Make Mol the primary operating context
This commit is contained in:
@@ -7,6 +7,14 @@
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# Changelog
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## Sprint 177 Mol-first operating context (2026-07-13)
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- Made Mol the explicit primary operating focus while retaining the broader Kempen as the validation and interoperability region.
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- Added one centralized frontend focus definition for the empty-map center, new-project region, default AOI and persisted project/dataset recognition.
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- Initial workbench selection now prefers real persisted Mol data without overriding an explicit current or newly created project selection.
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- Moved Mol to the front of default operator sample preparation and added AOI slugs to future detection quality-matrix project names.
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- Kept APIs, migrations, persistence, providers, AI dependencies and model behavior unchanged.
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## Sprint 176 Detection false-positive visual review gate (2026-07-13)
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- Enriched existing QA evidence GeoJSON with persisted detection and segmentation provenance without changing its endpoint or canonical envelope.
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@@ -2,6 +2,8 @@
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GeoIntel Kempen is a GeoAI Workbench for the Belgian Kempen. It is designed as a portfolio-grade project combining GIS, remote sensing, raster/vector processing, computer vision, QA/QC and geospatial exports.
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The primary operating focus is Mol. New workbench contexts, AOIs and operator samples start there, while the broader Kempen remains fully supported for cross-area validation and regional interoperability.
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GeoIntel is not a generic dashboard or chatbot. The core product is:
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> data → processing → geospatial output → QA/QC → export
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@@ -0,0 +1,54 @@
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from pathlib import Path
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ROOT = Path(__file__).resolve().parents[2]
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def test_frontend_declares_mol_as_primary_operating_focus() -> None:
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focus = (ROOT / "frontend" / "src" / "config" / "primaryFocus.ts").read_text(
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encoding="utf-8"
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)
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project_hook = (ROOT / "frontend" / "src" / "hooks" / "useProjectWorkspace.ts").read_text(
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encoding="utf-8"
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)
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map_source = (ROOT / "frontend" / "src" / "components" / "GeoMap.tsx").read_text(
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encoding="utf-8"
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)
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app = (ROOT / "frontend" / "src" / "App.tsx").read_text(encoding="utf-8")
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assert "PRIMARY_FOCUS_LABEL = 'Mol'" in focus
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assert "PRIMARY_FOCUS_REGION = 'Mol, Kempen'" in focus
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assert "[5.1167, 51.1919]" in focus
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assert "isPrimaryFocusProjectData" in focus
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assert "isPrimaryFocusProjectData(project, data.datasets)" in project_hook
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assert "PRIMARY_FOCUS_AREA_NAME" in project_hook
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assert "PRIMARY_FOCUS_AREA_GEOJSON" in project_hook
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assert "4.35,51.28" not in project_hook
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assert "center: PRIMARY_FOCUS_CENTER" in map_source
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assert "GeoAI Workbench · Mol / Kempen" in app
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def test_operator_workflows_put_mol_first_and_name_future_projects() -> None:
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samples = (ROOT / "scripts" / "prepare_operator_real_data_samples.py").read_text(
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encoding="utf-8"
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)
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matrix = (ROOT / "scripts" / "run_detection_quality_matrix.sh").read_text(
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encoding="utf-8"
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)
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multi_matrix = (
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ROOT / "scripts" / "run_multi_sample_detection_quality_matrix.sh"
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).read_text(encoding="utf-8")
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assert samples.index('"mol": OperatorSample(') < samples.index('"geel": OperatorSample(')
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assert 'QUALITY_SAMPLE_SLUG="${QUALITY_SAMPLE_SLUG:-}"' in matrix
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assert "sample ${QUALITY_SAMPLE_SLUG}" in matrix
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assert 'QUALITY_SAMPLE_SLUG="${sample_slug}"' in multi_matrix
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def test_product_docs_record_mol_primary_focus_without_dropping_kempen_scope() -> None:
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readme = (ROOT / "README.md").read_text(encoding="utf-8")
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vision = (ROOT / "docs" / "PRODUCT_VISION.md").read_text(encoding="utf-8")
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assert "primary operating focus is Mol" in readme
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assert "Mol is de primaire operationele focus" in vision
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assert "broader Kempen" in readme
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@@ -7233,4 +7233,28 @@ Open:
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## Next recommended pass
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- Re-export the seven-AOI evidence portfolio from the deployed backend, render the Turnhout/Herentals/Geel 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.
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- 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.
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# Sprint 177 - Mol-first operating context
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## Product and workbench focus
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- Declared Mol as the primary operational context while preserving the broader Kempen for cross-area validation and regional interoperability.
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- Centralized Mol coordinates, default region and a compact 1 km EPSG:4326 MultiPolygon AOI in the frontend focus configuration.
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- Initial project discovery now recognizes Mol from project metadata or persisted dataset provenance and inspects those candidates first.
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- Explicitly selected and newly created projects still take precedence, so the focus rule does not fight operator intent.
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- The empty MapLibre workbench starts over Mol; loaded AOIs and data continue to determine map bounds normally.
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## Operator provenance
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- Moved Mol to the first position in default real-data sample preparation without dropping any existing Kempen sample.
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- 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.
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- No provider fetch, AI output, QA metric, migration, API contract or model configuration was changed.
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## Validation
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- Focused Mol-primary regression coverage: `3 passed`.
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- `bash scripts/run_readiness_check.sh`: passed with `481` backend tests, API-contract audit, single Alembic head, frontend typecheck and production build.
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- Frontend production bundles: app `217.69 kB`, React vendor `140.74 kB`, MapLibre `801.82 kB` before gzip.
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- `python -m alembic upgrade head --sql`: complete migration chain rendered through single head `202606120900`.
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- Both changed matrix scripts pass `bash -n`; no migration file changed.
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@@ -32,11 +32,13 @@ GeoIntel moet bewijzen dat de ontwikkelaar de volledige keten begrijpt:
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De Kempen vormen de afgebakende regio. Dit maakt het project concreet, realistisch en demo-baar. Voorbeelden:
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- gebouwdetectie in Geel
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- infrastructuurdruk rond Mol
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- gebouwdetectie en infrastructuuranalyse in Mol
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- vergelijkende validatie in Geel
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- verstedelijking rond Turnhout
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- natuurfragmentatie rond Kasterlee of Retie
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Mol is de primaire operationele focus. De standaardkaart, nieuwe AOI-context en operator-volgorde vertrekken daarom vanuit Mol. De bredere Kempen blijft bewust onderdeel van de productscope voor onafhankelijke validatie, overdraagbaarheid en regionale vergelijking.
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## Richting
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De definitieve richting is:
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@@ -18,6 +18,7 @@ This file now starts with the current implementation status. Older preparation/b
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## Current implementation status
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- [x] Make Mol the primary workbench, AOI and operator-sample context while preserving broader Kempen coverage.
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- [x] Backend FastAPI foundation, health endpoint and service structure.
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- [x] React/TypeScript frontend foundation and MapLibre workbench.
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- [x] Map layer visibility, opacity and feature property inspection.
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@@ -2,6 +2,8 @@
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React + TypeScript + MapLibre foundation for project/area/dataset workflow.
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Mol is the primary operating context. On a fresh session the workbench prefers a persisted Mol project or dataset, centers an empty MapLibre view on Mol and pre-fills a compact Mol AOI. Explicit project and dataset selections remain authoritative, and all broader Kempen workflows remain available.
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The workbench now uses a task-based shell instead of a single long panel stack. `App.tsx` still owns shared orchestration state, but the UI is organized into Overview, Data, Map, QA/QC, AI Labs, Exports and System workspaces with a persistent top context bar and right-side dataset inspector.
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The shell has a calmer V1 workbench density pass: the duplicated workspace command bar is hidden, the sidebar is more compact, the top context bar is quieter, readiness tiles are smaller and panels use softer borders/shadows. This keeps the same workflows and API calls while reducing visual noise on desktop and mobile.
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@@ -643,7 +643,7 @@ function App(): JSX.Element {
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</a>
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<header className="workbench-topbar">
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<div className="brand-block">
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<p className="eyebrow">GeoAI Workbench</p>
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<p className="eyebrow">GeoAI Workbench · Mol / Kempen</p>
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<h1>GeoIntel Kempen</h1>
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</div>
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<div className="context-bar" aria-label="Active workbench context">
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@@ -1,6 +1,7 @@
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import { useEffect, useRef, useState } from 'react'
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import maplibregl from 'maplibre-gl'
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import 'maplibre-gl/dist/maplibre-gl.css'
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import { PRIMARY_FOCUS_CENTER } from '../config/primaryFocus'
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interface GeoMapProps {
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data: GeoJSON.FeatureCollection | null
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@@ -162,8 +163,8 @@ function GeoMap({
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const map = new maplibregl.Map({
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container: containerRef.current,
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style: defaultMapStyle(),
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center: [5.3, 51.3],
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zoom: 9,
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center: PRIMARY_FOCUS_CENTER,
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zoom: 11,
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attributionControl: false,
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})
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map.addControl(new maplibregl.NavigationControl(), 'top-right')
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@@ -0,0 +1,37 @@
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import type { DatasetCreateResponse, ProjectRead } from '../types'
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export const PRIMARY_FOCUS_LABEL = 'Mol'
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export const PRIMARY_FOCUS_REGION = 'Mol, Kempen'
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export const PRIMARY_FOCUS_CENTER: [number, number] = [5.1167, 51.1919]
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export const PRIMARY_FOCUS_AREA_NAME = 'Mol primary AOI'
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export const PRIMARY_FOCUS_AREA_GEOJSON =
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'{"type":"MultiPolygon","coordinates":[[[[5.109476746222376,51.18745107550715],[5.123924622861509,51.18745107550715],[5.123924622861509,51.19634848029239],[5.109476746222376,51.19634848029239],[5.109476746222376,51.18745107550715]]]]}'
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const PRIMARY_FOCUS_TOKEN = /(^|[^a-z0-9])mol([^a-z0-9]|$)/i
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function containsPrimaryFocus(values: Array<string | null | undefined>): boolean {
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return values.some((value) => Boolean(value && PRIMARY_FOCUS_TOKEN.test(value)))
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}
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export function isPrimaryFocusProject(project: ProjectRead): boolean {
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return containsPrimaryFocus([project.name, project.description, project.region])
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}
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export function isPrimaryFocusProjectData(
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project: ProjectRead,
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datasets: DatasetCreateResponse[],
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): boolean {
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if (isPrimaryFocusProject(project)) {
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return true
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}
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return datasets.some((dataset) =>
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containsPrimaryFocus([
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dataset.name,
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dataset.original_filename,
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dataset.stored_filename,
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dataset.storage_path,
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dataset.source_name,
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dataset.reference_layer_name,
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]),
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)
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}
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@@ -1,4 +1,11 @@
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import { FormEvent, useMemo, useState } from 'react'
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import {
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PRIMARY_FOCUS_AREA_GEOJSON,
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PRIMARY_FOCUS_AREA_NAME,
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PRIMARY_FOCUS_REGION,
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isPrimaryFocusProject,
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isPrimaryFocusProjectData,
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} from '../config/primaryFocus'
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import { areasApi } from '../services/api/areas'
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import { datasetsApi } from '../services/api/datasets'
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import { projectsApi } from '../services/api/projects'
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@@ -31,12 +38,11 @@ export function useProjectWorkspace() {
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const [projectForm, setProjectForm] = useState<ProjectCreate>({
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name: '',
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description: '',
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region: 'Kempen',
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region: PRIMARY_FOCUS_REGION,
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})
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const [areaForm, setAreaForm] = useState({
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name: 'Demo AOI',
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geometry:
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'{"type":"MultiPolygon","coordinates":[[[[4.35,51.28],[4.55,51.28],[4.55,51.46],[4.35,51.46],[4.35,51.28]]]]}',
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name: PRIMARY_FOCUS_AREA_NAME,
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geometry: PRIMARY_FOCUS_AREA_GEOJSON,
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crs: 'EPSG:4326',
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})
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@@ -60,19 +66,32 @@ export function useProjectWorkspace() {
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if (selectedProjectId && items.some((project) => project.id === selectedProjectId)) {
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return selectedProjectId
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}
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const primaryProjects = items.filter(isPrimaryFocusProject)
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const demoProjects = items.filter(isDemoProject)
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const candidates = [...demoProjects, ...items.filter((project) => !isDemoProject(project))].slice(0, 8)
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const candidates = Array.from(
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new Map(
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[...primaryProjects, ...demoProjects, ...items].map((project) => [project.id, project]),
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).values(),
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).slice(0, 12)
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const inspectedCandidates: Array<{
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project: ProjectRead
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data: { areas: AreaRead[]; datasets: DatasetCreateResponse[] }
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}> = []
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for (const project of candidates) {
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try {
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const data = await fetchProjectData(project.id)
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if (data.areas.length > 0 && data.datasets.length > 0) {
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inspectedCandidates.push({ project, data })
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if (data.datasets.length > 0 && isPrimaryFocusProjectData(project, data.datasets)) {
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return project.id
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}
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} catch {
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// Project list should still render if a candidate's detail endpoints are temporarily unavailable.
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}
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}
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return demoProjects[0]?.id ?? items[0]?.id ?? null
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const completeContext = inspectedCandidates.find(
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({ data }) => data.areas.length > 0 && data.datasets.length > 0,
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)
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return completeContext?.project.id ?? primaryProjects[0]?.id ?? demoProjects[0]?.id ?? items[0]?.id ?? null
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}
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const loadProjects = async (preferredProjectId?: string | null) => {
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@@ -120,7 +139,7 @@ export function useProjectWorkspace() {
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const createdProject = await projectsApi.create({
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name: projectForm.name.trim(),
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description: projectForm.description?.trim() || undefined,
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region: projectForm.region?.trim() || 'Kempen',
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region: projectForm.region?.trim() || PRIMARY_FOCUS_REGION,
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})
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setProjectForm((previous) => ({ ...previous, name: '', description: '' }))
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setSelectedProjectId(createdProject.id)
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@@ -64,18 +64,18 @@ class OperatorSample:
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SAMPLES: dict[str, OperatorSample] = {
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"geel": OperatorSample(
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slug="geel",
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display_name="Geel center",
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center_lon=4.991,
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center_lat=51.162,
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),
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"mol": OperatorSample(
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slug="mol",
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display_name="Mol center",
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center_lon=5.1167,
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center_lat=51.1919,
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),
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"geel": OperatorSample(
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slug="geel",
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display_name="Geel center",
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center_lon=4.991,
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center_lat=51.162,
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),
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"turnhout": OperatorSample(
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slug="turnhout",
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display_name="Turnhout center",
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@@ -10,6 +10,7 @@ Usage:
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QUALITY_TILE_SIZES="512 640" \
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QUALITY_TILE_OVERLAPS="64" \
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QUALITY_THRESHOLDS="0.50 0.25 0.15" \
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QUALITY_SAMPLE_SLUG="mol" \
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bash scripts/run_detection_quality_matrix.sh [base_url]
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or:
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@@ -25,6 +26,7 @@ Optional environment:
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QUALITY_TILE_OVERLAPS Space/comma separated raster tile overlaps, default: 64.
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QUALITY_THRESHOLDS Space/comma separated confidence thresholds, default: 0.50 0.25 0.15.
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QUALITY_OUTPUT_DIR Output directory, default: artifacts/detection-quality-matrix/<timestamp>.
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QUALITY_SAMPLE_SLUG Optional AOI slug included in persisted project names.
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REAL_IOU_THRESHOLD QA IoU threshold, default inherited by the underlying workflow.
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This script never downloads models and never uses fixture detections. It repeats
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@@ -42,6 +44,7 @@ QUALITY_MODEL_ASSET_IDS="${QUALITY_MODEL_ASSET_IDS:-${REAL_MODEL_ASSET_ID:-__act
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QUALITY_TILE_SIZES="${QUALITY_TILE_SIZES:-640}"
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QUALITY_TILE_OVERLAPS="${QUALITY_TILE_OVERLAPS:-64}"
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QUALITY_THRESHOLDS="${QUALITY_THRESHOLDS:-0.50 0.25 0.15}"
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QUALITY_SAMPLE_SLUG="${QUALITY_SAMPLE_SLUG:-}"
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QUALITY_OUTPUT_DIR="${QUALITY_OUTPUT_DIR:-artifacts/detection-quality-matrix/$(date -u +%Y%m%dT%H%M%SZ)}"
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if [ "${BASE_URL}" = "-h" ] || [ "${BASE_URL}" = "--help" ]; then
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@@ -174,9 +177,13 @@ while IFS=$'\t' read -r model_request tile_size tile_overlap threshold run_label
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if [ "${model_request}" = "__active__" ]; then
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model_env=""
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fi
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project_sample_label=""
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if [ -n "${QUALITY_SAMPLE_SLUG}" ]; then
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project_sample_label=" sample ${QUALITY_SAMPLE_SLUG}"
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fi
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echo "-- Matrix run ${run_index}: model=${model_request} tile=${tile_size} overlap=${tile_overlap} threshold=${threshold} --"
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if ! REAL_PROJECT_NAME="GeoIntel Detection Quality Matrix ${model_request} tile ${tile_size} overlap ${tile_overlap} threshold ${threshold}" \
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if ! REAL_PROJECT_NAME="GeoIntel Detection Quality Matrix${project_sample_label} ${model_request} tile ${tile_size} overlap ${tile_overlap} threshold ${threshold}" \
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REAL_MODEL_ASSET_ID="${model_env}" \
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REAL_TILE_SIZE="${tile_size}" \
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REAL_TILE_OVERLAP="${tile_overlap}" \
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@@ -137,6 +137,7 @@ while IFS=$'\t' read -r sample_slug raster_path reference_path reference_feature
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echo "-- Sample ${sample_slug}: reference_features=${reference_feature_count} --"
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REAL_RASTER_PATH="${raster_path}" \
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REAL_REFERENCE_VECTOR_PATH="${reference_path}" \
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QUALITY_SAMPLE_SLUG="${sample_slug}" \
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QUALITY_OUTPUT_DIR="${sample_output_dir}" \
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bash scripts/run_detection_quality_matrix.sh "${BASE_URL}"
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done < "${sample_manifest_tsv}"
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