Files
geointel/frontend/src/hooks/useDetectionWorkflow.ts
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feat: simplify regional end user workbench
2026-07-14 21:40:32 +02:00

429 lines
16 KiB
TypeScript

import { useEffect, useState } from 'react'
import { detectionApi } from '../services/api'
import type {
DatasetCreateResponse,
DetectionModelCapability,
DetectionQaResult,
DetectionRead,
DetectionRunRead,
DetectionRunResponse,
ModelAssetRead,
QualityCheckRead,
YoloPreflightResponse,
} from '../types'
import { formatError } from '../lib/formatError'
interface DetectionWorkflowOptions {
selectedProjectId: string | null
rasterDatasets: DatasetCreateResponse[]
qaIouThreshold: number
loadProjectData: (projectId: string) => Promise<unknown>
loadQualityChecks: (projectId?: string | null) => Promise<QualityCheckRead[] | void>
}
interface DetectionOperatorProfileSelection {
modelAssetId: string
confidenceThreshold: number
}
export interface DetectionCalibrationRunRow {
threshold: number
status: 'queued' | 'running' | 'success' | 'failed'
analysis_run_id?: string | null
job_id?: string | null
quality_check_id?: string | null
detection_count?: number | null
precision?: number | null
recall?: number | null
f1_score?: number | null
false_positives?: number | null
false_negatives?: number | null
message?: string | null
}
function parseCalibrationThresholds(value: string): number[] {
const tokens = value
.split(/[\s,;]+/)
.map((token) => token.trim())
.filter(Boolean)
const thresholds: number[] = []
for (const token of tokens) {
const threshold = Number(token)
if (!Number.isFinite(threshold) || threshold < 0 || threshold > 1) {
return []
}
if (!thresholds.includes(threshold)) {
thresholds.push(threshold)
}
}
return thresholds
}
export function useDetectionWorkflow({
selectedProjectId,
rasterDatasets,
qaIouThreshold,
loadProjectData,
loadQualityChecks,
}: DetectionWorkflowOptions) {
const [detectionModels, setDetectionModels] = useState<DetectionModelCapability[]>([])
const [modelAssets, setModelAssets] = useState<ModelAssetRead[]>([])
const [loadingDetectionModels, setLoadingDetectionModels] = useState(false)
const [detectionModelError, setDetectionModelError] = useState<string | null>(null)
const [modelAssetError, setModelAssetError] = useState<string | null>(null)
const [selectedDetectionDatasetId, setSelectedDetectionDatasetId] = useState('')
const [selectedDetectionModelId, setSelectedDetectionModelId] = useState('yolo-configured')
const [selectedModelAssetId, setSelectedModelAssetId] = useState('')
const [detectionTileManifestPath, setDetectionTileManifestPath] = useState('')
const [detectionConfidenceThreshold, setDetectionConfidenceThreshold] = useState(0.15)
const [runningDetection, setRunningDetection] = useState(false)
const [detectionRunResult, setDetectionRunResult] = useState<DetectionRunResponse | null>(null)
const [detectionRunError, setDetectionRunError] = useState<string | null>(null)
const [detectionRuns, setDetectionRuns] = useState<DetectionRunRead[]>([])
const [selectedDetectionRunId, setSelectedDetectionRunId] = useState('')
const [detectionItems, setDetectionItems] = useState<DetectionRead[]>([])
const [detectionGeoJson, setDetectionGeoJson] = useState<GeoJSON.FeatureCollection | null>(null)
const [detectionClassFilter, setDetectionClassFilter] = useState('')
const [detectionMinConfidenceFilter, setDetectionMinConfidenceFilter] = useState(0)
const [loadingDetectionResults, setLoadingDetectionResults] = useState(false)
const [detectionReferenceDatasetId, setDetectionReferenceDatasetId] = useState('')
const [detectionQaResult, setDetectionQaResult] = useState<DetectionQaResult | null>(null)
const [detectionQaError, setDetectionQaError] = useState<string | null>(null)
const [runningDetectionQa, setRunningDetectionQa] = useState(false)
const [yoloPreflight, setYoloPreflight] = useState<YoloPreflightResponse | null>(null)
const [loadingYoloPreflight, setLoadingYoloPreflight] = useState(false)
const [yoloPreflightError, setYoloPreflightError] = useState<string | null>(null)
const [calibrationThresholdText, setCalibrationThresholdText] = useState('0.50 0.25 0.15')
const [runningDetectionCalibration, setRunningDetectionCalibration] = useState(false)
const [detectionCalibrationRows, setDetectionCalibrationRows] = useState<DetectionCalibrationRunRow[]>([])
const [detectionCalibrationError, setDetectionCalibrationError] = useState<string | null>(null)
useEffect(() => {
if (!selectedDetectionDatasetId && rasterDatasets.length > 0) {
setSelectedDetectionDatasetId(rasterDatasets[0].id)
}
}, [rasterDatasets, selectedDetectionDatasetId])
const loadDetectionModels = async () => {
setLoadingDetectionModels(true)
setDetectionModelError(null)
setModelAssetError(null)
try {
const response = await detectionApi.listModels()
setDetectionModels(response.models)
const selectedModelStillAvailable = response.models.some((model) => model.model_id === selectedDetectionModelId)
if (!selectedModelStillAvailable && response.models.length > 0) {
const configuredModel = response.models.find(
(model) => model.configured && model.model_id !== 'manual-fixture-detector',
)
setSelectedDetectionModelId(configuredModel?.model_id ?? response.models[0].model_id)
}
} catch (error) {
setDetectionModelError(formatError(error, 'Failed to load detection models'))
}
try {
const assetResponse = await detectionApi.listModelAssets()
setModelAssets(assetResponse.items)
const activeAsset = assetResponse.items.find((asset) => asset.active) ?? null
const selectedAssetStillAvailable = assetResponse.items.some((asset) => asset.model_asset_id === selectedModelAssetId)
const nextAssetId = selectedAssetStillAvailable ? selectedModelAssetId : activeAsset?.model_asset_id ?? ''
setSelectedModelAssetId(nextAssetId)
try {
const preflight = await detectionApi.getYoloPreflight({ model_asset_id: nextAssetId || null })
setYoloPreflight(preflight)
setYoloPreflightError(null)
} catch (error) {
setYoloPreflightError(formatError(error, 'Failed to load YOLO preflight status'))
}
} catch (error) {
setModelAssets([])
setModelAssetError(formatError(error, 'Failed to load local model assets'))
} finally {
setLoadingDetectionModels(false)
}
}
const loadYoloPreflight = async (tileManifestPath = detectionTileManifestPath) => {
setLoadingYoloPreflight(true)
setYoloPreflightError(null)
try {
const response = await detectionApi.getYoloPreflight({
tile_manifest_path: tileManifestPath.trim() || null,
model_asset_id: selectedModelAssetId || null,
})
setYoloPreflight(response)
} catch (error) {
setYoloPreflightError(formatError(error, 'Failed to load YOLO preflight status'))
} finally {
setLoadingYoloPreflight(false)
}
}
const loadDetectionRuns = async (projectId = selectedProjectId) => {
if (!projectId) {
setDetectionRuns([])
return
}
try {
const response = await detectionApi.listRuns({ project_id: projectId })
setDetectionRuns(response.items)
if (!selectedDetectionRunId && response.items.length > 0) {
setSelectedDetectionRunId(response.items[0].id)
}
} catch (error) {
setDetectionRunError(formatError(error, 'Failed to load detection runs'))
}
}
const loadDetectionResults = async (analysisRunId = selectedDetectionRunId) => {
if (!analysisRunId) {
setDetectionItems([])
setDetectionGeoJson(null)
return
}
setLoadingDetectionResults(true)
setDetectionRunError(null)
try {
const params = {
class_name: detectionClassFilter || null,
min_confidence: detectionMinConfidenceFilter > 0 ? detectionMinConfidenceFilter : null,
}
const [detectionsResponse, geoJsonResponse] = await Promise.all([
detectionApi.listDetections(analysisRunId, params),
detectionApi.getRunGeoJson(analysisRunId, params),
])
setDetectionItems(detectionsResponse.items)
setDetectionGeoJson(geoJsonResponse)
} catch (error) {
setDetectionRunError(formatError(error, 'Failed to load detection results'))
} finally {
setLoadingDetectionResults(false)
}
}
const runDetection = async () => {
if (!selectedProjectId) {
setDetectionRunError('Select a project first')
return
}
const datasetId = selectedDetectionDatasetId || rasterDatasets[0]?.id
if (!datasetId) {
setDetectionRunError('Select a raster dataset')
return
}
setDetectionRunError(null)
setDetectionRunResult(null)
setRunningDetection(true)
try {
const result = await detectionApi.run({
project_id: selectedProjectId,
dataset_id: datasetId,
model_id: selectedDetectionModelId,
model_asset_id: selectedModelAssetId || null,
confidence_threshold: detectionConfidenceThreshold,
tile_manifest_path: detectionTileManifestPath.trim() || null,
parameters_json: {},
})
setDetectionRunResult(result)
setSelectedDetectionRunId(result.analysis_run_id)
await loadDetectionRuns(selectedProjectId)
await loadDetectionResults(result.analysis_run_id)
await loadProjectData(selectedProjectId)
} catch (error) {
setDetectionRunError(formatError(error, 'Detection run failed'))
} finally {
setRunningDetection(false)
}
}
const runDetectionQa = async () => {
if (!selectedDetectionRunId) {
setDetectionQaError('Select a detection run')
return
}
if (!detectionReferenceDatasetId) {
setDetectionQaError('Select a reference dataset')
return
}
setDetectionQaError(null)
setDetectionQaResult(null)
setRunningDetectionQa(true)
try {
const result = await detectionApi.compareWithReference(selectedDetectionRunId, {
reference_dataset_id: detectionReferenceDatasetId,
iou_threshold: qaIouThreshold,
class_name: detectionClassFilter || null,
min_confidence: detectionMinConfidenceFilter > 0 ? detectionMinConfidenceFilter : null,
})
setDetectionQaResult(result)
await loadQualityChecks(selectedProjectId)
} catch (error) {
setDetectionQaError(formatError(error, 'Detection QA failed'))
} finally {
setRunningDetectionQa(false)
}
}
const runDetectionCalibration = async () => {
if (!selectedProjectId) {
setDetectionCalibrationError('Select a project before calibration')
return
}
const datasetId = selectedDetectionDatasetId || rasterDatasets[0]?.id
if (!datasetId) {
setDetectionCalibrationError('Select a raster dataset before calibration')
return
}
if (!detectionReferenceDatasetId) {
setDetectionCalibrationError('Select a reference dataset before calibration')
return
}
const selectedModel = detectionModels.find((model) => model.model_id === selectedDetectionModelId)
if (!selectedModel?.configured || selectedDetectionModelId === 'manual-fixture-detector') {
setDetectionCalibrationError('Select a configured non-fixture detection model before calibration')
return
}
if (selectedDetectionModelId === 'yolo-configured' && !detectionTileManifestPath.trim()) {
setDetectionCalibrationError('Configured YOLO calibration requires a tile manifest')
return
}
if (selectedDetectionModelId === 'yolo-configured' && modelAssets.length > 0 && !selectedModelAssetId) {
setDetectionCalibrationError('Select a local model asset before calibration')
return
}
const thresholds = parseCalibrationThresholds(calibrationThresholdText)
if (thresholds.length === 0) {
setDetectionCalibrationError('Provide at least one valid threshold between 0 and 1')
return
}
setDetectionCalibrationError(null)
setDetectionCalibrationRows(thresholds.map((threshold) => ({ threshold, status: 'queued' })))
setRunningDetectionCalibration(true)
try {
for (const threshold of thresholds) {
setDetectionCalibrationRows((rows) =>
rows.map((row) => row.threshold === threshold ? { ...row, status: 'running', message: 'Running detection' } : row),
)
try {
const result = await detectionApi.run({
project_id: selectedProjectId,
dataset_id: datasetId,
model_id: selectedDetectionModelId,
model_asset_id: selectedModelAssetId || null,
confidence_threshold: threshold,
tile_manifest_path: detectionTileManifestPath.trim() || null,
parameters_json: { calibration: true, calibration_thresholds: thresholds },
})
setSelectedDetectionRunId(result.analysis_run_id)
const qa = await detectionApi.compareWithReference(result.analysis_run_id, {
reference_dataset_id: detectionReferenceDatasetId,
iou_threshold: qaIouThreshold,
class_name: detectionClassFilter || null,
min_confidence: null,
})
setDetectionCalibrationRows((rows) =>
rows.map((row) => row.threshold === threshold
? {
...row,
status: 'success',
analysis_run_id: result.analysis_run_id,
job_id: result.job_id,
quality_check_id: qa.quality_check_id,
detection_count: result.detection_count,
precision: qa.precision ?? null,
recall: qa.recall ?? null,
f1_score: qa.f1_score ?? null,
false_positives: qa.false_positives,
false_negatives: qa.false_negatives,
message: result.message,
}
: row),
)
} catch (error) {
const message = formatError(error, `Calibration threshold ${threshold} failed`)
setDetectionCalibrationRows((rows) =>
rows.map((row) => row.threshold === threshold ? { ...row, status: 'failed', message } : row),
)
setDetectionCalibrationError(message)
break
}
}
await loadDetectionRuns(selectedProjectId)
await loadQualityChecks(selectedProjectId)
await loadProjectData(selectedProjectId)
} finally {
setRunningDetectionCalibration(false)
}
}
const applyDetectionOperatorProfile = (profile: DetectionOperatorProfileSelection) => {
setSelectedDetectionModelId('yolo-configured')
setSelectedModelAssetId(profile.modelAssetId)
setDetectionConfidenceThreshold(profile.confidenceThreshold)
}
const resetDetectionForProject = () => {
setSelectedDetectionDatasetId('')
setDetectionRuns([])
setSelectedDetectionRunId('')
setDetectionItems([])
setDetectionGeoJson(null)
setDetectionRunResult(null)
setDetectionCalibrationRows([])
setDetectionCalibrationError(null)
}
return {
detectionModels,
modelAssets,
loadingDetectionModels,
detectionModelError,
modelAssetError,
selectedDetectionDatasetId,
selectedDetectionModelId,
selectedModelAssetId,
detectionTileManifestPath,
detectionConfidenceThreshold,
runningDetection,
detectionRunResult,
detectionRunError,
detectionRuns,
selectedDetectionRunId,
detectionItems,
detectionGeoJson,
detectionClassFilter,
detectionMinConfidenceFilter,
loadingDetectionResults,
detectionReferenceDatasetId,
detectionQaResult,
detectionQaError,
runningDetectionQa,
yoloPreflight,
loadingYoloPreflight,
yoloPreflightError,
calibrationThresholdText,
runningDetectionCalibration,
detectionCalibrationRows,
detectionCalibrationError,
loadDetectionModels,
loadYoloPreflight,
loadDetectionRuns,
loadDetectionResults,
runDetection,
runDetectionQa,
runDetectionCalibration,
applyDetectionOperatorProfile,
resetDetectionForProject,
setSelectedDetectionDatasetId,
setSelectedDetectionModelId,
setSelectedModelAssetId,
setDetectionTileManifestPath,
setDetectionConfidenceThreshold,
setSelectedDetectionRunId,
setDetectionClassFilter,
setDetectionMinConfidenceFilter,
setDetectionReferenceDatasetId,
setCalibrationThresholdText,
}
}