V73 voorkomt wel dat een slechter model -in productie komt en levert nieuwe, herleidbare foutdekking voor een latere -training. Voor een echte volgende kwaliteitsstap zijn minimaal een grotere -onafhankelijk menselijk beoordeelde trainset, meer pure-backgroundtegels en -governed PICC/UrbIS-contracten nodig. Tot dan moeten resultaten als -modelvoorstellen met bronvergelijking en onzekerheid worden gepresenteerd. - -Alle ruwe manifests, matrices, hashes en contact sheets staan onder -`artifacts/evidence/accuracy/model-training/20260810-v73-flanders-remediation/`. diff --git a/docs/accuracy-program/14-v74-root-cause-and-authority-first-results.md b/docs/accuracy-program/14-v74-root-cause-and-authority-first-results.md deleted file mode 100644 index c3115546..00000000 --- a/docs/accuracy-program/14-v74-root-cause-and-authority-first-results.md +++ /dev/null @@ -1,71 +0,0 @@ -# V74 foutoorzaak en authority-first resultaten - -## Uitkomst - -V74 heeft geen nieuw productiemodel opgeleverd. De actieve checkpoint blijft -ongewijzigd omdat zowel de experimentele proposal-filter als twee -rehearsal-kandidaten op de bevroren V72-calibratie slechter presteren. GeoIntel -presenteert de automatische gebouwanalyse daarom niet langer als één uniforme -resultaatlaag: de GRB-vergelijking maakt voortaan zichtbaar welke AI-kandidaten -officieel bevestigd zijn, welke alleen modelvoorstellen zijn en welke -GRB-gebouwen door AI gemist zijn. - -## Visuele foutanalyse - -De volledige V72-portfolio van 24 onafhankelijke tegels is met het actieve model -op confidence 0,30 gerenderd. De contact sheet toont terugkerende foutpositieven -op spoorlijnen, voertuigen, bomen, schaduwen en andere contrastrijke structuren. -Daarnaast ontbreken veel gebouwen. Dit ondersteunt de conclusie dat extra -epochs op alleen de nieuwe Vlaamse shard de hoofdoorzaak niet oplossen. - -De review is AI-assisted en niet menselijk. Het bewijs mag dus geen menselijke -acceptatie of promotiegate vervangen. - -## Afgewezen proposal-filter - -Een experimentele ResNet18-filter werd op afzonderlijke V73-AOI's getraind om -building proposals van moeilijke negatieve patches te onderscheiden. De interne -V73-validatie behaalde F1 0,8068, maar die score generaliseerde niet naar V72. -De beste globale V72-combinatie behaalde precision 0,2161, recall 0,2241 en F1 -0,2200. Het actieve model zonder filter behaalt op confidence 0,30 F1 0,2504. -De filter kan precision verhogen bij een vaste detectordrempel, maar halveert -dan de recall. Hij blijft daarom experimenteel en wordt niet geladen in -productie. - -## Afgewezen rehearsal-training - -De trainingsset combineert 180 historische trainingstegels met de 48 nieuwe -V73-tegels, waarbij V73 tweemaal voorkomt. V72 is alleen evaluatie en komt niet -in de fitdata voor. - -| Model | Precision | Recall | mAP50 | mAP50-95 | Besluit | -|---|---:|---:|---:|---:|---| -| Actief | 0,1577 | 0,1178 | 0,0568 | 0,0218 | behouden | -| Rehearsal, optimizer auto, 10 epochs | 0,0710 | 0,0776 | 0,0262 | 0,0098 | afgewezen | -| Rehearsal, AdamW 0,0001, 6 epochs | 0,0839 | 0,1034 | 0,0349 | 0,0136 | afgewezen | - -De eerste run bracht bovendien een reproduceerbaarheidsfout aan het licht: -Ultralytics `optimizer=auto` negeerde de gevraagde learning rate en koos AdamW -0,002. De wrapper bindt daarom nu expliciet `optimizer=AdamW` en legt dit vast -in het trainingsmanifest. De gecorrigeerde low-learning-rate-run bleef eveneens -onder de actieve baseline. - -## Productcorrectheid - -Voor actuele gebouwvalidatie in Vlaanderen is GRB de gezagsbron binnen de -beschikbare editie en dekking. De kaartwerkstroom laadt na detectie automatisch -het bewaarde QA-bewijs en toont afzonderlijk: - -- GRB-bevestigde AI-kandidaten; -- AI-only, onbevestigde onderzoeksvoorstellen; -- officiële GRB-gebouwen die het model miste. - -AI-only voorstellen worden niet als officiële gebouwen voorgesteld. Dit maakt -de productuitvoer aantoonbaar correcter zonder de zwakke modelscore te verbergen -of een niet-bewezen nauwkeurigheidsclaim te maken. - -## Evidence - -Alle ruwe contact sheets, foutmanifesten, filtermatrices, trainingssamenvattingen -en modelhashes staan onder -`artifacts/evidence/accuracy/model-training/20260810-v74-root-cause/`. diff --git a/docs/accuracy-program/15-runtime-model-provenance-remediation.md b/docs/accuracy-program/15-runtime-model-provenance-remediation.md deleted file mode 100644 index 7668cb23..00000000 --- a/docs/accuracy-program/15-runtime-model-provenance-remediation.md +++ /dev/null @@ -1,39 +0,0 @@ -# Runtime model provenance remediation — 2026-08-23 - -## Outcome and claim boundary - -The active detection checkpoint can receive a truthful narrow runtime sidecar -because its surviving training artifacts now establish an exact byte chain. -This remediation binds model bytes, retained checkpoint, base model, dataset -contract inputs and the surviving Ultralytics training receipts. It does not -retroactively assert a missing historical code commit/container, signed human -review, protected-test independence, national validity or a new promotion. - -## Recovered immutable evidence - -| Artifact | SHA-256 | -|---|---| -| active model and retained `best.pt` | `a9088b8491dfae36694b53e9e9406cb4e3511d334a5712fa34f75078a47759c1` | -| base model | `a8a79cf5b0bdc19a0245acc322cf77232c335e222bd5f3c00a17d5f29402c196` | -| training `args.yaml` | `2b482e6bbef26f433d4406e1acb5cbbf4ce63a63644b180a2d51b93f8c8f0dcb` | -| training `results.csv` | `6f83fdea2c59cfc5f3e4fe9673494e073c4e0054980b3020bad0289d0118b777` | -| training summary | `6d438308c923f50d885dc777d381f469fa215a0557f0f3e9d3facc2f75ce0b8e` | -| dataset YAML | `3a2ea97c35a18072a1ab6738cd673c0ecec5344b19461c91d72a15e138d46e8d` | -| dataset summary | `49b2a07d2105d08356431757b83eafc1498eaf1fb76965b1efe05b776824942a` | - -The checkpoint embeds an Ultralytics detection task, class mapping -`0: building`, framework version `8.4.93`, 30 epochs, image size 640, seed 0 -and deterministic mode. The dataset summary retains 198 tiles, 180 training -tiles, 18 validation tiles and 58,820 labels. - -## Guarded migration - -`scripts/migrate_runtime_model_provenance.py` performs the migration. It fails -closed on any mismatched file or recorded checksum, is dry-run by default, -writes the sidecar atomically and reuses only an identical immutable database -snapshot. The production check then validates the sidecar against the -server-owned `model` registry and snapshot before model loading. - -The operational source version is -`sprint174-20260713-smallbld-minpx3-img640-ft30`. This is a recovered runtime -artifact identity, not an accuracy or release-level claim. diff --git a/docs/accuracy-program/status.json b/docs/accuracy-program/status.json deleted file mode 100644 index b77b56a4..00000000 --- a/docs/accuracy-program/status.json +++ /dev/null @@ -1,422 +0,0 @@ -{ - "schema_version": 1, - "program": "GeoIntel Accuracy Improvement Program", - "phase": "P4", - "generated_at": "2026-08-30T05:58:29+02:00", - "scope": { - "product": "Belgium and the Belgian North Sea", - "active_building_model_claim": "Mol/Kempen only, operator review required", - "national_building_validation": false, - "result_authority_policy": "Task-appropriate official sources remain decisive for product results; AI output is a reviewable proposal unless a governed task-specific release gate proves otherwise." - }, - "baseline": { - "branch": "codex/geointel-accuracy-program", - "repository_commit": "0c019bb22f816db1e4b7a68379bcad08924d9a21", - "database_migration_head": "202607260001", - "phase2_migration_revision": "202608010001", - "phase2_migration_live_disposable_verified": true, - "phase2_migration_production_deployed": false, - "phase1_mutation_scope": "audit tooling, tests, documentation and retained evidence only" - }, - "phase1": { - "status": "complete", - "meaning": "The forensic inventory, reproducible baseline, lineage assessment, risk register, metric contract, implementation roadmap and retained evidence exist.", - "does_not_mean": [ - "release ready", - "nationally validated", - "human-reviewed corpus", - "strictly independent protected test", - "calibrated confidence", - "fully trained" - ] - }, - "release": { - "status": "blocked", - "promotion_allowed": false, - "scope_widening_allowed": false, - "training_allowed_now": false, - "training_unlock_gate": "A corrected checksum-frozen corpus, independent splits, representative human acceptance and every applicable pre-registered training gate must pass before a new governed run.", - "activation_gate": "Activation requires the exact candidate key and model SHA-256 bound to a passing governed Phase-4/5 release-gate report and its benchmark-manifest SHA-256; a legacy diagnostic promotion report alone has no activation authority.", - "critical_risk_count": 8, - "high_risk_count": 17, - "medium_risk_count": 4 - }, - "phase2": { - "status": "in_progress", - "meaning": "The source/provenance foundation is implemented and verified in a disposable PostGIS environment; the full P2 roadmap and its training/release gates are not complete.", - "roadmap": "docs/accuracy-program/06-implementation-roadmap.md", - "first_work_package": "P2-00", - "required_order": [ - "P2-00", - "P2-01", - "P2-02", - "P2-03", - "P2-04", - "P2-05", - "P2-06", - "P2-07", - "P2-08", - "P2-09", - "P2-10", - "P2-11", - "P2-12" - ], - "protected_test_rule": "Open exactly once for a pre-registered immutable candidate after all pre-test gates pass; never feed its results back into that candidate family." - }, - "phase2_source_provenance": { - "status": "implemented_and_verified_in_disposable_environment", - "evidence_root": "artifacts/evidence/accuracy/P2", - "implemented": [ - "server-owned source registry and immutable source snapshots", - "versioned vector, raster, label and PyTorch model contracts", - "checksum-bound dataset and dataset-version provenance", - "lineage graph, quarantine propagation and consumption gates", - "live disposable PostGIS upgrade, guard and downgrade verification" - ], - "does_not_mean": [ - "all legacy records are provenance complete", - "physical quarantine or protected-test storage isolation is proven", - "every UI result has end-to-end provenance rendering evidence", - "the full P2 roadmap is complete", - "training, promotion or national validation is allowed" - ] - }, - "phase3": { - "status": "local_complete_production_inventory_pending", - "meaning": "All 1013 safe local files in the configured GeoIntel roots were scanned read-only; three declared external production boundaries were recorded explicitly and still require a controlled server-side inventory.", - "scanner": "scripts/run_accuracy_phase3_full_data_scan.py", - "scanner_version": "3.1.0", - "scan_id": "p3-eb67185e61107cc7", - "evidence_root": "artifacts/evidence/accuracy/P3", - "content_hash": "f4ea193d2bdd96a5b391cf7d9d93685cc58e98742c40e4513bcbc434907e720a", - "reconciliation": { - "examined": 1013, - "skipped": 0, - "unreachable": 3, - "inventory_total": 1016, - "reconciles": true - }, - "anomaly_count": 711, - "quarantine_item_count": 682, - "does_not_mean": [ - "the total production inventory is complete", - "all anomalies are repaired", - "AOI split independence is proven", - "GRB ground truth is locally available", - "training, promotion or national validation is allowed" - ] - }, - "phase4": { - "status": "in_progress", - "meaning": "The content-addressed local evaluation harness passes, but the governed product benchmark fails on confirmed Phase-3 leakage and remains not evaluable for missing product evidence.", - "workflow": "scripts/run_accuracy_phase4_benchmark.py", - "workflow_version": "2.0.1", - "evaluator_version": "2.1.0", - "split_generator_version": "1.3.0", - "local_harness_status": "pass", - "product_benchmark_status": "fail", - "phase4_done": false, - "evidence_run_id": "p4-2.0.1-9677d0ef37db82bcf39b", - "evidence_root": "artifacts/evidence/accuracy/P4/runs/p4-2.0.1-9677d0ef37db82bcf39b", - "repository_commit": "70fb4b94e5cb7c248beec5a936ce186f38cc183c", - "benchmark_manifest_sha256": "0ea5ab07f46c509a7a24943b31d5e9bfd6368920609227bc47613e18e52c4642", - "benchmark_file_sha256": "868dd7eb2dfa8344e417879ed3f5dd7c7d9e5673add7e3e2294c5cbde4b75d57", - "evidence_manifest_file_sha256": "fdc15a95ee2a0754dfa169f4b41036e084b8d8909afc37fd8ea68ee6b9210f98", - "release_gate_report_file_sha256": "e5f1c9c43c8da22acfa5486e641c010a278431f90634f91335b039ab7bdb50a4", - "product_gate_evidence_sha256": "c9f5e3de3ab6d64911f8807b26caa661ccf911a5fd6b995107edda2004836e0c", - "case_count": 9, - "task_family_count": 7, - "implemented_capability_count": 15, - "failure_example_count": 14, - "split_counts": { - "background-test": 2, - "calibration": 2, - "challenge": 4, - "test": 7, - "train": 3, - "val": 3 - }, - "blockers": [ - "configured active model bytes are not locally accessible", - "no governed seven-task product baseline manifest with current CUDA receipt exists", - "Phase-3 leakage status is attention and therefore a failing product gate", - "no checksum-bound representative human review ledger exists", - "no governed zero-under-2-km product split audit exists", - "no protected vault evidence with hash-chained access log exists", - "no complete task-zone authority portfolio exists", - "no representative support over all thirteen subgroup dimensions exists" - ], - "does_not_mean": [ - "Phase 4 is complete", - "production accuracy is measured", - "Phase 5 is ready", - "training or promotion is allowed" - ] - }, - "phase5": { - "status": "not_ready", - "meaning": "Phase 5 remains blocked until every governed Phase-4 product gate passes in the same checksum-bound workflow.", - "blocked_by": "phase4" - }, - "runtime": { - "cuda_available": true, - "device": "NVIDIA GeForce RTX 4080 SUPER", - "configured_device": "cuda:0", - "python": "3.11.2", - "torch": "2.11.0+cu128", - "cuda_runtime": "12.8", - "ultralytics": "8.4.99", - "active_model": { - "model_id": "yolo-configured", - "model_version": "", - "path": "/app/models/geointel-building-yolov8s-smallbld-minpx3-img640-ft30.pt", - "sha256": "a9088b8491dfae36694b53e9e9406cb4e3511d334a5712fa34f75078a47759c1", - "size_bytes": 22516074, - "validated_area_names": [ - "Mol", - "Kempen" - ], - "nationally_validated": false - }, - "gpu_smoke": { - "status": "passed", - "read_only": true, - "tile_crs": "EPSG:31370", - "tile_sha256": "134a9e86850c92c577c73bc6ee57a9df7d4c1c513ae6450263e800b6dd47b6ee", - "manifest_sha256": "6ab8a96bf2a1405e224932afb90255311a09bbeaed4e9a2fdcdf8b1bc2230abd", - "raw_detection_count": 17, - "inference_seconds": 0.8836944859940559, - "claim_boundary": "Runtime execution only; no accuracy, calibration, generalization or release claim." - } - }, - "database": { - "mode": "read_only_audit", - "storage_references_checked": 5816, - "storage_references_missing": 0, - "table_counts": { - "projects": 1097, - "areas": 387, - "datasets": 3377, - "dataset_versions": 1671, - "vector_features": 6689447, - "analysis_runs": 1146, - "detections": 299233, - "segmentations": 0, - "detection_reviews": 0, - "quality_checks": 697, - "metrics": 4182, - "jobs": 4460, - "exports": 768, - "aoi_operations": 4, - "aoi_operation_partitions": 61 - }, - "lineage_gaps": { - "datasets_missing_observed_at": 2377, - "datasets_missing_source_version": 1761, - "detection_runs_with_empty_model_version": 1146, - "detections_with_empty_model_version": 299233, - "detection_runs_missing_model_hash": 3, - "detection_runs_missing_tile_manifest_hash": 1146 - }, - "geometry": { - "areas_invalid_or_wrong_srid": 0, - "vector_features_invalid_or_wrong_srid": 0, - "detections_outside_epsg4326_domain": 4, - "outside_domain_interpretation": "Four Geel detections contain Lambert-domain coordinates while persisted under SRID 4326." - } - }, - "ml_data": { - "model_asset_count": 26, - "training_checkpoint_count": 229, - "training_json_report_count": 424, - "operator_manifest_count": 36, - "v56": { - "sample_count": 180, - "reviewed_sample_count": 0, - "review_complete": false, - "input_feature_count": 31452, - "accepted_feature_count": 30662, - "below_resolvable_pixel_size": 326, - "created_after_imagery_period": 464, - "pure_empty_background_count": 3, - "pure_empty_background_by_region": { - "flanders": 2, - "wallonia": 1, - "brussels": 0 - }, - "minimum_cross_split_aoi_distance_m": 95.72033647650719, - "cross_split_pairs_below_2000_m": 24, - "exact_cross_split_raster_hash_duplicates": 0, - "perceptual_pairs_hamming_at_or_below_4": 0, - "split_independence_proven": false - }, - "candidate_evidence": { - "v58_v62_kind": "calibration-only tile-level bbox metrics", - "threshold_0_15_aggregate_f1": 0.512905360688286, - "threshold_0_15_flanders_recall": 0.0, - "protected_test_evidence": false, - "background_test_release_evidence": false, - "promotion_evidence": false - }, - "protected_test_isolation": false, - "human_label_acceptance": false, - "latest_independent_ai_visual_review": { - "review_id": "20260830-independent-ai-visual-review", - "evidence": "artifacts/evidence/accuracy/model-training/20260830-independent-ai-visual-review.json", - "human_reviewer": false, - "corpus_accepted": false, - "training_gate": "blocked", - "promotion_allowed": false, - "claim_boundary": "Independent AI visual inspection is triage evidence only; it is not representative human acceptance, protected-test evidence or an accuracy measurement." - } - }, - "verification": { - "backend_full_suite": { - "status": "passed", - "passed": 1702, - "skipped": 1, - "failed": 0, - "duration_seconds": 279.63, - "classification": "The complete canonical backend suite passes with deprecations promoted to errors. The single skip is the Windows-host symlink fixture; the symlink refusal path remains covered by static and Linux-targeted release checks." - }, - "backend_ci_entrypoint": { - "status": "passed", - "collected": 1703, - "result": "1702 passed, 1 skipped", - "note": "The canonical backend test import boundary, deployment contracts, guest analysis flow and governed raster handoff all collect and pass." - }, - "phase1_tooling_tests": { - "status": "passed", - "passed": 4 - }, - "new_phase1_code_ruff": { - "status": "passed" - }, - "repository_ruff": { - "status": "passed", - "finding_count": 0, - "note": "Repository-wide Ruff validation passes across backend, scripts and tests without policy weakening." - }, - "frontend_unit": { - "status": "passed", - "test_files": 40, - "tests": 170, - "command": "npm run test:unit" - }, - "frontend_typecheck": { - "status": "passed" - }, - "frontend_build": { - "status": "passed" - }, - "frontend_lint": { - "status": "missing", - "error": "npm run lint: Missing script" - }, - "openapi_contract": { - "status": "passed", - "implemented_routes": 155, - "explicit_non_envelope_endpoints": 12 - }, - "alembic": { - "status": "passed_offline_and_disposable_postgis", - "heads": [ - "202608230001" - ], - "offline_upgrade_rendered": true, - "offline_downgrade_rendered": true, - "live_migration_tested_locally": true, - "production_migration_deployed": false - }, - "phase2_source_provenance": { - "status": "passed_in_disposable_environment", - "source_registry_definitions": 40, - "migration_revision": "202608010001", - "migration_guards": "artifacts/evidence/accuracy/P2/postgres-migration-guards.json", - "static_inventory": "artifacts/evidence/accuracy/P2/source-contract-inventory.json", - "claim_boundary": "This is not a production migration deployment, corpus-release, accuracy or promotion result." - }, - "phase4_evaluation": { - "status": "local_pass_product_fail", - "targeted_tests": { - "passed": 60, - "duration_seconds": 22.28 - }, - "relevant_regression_tests": { - "passed": 103, - "duration_seconds": 27.61, - "shell_provider": "C:/Program Files/Git/bin/bash.exe", - "note": "The Windows Store WSL bash stub was unavailable; the same shell syntax test passed with the installed Git Bash provider." - }, - "ruff": "pass", - "format_check": "pass", - "compileall": "pass", - "python_typecheck": "not_configured", - "alembic_head": "202608010001", - "migration_and_provenance_tests": { - "passed": 29, - "duration_seconds": 5.73 - }, - "workflow_reproduction": { - "allow_product_blocked_exit": 0, - "default_exit": 2, - "byte_identical": true, - "status_bookkeeping_stable": true - }, - "claim_boundary": "Local harness and contract gates pass. Product accuracy is not measured; Phase-3 leakage fails and missing governed product evidence remains not evaluable." - }, - "golden_qa": { - "semantic_results_stable": true, - "byte_identical": false, - "reason": "UUID4-backed run identity" - } - }, - "reproduced_contract_violations": [ - "P1-COV-001", - "P1-CRS-001", - "P1-CRS-002", - "P1-AUTH-001", - "P1-AI-001", - "P1-COV-002", - "P1-API-001" - ], - "critical_blockers": [ - "ACC-R01", - "ACC-R02", - "ACC-R03", - "ACC-R04", - "ACC-R06", - "ACC-R09", - "ACC-R16", - "ACC-R17" - ], - "documents": [ - "docs/accuracy-program/00-execution-contract.md", - "docs/accuracy-program/01-system-inventory.md", - "docs/accuracy-program/02-data-lineage.md", - "docs/accuracy-program/03-baseline-and-gaps.md", - "docs/accuracy-program/04-risk-register.md", - "docs/accuracy-program/05-metric-framework.md", - "docs/accuracy-program/06-implementation-roadmap.md", - "docs/accuracy-program/07-source-authority-matrix.md", - "docs/accuracy-program/08-data-contracts.md", - "docs/accuracy-program/09-full-data-scan.md", - "docs/accuracy-program/10-evaluation-protocol.md", - "docs/accuracy-program/11-baseline-benchmark.md", - "docs/accuracy-program/12-release-gates.md", - "docs/accuracy-program/13-nested-mirror-retirement.md" - ], - "evidence_root": "artifacts/evidence/accuracy/P1", - "evidence_manifest": "artifacts/evidence/accuracy/P1/evidence-manifest.json", - "latest_verification_evidence_manifest": "artifacts/evidence/accuracy/P1/evidence-manifest-20260830-verification.json", - "phase2_evidence_root": "artifacts/evidence/accuracy/P2", - "phase2_evidence_manifest": "artifacts/evidence/accuracy/P2/evidence-manifest.json", - "phase3_evidence_root": "artifacts/evidence/accuracy/P3", - "phase3_manifest": "artifacts/evidence/accuracy/P3/full-scan-manifest.json", - "phase4_evidence_root": "artifacts/evidence/accuracy/P4/runs/p4-2.0.1-9677d0ef37db82bcf39b", - "phase4_evidence_manifest": "artifacts/evidence/accuracy/P4/runs/p4-2.0.1-9677d0ef37db82bcf39b/evidence-manifest.json", - "phase4_benchmark_manifest": "artifacts/evidence/accuracy/P4/runs/p4-2.0.1-9677d0ef37db82bcf39b/benchmark-manifest.json", - "phase4_release_gate_report": "artifacts/evidence/accuracy/P4/runs/p4-2.0.1-9677d0ef37db82bcf39b/release-gate-report.json", - "phase4_metric_report": "artifacts/evidence/accuracy/P4/runs/p4-2.0.1-9677d0ef37db82bcf39b/metric-report.json", - "phase4_failure_gallery": "artifacts/evidence/accuracy/P4/runs/p4-2.0.1-9677d0ef37db82bcf39b/failure-gallery.json" -} diff --git a/docs/reviews/2026-07-15-reviewed-accuracy-challenger.md b/docs/reviews/2026-07-15-reviewed-accuracy-challenger.md deleted file mode 100644 index 9ab65b29..00000000 --- a/docs/reviews/2026-07-15-reviewed-accuracy-challenger.md +++ /dev/null @@ -1,77 +0,0 @@ -# Reviewed accuracy challenger - 2026-07-15 - -## Scope - -This pass closes the evidence requirement from the preceding FP/FN review. It -adds complete, training-only orthophoto/GRB AOIs outside all protected -operational holdouts, trains one inactive local challenger and compares both -models through the current persisted GeoIntel workflow. No model was -downloaded and the active runtime configuration was not changed. - -- Active model: `geointel-building-yolov8s-smallbld-minpx3-img640-ft30-pt` -- Active SHA256: `a9088b8491dfae36694b53e9e9406cb4e3511d334a5712fa34f75078a47759c1` -- Challenger: `geointel-building-yolov8s-reviewedexp6-minpx3-img640-ft20-pt` -- Challenger SHA256: `038f1f97a6afd534f29e1f392a730a58207b928ca01e31ab8d8fed6106705820` -- Fixed profile: tile `512`, overlap `64`, confidence `0.15`, QA IoU `0.25` - -## Data and training - -Six new training-only centers were added in Arendonk, Dessel, Meerhout, -Laakdal, Nijlen and Hulshout. Every center is in its documented municipality, -uses a complete paged GRB GBG export and remains at least 2 km from every -protected positive holdout. - -- New GRB references: 9,964 features -- Corpus: 252 tiles, 234 positive and 18 negative -- Split: 234 training and 18 validation tiles -- Labels: 79,192 -- Dataset audit: `ok`, zero invalid or missing labels -- Visual audit: 64 tiles across 28 retained sources, zero invalid or - low-variance selections -- Fine-tuning: 20 CPU epochs from the active local model, image size `640` -- Best checkpoint: epoch 16, validation precision `0.700`, recall `0.406`, - mAP50 `0.369`, mAP50-95 `0.159` - -## Coverage-aligned result - -Both assets were rerun after the current coverage-aware QA logic was deployed. -Each zone comparison uses the same evaluated reference population; older runs -with different edge coverage are not used for the decision. - -| Zone | Active F1 | Challenger F1 | Delta | -| --- | ---: | ---: | ---: | -| Mol Achterbos | 0.6694 | 0.6850 | +0.0156 | -| Mol Donk | 0.5894 | 0.6259 | +0.0365 | -| Mol Gompel | 0.6564 | 0.6694 | +0.0131 | -| Mol Postel | 0.4749 | 0.4753 | +0.0005 | -| Retie | 0.6325 | 0.6491 | +0.0166 | -| Turnhout | 0.5919 | 0.5988 | +0.0069 | -| Westerlo | 0.6336 | 0.6700 | +0.0364 | - -| Aggregate | Active | Challenger | -| --- | ---: | ---: | -| Mean precision | 0.6141 | 0.6251 | -| Mean recall | 0.6062 | 0.6293 | -| Mean F1 | 0.6069 | 0.6248 | -| Matches | 5,711 | 5,919 | -| False positives | 3,568 | 3,506 | -| False negatives | 3,416 | 3,208 | - -## Promotion decision - -| Pure-empty control | Active detections | Challenger detections | -| --- | ---: | ---: | -| Arendonk-heide | 0 | 0 | -| Lommel-heide | 0 | 0 | -| Postel-bos | 0 | 2 | - -Decision: **retain the active model**. The challenger improves every positive -zone but violates the zero-detection Postel-bos gate. The formal promotion -report therefore recommends the existing active key -`geointel-building-yolov8s-smallbld-minpx3-img640-ft30-pt|512|64|0.15`. -Positive-score gains do not override a failed fail-closed background control. - -Persistent evidence is stored below -`/app/storage/operator-data/model-review/reviewed-accuracy-expansion/` and -`/app/storage/operator-evidence/mol-operational-validation/`. Generated rasters, -weights and large evidence JSON files remain outside Git. diff --git a/docs/reviews/2026-07-15-small-building-model-review.md b/docs/reviews/2026-07-15-small-building-model-review.md deleted file mode 100644 index 03870fd9..00000000 --- a/docs/reviews/2026-07-15-small-building-model-review.md +++ /dev/null @@ -1,71 +0,0 @@ -# Small-building model review - 2026-07-15 - -## Scope - -This review uses persisted configured-YOLO detections, persisted GRB building -features and the exact orthophoto inference tiles from Geel, Herentals and -Turnhout. It does not infer labels from QA status alone and does not alter the -active model. - -- Model asset: `geointel-building-yolov8s-smallbld-minpx3-img640-ft30-pt` -- SHA256: `a9088b8491dfae36694b53e9e9406cb4e3511d334a5712fa34f75078a47759c1` -- Canonical QA method: candidate polygon versus GRB footprint IoU `0.25` -- False-positive cards reviewed: 48 -- False-negative cards reviewed: 48 -- False negatives outside persisted inference-tile coverage: 731, excluded - -Every card was checked against its orthophoto and the persisted candidate and -reference overlays. Geometric overlap diagnostics were used to distinguish a -model error from box/footprint or one-to-one matching effects. Ambiguous cards -remain excluded from training. - -## Decisions - -| Evidence | Confirmed model error | QA alignment | Reference gap/change | Uncertain/obscured | -| --- | ---: | ---: | ---: | ---: | -| False positive | 5 | 34 | 5 | 4 | -| False negative | 10 | 25 | 5 | 8 | -| Total | 15 | 59 | 10 | 12 | - -The dominant finding is not a model error. In 59 of 96 reviewed cards, a real -candidate and reference overlap but the canonical box-versus-footprint or -one-to-one assignment does not count that pair as a match. Those records must -not become positive or negative training labels. - -## Training-readiness audit - -The active tile corpus already uses Geel and Herentals as training sources and -keeps Turnhout excluded as an operation-level holdout. - -| Confirmed evidence | Geel | Herentals | Turnhout holdout | -| --- | ---: | ---: | ---: | -| False positive | 3 | 1 | 1 | -| False negative | 0 | 4 | 6 | - -- The four confirmed false negatives in Herentals already exist as GRB labels - in the current training source. Re-adding them would not add new ground - truth; it would only change sample weighting. -- Confirmed false-positive detections in Geel and Herentals occur on urban - source tiles that also contain valid GRB buildings. Treating those complete - tiles as empty hard negatives would create false negative labels. -- The seven confirmed errors in Turnhout remain holdout evidence and cannot be - used for training without invalidating the independent benchmark. - -Result: **0 novel, leakage-free training labels are available from this review -bundle.** A new fine-tuning run is therefore rejected. The active model and -confidence `0.15` remain unchanged. - -## Required next evidence before training - -1. Collect new training-only orthophoto AOIs outside all Mol/Turnhout/Retie/ - Westerlo operational holdouts. -2. Label the complete contents of each selected tile from an authoritative - reference snapshot; never label only the reviewed detection box. -3. Add enough independent confirmed small-building and true empty-background - examples to justify a separate candidate. -4. Keep the candidate inactive until it passes the same positive-AOI, - pure-empty-background and Mol holdout gates. - -The review CSVs, contact sheets and validator outputs remain under the -persistent operator-data mount and are intentionally not committed as generated -repository artifacts. diff --git a/docs/reviews/2026-08-09-ai-assisted-checkpoint-review.md b/docs/reviews/2026-08-09-ai-assisted-checkpoint-review.md deleted file mode 100644 index f3c23212..00000000 --- a/docs/reviews/2026-08-09-ai-assisted-checkpoint-review.md +++ /dev/null @@ -1,303 +0,0 @@ -# AI-assisted building checkpoint review — 2026-08-09 - -## Outcome - -GeoIntel still runs the proven active building checkpoint. A new 12-epoch GPU -fine-tune was rejected because it reduced mAP and introduced three detections -on pure-background validation tiles. A wider checkpoint comparison identified -the older `reviewedexp6` checkpoint as the strongest non-protected validation -challenger, but it was not promoted. - -The production runtime was verified healthy after the review with: - -- image `geointel-all-in-one:0209167cfd37-wip25e7de62cde9-ai`; -- active weights SHA-256 - `a9088b8491dfae36694b53e9e9406cb4e3511d334a5712fa34f75078a47759c1`; -- NVIDIA RTX 4080 SUPER inference; and -- the existing Kempen validation-scope enforcement. - -## Metric review - -The checkpoint matrix used only the 36-image non-protected validation split: -18 positive images and 18 declared pure-background images. The active model -measured mAP50 `0.345426` and mAP50-95 `0.140719`. The `reviewedexp6` -challenger measured `0.368177` and `0.155438` respectively. - -A later exact cross-tile reconstruction established that this 512 px corpus -uses stride 256. Across the full corpus, 74,113 interior label rows represent -34,082 unique reconstructed objects; 40,031 rows are overlap repetitions and -one object can occur four times. No reconstructed object crosses the -train/validation boundary, but the tile rows are not statistically independent. -The matrix therefore remains useful only for relative non-protected candidate -ranking. Its mAP values are not an independent object-level accuracy estimate -or a basis for narrow confidence claims. - -At confidence `0.25` and match IoU `0.25`, the active model measured F1 -`0.633058`; the challenger measured `0.642599`. Both produced zero detections -on the 18 pure-background validation tiles at this threshold. At confidence -`0.15`, however, the challenger still reproduces the two background detections -that blocked its July promotion. - -## Visual review - -The error sheets were inspected at original resolution. Green denotes a -matched prediction, red a false positive, magenta a false negative and yellow -the reference footprint. The challenger reduces missed-building pressure, -particularly in Westerlo, but dense Turnhout tiles still show extensive -low-IoU disagreement. - -A major part of that disagreement is not safely resolved by additional epochs: -the aerial image shows a roof while GRB GBG represents the building footprint -at ground level. Perspective, roof overhang and acquisition-date differences -can therefore shift visible roofs relative to the authoritative footprint. -These cases remain review candidates; they were not relabelled automatically. - -This is explicitly an AI-assisted inspection, not a signed human review. No -human-review gate or label-acceptance record was fabricated. - -## Fail-closed production decision - -The existing seven-zone API benchmark was started with the challenger at -confidence `0.25`, but the current provenance gate stopped it before model -loading. The historical checkpoint predates the required neighbouring -`.geointel-model.json` runtime manifest and its governed database snapshot. -That control was not bypassed and no production inference from the unbound -checkpoint was accepted. - -The challenger may only be reconsidered after its original training evidence -is migrated without invented lineage, followed by the same seven positive -zones and three pure-background controls. Until then, the active checkpoint is -the only safe production choice. - -Machine-readable hashes, metrics, paths and the exact decision are in -`artifacts/evidence/accuracy/model-training/20260809-v68-checkpoint-and-threshold-review.json`. - -## Provenance migration follow-up - -The original July training directory was audited after the threshold review. -It retains exact weights, Ultralytics arguments, result curves, dataset YAML, -dataset summary and a structural quality audit. This recovers useful facts, -including seed `0`, deterministic mode, the base-model hash and all dataset -counts. - -It does not retain the complete evidence required to construct a current -production sidecar truthfully. In particular, the exact training commit, -container digest, dependency/runtime receipt, immutable corpus and label -release manifests, independent split audit and accepted human-review ledger -are absent. The current review validator reproduces four failures: - -- `accepted_human_review_evidence_missing`; -- `review_audit_manifest_not_immutable`; -- `review_audit_spatial_leakage_not_ok`; and -- `review_complete_not_true`. - -No UUID, upstream checksum, historical runtime or reviewer decision was -invented. Consequently no runtime sidecar or database source snapshot was -created, and the challenger remains unavailable to production inference. The -full machine-readable audit is retained in -`artifacts/evidence/accuracy/model-training/20260809-reviewedexp6-provenance-migration-audit.json`. - -## Completed AI-assisted AOI ledger - -At the user's explicit request, the existing 64-tile contact sheet was -reviewed again at original resolution and recorded as AI-assisted evidence. -The sheet represents 28 AOIs and renders 21,611 labels. Twenty-six represented -training AOIs were classified as eligible for experimental training; -Grobbendonk and Vosselaar remain non-protected validation only. Lommel-heide -and Postel-bos were visually retained as pure-empty examples, while six sparse -contexts remain explicitly distinct from pure background. - -The ledger identifies `openai-codex` as an AI assistant and sets `human=false`. -It explicitly cannot satisfy the human-review release gate. The production -training wrapper reproduced that boundary and no bypass was added. The exact -ledger is retained in -`artifacts/evidence/accuracy/model-training/20260809-reviewedexp6-ai-assisted-review-ledger.json`. - -The renderer was subsequently paginated and the review expanded from the -64-tile sample to all 252 retained tiles. Four immutable pages now account for -all 79,192 labels with zero missing images, missing label files, invalid rows -or low-variance tiles. No exact or IoU>=0.90 duplicate box pair was found. A -separate containment probe identified 43 potentially nested pairs across 36 -tiles (0.0543% relative to rendered labels); these remain human-adjudication -candidates and were neither rewritten nor automatically excluded. - -The 36 flagged tiles were then rendered on a separate high-resolution sheet. -AI-assisted inspection found no systematic duplicate-label pattern: the -relationships predominantly represent adjacent or complex building components -in dense GRB contexts. All tiles remain available for experimental analysis, -while the exact 43 pairs stay visible for human release adjudication. - -A second focused render now binds the relationship manifest back to the exact -YOLO label-row indices. It highlights all 86 implicated rows: cyan for exact -duplicates, red for near duplicates and magenta for possible nesting. The sheet -contains only magenta relationship marks, confirming visually and -machine-readably that there are no exact or high-IoU duplicates in this set. -The nesting cases are geographically dispersed and commonly combine a larger -GRB object envelope with a smaller component. They are not deterministic -rewrite candidates. Excluding the 36 complete tiles would also discard 17,167 -unflagged labels, so no automatic tile exclusion or label mutation was made. -The checksum-bound highlighted sheet and summary are recorded in the AI review -ledger. - -## Row-level geometry and overlap follow-up - -The complete 79,192-label corpus was additionally audited at label-row level. -The immutable manifest identifies 6,657 unique rows with at least one geometric -training-risk signal: 1,812 rows have a width or height below 4 pixels, 26 have -aspect ratio at least 8 and 5,079 touch a tile edge. The categories were -rendered separately. All 23 extreme-aspect tiles and all 198 small-dimension -tiles were inspected, plus a 64-tile edge sample. - -The extreme-aspect group predominantly shows plausible elongated sheds and -building components. Sixteen of its 26 rows are also below 4 pixels, allowing -the resolution floor to address most ambiguous extremes without deleting valid -long structures. The small-dimension sheets contain many visually marginal -miniature targets. The next immutable experimental corpus should therefore use -the exporter's normal minimum dimension of at least 4 pixels instead of this -legacy corpus's 3-pixel override. This finding does not justify mutating the -frozen corpus or retroactively changing its checkpoint. - -The edge sample shows expected clipped buildings under the 0.35 minimum-visible -policy. Raising that value may reduce partial-target pressure, but it must be a -separately versioned ablation because removing all 5,079 rows without checking -the original visible fraction would be unsound. - -## Derived min-4px experimental corpus - -The row-level finding was converted into a new immutable derived corpus rather -than changing the historical dataset. The derivation is checksum-bound to the -79,192-label source summary and removes only labels whose smallest 512-tile -dimension is below 4 pixels. It retains all 252 tiles and 77,380 labels; no -positive tile became empty, and no source file was overwritten. - -Fresh audits report zero sub-4-pixel labels, zero invalid or missing label -files, zero exact/high-IoU duplicates and zero reconstructed cross-split -object groups. Extreme-aspect labels fall from 26 to 10, possible nesting from -43 to 41 and tile-edge rows from 5,079 to 4,840. The complete four-page visual -render was inspected again. Pure-background tiles remain visibly empty, sparse -contexts remain distinct and the ten remaining elongated labels predominantly -match plausible long structures. - -The generic quality auditor still reports `needs_attention` because normalized -median box area `0.000641` is below its conservative `0.001` warning threshold. -That corresponds to median dimensions near 12 by 13 pixels at source tile -resolution and is not a failed minimum-dimension gate. The warning remains -visible; it was not suppressed or relabelled as success. - -This min-4px version is the preferred experimental successor to the legacy -min-3px corpus. It explicitly remains ineligible for governed training until -real human review and all release-contract evidence exist. - -## Non-overlapping checkpoint re-evaluation - -The 36-tile checkpoint matrix was traced to a 512 px validation corpus with -stride 256. It contained nine views each of Turnhout, Westerlo, Postel-bos and -Arendonk-heide. Visual inspection then exposed that all Arendonk-heide views -are blank/no-data imagery, not meaningful pure-background observations. The -historical claim of 18 background images is therefore corrected: nine were -blank no-data and nine represented Postel under overlap. - -A training-disabled validation view now covers each 1024 px AOI with four -non-overlapping 512 px tiles. Four blank Arendonk representatives are excluded -with explicit reason codes. The resulting set contains eight positive tiles -from Turnhout/Westerlo, four real Postel background tiles and 2,551 labels. -Exact reconstruction finds 2,384 unique interior objects, 167 edge labels and -zero repeated interior objects. The view has empty train directories, a -checksum-bound `NO_TRAINING.json`, and the training wrapper rejects that marker. - -On the Tower RTX 4080 SUPER, the active checkpoint measures precision -`0.542632`, recall `0.435317`, mAP50 `0.342034` and mAP50-95 `0.141316`. -The reviewedexp6 challenger measures `0.581715`, `0.462300`, `0.368364` and -`0.155318` respectively. At background confidence 0.15 the active checkpoint -has zero Postel detections and the challenger has one. At 0.25 both have zero. -Thus the refined evidence confirms the challenger's relative metric advantage -and its threshold sensitivity, but still does not authorize promotion. - -Non-overlap is not overstated as statistical independence: the positive tiles -remain adjacent and come from only two AOIs, edge objects can remain split, and -there is only one real background AOI. The production model remains unchanged. - -## Training/evaluation membership correction - -The evaluation AOIs were subsequently checked against the exact tile summaries -of both compared checkpoints. `turnhout` and `westerlo` do not occur in either -train split. `postel_bos`, however, occurs in both: the active corpus contains -20 training AOIs and the challenger corpus 26, with Postel included in each. -The Postel image is real rather than blank/no-data, but it is training-seen. - -Consequently the positive Turnhout/Westerlo metrics remain a non-protected, -adjacent-AOI candidate ranking; the Postel detection counts are only -training-seen sanity/regression observations. They are not independent -pure-background validation and cannot support release, threshold or -generalisation claims. The earlier wording about a "real background AOI" must -be read with this correction. - -The checkpoint evaluator now accepts exact training summaries and, in governed -mode, fails before PyTorch import, model loading or GPU inference when any -evaluation AOI overlaps any supplied train split. The reproduced gate blocked -on `postel_bos` for both checkpoints. Its immutable machine-readable record is -`artifacts/evidence/accuracy/model-training/20260809-v70-evaluation-independence-gate.json`. - -## Full model-lineage correction - -The preceding correction still considered only the final fine-tune corpus of -each checkpoint. Exact retained Ultralytics arguments establish a longer -ancestry: the active checkpoint was initialized from -`geointel-building-yolov8s-aoi1024expandedminpx4vis035e50`, which was initialized -from the generic `yolov8s.pt`; the challenger was then initialized from the -active checkpoint. The copied model assets and retained `best.pt` files match -byte-for-byte at each building-model stage. - -The ancestral expanded corpus exposes all three evaluation AOIs: `postel_bos` -as train, and `turnhout` plus `westerlo` as validation. Therefore none of the -v69 AOIs is independent of the complete model family. Turnhout/Westerlo can -still be used as familiar regression diagnostics, but their metrics are not a -fresh candidate-ranking result and must not support accuracy, uncertainty, -generalisation or release claims. - -The gate now requires every ancestral corpus summary and checks every recorded -split, including validation and calibration. A reproduced Tower run blocked on -all three AOIs before PyTorch import, model loading or GPU inference. Evidence: -`artifacts/evidence/accuracy/model-training/20260809-v71-full-lineage-independence-gate.json`. -The byte-matching parent/output chain is retained separately in -`artifacts/evidence/accuracy/model-training/20260809-v71-model-lineage-receipt.json`. -Fresh geographically separated AOIs with complete spatial and lineage checks -are required for the next meaningful evaluation. - -## Fresh V72 calibration portfolio - -Six AOIs were pre-registered before inference and acquired again from the -governed regional orthophoto and building adapters: two each in Vlaanderen, -Wallonië and Brussel. All six are absent from every split of the retained model -lineage. A raster-bound spatial audit resolved all 31 ancestral AOIs and found -the nearest new AOI at 4,869.63 metres, above the frozen 2 km floor. - -The initial generic edge-cover tiling would have counted 54 tiles because its -final-row/final-column coverage nearly duplicated the preceding 512 px cells. -That view was rejected. The corrected evaluation-only exporter retains exactly -24 full grid cells, excludes 30 overlapping edge-cover views with reason codes, -and writes no training tiles. Both the corpus and tile view contain bound -`NO_TRAINING.json` markers. - -All 24 tiles and 348 retained labels were visually inspected. Havelange is a -positive village context despite its pre-registered `field-cal-bg` name. -Assenede and Laeken contain sparse official building labels and are difficult -contexts, not pure-empty backgrounds. The evaluator now refuses to accept a -pure-background prefix when any corresponding label file is non-empty. - -On the RTX 4080 SUPER the active model scores mAP50 `0.056779` and mAP50-95 -`0.021750`; the challenger scores `0.044705` and `0.016004`. At confidence 0.25 -and match IoU 0.25 their F1 scores are `0.231527` and `0.235885`. These low -values expose substantial domain-generalisation failure. The active model stays -in production because the challenger has weaker mAP, only a marginal F1 gain, -missing historical release provenance and no valid promotion bundle. - -The active model's aggregate calibration F1 peaks at threshold 0.30 -(`0.250356`), but its Flemish subgroup becomes worse than at lower thresholds. -No threshold was changed because a global average may not mask that subgroup -regression. PICC and UrbIS remain diagnostic-only while their regional semantic -harmonisation contracts are pending; no national release claim is made. - -Complete evidence is retained under -`artifacts/evidence/accuracy/model-training/20260809-v72-fresh-calibration/` -and summarized by `20260809-v72-fresh-calibration-summary.json`. diff --git a/docs/superpowers/plans/2026-07-06-model-reference-catalog.md b/docs/superpowers/plans/2026-07-06-model-reference-catalog.md deleted file mode 100644 index d129bb07..00000000 --- a/docs/superpowers/plans/2026-07-06-model-reference-catalog.md +++ /dev/null @@ -1,410 +0,0 @@ -# Model And Reference Catalog Implementation Plan - -> **For agentic workers:** REQUIRED SUB-SKILL: Use superpowers:subagent-driven-development (recommended) or superpowers:executing-plans to implement this plan task-by-task. Steps use checkbox (`- [ ]`) syntax for tracking. - -**Goal:** Add a read-only local model asset catalog and make official reference providers visually distinct from AI model selection. - -**Architecture:** Model files remain runtime assets in the mounted model directory; persisted domain state remains in jobs, analysis runs, detections, datasets and vector features. Detection runs keep `model_id="yolo-configured"` and optionally include a validated `model_asset_id` resolved by a dedicated backend service. - -**Tech Stack:** FastAPI, Pydantic, SQLAlchemy, React, TypeScript, Vite, MapLibre, existing GeoIntel API envelope helpers. - ---- - -## File Structure - -- Create `backend/app/services/model_asset_catalog_service.py`: read-only scanner and resolver for local model assets. -- Modify `backend/app/core/config.py`: add `YOLO_MODELS_DIR` setting with safe default `/app/models`. -- Modify `backend/app/schemas/detection.py`: add model asset response schemas and optional request fields. -- Modify `backend/app/api/routes/detection.py`: add model asset endpoint and pass selected asset IDs to preflight/detection. -- Modify `backend/app/services/detection_service.py`: resolve selected model asset into run-local YOLO settings and persist selection in parameters. -- Modify `backend/app/services/yolo_preflight_service.py`: accept selected asset ID and preflight against that asset path. -- Add `backend/tests/test_model_asset_catalog.py`: unit tests for scanning, resolving and envelope behavior. -- Add or extend `backend/tests/test_sprint8b_yolo_foundation.py`: detection run parameter persistence for selected assets. -- Modify `frontend/src/types.ts`: add model asset types and optional request fields. -- Modify `frontend/src/services/api/detection.ts`: add model asset endpoint and preflight query param. -- Modify `frontend/src/hooks/useDetectionWorkflow.ts`: load/select model assets and send selected asset ID. -- Modify `frontend/src/components/detection/DetectionLab.tsx`: add local model asset picker and clearer model state. -- Modify `frontend/src/components/providers/ProviderPanel.tsx`: sharpen reference-provider catalog copy. -- Update docs listed in the design document. - -## Task 1: Backend Catalog Tests - -**Files:** - -- Create: `backend/tests/test_model_asset_catalog.py` - -- [ ] **Step 1: Write catalog unit tests** - -```python -from pathlib import Path - -from app.core.config import Settings -from app.services.model_asset_catalog_service import ModelAssetCatalogService - - -def test_model_asset_catalog_lists_supported_files(tmp_path: Path) -> None: - model_file = tmp_path / "building-detector.pt" - model_file.write_bytes(b"local model") - ignored_file = tmp_path / "notes.txt" - ignored_file.write_text("ignore me", encoding="utf-8") - settings = Settings(yolo_models_dir=str(tmp_path), yolo_model_path=str(model_file), yolo_enabled=True) - - response = ModelAssetCatalogService.list_assets(settings=settings) - - assert response.total == 1 - asset = response.items[0] - assert asset.filename == "building-detector.pt" - assert asset.active is True - assert asset.model_path == str(model_file) - assert asset.size_bytes == len(b"local model") - assert len(asset.sha256) == 64 - assert asset.will_download_models is False - - -def test_model_asset_catalog_resolves_known_asset(tmp_path: Path) -> None: - model_file = tmp_path / "building-detector.pt" - model_file.write_bytes(b"local model") - settings = Settings(yolo_models_dir=str(tmp_path), yolo_enabled=True) - - asset = ModelAssetCatalogService.resolve_asset("building-detector-pt", settings=settings) - - assert asset.filename == "building-detector.pt" - assert asset.model_path == str(model_file) - - -def test_model_asset_catalog_rejects_unknown_asset(tmp_path: Path) -> None: - settings = Settings(yolo_models_dir=str(tmp_path), yolo_enabled=True) - - try: - ModelAssetCatalogService.resolve_asset("missing-model", settings=settings) - except Exception as exc: - assert getattr(exc, "code", "") == "DETECTION_MODEL_ASSET_NOT_FOUND" - else: - raise AssertionError("unknown model asset should fail") -``` - -- [ ] **Step 2: Run the tests to verify they fail before implementation** - -Run: - -```bash -cd backend -python -m pytest tests/test_model_asset_catalog.py -q -``` - -Expected: import failure for `model_asset_catalog_service`. - -## Task 2: Backend Catalog Implementation - -**Files:** - -- Create: `backend/app/services/model_asset_catalog_service.py` -- Modify: `backend/app/core/config.py` -- Modify: `backend/app/schemas/detection.py` - -- [ ] **Step 1: Add settings and schemas** - -Add `yolo_models_dir` to settings: - -```python -yolo_models_dir: str = Field(default="/app/models", validation_alias="YOLO_MODELS_DIR") -``` - -Add schemas: - -```python -class ModelAssetRead(BaseModel): - model_asset_id: str - filename: str - display_name: str - model_path: str - suffix: str - framework: str - task_type: str - size_bytes: int - sha256: str - active: bool - status: str - limitation_message: str - will_download_models: bool = False - - -class ModelAssetListResponse(BaseModel): - items: list[ModelAssetRead] - total: int - model_directory: str -``` - -- [ ] **Step 2: Implement the scanner and resolver** - -Implement a service that: - -- resolves `YOLO_MODELS_DIR`; -- scans `.pt`, `.onnx`, `.engine`; -- uses deterministic slug IDs such as `building-detector-pt`; -- computes SHA-256; -- marks active file by comparing resolved paths; -- raises `AppError(code="DETECTION_MODEL_ASSET_NOT_FOUND", status_code=404)` for unknown IDs. - -- [ ] **Step 3: Run focused tests** - -Run: - -```bash -cd backend -python -m pytest tests/test_model_asset_catalog.py -q -``` - -Expected: pass. - -## Task 3: API And Service Wiring - -**Files:** - -- Modify: `backend/app/api/routes/detection.py` -- Modify: `backend/app/services/detection_service.py` -- Modify: `backend/app/services/yolo_preflight_service.py` -- Modify: `backend/app/schemas/detection.py` -- Test: `backend/tests/test_model_asset_catalog.py` - -- [ ] **Step 1: Add endpoint test** - -Add a FastAPI test that calls `GET /api/v1/detection/model-assets` and asserts: - -```python -assert "data" in response.json() -assert response.json()["data"]["total"] == 1 -``` - -- [ ] **Step 2: Add optional request fields** - -Extend `DetectionRunRequest` with: - -```python -model_asset_id: str | None = None -``` - -Extend preflight query handling with `model_asset_id: str | None = None`. - -- [ ] **Step 3: Wire endpoint** - -Add route: - -```python -@router.get("/model-assets", response_model=dict) -def list_detection_model_assets() -> dict: - return envelope(ModelAssetCatalogService.list_assets().model_dump()) -``` - -- [ ] **Step 4: Resolve selected asset in detection service** - -When `model_asset_id` is present and `model_id` equals the configured YOLO model ID: - -- resolve the asset through `ModelAssetCatalogService`; -- copy settings with `yolo_model_path=asset.model_path`; -- persist `model_asset_id`, `model_asset_path`, and `model_asset_sha256` in run parameters. - -- [ ] **Step 5: Resolve selected asset in preflight** - -When `model_asset_id` is present: - -- resolve the asset; -- preflight against that asset path; -- include `model_asset_id` in the response. - -- [ ] **Step 6: Run focused tests** - -Run: - -```bash -cd backend -python -m pytest tests/test_model_asset_catalog.py tests/test_sprint8b_yolo_foundation.py -q -``` - -Expected: pass. - -## Task 4: Frontend Model Asset Selection - -**Files:** - -- Modify: `frontend/src/types.ts` -- Modify: `frontend/src/services/api/detection.ts` -- Modify: `frontend/src/hooks/useDetectionWorkflow.ts` -- Modify: `frontend/src/components/detection/DetectionLab.tsx` - -- [ ] **Step 1: Add frontend types and API call** - -Add: - -```ts -export interface ModelAssetRead { - model_asset_id: string - filename: string - display_name: string - model_path: string - suffix: string - framework: string - task_type: string - size_bytes: number - sha256: string - active: boolean - status: string - limitation_message: string - will_download_models: boolean -} - -export interface ModelAssetListResponse { - items: ModelAssetRead[] - total: number - model_directory: string -} -``` - -Add `model_asset_id?: string | null` to `DetectionRunRequest` and preflight params. - -- [ ] **Step 2: Add hook state** - -Add: - -```ts -const [modelAssets, setModelAssets] = useState([]) -const [selectedModelAssetId, setSelectedModelAssetId] = useState('') -const [modelAssetError, setModelAssetError] = useState(null) -``` - -Load assets alongside detection models and default to the active asset when one exists. - -- [ ] **Step 3: Send selected asset** - -Send `model_asset_id: selectedModelAssetId || null` in: - -- `getYoloPreflight`; -- `run`. - -- [ ] **Step 4: Add UI picker** - -In `DetectionLab`, render a local model asset picker when `selectedDetectionModelId === "yolo-configured"`. - -Show: - -- filename; -- active badge; -- size in MB; -- checksum prefix; -- no-download warning. - -- [ ] **Step 5: Typecheck** - -Run: - -```bash -cd frontend -npm run typecheck -``` - -Expected: pass. - -## Task 5: Provider Catalog Clarity - -**Files:** - -- Modify: `frontend/src/components/providers/ProviderPanel.tsx` - -- [ ] **Step 1: Update copy and grouping** - -Keep existing provider cards but add a concise heading that states: - -- GRB/OSM are source capabilities, not model choices; -- manual upload is the currently configured reference data path; -- fixture is test/demo only. - -- [ ] **Step 2: Build** - -Run: - -```bash -cd frontend -npm run build -``` - -Expected: pass. - -## Task 6: Documentation - -**Files:** - -- Modify: `docs/API_CONTRACTS.md` -- Modify: `docs/AI_PIPELINES.md` -- Modify: `backend/README.md` -- Modify: `frontend/README.md` -- Modify: `docs/CODEX_EXECUTION_LOG.md` -- Modify: `CHANGELOG.md` -- Modify: `docs/TODO.md` - -- [ ] **Step 1: Document backend API** - -Document: - -- `GET /api/v1/detection/model-assets`; -- optional `model_asset_id` on preflight and run; -- no model downloads; -- `YOLO_MODELS_DIR`. - -- [ ] **Step 2: Document UI behavior** - -Document: - -- model assets are local runtime files; -- GRB/OSM are reference data providers; -- manual upload remains the configured reference path. - -## Task 7: Full Validation - -**Files:** none unless validation reveals a bug. - -- [ ] **Step 1: Run backend compile** - -```bash -python -m compileall backend/app -``` - -- [ ] **Step 2: Run backend tests** - -```bash -cd backend -python -m pytest -``` - -- [ ] **Step 3: Run readiness** - -```bash -bash scripts/run_readiness_check.sh -``` - -- [ ] **Step 4: Run frontend typecheck and build** - -```bash -cd frontend -npm run typecheck -npm run build -``` - -- [ ] **Step 5: Run migration checks** - -```bash -cd backend -python -m alembic heads -python -m alembic upgrade head --sql -bash ../scripts/live_migration_smoke.sh -``` - -- [ ] **Step 6: Runtime smoke after deploy** - -Call: - -```bash -curl http://192.0.2.10:1202/api/v1/detection/model-assets -curl "http://192.0.2.10:1202/api/v1/detection/yolo/preflight?model_asset_id=&tile_manifest_path=" -``` - -Expected: canonical envelopes and no model downloads. diff --git a/docs/superpowers/plans/2026-07-11-yolo-label-qa-contact-sheets.md b/docs/superpowers/plans/2026-07-11-yolo-label-qa-contact-sheets.md deleted file mode 100644 index a28f4bd6..00000000 --- a/docs/superpowers/plans/2026-07-11-yolo-label-qa-contact-sheets.md +++ /dev/null @@ -1,63 +0,0 @@ -# YOLO Label QA Contact Sheets Implementation Plan - -> **For agentic workers:** REQUIRED SUB-SKILL: Use superpowers:subagent-driven-development (recommended) or superpowers:executing-plans to implement this plan task-by-task. Steps use checkbox (`- [ ]`) syntax for tracking. - -**Goal:** Build an operator-only visual QA script that creates deterministic contact-sheet PNG artifacts from existing YOLO tile datasets. - -**Architecture:** Add a standalone script under `scripts/` with no backend/API/database changes. The script reads `yolo_tile_dataset_summary.json`, resolves image and label paths, selects a bounded deterministic tile subset, draws normalized YOLO labels using Pillow, and writes JSON/Markdown/PNG artifacts. - -**Tech Stack:** Python standard library, Pillow, pytest subprocess-based script tests. - ---- - -### Task 1: Regression Test - -**Files:** -- Create: `backend/tests/test_sprint167_operator_yolo_label_qa_contact_sheets.py` - -- [ ] Write a failing test that creates a tiny YOLO dataset with train/val images, valid labels, an invalid label row and a missing label path. -- [ ] Run `python -m pytest backend/tests/test_sprint167_operator_yolo_label_qa_contact_sheets.py -q`. -- [ ] Expected result: failure because `scripts/render_operator_yolo_label_qa_contact_sheets.py` does not exist. - -### Task 2: Script Implementation - -**Files:** -- Create: `scripts/render_operator_yolo_label_qa_contact_sheets.py` - -- [ ] Implement CLI arguments: - - `--summary-path` - - `--output-dir` - - `--max-tiles` - - `--columns` - - `--thumb-size` -- [ ] Implement summary loading and `/app/...` path resolution consistent with existing operator scripts. -- [ ] Implement YOLO label parsing with invalid/missing counts. -- [ ] Implement deterministic tile selection. -- [ ] Implement Pillow rendering to PNG contact sheets. -- [ ] Implement JSON and Markdown reports. -- [ ] Run the targeted test and keep the implementation minimal until it passes. - -### Task 3: Documentation - -**Files:** -- Modify: `scripts/README.md` -- Modify: `docs/TODO.md` -- Modify: `docs/CODEX_EXECUTION_LOG.md` - -- [ ] Document the command and intended usage. -- [ ] Mark visual contact sheets as implemented in TODO. -- [ ] Record local and Tower validation evidence. - -### Task 4: Verification And Deploy - -**Commands:** -- `python -m pytest backend/tests/test_sprint167_operator_yolo_label_qa_contact_sheets.py -q` -- `python -m pytest backend/tests/test_sprint146_operator_yolo_dataset_quality_audit.py backend/tests/test_sprint167_operator_yolo_label_qa_contact_sheets.py -q` -- `bash scripts/run_readiness_check.sh` -- `powershell -NoProfile -ExecutionPolicy Bypass -File scripts/deploy_tower.ps1` -- Tower script run against `/app/storage/operator-data/yolo-building-aoi1024-cleanpx12vis035/yolo_tile_dataset_summary.json` - -- [ ] Commit and push after local readiness. -- [ ] Redeploy Tower. -- [ ] Generate Tower contact sheets. -- [ ] Commit and push evidence docs. diff --git a/docs/superpowers/plans/2026-07-11-yolo-low-variance-negative-filter.md b/docs/superpowers/plans/2026-07-11-yolo-low-variance-negative-filter.md deleted file mode 100644 index 3f7d89f2..00000000 --- a/docs/superpowers/plans/2026-07-11-yolo-low-variance-negative-filter.md +++ /dev/null @@ -1,56 +0,0 @@ -# YOLO Low-Variance Negative Filter Implementation Plan - -> **For agentic workers:** REQUIRED SUB-SKILL: Use superpowers:subagent-driven-development (recommended) or superpowers:executing-plans to implement this plan task-by-task. Steps use checkbox (`- [ ]`) syntax for tracking. - -**Goal:** Add opt-in filtering for blank/low-variance negative tiles in the operator YOLO tile exporter. - -**Architecture:** Keep the behavior inside `scripts/export_operator_yolo_tile_dataset.py` because this is operator-only dataset construction, not application inference. Compute low-variance from the raster window image array, skip only negative tiles when explicitly enabled, and expose all decisions in `yolo_tile_dataset_summary.json`. - -**Tech Stack:** Python, pytest, rasterio/Pillow runtime helpers already used by the exporter. - ---- - -### Task 1: Regression Test - -**Files:** -- Modify: `backend/tests/test_sprint130_operator_yolo_tile_dataset.py` - -- [x] Add a test that monkeypatches `image_array_from_raster_window` and verifies `export_sample_tiles` skips only low-variance negative tiles when `drop_low_variance_negatives=True`. -- [x] Run the targeted test and confirm it fails because the exporter does not yet accept/report the new filter fields. - -### Task 2: Exporter Implementation - -**Files:** -- Modify: `scripts/export_operator_yolo_tile_dataset.py` - -- [x] Add CLI/env options: - - `--drop-low-variance-negatives` - - `--blank-range-threshold` -- [x] Add a helper to detect low visual variance from an image array. -- [x] Thread the options into `export_sample_tiles`. -- [x] Skip only negative low-variance tiles when the option is enabled. -- [x] Add `low_visual_variance` to kept tile records. -- [x] Add skipped records with `skip_reason="low_visual_variance_negative"`. -- [x] Add summary fields for the option, threshold and skipped count. - -### Task 3: Documentation - -**Files:** -- Modify: `scripts/README.md` -- Modify: `docs/CODEX_EXECUTION_LOG.md` -- Modify: `docs/TODO.md` - -- [x] Document the new operator export flags and intended Tower command. -- [x] Record local validation and known limitation. -- [x] Mark the low-variance export filter item as implemented after validation. - -### Task 4: Validation and Handoff - -**Files:** -- No additional file changes expected. - -- [x] Run targeted pytest for the exporter/contact-sheet tests. -- [x] Run `bash scripts/run_readiness_check.sh`. -- [x] Commit and push. -- [x] Rebuild/deploy Tower if code changed. -- [x] Regenerate the AOI1024 dataset with the new filter enabled, then render contact sheets and record the result. diff --git a/docs/superpowers/specs/2026-07-06-model-reference-catalog-design.md b/docs/superpowers/specs/2026-07-06-model-reference-catalog-design.md deleted file mode 100644 index 6b68d8a3..00000000 --- a/docs/superpowers/specs/2026-07-06-model-reference-catalog-design.md +++ /dev/null @@ -1,217 +0,0 @@ -# Model And Reference Catalog Design - -## Goal - -Make GeoIntel operationally clearer for V1 users by separating two concepts that currently look too similar in the UI: - -- local AI model assets that can be selected for configured YOLO inference; -- official or contextual reference data providers such as GRB, OSM, manual uploads and fixtures. - -This pass must not download model weights, fetch live GRB/OSM data, add training, add auth, or bypass the existing dataset, job, analysis run and detection persistence architecture. - -## Current State - -Detection currently exposes a model capability list with: - -- `yolo-placeholder`; -- one configured slot, `yolo-configured`, backed by `YOLO_MODEL_PATH`; -- `manual-fixture-detector`. - -This is import-safe and honest, but it does not feel like a model picker. A user can place multiple files in `/app/models`, yet the UI can only show the single configured environment slot. - -Reference data currently exposes provider capabilities for: - -- `grb`; -- `osm`; -- `manual`; -- `fixture`. - -This is architecturally correct, but the UI does not yet make the distinction explicit enough between authoritative reference sources and AI model assets. - -## Non-Goals - -- No automatic model downloads. -- No bundled production model files in git. -- No live GRB WFS or OSM Overpass import. -- No direct writes from providers into `vector_features`. -- No new database tables for model assets in this pass. -- No training studio, model management workflow, LiDAR, reports, copilot or multi-user scope. - -## Options Considered - -### Option A: Keep Only `YOLO_MODEL_PATH` - -Keep the current single configured model slot and document that users must edit `.env`. - -Benefits: - -- smallest code change; -- preserves all existing contracts. - -Drawbacks: - -- poor operator experience; -- no visible list of available local model files; -- users cannot tell whether the model directory contains other usable files. - -### Option B: Filesystem-Backed Model Asset Catalog - -Scan a configured model directory, expose local model files through an API, and let the UI select one asset for `yolo-configured` runs. - -Benefits: - -- aligns with the current runtime model mount (`/app/models`); -- no database migration; -- no downloads or fake model metadata; -- can show file existence, size, checksum and active environment model; -- keeps actual inference inside `DetectionService` and `YoloDetectionAdapter`. - -Drawbacks: - -- metadata is limited unless optional sidecar files are added later; -- model classes are not guaranteed without loading the model. - -### Option C: Persisted Model Registry - -Create database tables for model registry records, model versions, model artifacts and model lifecycle state. - -Benefits: - -- strong long-term foundation for training studio and MLOps; -- full metadata and auditability. - -Drawbacks: - -- too broad for V1; -- adds migration and lifecycle complexity before runtime needs justify it; -- risks distracting from core GIS workflow completion. - -## Recommended Approach - -Use Option B. - -Add a filesystem-backed model asset catalog for local runtime model files. It should scan `YOLO_MODELS_DIR`, defaulting to `/app/models`, and fall back to the parent directory of `YOLO_MODEL_PATH` when appropriate. It should only report local files with known model suffixes such as `.pt`, `.onnx` and `.engine`. - -The catalog must be read-only. It must never download, create, mutate, move or delete model files. - -Detection runs should still use `model_id="yolo-configured"` for the real YOLO execution path, but may include a selected `model_asset_id`. The backend resolves that ID to a path inside the configured model directory and uses that path for the run. This avoids arbitrary path injection while keeping the existing detection contract compatible. - -## Backend Design - -Create `ModelAssetCatalogService`. - -Responsibilities: - -- resolve the model directory from settings; -- scan known model file suffixes; -- return deterministic asset IDs derived from file names; -- compute SHA-256 and size for visible provenance; -- mark which asset matches the active `YOLO_MODEL_PATH`; -- resolve a selected asset ID to a local path; -- reject missing, unknown or out-of-directory model assets. - -Add schemas: - -- `ModelAssetRead`; -- `ModelAssetListResponse`. - -Add endpoint: - -- `GET /api/v1/detection/model-assets` - -Extend existing endpoints without breaking older clients: - -- `GET /api/v1/detection/yolo/preflight` accepts optional `model_asset_id`; -- `POST /api/v1/detection/run` accepts optional `model_asset_id`. - -When `model_asset_id` is supplied, `DetectionService` should use a settings copy with `yolo_model_path` replaced by the resolved asset path. The run parameters should persist the selected asset ID and path for reproducibility. - -## Frontend Design - -Detection Lab should show: - -- model capability cards; -- a local model asset picker for configured YOLO; -- active model indicator; -- asset size and checksum prefix; -- selected asset passed to preflight and detection run; -- clear warning that GeoIntel does not download weights. - -Provider panel should show: - -- official reference source catalog; -- GRB as authoritative but not configured for live fetch; -- OSM as contextual and not configured for live fetch; -- manual uploads as the configured way to add real reference datasets now; -- fixtures as demo/test only. - -## Data Flow - -```text -/app/models/*.pt - -> ModelAssetCatalogService - -> GET /api/v1/detection/model-assets - -> Detection Lab model asset picker - -> POST /api/v1/detection/run model_id=yolo-configured + model_asset_id - -> DetectionService resolves local path - -> YoloDetectionAdapter loads selected local model - -> Job + AnalysisRun + Detection persistence -``` - -Reference data remains: - -```text -Provider registry - -> capabilities/status/limitations - -> manual upload or future provider import - -> DatasetService / VectorFeatureService - -> vector_features - -> detection/segmentation QA -``` - -## Error Handling - -- Unknown `model_asset_id`: `DETECTION_MODEL_ASSET_NOT_FOUND`. -- Model asset outside configured directory: `DETECTION_MODEL_ASSET_INVALID`. -- Missing configured YOLO dependencies: existing dependency unavailable behavior. -- Missing tile manifest: existing tile manifest required behavior. -- Missing model file after catalog resolution: existing model unavailable behavior. - -## Tests - -Backend tests should cover: - -- catalog lists only supported local model files; -- catalog marks the active model; -- checksum and size are reported; -- invalid assets are ignored; -- unknown asset ID fails cleanly; -- selected model asset is persisted in job and analysis run parameters; -- model assets endpoint uses canonical envelope; -- preflight accepts selected asset without model downloads. - -Frontend tests should cover: - -- Detection Lab exposes local model asset selection; -- selected model asset is sent to run and preflight requests; -- Provider Panel copy distinguishes reference providers from model assets. - -## Documentation - -Update: - -- `docs/API_CONTRACTS.md`; -- `docs/AI_PIPELINES.md`; -- `backend/README.md`; -- `frontend/README.md`; -- `docs/CODEX_EXECUTION_LOG.md`; -- `CHANGELOG.md`; -- `docs/TODO.md`. - -## Future Work - -- Sidecar model metadata files, for example `model.pt.json`, for class names, source, license and intended task; -- optional model compatibility smoke per selected asset; -- persisted model registry after V1 foundation is stable; -- live GRB/OSM imports through provider contracts; -- official reference dataset browser after live provider imports exist. diff --git a/docs/superpowers/specs/2026-07-11-yolo-label-qa-contact-sheets-design.md b/docs/superpowers/specs/2026-07-11-yolo-label-qa-contact-sheets-design.md deleted file mode 100644 index 0292d39a..00000000 --- a/docs/superpowers/specs/2026-07-11-yolo-label-qa-contact-sheets-design.md +++ /dev/null @@ -1,73 +0,0 @@ -# YOLO Label QA Contact Sheets Design - -## Goal - -Add an operator-only visual QA helper that renders existing YOLO tile images with -their YOLO bbox labels overlaid into deterministic contact-sheet PNG artifacts. - -## Scope - -This is not a product feature and does not change API contracts, database -schema, model activation, detection inference, provider fetching or training. -It only reads an already exported YOLO tile dataset and writes visual evidence -artifacts for human inspection before another training run. - -## Inputs - -- `yolo_tile_dataset_summary.json` from `scripts/export_operator_yolo_tile_dataset.py`. -- Existing tile image files referenced by the summary. -- Existing YOLO label files referenced by the summary. - -## Outputs - -- `operator_yolo_label_qa_summary.json` -- `operator_yolo_label_qa_contact_sheet.md` -- One or more PNG contact sheets under the chosen output directory. - -Each selected tile preview shows the image, label boxes and compact metadata: -sample slug, split, label count and background category when present. - -## Selection Strategy - -The first implementation should be deterministic and small: - -- include tiles with the highest label counts; -- include tiles from low-label positive/context samples; -- include a small number of negative tiles; -- limit total rendered tiles with `--max-tiles`. - -This is enough to catch common issues such as shifted imagery, clipped labels, -wrong class files, empty positives and mislabeled background tiles. - -## Rendering Strategy - -Use Pillow, already available in the project runtime. Draw boxes from normalized -YOLO labels directly onto the tile image. Invalid or missing label files are -reported in JSON/Markdown and skipped for box drawing, not silently ignored. - -## Error Handling - -- Missing summary file: fail with a clear process error. -- Missing image files: record skipped image count and continue if other selected - images can be rendered. -- Missing label files: record missing label count and render the image without - boxes. -- Invalid label rows: record invalid row count and render only valid boxes. - -## Tests - -Add focused tests that create tiny fixture images and YOLO labels in a temporary -dataset directory, run the script and assert: - -- JSON and Markdown reports are created; -- contact-sheet PNG exists; -- selected tile count is deterministic; -- invalid labels are counted; -- missing label files are counted; -- rendered output is not blank. - -## Acceptance - -The helper is acceptable when local targeted tests pass, full readiness passes, -the all-in-one Tower runtime is redeployed, and the clean AOI1024 dataset emits -contact sheets on Tower. diff --git a/docs/superpowers/specs/2026-07-11-yolo-low-variance-negative-filter-design.md b/docs/superpowers/specs/2026-07-11-yolo-low-variance-negative-filter-design.md deleted file mode 100644 index 440a189d..00000000 --- a/docs/superpowers/specs/2026-07-11-yolo-low-variance-negative-filter-design.md +++ /dev/null @@ -1,34 +0,0 @@ -# YOLO Low-Variance Negative Filter Design - -## Goal - -Prevent blank/no-data pure-empty negative tiles from entering the next operator YOLO training dataset while keeping the exporter conservative and auditable. - -## Scope - -This pass changes only operator-side YOLO tile export tooling. It does not change backend APIs, database schema, frontend behavior, model activation, training behavior, provider fetching or inference. - -## Approach - -Add an opt-in filter to `scripts/export_operator_yolo_tile_dataset.py` that evaluates raster tile image variance before writing negative tiles. The filter applies only after labels are computed and only when a tile is negative. Positive tiles are never dropped by this gate, even if visually low-variance, because dropping labeled data silently would be a worse failure mode. - -The filter will use the same simple max-min grayscale range heuristic as the contact-sheet QA script. A tile with range at or below `OPERATOR_YOLO_BLANK_RANGE_THRESHOLD` is treated as low-variance. When `--drop-low-variance-negatives` is enabled, that negative tile is skipped and recorded in summary fields instead of being written into `images/` and `labels/`. - -## Reporting - -The dataset summary must include: - -- `drop_low_variance_negatives` -- `blank_range_threshold` -- `skipped_low_variance_negative_tile_count` -- skipped tile records with `skip_reason="low_visual_variance_negative"` - -Kept tile records should include `low_visual_variance` so downstream contact-sheet and audit tooling can expose the signal. - -## Validation - -Add a regression test that constructs a blank negative raster window and a patterned negative raster window, enables the filter, and verifies that only the blank negative is skipped for `low_visual_variance_negative`. - -## Known Limitation - -The heuristic is intentionally simple. It identifies blank/no-data tiles, not semantic quality. Operator visual QA remains required before another training run. diff --git a/fixtures/accuracy/readiness/full-scan-manifest.json b/fixtures/accuracy/readiness/full-scan-manifest.json new file mode 100644 index 00000000..7a6fa808 --- /dev/null +++ b/fixtures/accuracy/readiness/full-scan-manifest.json @@ -0,0 +1,6 @@ +{ + "schema_version": 1, + "scan_id": "synthetic-public-fixture", + "content_hash": "not-runtime-evidence", + "grb_consistency": "not_evaluable" +} diff --git a/fixtures/accuracy/readiness/leakage-report.json b/fixtures/accuracy/readiness/leakage-report.json new file mode 100644 index 00000000..fca42dfa --- /dev/null +++ b/fixtures/accuracy/readiness/leakage-report.json @@ -0,0 +1,7 @@ +{ + "schema_version": 1, + "status": "not_evaluable", + "limitations": [ + "Public source does not contain runtime datasets or split geometry." + ] +} diff --git a/fixtures/accuracy/readiness/status.json b/fixtures/accuracy/readiness/status.json new file mode 100644 index 00000000..5427ddb1 --- /dev/null +++ b/fixtures/accuracy/readiness/status.json @@ -0,0 +1,7 @@ +{ + "schema_version": 1, + "runtime": { + "active_model": null + }, + "note": "Synthetic public readiness fixture; live model state is supplied outside Git." +} diff --git a/scripts/build_accuracy_phase1_evidence_manifest.py b/scripts/build_accuracy_phase1_evidence_manifest.py index 2e863f69..9af71075 100644 --- a/scripts/build_accuracy_phase1_evidence_manifest.py +++ b/scripts/build_accuracy_phase1_evidence_manifest.py @@ -14,14 +14,11 @@ DEFAULT_EVIDENCE_ROOT = REPOSITORY_ROOT / "artifacts" / "evidence" / "accuracy" DEFAULT_OUTPUT = DEFAULT_EVIDENCE_ROOT / "evidence-manifest.json" PROGRAM_PATHS = ( - "docs/accuracy-program/00-execution-contract.md", - "docs/accuracy-program/01-system-inventory.md", - "docs/accuracy-program/02-data-lineage.md", - "docs/accuracy-program/03-baseline-and-gaps.md", - "docs/accuracy-program/04-risk-register.md", - "docs/accuracy-program/05-metric-framework.md", - "docs/accuracy-program/06-implementation-roadmap.md", - "docs/accuracy-program/status.json", + "docs/ACCURACY.md", + "docs/DATA_SOURCES.md", + "docs/KNOWN_LIMITATIONS.md", + "SECURITY.md", + "fixtures/accuracy/readiness/status.json", "scripts/build_accuracy_phase1_evidence_manifest.py", "scripts/collect_accuracy_phase1_inference_smoke.py", "scripts/collect_accuracy_phase1_ml_lineage.py", @@ -29,7 +26,6 @@ PROGRAM_PATHS = ( "scripts/reproduce_accuracy_phase1_findings.py", "scripts/run_accuracy_phase1_baseline.py", "scripts/verify_accuracy_phase1_evidence.py", - "tests/test_accuracy_phase1_baseline.py", ) diff --git a/scripts/check_repository_hygiene.py b/scripts/check_repository_hygiene.py index e61f2cd3..3078461c 100644 --- a/scripts/check_repository_hygiene.py +++ b/scripts/check_repository_hygiene.py @@ -10,7 +10,13 @@ from pathlib import Path ROOT = Path(__file__).resolve().parents[1] BLOCKED_PATHS = {".mcp.json"} -BLOCKED_PREFIXES = (".codex-input/", ".codex-artifacts/", ".playwright-mcp/", "data/") +BLOCKED_PREFIXES = ( + ".codex-input/", + ".codex-artifacts/", + ".playwright-mcp/", + "artifacts/", + "data/", +) BLOCKED_SUFFIXES = (".db", ".db-shm", ".db-wal") BLOCKED_CONTENT = ( b"192.168." + b"10.150", @@ -21,7 +27,6 @@ BLOCKED_CONTENT = ( ) LARGE_FILE_LIMIT = 20 * 1024 * 1024 LARGE_FILE_ALLOWLIST_PREFIXES = ( - "artifacts/evidence/accuracy/", "docs/assets/", "frontend/public/portfolio/", "output/pdf/", diff --git a/scripts/run_accuracy_phase3_full_data_scan.py b/scripts/run_accuracy_phase3_full_data_scan.py index 2b4a82ab..076f12f0 100644 --- a/scripts/run_accuracy_phase3_full_data_scan.py +++ b/scripts/run_accuracy_phase3_full_data_scan.py @@ -464,7 +464,7 @@ def detect_leakage(items: list[dict[str, Any]], repo_root: Path | None = None) - prior_quality: dict[str, Any] | None = None prior_attention = False if repo_root is not None: - status_path = repo_root / "docs/accuracy-program/status.json" + status_path = repo_root / "fixtures/accuracy/readiness/status.json" try: status = json.loads(status_path.read_text(encoding="utf-8")) v56 = ((status.get("ml_data") or {}).get("v56") or {}) diff --git a/scripts/run_accuracy_phase4_benchmark.py b/scripts/run_accuracy_phase4_benchmark.py index 7327a967..97450218 100644 --- a/scripts/run_accuracy_phase4_benchmark.py +++ b/scripts/run_accuracy_phase4_benchmark.py @@ -2148,9 +2148,9 @@ def product_baseline_manifest_gate( def readiness_snapshot(repo_root: Path) -> dict[str, Any]: - status_path = repo_root / "docs/accuracy-program/status.json" - p3_path = repo_root / "artifacts/evidence/accuracy/P3/full-scan-manifest.json" - leakage_path = repo_root / "artifacts/evidence/accuracy/P3/leakage-report.json" + status_path = repo_root / "fixtures/accuracy/readiness/status.json" + p3_path = repo_root / "fixtures/accuracy/readiness/full-scan-manifest.json" + leakage_path = repo_root / "fixtures/accuracy/readiness/leakage-report.json" status = json.loads(status_path.read_text(encoding="utf-8")) p3 = json.loads(p3_path.read_text(encoding="utf-8")) leakage = json.loads(leakage_path.read_text(encoding="utf-8")) @@ -2162,15 +2162,15 @@ def readiness_snapshot(repo_root: Path) -> dict[str, Any]: "schema_version": 1, "source_paths": { "accuracy_status_projection": { - "path": "docs/accuracy-program/status.json", + "path": "fixtures/accuracy/readiness/status.json", "selected_json_pointers": ["/runtime/active_model"], "sha256": canonical_hash(status_projection), }, "phase3_full_scan": repository_file( - repo_root, "artifacts/evidence/accuracy/P3/full-scan-manifest.json" + repo_root, "fixtures/accuracy/readiness/full-scan-manifest.json" ), "phase3_leakage": repository_file( - repo_root, "artifacts/evidence/accuracy/P3/leakage-report.json" + repo_root, "fixtures/accuracy/readiness/leakage-report.json" ), }, "active_model": status_projection["runtime"]["active_model"], @@ -2610,10 +2610,10 @@ def build_input_manifest( "fixtures/accuracy/p4/split-source-manifest.json", "fixtures/accuracy/p4/protected-baseline-cases.json", "fixtures/golden/golden_qa_benchmarks.json", - "docs/accuracy-program/05-metric-framework.md", - "docs/accuracy-program/07-source-authority-matrix.md", - "artifacts/evidence/accuracy/P3/full-scan-manifest.json", - "artifacts/evidence/accuracy/P3/leakage-report.json", + "docs/ACCURACY.md", + "docs/DATA_SOURCES.md", + "fixtures/accuracy/readiness/full-scan-manifest.json", + "fixtures/accuracy/readiness/leakage-report.json", ] baseline_gate = product_gates.get("executed_product_incumbent_baseline") or {} manifest_binding: dict[str, Any] | None = None @@ -2722,7 +2722,7 @@ def run_workflow( "evaluator_families": sorted(evaluation["evaluated_task_families"]), "implemented_capabilities": evaluation["task_inventory"], "metric_contract": repository_file( - repo_root, "docs/accuracy-program/05-metric-framework.md" + repo_root, "docs/ACCURACY.md" ), "gate_states": sorted(GATE_STATES), "protected_policy": evaluation["protected_policy"], @@ -2756,7 +2756,7 @@ def run_workflow( ] failure_gallery = { "schema_version": 2, - "taxonomy": "docs/accuracy-program/05-metric-framework.md section 4", + "taxonomy": "docs/ACCURACY.md", "failure_count": len(evaluation["failures"]), "items": evaluation["failures"], "items_canonical_json_sha256": canonical_hash(evaluation["failures"]), @@ -2770,7 +2770,7 @@ def run_workflow( ) error_taxonomy = { "schema_version": 2, - "source": "docs/accuracy-program/05-metric-framework.md section 4", + "source": "docs/ACCURACY.md", "observed_codes": [ {"error_code": code, "kind": kind} for code, kind in taxonomy_entries ], @@ -2893,10 +2893,10 @@ def run_workflow( repo_root, "fixtures/golden/golden_qa_benchmarks.json" ), "phase3_full_scan": repository_file( - repo_root, "artifacts/evidence/accuracy/P3/full-scan-manifest.json" + repo_root, "fixtures/accuracy/readiness/full-scan-manifest.json" ), "phase3_leakage": repository_file( - repo_root, "artifacts/evidence/accuracy/P3/leakage-report.json" + repo_root, "fixtures/accuracy/readiness/leakage-report.json" ), }, "code": input_manifest["code"], diff --git a/scripts/train_building_proposal_classifier.py b/scripts/train_building_proposal_classifier.py index b0dff734..74717fd6 100644 --- a/scripts/train_building_proposal_classifier.py +++ b/scripts/train_building_proposal_classifier.py @@ -319,7 +319,7 @@ def main() -> int: state_path = args.output_dir / "best-state.pt" if not state_path.is_file(): raise RuntimeError(f"missing existing best state: {state_path}") - model.load_state_dict(torch.load(state_path, map_location=device)) + model.load_state_dict(torch.load(state_path, map_location=device, weights_only=True)) model.eval() torch.jit.script(model).save(str(args.output_dir / "proposal-classifier.torchscript.pt")) print( @@ -369,7 +369,7 @@ def main() -> int: if float(metric["f1"]) > best_f1: best_f1 = float(metric["f1"]) torch.save(model.state_dict(), args.output_dir / "best-state.pt") - model.load_state_dict(torch.load(args.output_dir / "best-state.pt", map_location=device)) + model.load_state_dict(torch.load(args.output_dir / "best-state.pt", map_location=device, weights_only=True)) model.eval() scripted = torch.jit.script(model) model_path = args.output_dir / "proposal-classifier.torchscript.pt"