fix(lab): preserve replay view and restore SLAM semantics
This commit is contained in:
DCCONSTRUCTIONS
@@ -4,6 +4,10 @@ import type {
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RecordedEvidenceSemanticClass,
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RecordedEvidenceSemanticPaletteEntry,
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} from "../../components/laboratory/RecordedEvidenceSemanticMaskOverlay";
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import {
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fetchE47SemanticSlamResult,
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type E47SemanticSlamResult,
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} from "../../core/laboratory/e47SemanticSlam";
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import {
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fetchM49TgsFullShadowSpatialChunk,
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type M49TgsFullShadowResult,
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@@ -46,6 +50,8 @@ function message(error: unknown): string {
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export function M49TgsFullShadowEvidence({ result }: { result: M49TgsFullShadowResult }) {
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const [activeSequence, setActiveSequence] = useState<number | null>(null);
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const [semantic, setSemantic] = useState<E47SemanticSlamResult | null>(null);
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const [semanticError, setSemanticError] = useState<string | null>(null);
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const [chunks, setChunks] = useState<ReadonlyMap<number, M49TgsFullShadowSpatialChunk>>(
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() => new Map(),
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);
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@@ -57,6 +63,27 @@ export function M49TgsFullShadowEvidence({ result }: { result: M49TgsFullShadowR
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const activeChunkStartRef = useRef(activeChunkStart);
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activeChunkStartRef.current = activeChunkStart;
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useEffect(() => {
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const controller = new AbortController();
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setSemantic(null);
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setSemanticError(null);
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void fetchE47SemanticSlamResult({
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resultId: result.source.linkedSemanticResultId,
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signal: controller.signal,
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})
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.then((next) => {
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if (controller.signal.aborted) return;
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if (!next || next.baseM4ResultId !== result.source.linkedVisualResultId) {
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throw new Error("Semantic archive не совпал с исходным M4 timeline.");
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}
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setSemantic(next);
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})
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.catch((caught: unknown) => {
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if (!controller.signal.aborted) setSemanticError(message(caught));
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});
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return () => controller.abort();
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}, [result.source.linkedSemanticResultId, result.source.linkedVisualResultId]);
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useEffect(() => {
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for (const controller of inFlightRef.current.values()) controller.abort();
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inFlightRef.current.clear();
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@@ -142,23 +169,34 @@ export function M49TgsFullShadowEvidence({ result }: { result: M49TgsFullShadowR
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}, []);
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return (
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<M4ReplayThreatVisual
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resultId={result.source.linkedVisualResultId}
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showReviewAnchorBoxes={false}
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reviewLabel="4 489 source-paced TGS frames"
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evidenceLabel="M49 · full TGS shadow"
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initialSpatialMode="3d"
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onActiveSequenceChange={handleSequenceChange}
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classifiedSpatialLayer={{
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label: "TGS full shadow · causal rolling 1 s",
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pointLayerLabel: "SOURCE POINTS",
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cellLayerLabel: "TGS COSTMAP",
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expectedAtSequence: true,
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frame: classifiedFrame,
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loading,
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error,
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replacePointCloud: false,
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}}
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/>
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<>
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<M4ReplayThreatVisual
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resultId={result.source.linkedVisualResultId}
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semantic={semantic ? {
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resultId: semantic.resultId,
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taxonomy: semantic.taxonomy,
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} : undefined}
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showReviewAnchorBoxes={false}
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reviewLabel="4 489 source-paced TGS frames"
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evidenceLabel="M49 · full TGS shadow"
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initialSpatialMode="3d"
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onActiveSequenceChange={handleSequenceChange}
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classifiedSpatialLayer={{
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label: "TGS full shadow · causal rolling 1 s",
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pointLayerLabel: "SOURCE POINTS",
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cellLayerLabel: "TGS COSTMAP",
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expectedAtSequence: true,
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frame: classifiedFrame,
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loading,
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error,
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replacePointCloud: false,
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}}
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/>
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{semanticError ? (
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<div className="m4-replay-threat-visual__pane-status" role="alert">
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Semantic overlay недоступен: {semanticError}
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</div>
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) : null}
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</>
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);
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}
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@@ -409,6 +409,17 @@ export function M4ReplayThreatVisual({
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const classifiedSpatialFrame = classifiedSpatialLayer?.frame?.sourceSequence === timelineFrame.activeSequence
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? classifiedSpatialLayer?.frame ?? null
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: null;
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const lastClassifiedSpatialFrameRef = useRef<{
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resultId: string;
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frame: M4ReplayClassifiedSpatialFrame;
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} | null>(null);
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if (classifiedSpatialLayer?.frame) {
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lastClassifiedSpatialFrameRef.current = { resultId, frame: classifiedSpatialLayer.frame };
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}
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const displayedClassifiedSpatialFrame = classifiedSpatialFrame
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?? (lastClassifiedSpatialFrameRef.current?.resultId === resultId
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? lastClassifiedSpatialFrameRef.current.frame
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: null);
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const replaceClassifiedPointCloud = classifiedSpatialLayer?.replacePointCloud ?? true;
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const nominalSensorHeightM = metadata.timeline?.rig.nominalSensorHeightM ?? 0;
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const mapGravityLocalSensorToBodyGround = useCallback((
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@@ -425,13 +436,13 @@ export function M4ReplayThreatVisual({
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return [rotated[0], rotated[1], rotated[2] + nominalSensorHeightM];
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}, [activeSpatialFrame?.bodyFrame?.basisMapFromBody, nominalSensorHeightM]);
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const classifiedPointsBody = useMemo(
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() => classifiedSpatialFrame?.pointsMapGravityLocalXyzM.map(
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() => displayedClassifiedSpatialFrame?.pointsMapGravityLocalXyzM.map(
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mapGravityLocalSensorToBodyGround,
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) ?? [],
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[classifiedSpatialFrame, mapGravityLocalSensorToBodyGround],
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[displayedClassifiedSpatialFrame, mapGravityLocalSensorToBodyGround],
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);
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const classifiedCellsBody = useMemo<readonly LaboratoryMetricCellEvidence[]>(
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() => classifiedSpatialFrame?.cellsMapGravityLocal.map((cell) => {
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() => displayedClassifiedSpatialFrame?.cellsMapGravityLocal.map((cell) => {
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const body = mapGravityLocalSensorToBodyGround([
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cell.centerXyM[0],
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cell.centerXyM[1],
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@@ -451,7 +462,7 @@ export function M4ReplayThreatVisual({
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state: cell.state,
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};
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}) ?? [],
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[classifiedSpatialFrame, mapGravityLocalSensorToBodyGround, nominalSensorHeightM],
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[displayedClassifiedSpatialFrame, mapGravityLocalSensorToBodyGround, nominalSensorHeightM],
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);
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const classifiedCellCounts = useMemo(() => ({
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ground: classifiedSpatialFrame?.cellsMapGravityLocal.filter(
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@@ -641,6 +652,16 @@ export function M4ReplayThreatVisual({
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>
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{classifiedSpatialLayer.pointLayerLabel}
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</Button>
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<Button
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size="compact"
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shape="pill"
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variant={showLocalSurface ? "primary" : "secondary"}
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aria-pressed={showLocalSurface}
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title="Bounded local SLAM surface · visual-derived"
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onClick={() => setShowLocalSurface((visible) => !visible)}
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>
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LOCAL SLAM
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</Button>
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<Button
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size="compact"
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shape="pill"
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@@ -650,6 +671,17 @@ export function M4ReplayThreatVisual({
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>
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{classifiedSpatialLayer.cellLayerLabel}
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</Button>
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{semantic ? (
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<Button
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size="compact"
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shape="pill"
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variant={showSpatialSemantic ? "primary" : "secondary"}
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aria-pressed={showSpatialSemantic}
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onClick={() => setShowSpatialSemantic((visible) => !visible)}
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>
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SEMANTICS
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</Button>
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) : null}
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</div>
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) : (
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<div
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@@ -952,38 +984,38 @@ export function M4ReplayThreatVisual({
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</div>
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</div>
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) : null}
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{(!classifiedSpatialLayer ? spatialFrame : classifiedSpatialFrame) ? (
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{(!classifiedSpatialLayer ? spatialFrame : displayedClassifiedSpatialFrame) ? (
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<LaboratoryMetricEvidenceScene
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ref={metricSceneRef}
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pointCloudBodyXyzM={classifiedSpatialFrame && replaceClassifiedPointCloud
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pointCloudBodyXyzM={displayedClassifiedSpatialFrame && replaceClassifiedPointCloud
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? classifiedPointsBody
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: activeSpatialFrame?.pointCloudBodyXyzM ?? []}
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localSurfaceBodyXyzM={classifiedSpatialFrame ? [] : localSurface.pointsBodyXyzM}
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obstacles={classifiedSpatialFrame ? [] : sceneObstacles}
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localSurfaceBodyXyzM={localSurface.pointsBodyXyzM}
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obstacles={displayedClassifiedSpatialFrame ? [] : sceneObstacles}
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rig={timeline.rig}
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corridor={timeline.corridor}
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occupiedVoxelSizeM={classifiedSpatialFrame?.cellSizeM ?? timeline.occupiedVoxelSizeM}
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occupiedVoxelSizeM={displayedClassifiedSpatialFrame?.cellSizeM ?? timeline.occupiedVoxelSizeM}
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mode={spatialMode}
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label={`${evidenceLabel} exact current increment, bounded local SLAM surface and rolling occupancy`}
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showCurrentIncrement={showCurrentIncrement}
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showLocalSurface={classifiedSpatialFrame ? false : showLocalSurface}
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showLocalSurface={showLocalSurface}
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showRollingMap={showRollingMap}
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showLowStep={classifiedSpatialFrame ? false : showLowStep}
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pointSemanticClassIds={classifiedSpatialFrame && replaceClassifiedPointCloud
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? classifiedSpatialFrame.pointClassIds
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showLowStep={displayedClassifiedSpatialFrame ? false : showLowStep}
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pointSemanticClassIds={displayedClassifiedSpatialFrame && replaceClassifiedPointCloud
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? displayedClassifiedSpatialFrame.pointClassIds
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: alignedSemanticPointIds}
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semanticClasses={classifiedSpatialFrame && replaceClassifiedPointCloud
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? classifiedSpatialFrame.classes
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semanticClasses={displayedClassifiedSpatialFrame && replaceClassifiedPointCloud
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? displayedClassifiedSpatialFrame.classes
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: semanticClasses}
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semanticPalette={classifiedSpatialFrame && replaceClassifiedPointCloud
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? classifiedSpatialFrame.palette
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semanticPalette={displayedClassifiedSpatialFrame && replaceClassifiedPointCloud
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? displayedClassifiedSpatialFrame.palette
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: semanticPalette}
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classifiedCells={classifiedCellsBody}
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classifiedCellSizeM={classifiedSpatialFrame?.cellSizeM}
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classifiedCellSizeM={displayedClassifiedSpatialFrame?.cellSizeM}
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showClassifiedCells={showRollingMap}
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/>
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) : null}
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{classifiedSpatialLayer && !classifiedSpatialFrame ? (
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{classifiedSpatialLayer && !displayedClassifiedSpatialFrame ? (
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<div className="l3-visual-audit__state" role={classifiedSpatialLayer.error ? "alert" : "status"}>
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{classifiedSpatialLayer.loading || displayingBufferedFrame
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? <span className="busy-indicator" aria-hidden="true" />
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