geointel/docs/CODEX_EXECUTION_LOG.md

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_<year>_<date>_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://192.168.10.150:1202 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://192.168.10.150:1202.
• 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://192.168.10.150:1202.
• 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://192.168.10.150:1202
  • 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://192.168.10.150:1202
  • 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://192.168.10.150:1202
  • 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://192.168.10.150:1202.
• 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://192.168.10.150:1202.
• 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://192.168.10.150:1202.
• 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://192.168.10.150:1202
  • 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://192.168.10.150:1202.

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://192.168.10.150:1202.
• 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://192.168.10.150:1202.
• Live GIS capability smoke passed: bash scripts/verify_gis_runtime.sh http://192.168.10.150:1202.
• Live raster workflow smoke passed: bash scripts/verify_demo_raster_workflow.sh http://192.168.10.150:1202.
• Live workbench default-state smoke passed: bash scripts/verify_workbench_default_state.sh http://192.168.10.150:1202.
• Live workbench backing-state smoke passed: bash scripts/verify_workbench_interactions.sh http://192.168.10.150:1202.
• Live demo/export workflow smoke passed: bash scripts/verify_demo_export_workflow.sh http://192.168.10.150:1202.
• bash scripts/verify_ai_handoff_interactions.sh http://192.168.10.150:1202 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://192.168.10.150:1202: 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://192.168.10.150:1202, API proxy and icon.
• Post-deploy live model asset detection workflow smoke passed: bash scripts/verify_model_asset_detection_workflow.sh http://192.168.10.150:1202 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://192.168.10.150:1202, API proxy and icon.
• Live GET http://192.168.10.150:1202/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://192.168.10.150:1202: 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://192.168.10.150:1202, 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://192.168.10.150:1202: 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://192.168.10.150:1202, 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://192.168.10.150:1202, API proxy and icon.
• Live API check passed for GET http://192.168.10.150:1202/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://192.168.10.150:1202 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://192.168.10.150:1202: 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://192.168.10.150:1202 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://192.168.10.150:1202 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://192.168.10.150:1202 passed on Tower for frontend, API proxy and icon.
• Internal Codex browser validation passed against http://192.168.10.150:1202: 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://192.168.10.150:1202 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://192.168.10.150:1202.

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://192.168.10.150:1202 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://192.168.10.150:1202.

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://192.168.10.150:1202 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://192.168.10.150:1202.

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://192.168.10.150:1202 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://192.168.10.150:1202: 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://192.168.10.150:1202.
• 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://192.168.10.150:1202.
• 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://192.168.10.150:1202/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://192.168.10.150:1202.
• 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://192.168.10.150:1202.
• 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://192.168.10.150:1202.
• 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://192.168.10.150:1202 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://192.168.10.150:1202: 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://192.168.10.150:1202.
• 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://192.168.10.150:1202 passed: inspect, preview, stats and raster.tile.
• bash scripts/verify_workbench_default_state.sh http://192.168.10.150:1202 passed with 3/3 ready datasets.
• bash scripts/verify_workbench_interactions.sh http://192.168.10.150:1202 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://192.168.10.150:1202 passed: inspect, preview, stats and raster.tile.
• bash scripts/verify_workbench_default_state.sh http://192.168.10.150:1202 passed with 3/3 ready datasets.
• bash scripts/verify_workbench_interactions.sh http://192.168.10.150:1202 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://192.168.10.150:1202 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://192.168.10.150:1202 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://192.168.10.150:1202 passed after the smoke status fix: inspect, preview, stats and raster tile manifest all succeeded.
• bash scripts/verify_workbench_default_state.sh http://192.168.10.150:1202 passed after redeploy.
• bash scripts/verify_workbench_interactions.sh http://192.168.10.150:1202 passed after redeploy.
• bash scripts/verify_demo_export_workflow.sh http://192.168.10.150:1202 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://192.168.10.150:1202.

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://192.168.10.150:1202 passed and reported Datasets: 3/3 ready.
• bash scripts/verify_workbench_interactions.sh http://192.168.10.150:1202 passed and verified candidate, reference and raster fixture datasets.
• bash scripts/verify_demo_export_workflow.sh http://192.168.10.150:1202 passed.
• bash scripts/verify_gis_runtime.sh http://192.168.10.150:1202 passed.
• bash scripts/verify_browser_runtime.sh http://192.168.10.150:1202 passed.
• Live API check confirmed demo_context_raster.tif as raster/fixture/ready with EPSG:4326.
• Chrome headless screenshot of http://192.168.10.150:1202 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://192.168.10.150:1202 passed after redeploy.
• bash scripts/verify_workbench_default_state.sh http://192.168.10.150:1202 passed after redeploy.
• bash scripts/verify_workbench_interactions.sh http://192.168.10.150:1202 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://192.168.10.150:1202 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://192.168.10.150:1202 passed after redeploy.
• bash scripts/verify_workbench_default_state.sh http://192.168.10.150:1202 passed after redeploy.
• bash scripts/verify_gis_runtime.sh http://192.168.10.150:1202 passed after redeploy.
• Live browser check against http://192.168.10.150:1202 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://192.168.10.150:1202 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://192.168.10.150:1202 passed after redeploy.
• bash scripts/verify_gis_runtime.sh http://192.168.10.150:1202 passed after redeploy.
• bash scripts/verify_demo_export_workflow.sh http://192.168.10.150:1202 passed after redeploy.
• Live browser check against http://192.168.10.150:1202 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://192.168.10.150:1202 passed.
• bash scripts/verify_demo_export_workflow.sh http://192.168.10.150:1202 passed.
• Live browser check against http://192.168.10.150:1202 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://192.168.10.150:1202 passed.
• bash scripts/verify_demo_export_workflow.sh http://192.168.10.150:1202 passed.
• Live browser check against http://192.168.10.150:1202 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://192.168.10.150:1202 passed.
• bash scripts/verify_demo_export_workflow.sh http://192.168.10.150:1202 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://192.168.10.150:1202 passed.
• bash scripts/verify_demo_export_workflow.sh http://192.168.10.150:1202 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://192.168.10.150:1202 passed.
• bash scripts/verify_demo_export_workflow.sh http://192.168.10.150:1202 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://192.168.10.150:1202.
• Tower live migration smoke passed and reported Database collation version: ok.
• Tower browser runtime verification passed.
• bash scripts/verify_gis_runtime.sh http://192.168.10.150:1202 passed.
• bash scripts/verify_demo_export_workflow.sh http://192.168.10.150:1202 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://192.168.10.150:1202.
• Tower live migration smoke passed and reported Database collation version: ok.
• Tower browser runtime verification passed.
• bash scripts/verify_gis_runtime.sh http://192.168.10.150:1202 passed.
• bash scripts/verify_demo_export_workflow.sh http://192.168.10.150:1202 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://192.168.10.150:1202.
• Tower live migration smoke passed and reported Database collation version: ok.
• bash scripts/verify_gis_runtime.sh http://192.168.10.150:1202 passed.
• bash scripts/verify_demo_export_workflow.sh http://192.168.10.150:1202 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://192.168.10.150:1202 passed.
• bash scripts/verify_gis_runtime.sh http://192.168.10.150:1202 passed.
• bash scripts/verify_demo_export_workflow.sh http://192.168.10.150:1202 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://192.168.10.150:1202.
• 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://192.168.10.150:1202.
• 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://192.168.10.150:1202.
• 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://192.168.10.150:1202.
• 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://192.168.10.150:1202.
• 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://192.168.10.150:1202: 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://192.168.10.150:1202: 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

## 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

• Add ADR decision records.
• Add RFC placeholders for future modules.
• Add API/database/event contracts.
• Add model registry and class catalogs.
• Add queue architecture.
• Add acceptance matrix and test catalog.
• 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://192.168.10.150:1202 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://192.168.10.150:1202 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://192.168.10.150:1202 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://192.168.10.150:1202.

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://192.168.10.150:1202.

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://192.168.10.150:1202

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://192.168.10.150:1202.

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 <Name> to geointel so it matches the running all-in-one container name.
• Changed the template icon URL to the absolute PNG URL http://192.168.10.150:1202/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://192.168.10.150:1202
• bash scripts/verify_gis_runtime.sh http://192.168.10.150:1202
• bash scripts/verify_demo_export_workflow.sh http://192.168.10.150:1202

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://192.168.10.150:1202
• bash scripts/verify_gis_runtime.sh http://192.168.10.150:1202
• bash scripts/verify_demo_export_workflow.sh http://192.168.10.150:1202

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://192.168.10.150:1202
• bash scripts/verify_gis_runtime.sh http://192.168.10.150:1202
• bash scripts/verify_demo_export_workflow.sh http://192.168.10.150:1202

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://192.168.10.150:1202.

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://192.168.10.150:1202.

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://192.168.10.150:1202.

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://192.168.10.150:1202.

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://192.168.10.150:1202.

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://192.168.10.150:1202
• 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://192.168.10.150:1202.
• Direct HTTP check passed for http://192.168.10.150:1202 and http://192.168.10.150:1202/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://192.168.10.150:1202.
• 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://192.168.10.150:1202.
• Live Browser visual verification passed for Overview and Map on http://192.168.10.150:1202.

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://192.168.10.150:1202.

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://192.168.10.150:1202.
• 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://192.168.10.150:1202 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://192.168.10.150:1202.
• 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://192.168.10.150:1202: 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://192.168.10.150:1202: 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://192.168.10.150:1202 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://192.168.10.150:1202: 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://192.168.10.150:1202: 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://192.168.10.150:1202: 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://192.168.10.150:1202: 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://192.168.10.150:1202: 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://192.168.10.150:1202: 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://192.168.10.150:1202 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://192.168.10.150:1202: 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://192.168.10.150:1202 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://192.168.10.150:1202 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://192.168.10.150:1202 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://192.168.10.150:1202 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://192.168.10.150:1202 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://192.168.10.150:1202 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://192.168.10.150:1202 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://192.168.10.150:1202 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://192.168.10.150:1202 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://192.168.10.150:1202 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://192.168.10.150:1202 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://192.168.10.150:1202 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://192.168.10.150:1202 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://192.168.10.150:1202.
• 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://192.168.10.150:1202.
• 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://192.168.10.150:1202 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://192.168.10.150:1202.
• 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://192.168.10.150:1202 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://192.168.10.150:1202 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://192.168.10.150:1202 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://192.168.10.150:1202 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://192.168.10.150:1202 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://192.168.10.150:1202.
• 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://192.168.10.150:1202 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://192.168.10.150:1202 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://192.168.10.150:1202 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://192.168.10.150:1202 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://192.168.10.150:1202 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://192.168.10.150:1202 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://192.168.10.150:1202.
• Live smoke passed: bash scripts/verify_workbench_default_state.sh http://192.168.10.150:1202.
• Live smoke passed: bash scripts/verify_workbench_interactions.sh http://192.168.10.150:1202.
• Live smoke passed: bash scripts/verify_browser_runtime.sh http://192.168.10.150:1202.
• Live browser-click validation with Codex Playwright plus installed Chrome passed against http://192.168.10.150:1202: 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://192.168.10.150:1202.
• Live smoke passed: bash scripts/verify_workbench_default_state.sh http://192.168.10.150:1202.
• Live smoke passed: bash scripts/verify_workbench_interactions.sh http://192.168.10.150:1202.
• Live smoke passed: bash scripts/verify_browser_runtime.sh http://192.168.10.150:1202.
• Internal Codex browser validation passed against http://192.168.10.150:1202: 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://192.168.10.150:1202.
• Live smoke passed: bash scripts/verify_workbench_default_state.sh http://192.168.10.150:1202.
• Live smoke passed: bash scripts/verify_workbench_interactions.sh http://192.168.10.150:1202.
• Live smoke passed: bash scripts/verify_browser_runtime.sh http://192.168.10.150:1202.
• Internal Codex browser validation passed against http://192.168.10.150:1202: 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://192.168.10.150:1202 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 AppErrors 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://192.168.10.150:1202.
• Live smoke passed: bash scripts/verify_workbench_default_state.sh http://192.168.10.150:1202.
• Live smoke passed: bash scripts/verify_workbench_interactions.sh http://192.168.10.150:1202.
• Live smoke passed: bash scripts/verify_browser_runtime.sh http://192.168.10.150:1202.
• Internal Codex browser validation passed against http://192.168.10.150:1202: 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://192.168.10.150:1202.
  • /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://192.168.10.150:1202.
• 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://192.168.10.150:1202
  • 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://192.168.10.150:1202.
• 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://192.168.10.150:1202 is reachable from this workstation, but ssh -p 222 root@192.168.10.150 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://192.168.10.150:1202
• 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://192.168.10.150:1202/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://192.168.10.150:1202
• 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://192.168.10.150:1202 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://192.168.10.150:1202 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@192.168.10.150 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://192.168.10.150:1202.
• GIS runtime smoke passed against http://192.168.10.150:1202.
• 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://192.168.10.150:1202 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://192.168.10.150:1202 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://192.168.10.150:1202 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://192.168.10.150:1202
• 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://192.168.10.150:1202.
• 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://192.168.10.150:1202.
• 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://192.168.10.150:1202.
• 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://192.168.10.150:1202.
• 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://192.168.10.150:1202; 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://192.168.10.150:1202.
• 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://192.168.10.150:1202 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://192.168.10.150:1202. 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://192.168.10.150:1202. 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_<year>_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://192.168.10.150:1202 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://192.168.10.150:1202; 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://192.168.10.150:1202; 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/<iteration>/weights/last.pt exists, the orchestrator uses YOLO's exact resume=<checkpoint> 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.