refactor(lab): restore canonical RAV004 replay
This commit is contained in:
DCCONSTRUCTIONS
@@ -153,6 +153,7 @@ export interface M4ReplayClassifiedSpatialLayer {
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label: string;
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pointLayerLabel: string;
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cellLayerLabel: string;
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cellLayerAvailable?: boolean;
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expectedAtSequence: boolean;
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frame: M4ReplayClassifiedSpatialFrame | null;
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loading: boolean;
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@@ -178,6 +179,8 @@ export function M4ReplayThreatVisual({
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classifiedSpatialLayer,
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showReferenceMediaLayers = true,
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showSpatialOverlaySummary = true,
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playbackTransport = "epoch-stream",
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recoverTimestampStalls = false,
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onActiveSequenceChange,
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}: {
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resultId: string;
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@@ -194,6 +197,8 @@ export function M4ReplayThreatVisual({
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classifiedSpatialLayer?: M4ReplayClassifiedSpatialLayer;
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showReferenceMediaLayers?: boolean;
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showSpatialOverlaySummary?: boolean;
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playbackTransport?: "segmented" | "epoch-stream";
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recoverTimestampStalls?: boolean;
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onActiveSequenceChange?: (sequence: number | null) => void;
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}) {
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const {
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@@ -256,7 +261,7 @@ export function M4ReplayThreatVisual({
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showMediaSemantic: Boolean(activeSemantic) && showMediaSemantic,
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showSpatialSemantic: Boolean(activeSpatialSemantic) && showSpatialSemantic,
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showMediaPoints,
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classifiedSpatialMode: !classifiedSpatialLayer
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classifiedSpatialMode: !classifiedSpatialLayer || classifiedSpatialLayer.cellLayerAvailable === false
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? "none"
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: classifiedSpatialLayer.replacePointCloud
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? "replace-source"
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@@ -278,7 +283,7 @@ export function M4ReplayThreatVisual({
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endSeconds: metadata.timeline.timelineEndSeconds,
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}) : null, [metadata.timeline]);
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const playbackController = useRecordedEvidencePlayback(playbackRange, {
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clock: "animation",
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clock: "external",
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});
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const seekPlayback = playbackController.seek;
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const setPlaybackPlaying = playbackController.setPlaying;
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@@ -356,11 +361,19 @@ export function M4ReplayThreatVisual({
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useEffect(() => {
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lastSpatialFrameRef.current = null;
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}, [evidenceDemand.sourceSpatialPoints, resultId]);
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if (frame?.spatialAvailable) {
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lastSpatialFrameRef.current = { resultId, frame };
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const latestAvailableSpatialFrame = [...timelineFrame.availableFrames]
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.reverse()
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.find((candidate) => (
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candidate.spatialAvailable
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&& (timelineFrame.activeSequence === null
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|| candidate.sequence <= timelineFrame.activeSequence)
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)) ?? null;
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const currentSpatialFrame = frame?.spatialAvailable ? frame : latestAvailableSpatialFrame;
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if (currentSpatialFrame) {
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lastSpatialFrameRef.current = { resultId, frame: currentSpatialFrame };
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}
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const spatialFrame = frame?.spatialAvailable
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? frame
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const spatialFrame = currentSpatialFrame
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? currentSpatialFrame
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: lastSpatialFrameRef.current?.resultId === resultId
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? lastSpatialFrameRef.current.frame
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: null;
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@@ -541,14 +554,20 @@ export function M4ReplayThreatVisual({
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const activeSpatialFrame = spatialFrame?.sequence === timelineFrame.activeSequence
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? spatialFrame
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: null;
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const classifiedSpatialFrame = classifiedSpatialLayer?.frame?.sourceSequence === timelineFrame.activeSequence
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const hasClassifiedSpatialOutput = Boolean(
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classifiedSpatialLayer && classifiedSpatialLayer.cellLayerAvailable !== false,
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);
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const classifiedSpatialFrame = hasClassifiedSpatialOutput
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&& 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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const incomingClassifiedSpatialFrame = classifiedSpatialLayer?.frame ?? null;
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const incomingClassifiedSpatialFrame = hasClassifiedSpatialOutput
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? classifiedSpatialLayer?.frame ?? null
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: null;
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if (incomingClassifiedSpatialFrame && incomingClassifiedSpatialFrame.sampleAvailable !== false) {
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lastClassifiedSpatialFrameRef.current = { resultId, frame: incomingClassifiedSpatialFrame };
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}
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@@ -577,7 +596,9 @@ export function M4ReplayThreatVisual({
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? spatialFrame
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: null)
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: null;
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const replaceClassifiedPointCloud = classifiedSpatialLayer?.replacePointCloud ?? true;
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const replaceClassifiedPointCloud = hasClassifiedSpatialOutput
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? classifiedSpatialLayer?.replacePointCloud ?? true
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: false;
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const nominalSensorHeightM = metadata.timeline?.rig.nominalSensorHeightM ?? 0;
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const mapGravityLocalSensorToBodyGround = useCallback((
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point: readonly [number, number, number],
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@@ -695,7 +716,12 @@ export function M4ReplayThreatVisual({
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.map((item) => item.assessment.closestApproachM)
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.filter((value): value is number => value !== null)
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.sort((left, right) => left - right)[0] ?? null;
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const localSurface = useMemo(() => buildM4LocalSurface(
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const localSurface = useMemo(() => spatialFrame?.localSlamBodyXyzM?.length ? ({
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pointsBodyXyzM: spatialFrame.localSlamBodyXyzM,
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sourceFrameCount: spatialFrame.localSlamSourceFrameCount ?? 0,
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sourcePointCount: spatialFrame.localSlamSourcePointCount ?? 0,
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voxelCount: spatialFrame.localSlamBodyXyzM.length,
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}) : buildM4LocalSurface(
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timelineFrame.availableFrames,
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spatialFrame,
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metadata.timeline?.localSurfaceVisualization ?? {
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@@ -843,16 +869,24 @@ export function M4ReplayThreatVisual({
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shape="pill"
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variant={showRollingMap ? "primary" : "secondary"}
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aria-pressed={showRollingMap}
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disabled={classifiedSpatialLayer.cellLayerAvailable === false}
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title={classifiedSpatialLayer.cellLayerAvailable === false
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? `${classifiedSpatialLayer.cellLayerLabel} недоступен: для этой записи нет запечатанного полного результата`
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: undefined}
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onClick={() => setShowRollingMap((visible) => !visible)}
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>
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{classifiedSpatialLayer.cellLayerLabel}
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</Button>
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{semanticSpatialResultId ? (
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{activeSpatialSemantic ? (
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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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disabled={!semanticSpatialResultId}
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title={semanticSpatialResultId
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? "Point-aligned semantic evidence"
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: "Point-aligned 3D semantics отсутствует в запечатанном результате"}
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onClick={() => setShowSpatialSemantic((visible) => !visible)}
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>
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SEMANTICS
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@@ -905,12 +939,16 @@ export function M4ReplayThreatVisual({
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LOW-STEP
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</Button>
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) : null}
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{semanticSpatialResultId ? (
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{activeSpatialSemantic ? (
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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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disabled={!semanticSpatialResultId}
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title={semanticSpatialResultId
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? "Point-aligned semantic evidence"
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: "Point-aligned 3D semantics отсутствует в запечатанном результате"}
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onClick={() => setShowSpatialSemantic((visible) => !visible)}
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>
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SEMANTICS
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@@ -1014,14 +1052,14 @@ export function M4ReplayThreatVisual({
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<>
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<div>
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<span>Spatial evidence</span>
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<strong>{classifiedSpatialLayer
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<strong>{hasClassifiedSpatialOutput
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? classifiedSpatialFrame
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? replaceClassifiedPointCloud
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? `${classifiedSpatialFrame.pointsMapGravityLocalXyzM.length.toLocaleString("ru-RU")} TGS points · ${classifiedCellCount.toLocaleString("ru-RU")} cells`
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: `${(activeSpatialFrame?.pointCloudSourceCount ?? classifiedSpatialFrame.sourcePointCount ?? 0).toLocaleString("ru-RU")} source points · ${classifiedCellCount.toLocaleString("ru-RU")} TGS cells`
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: "TGS spatial buffer"
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: `${currentIncrementObstacles.length} current · ${rollingMapObstacles.length} rolling${metadata.timeline.occupancyProvenanceDelivery ? ` · ${lowStepObstacles.length} low-step` : ""}`}</strong>
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<small>{classifiedSpatialLayer
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<small>{hasClassifiedSpatialOutput
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? classifiedSpatialFrame
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? classifiedSpatialFrame.sampleAvailable === false
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? displayedClassifiedFrameHeld && displayedClassifiedSpatialFrame
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@@ -1030,9 +1068,9 @@ export function M4ReplayThreatVisual({
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: activeSpatialFrame
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? "map-gravity-local · all eligible points accounted · causal rolling 1 s"
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: "TGS рассчитан · linked source cloud недоступен для этого кадра"
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: classifiedSpatialLayer.error
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?? classifiedSpatialLayer.loadingLabel
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?? `Открываем ${classifiedSpatialLayer.label}`
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: classifiedSpatialLayer?.error
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?? classifiedSpatialLayer?.loadingLabel
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?? `Открываем ${classifiedSpatialLayer?.label ?? "spatial evidence"}`
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: (
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<>
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{spatialFrame
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@@ -1057,13 +1095,13 @@ export function M4ReplayThreatVisual({
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)}</small>
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</div>
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<div>
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<span>{classifiedSpatialLayer ? "TGS fail-closed" : "Virtual corridor"}</span>
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<strong>{classifiedSpatialLayer
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<span>{hasClassifiedSpatialOutput ? "TGS fail-closed" : "Virtual corridor"}</span>
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<strong>{hasClassifiedSpatialOutput
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? classifiedSpatialFrame
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? `${classifiedCellCounts.occupied} occupied · ${classifiedCellCounts.rejected} rejected · ${classifiedCellCounts.unobserved} unobserved`
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: classifiedSpatialLayer.loading || displayingBufferedFrame ? "loading" : "unavailable"
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: classifiedSpatialLayer?.loading || displayingBufferedFrame ? "loading" : "unavailable"
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: `${spatialFrame?.decisionCounts.threat ?? 0} threat · nearest ${nearest === null ? "—" : `${nearest.toFixed(2)} м`}`}</strong>
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<small>{classifiedSpatialLayer
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<small>{hasClassifiedSpatialOutput
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? classifiedSpatialFrame
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? `${classifiedCellCounts.ground} ground-support · visual review only · navigation authority OFF`
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: "visual review only · navigation authority OFF"
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@@ -1116,8 +1154,9 @@ export function M4ReplayThreatVisual({
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}
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segmentCount={timeline.frameCount}
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onPlaybackChange={playbackController.synchronize}
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playbackAuthority="host"
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playbackTransport="epoch-stream"
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playbackAuthority="media"
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playbackTransport={playbackTransport}
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recoverTimestampStalls={recoverTimestampStalls}
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/>
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) : videoError ? (
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<SpatialState message={videoError} />
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@@ -1148,9 +1187,11 @@ export function M4ReplayThreatVisual({
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ref={metricSceneRef}
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pointCloudBodyXyzM={displayedClassifiedSpatialFrame && replaceClassifiedPointCloud
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? classifiedPointsBody
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: classifiedContextSpatialFrame?.pointCloudBodyXyzM ?? []}
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: classifiedContextSpatialFrame?.pointCloudBodyXyzM
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?? activeSpatialFrame?.pointCloudBodyXyzM
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?? []}
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localSurfaceBodyXyzM={localSurface.pointsBodyXyzM}
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obstacles={classifiedSpatialLayer ? [] : sceneObstacles}
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obstacles={hasClassifiedSpatialOutput ? [] : sceneObstacles}
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rig={timeline.rig}
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corridor={timeline.corridor}
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occupiedVoxelSizeM={displayedClassifiedSpatialFrame?.cellSizeM ?? timeline.occupiedVoxelSizeM}
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@@ -1159,7 +1200,7 @@ export function M4ReplayThreatVisual({
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showCurrentIncrement={showCurrentIncrement}
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showLocalSurface={showLocalSurface}
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showRollingMap={showRollingMap}
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showLowStep={classifiedSpatialLayer ? false : showLowStep}
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showLowStep={hasClassifiedSpatialOutput ? false : showLowStep}
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pointSemanticClassIds={displayedClassifiedSpatialFrame && replaceClassifiedPointCloud
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? displayedClassifiedSpatialFrame.pointClassIds
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: alignedSemanticPointIds}
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@@ -1174,7 +1215,7 @@ export function M4ReplayThreatVisual({
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classifiedCellSizeM={displayedClassifiedSpatialFrame?.cellSizeM}
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showClassifiedCells={showRollingMap}
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/>
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{classifiedSpatialLayer && !displayedClassifiedSpatialFrame ? (
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{hasClassifiedSpatialOutput && 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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@@ -1,30 +1,5 @@
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import {
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useEffect,
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useMemo,
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useRef,
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useState,
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type CSSProperties,
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} from "react";
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import {
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Button,
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Icon,
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IconButton,
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SegmentedControl,
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} from "@nodedc/ui-react";
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import { useEffect, useMemo, useState } from "react";
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import { ObservationTimeline } from "../../components/ObservationTimeline";
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import {
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CanonicalRecordedLabReplay,
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useCanonicalRecordedLabReplayState,
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} from "../../components/laboratory/CanonicalRecordedLabReplay";
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import {
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LaboratoryMetricEvidenceScene,
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type LaboratoryMetricEvidenceSceneHandle,
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type LaboratoryMetricPackedCellEvidence,
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} from "../../components/laboratory/LaboratoryMetricEvidenceScene";
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import { RecordedEvidenceVideoScene } from "../../components/laboratory/RecordedEvidenceVideoScene";
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import { useCanonicalRecordedLabSpatialFrame } from "../../components/laboratory/useCanonicalRecordedLabSpatialFrame";
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import { useRecordedEvidencePlayback } from "../../components/laboratory/useRecordedEvidencePlayback";
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import {
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LaboratoryEvidence,
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LaboratoryResultSummary,
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@@ -32,23 +7,9 @@ import {
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LaboratoryWorkTemplate,
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} from "../../components/laboratory/LaboratoryPresentation";
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import {
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type RecordedEvidenceSemanticClass,
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type RecordedEvidenceSemanticPaletteEntry,
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} from "../../components/laboratory/RecordedEvidenceSemanticMaskOverlay";
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import {
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canonicalRecordedLabPackedTgsCells,
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canonicalRecordedLabTgsIsCurrent,
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} from "../../core/laboratory/canonicalRecordedLab";
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import {
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fetchVegetationShadowResult,
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fetchVegetationRouteTgsAnchor,
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vegetationFullRouteMaskUrl,
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vegetationVideoMaskUrl,
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type VegetationFullRouteLayer,
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type VegetationFullRouteReview,
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type VegetationMixedRouteCase,
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type VegetationMixedRouteReview,
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type VegetationRouteTgsAnchor,
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type VegetationShadowResult,
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} from "../../core/laboratory/vegetationShadow";
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import {
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@@ -56,81 +17,18 @@ import {
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type M49TgsFullShadowResult,
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} from "../../core/laboratory/m49TgsFullShadow";
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import { M49TgsFullShadowEvidence } from "./M49TgsFullShadowEvidence";
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import { recordedObservationSources } from "../../core/observation/recordedObservationSources";
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import type { ObservationSessionReplayLaunch } from "../../core/observation/sessionArchive";
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import { resolveObservationSessionReplay } from "../../core/observation/useObservationSessions";
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import type { ObservationSourceDescriptor } from "../../core/runtime/contracts";
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import {
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M4ReplayThreatVisual,
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type M4ReplayClassifiedSpatialLayer,
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type M4ReplayThreatSemanticLayer,
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} from "./M4ReplayThreatVisual";
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const VEGETATION_TIMELINE_ENDPOINT = "/api/v1/laboratory/vegetation-shadow";
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function decimal(value: number, digits = 1): string {
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return value.toLocaleString("ru-RU", { maximumFractionDigits: digits });
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}
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const FULL_ROUTE_SEMANTIC_MODES = [
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{ value: "city", label: "ГОРОД · EoMT" },
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{ value: "vegetation", label: "ПРИРОДА · DDRNet" },
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] as const;
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type FullRouteMediaMode = "video" | "camera";
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type FullRouteSpatialMode = "3d" | "plan";
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const FULL_ROUTE_MEDIA_MODES = [
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{ value: "video", label: "VIDEO" },
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{ value: "camera", label: "CAMERA" },
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] as const;
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const FULL_ROUTE_SPATIAL_MODES = [
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{ value: "3d", label: "3D" },
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{ value: "plan", label: "PLAN" },
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] as const;
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function semanticPresentation(layer: VegetationFullRouteLayer): {
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classes: readonly RecordedEvidenceSemanticClass[];
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palette: readonly RecordedEvidenceSemanticPaletteEntry[];
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} {
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return {
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classes: layer.taxonomy.map((item) => ({ id: item.classId, label: item.label })),
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palette: layer.taxonomy.map((item) => ({
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classId: item.classId,
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color: item.classId === 0
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? { kind: "transparent" as const }
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: { kind: "diagnostic" as const, rgb: item.colorRgb },
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})),
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};
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}
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function causalTgsCase(
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cases: readonly VegetationMixedRouteCase[],
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sequence: number,
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): VegetationMixedRouteCase | null {
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if (!cases.length) return null;
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return cases.reduce<VegetationMixedRouteCase | null>((latest, candidate) => (
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candidate.sourceSequence <= sequence
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&& (!latest || candidate.sourceSequence > latest.sourceSequence)
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? candidate
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: latest
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), null);
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}
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function nearestFullRouteFrameIndex(
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frameSourceTimesNs: readonly number[],
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sourceTimeNs: number,
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): number {
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if (!frameSourceTimesNs.length) return 0;
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let low = 0;
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let high = frameSourceTimesNs.length - 1;
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while (low < high) {
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const middle = Math.floor((low + high) / 2);
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if ((frameSourceTimesNs[middle] ?? 0) < sourceTimeNs) low = middle + 1;
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else high = middle;
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}
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if (low === 0) return 0;
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const previous = frameSourceTimesNs[low - 1] ?? frameSourceTimesNs[0] ?? 0;
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const current = frameSourceTimesNs[low] ?? previous;
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return Math.abs(sourceTimeNs - previous) <= Math.abs(current - sourceTimeNs)
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? low - 1
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: low;
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}
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function FullRouteReviewEvidence({
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resultId,
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review,
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@@ -138,425 +36,53 @@ function FullRouteReviewEvidence({
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resultId: string;
|
||||
review: VegetationFullRouteReview;
|
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}) {
|
||||
const {
|
||||
mediaMode,
|
||||
spatialMode,
|
||||
splitView,
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||||
splitPrimarySize,
|
||||
splitOrientation,
|
||||
expanded,
|
||||
onMediaModeChange: handleMediaModeChange,
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onSpatialModeChange: handleSpatialModeChange,
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onSplitPrimarySizeChange: setSplitPrimarySize,
|
||||
onExpandedChange: setExpanded,
|
||||
} = useCanonicalRecordedLabReplayState<FullRouteMediaMode, FullRouteSpatialMode>({
|
||||
initialMediaMode: "video",
|
||||
initialSpatialMode: "3d",
|
||||
});
|
||||
const [semanticLayer, setSemanticLayer] = useState<"city" | "vegetation">("vegetation");
|
||||
const [showCameraSemantic, setShowCameraSemantic] = useState(true);
|
||||
const [showSourcePoints, setShowSourcePoints] = useState(true);
|
||||
const [showLocalSlam, setShowLocalSlam] = useState(true);
|
||||
const [showTgs, setShowTgs] = useState(true);
|
||||
const [videoSource, setVideoSource] = useState<ObservationSourceDescriptor | null>(null);
|
||||
const [replayLaunch, setReplayLaunch] = useState<ObservationSessionReplayLaunch | null>(null);
|
||||
const [videoError, setVideoError] = useState<string | null>(null);
|
||||
const [linkedReview, setLinkedReview] = useState<VegetationMixedRouteReview | null>(null);
|
||||
const [linkedReviewError, setLinkedReviewError] = useState<string | null>(null);
|
||||
const [tgsAnchor, setTgsAnchor] = useState<VegetationRouteTgsAnchor | null>(null);
|
||||
const [tgsAnchorLoading, setTgsAnchorLoading] = useState(false);
|
||||
const [tgsAnchorError, setTgsAnchorError] = useState<string | null>(null);
|
||||
const metricSceneRef = useRef<LaboratoryMetricEvidenceSceneHandle | null>(null);
|
||||
const playbackRange = useMemo(() => ({
|
||||
startSeconds: review.timelineStartSeconds,
|
||||
endSeconds: review.timelineEndSeconds,
|
||||
}), [review.timelineEndSeconds, review.timelineStartSeconds]);
|
||||
const playbackController = useRecordedEvidencePlayback(playbackRange, { clock: "animation" });
|
||||
const sequenceIndex = nearestFullRouteFrameIndex(
|
||||
review.frameSourceTimesNs,
|
||||
Math.round(playbackController.playback.currentSeconds * 1_000_000_000),
|
||||
);
|
||||
const sequence = sequenceIndex + 1;
|
||||
const spatialRequestIndex = Math.floor(sequenceIndex / 5) * 5;
|
||||
const spatialRequestTimeNs = review.frameSourceTimesNs[spatialRequestIndex]
|
||||
?? review.frameSourceTimesNs[sequenceIndex]
|
||||
?? Math.round(playbackController.playback.currentSeconds * 1_000_000_000);
|
||||
const spatialEvidence = useCanonicalRecordedLabSpatialFrame({
|
||||
sessionId: review.sessionId,
|
||||
generationSha256: replayLaunch?.sha256 ?? null,
|
||||
targetTimeNs: spatialRequestTimeNs,
|
||||
});
|
||||
const layer = review[semanticLayer];
|
||||
const semantic = useMemo(() => semanticPresentation(layer), [layer]);
|
||||
const prefetchSrcs = useMemo(() => showCameraSemantic
|
||||
? Array.from({ length: 8 }, (_, offset) => sequenceIndex + offset + 1)
|
||||
.filter((candidate) => candidate < review.frameCount)
|
||||
.map((candidate) => vegetationFullRouteMaskUrl(resultId, semanticLayer, candidate))
|
||||
: [], [resultId, review.frameCount, semanticLayer, sequenceIndex, showCameraSemantic]);
|
||||
|
||||
useEffect(() => {
|
||||
const controller = new AbortController();
|
||||
setVideoSource(null);
|
||||
setReplayLaunch(null);
|
||||
setVideoError(null);
|
||||
void resolveObservationSessionReplay(review.sessionId, { signal: controller.signal })
|
||||
.then((launch) => {
|
||||
const source = recordedObservationSources(launch).find((candidate) => (
|
||||
candidate.id === review.recordedMediaSourceId
|
||||
&& candidate.modality === "video"
|
||||
&& candidate.semanticChannelId === "camera.video.recorded"
|
||||
&& candidate.delivery?.kind === "recorded-fmp4-manifest"
|
||||
&& candidate.delivery.manifestGenerationSha256 === review.recordedMediaGenerationSha256
|
||||
&& candidate.delivery.timelineStartSeconds === review.timelineStartSeconds
|
||||
&& candidate.delivery.timelineEndSeconds >= review.timelineEndSeconds
|
||||
));
|
||||
if (!source) {
|
||||
throw new Error("RIGHT-видео не совпало с sealed RAVNOVES004TREE timeline.");
|
||||
}
|
||||
if (!controller.signal.aborted) {
|
||||
setVideoSource(source);
|
||||
setReplayLaunch(launch);
|
||||
}
|
||||
})
|
||||
.catch((caught: unknown) => {
|
||||
if (!controller.signal.aborted) {
|
||||
setVideoError(caught instanceof Error ? caught.message : "Записанное видео недоступно.");
|
||||
}
|
||||
});
|
||||
return () => controller.abort();
|
||||
}, [
|
||||
review.recordedMediaGenerationSha256,
|
||||
review.recordedMediaSourceId,
|
||||
review.sessionId,
|
||||
review.timelineEndSeconds,
|
||||
review.timelineStartSeconds,
|
||||
]);
|
||||
|
||||
useEffect(() => {
|
||||
const controller = new AbortController();
|
||||
setLinkedReview(null);
|
||||
setLinkedReviewError(null);
|
||||
void fetchVegetationShadowResult(review.linkedRouteReviewResultId, {
|
||||
signal: controller.signal,
|
||||
}).then((result) => {
|
||||
if (
|
||||
!result.routeReview
|
||||
|| result.routeReview.sourceId !== review.sourceId
|
||||
|| result.routeReview.sessionId !== review.sessionId
|
||||
) {
|
||||
throw new Error("TGS anchors имеют другую source identity.");
|
||||
}
|
||||
if (!controller.signal.aborted) setLinkedReview(result.routeReview);
|
||||
}).catch((caught: unknown) => {
|
||||
if (!controller.signal.aborted) {
|
||||
setLinkedReviewError(caught instanceof Error ? caught.message : "TGS anchors недоступны.");
|
||||
}
|
||||
});
|
||||
return () => controller.abort();
|
||||
}, [review.linkedRouteReviewResultId, review.sessionId, review.sourceId]);
|
||||
|
||||
const selectedTgsCase = linkedReview
|
||||
? causalTgsCase(linkedReview.cases, sequence)
|
||||
: null;
|
||||
const selectedTgsTimeNs = selectedTgsCase
|
||||
? review.frameSourceTimesNs[selectedTgsCase.sourceSequence - 1]
|
||||
?? Math.round(selectedTgsCase.sessionSeconds * 1_000_000_000)
|
||||
: spatialRequestTimeNs;
|
||||
const currentFrameTimeNs = review.frameSourceTimesNs[sequenceIndex]
|
||||
?? Math.round(playbackController.playback.currentSeconds * 1_000_000_000);
|
||||
const tgsWithinEvidenceWindow = Boolean(
|
||||
selectedTgsCase
|
||||
&& canonicalRecordedLabTgsIsCurrent(currentFrameTimeNs, selectedTgsTimeNs),
|
||||
);
|
||||
const tgsReferenceEvidence = useCanonicalRecordedLabSpatialFrame({
|
||||
sessionId: review.sessionId,
|
||||
generationSha256: replayLaunch?.sha256 ?? null,
|
||||
targetTimeNs: selectedTgsTimeNs,
|
||||
});
|
||||
|
||||
useEffect(() => {
|
||||
if (!showTgs || !selectedTgsCase) {
|
||||
setTgsAnchor(null);
|
||||
setTgsAnchorLoading(false);
|
||||
setTgsAnchorError(null);
|
||||
return;
|
||||
}
|
||||
const controller = new AbortController();
|
||||
setTgsAnchorLoading(true);
|
||||
setTgsAnchorError(null);
|
||||
void fetchVegetationRouteTgsAnchor(
|
||||
review.linkedRouteReviewResultId,
|
||||
selectedTgsCase.sourceSequence,
|
||||
{ signal: controller.signal },
|
||||
).then((anchor) => {
|
||||
if (!controller.signal.aborted) setTgsAnchor(anchor);
|
||||
}).catch((caught: unknown) => {
|
||||
if (!controller.signal.aborted) {
|
||||
setTgsAnchorError(caught instanceof Error ? caught.message : "TGS anchor недоступен.");
|
||||
}
|
||||
}).finally(() => {
|
||||
if (!controller.signal.aborted) setTgsAnchorLoading(false);
|
||||
});
|
||||
return () => controller.abort();
|
||||
}, [review.linkedRouteReviewResultId, selectedTgsCase?.sourceSequence, showTgs]);
|
||||
|
||||
const packedTgsCells = useMemo<LaboratoryMetricPackedCellEvidence | undefined>(() => {
|
||||
if (!tgsAnchor || !tgsWithinEvidenceWindow) return undefined;
|
||||
const currentBody = spatialEvidence.frame?.bodyFrame;
|
||||
const anchorBody = tgsReferenceEvidence.frame?.bodyFrame;
|
||||
if (!currentBody || !anchorBody) return undefined;
|
||||
return canonicalRecordedLabPackedTgsCells(tgsAnchor.costmap, anchorBody, currentBody);
|
||||
}, [
|
||||
spatialEvidence.frame?.bodyFrame,
|
||||
tgsAnchor,
|
||||
tgsReferenceEvidence.frame?.bodyFrame,
|
||||
tgsWithinEvidenceWindow,
|
||||
]);
|
||||
|
||||
const semanticOverlay = showCameraSemantic ? {
|
||||
src: vegetationFullRouteMaskUrl(resultId, semanticLayer, sequenceIndex),
|
||||
prefetchSrcs,
|
||||
classes: semantic.classes,
|
||||
palette: semantic.palette,
|
||||
opacity: 0.46,
|
||||
ariaLabel: `${layer.name} semantic prediction frame ${sequence}`,
|
||||
} : undefined;
|
||||
|
||||
const mediaContent = (
|
||||
<div className="m4-replay-threat-visual__media-layer" data-media={mediaMode ?? "none"}>
|
||||
{videoSource ? (
|
||||
<RecordedEvidenceVideoScene
|
||||
source={videoSource}
|
||||
playback={playbackController.playback}
|
||||
imageWidth={review.width}
|
||||
imageHeight={review.height}
|
||||
boxes={[]}
|
||||
semanticOverlay={semanticOverlay}
|
||||
ariaLabel={`RAVNOVES004TREE recorded frame ${sequence}`}
|
||||
interactive={false}
|
||||
segmentSequence={sequence}
|
||||
segmentCount={review.frameCount}
|
||||
onPlaybackChange={playbackController.synchronize}
|
||||
playbackAuthority="host"
|
||||
playbackTransport="epoch-stream"
|
||||
/>
|
||||
) : (
|
||||
<div className="l3-visual-audit__state" role={videoError ? "alert" : "status"}>
|
||||
{videoError ?? "Открываем автономный RAVNOVES004TREE source…"}
|
||||
</div>
|
||||
)}
|
||||
</div>
|
||||
);
|
||||
|
||||
const spatialContent = spatialMode ? (
|
||||
<>
|
||||
{spatialEvidence.frame ? (
|
||||
<LaboratoryMetricEvidenceScene
|
||||
ref={metricSceneRef}
|
||||
pointCloudBodyXyzM={showSourcePoints
|
||||
? spatialEvidence.frame.sourcePointsBodyXyzM
|
||||
: []}
|
||||
localSurfaceBodyXyzM={showLocalSlam
|
||||
? spatialEvidence.frame.localSlamBodyXyzM
|
||||
: []}
|
||||
obstacles={[]}
|
||||
rig={{
|
||||
lengthM: 1,
|
||||
widthM: 0.8,
|
||||
nominalSensorHeightM: spatialEvidence.frame.sensorHeight.meters,
|
||||
}}
|
||||
corridor={{ forwardLengthM: 12, rearMarginM: 1, halfWidthM: 0.4 }}
|
||||
occupiedVoxelSizeM={tgsAnchor?.costmap.cellSizeM ?? 0.45}
|
||||
mode={spatialMode}
|
||||
label="RAV004 canonical source points, local SLAM and TGS costmap"
|
||||
showCurrentIncrement={showSourcePoints}
|
||||
showLocalSurface={showLocalSlam}
|
||||
showRollingMap={showTgs}
|
||||
showLowStep={false}
|
||||
classifiedPackedCells={packedTgsCells}
|
||||
classifiedCellSizeM={tgsAnchor?.costmap.cellSizeM}
|
||||
showClassifiedCells={showTgs && Boolean(packedTgsCells)}
|
||||
/>
|
||||
) : (
|
||||
<div className="l3-visual-audit__state" role={spatialEvidence.error ? "alert" : "status"}>
|
||||
{spatialEvidence.loading ? <span className="busy-indicator" aria-hidden="true" /> : null}
|
||||
<span>{spatialEvidence.error ?? "Открываем source points и Local SLAM из sealed RRD…"}</span>
|
||||
</div>
|
||||
)}
|
||||
{showTgs && selectedTgsCase ? (
|
||||
<div className="m4-replay-threat-visual__pane-status" role="status">
|
||||
{tgsAnchorError ?? linkedReviewError ?? (tgsAnchorLoading
|
||||
? `Открываем sealed TGS anchor ${selectedTgsCase.sourceSequence}; source/SLAM и общий clock продолжаются.`
|
||||
: tgsWithinEvidenceWindow
|
||||
? `TGS anchor ${selectedTgsCase.sourceSequence} из 10; source/SLAM и общий clock продолжаются.`
|
||||
: `TGS anchor ${selectedTgsCase.sourceSequence} старше доказанного окна 1 с; слой скрыт, playback продолжается.`)}
|
||||
</div>
|
||||
) : null}
|
||||
</>
|
||||
) : null;
|
||||
|
||||
const mediaLayerControls = (
|
||||
<div
|
||||
className="m4-replay-threat-visual__pane-layer-controls"
|
||||
role="group"
|
||||
aria-label="Слои камеры и видео"
|
||||
>
|
||||
<Button
|
||||
size="compact"
|
||||
shape="pill"
|
||||
variant={showCameraSemantic ? "primary" : "secondary"}
|
||||
aria-pressed={showCameraSemantic}
|
||||
onClick={() => setShowCameraSemantic((visible) => !visible)}
|
||||
>
|
||||
SEMANTICS
|
||||
</Button>
|
||||
<SegmentedControl
|
||||
value={semanticLayer}
|
||||
items={[...FULL_ROUTE_SEMANTIC_MODES]}
|
||||
label="Источник семантики"
|
||||
onChange={(value) => {
|
||||
setSemanticLayer(value);
|
||||
setShowCameraSemantic(true);
|
||||
}}
|
||||
/>
|
||||
</div>
|
||||
);
|
||||
|
||||
const spatialLayerControls = (
|
||||
<div
|
||||
className="m4-replay-threat-visual__pane-layer-controls"
|
||||
role="group"
|
||||
aria-label="Слои 3D и плана"
|
||||
>
|
||||
<Button
|
||||
size="compact"
|
||||
shape="pill"
|
||||
variant={showSourcePoints ? "primary" : "secondary"}
|
||||
aria-pressed={showSourcePoints}
|
||||
onClick={() => setShowSourcePoints((visible) => !visible)}
|
||||
>
|
||||
SOURCE POINTS
|
||||
</Button>
|
||||
<Button
|
||||
size="compact"
|
||||
shape="pill"
|
||||
variant={showLocalSlam ? "primary" : "secondary"}
|
||||
aria-pressed={showLocalSlam}
|
||||
onClick={() => setShowLocalSlam((visible) => !visible)}
|
||||
>
|
||||
LOCAL SLAM
|
||||
</Button>
|
||||
<Button
|
||||
size="compact"
|
||||
shape="pill"
|
||||
variant={showTgs ? "primary" : "secondary"}
|
||||
aria-pressed={showTgs}
|
||||
disabled={!linkedReview}
|
||||
title={linkedReviewError ?? "10 sealed causal TGS anchors; continuous TGS отсутствует"}
|
||||
onClick={() => setShowTgs((visible) => !visible)}
|
||||
>
|
||||
TGS COSTMAP
|
||||
</Button>
|
||||
<Button
|
||||
size="compact"
|
||||
shape="pill"
|
||||
variant={showCameraSemantic ? "primary" : "secondary"}
|
||||
aria-pressed={showCameraSemantic}
|
||||
title="Recorded semantic layer; camera-aligned prediction, без выдуманной 3D-проекции"
|
||||
onClick={() => setShowCameraSemantic((visible) => !visible)}
|
||||
>
|
||||
SEMANTICS
|
||||
</Button>
|
||||
</div>
|
||||
);
|
||||
|
||||
const resetSpatialView = (
|
||||
<IconButton
|
||||
label="Сбросить ракурс"
|
||||
onClick={() => metricSceneRef.current?.resetView()}
|
||||
>
|
||||
<Icon name="refresh" size={16} />
|
||||
</IconButton>
|
||||
);
|
||||
|
||||
const overlayPanePercent = splitView && splitOrientation === "vertical"
|
||||
? splitPrimarySize
|
||||
: 100;
|
||||
const overlay = (
|
||||
<div
|
||||
className="l3-visual-audit__overlay m4-replay-threat-visual__overlay"
|
||||
style={{
|
||||
"--m4-replay-threat-overlay-pane-width": `${overlayPanePercent}%`,
|
||||
} as CSSProperties}
|
||||
>
|
||||
<div>
|
||||
<span>RAVNOVES004TREE · recorded realtime</span>
|
||||
<strong>frame {sequence}/{review.frameCount}</strong>
|
||||
<small>
|
||||
+{(playbackController.playback.currentSeconds - review.timelineStartSeconds).toFixed(3)} с
|
||||
· {playbackController.playback.playing ? "воспроизведение" : "пауза / seek"}
|
||||
</small>
|
||||
</div>
|
||||
<div>
|
||||
<span>Spatial evidence</span>
|
||||
<strong>{showTgs && selectedTgsCase && tgsWithinEvidenceWindow
|
||||
? `TGS anchor ${selectedTgsCase.sourceSequence} · ${selectedTgsCase.tgs.occupiedCells} occupied`
|
||||
: "source RRD · points + bounded Local SLAM"}</strong>
|
||||
<small>{showTgs
|
||||
? "TGS visible only inside sealed 1 s evidence window · playback retained"
|
||||
: "5 s bounded Local SLAM · ground-rebased recorded source"}</small>
|
||||
</div>
|
||||
</div>
|
||||
);
|
||||
|
||||
const transport = (
|
||||
<ObservationTimeline
|
||||
className="m4-replay-threat-visual__timeline"
|
||||
active
|
||||
sourceCount={4}
|
||||
mode="recorded"
|
||||
seekable
|
||||
synchronization="host-arrival-best-effort"
|
||||
rangeNs={{
|
||||
min: Math.round(review.timelineStartSeconds * 1_000_000_000),
|
||||
max: Math.round(review.timelineEndSeconds * 1_000_000_000),
|
||||
}}
|
||||
currentNs={Math.round(playbackController.playback.currentSeconds * 1_000_000_000)}
|
||||
playing={playbackController.playback.playing}
|
||||
playbackRate={playbackController.playback.rate ?? 1}
|
||||
onSeek={(timeNs) => playbackController.seek(timeNs / 1_000_000_000)}
|
||||
onPlayingChange={playbackController.setPlaying}
|
||||
onPlaybackRateChange={playbackController.setRate}
|
||||
showJumpToEnd={false}
|
||||
/>
|
||||
);
|
||||
const semanticLayers = useMemo<readonly M4ReplayThreatSemanticLayer[]>(() => ([
|
||||
{
|
||||
id: "city",
|
||||
controlLabel: "ГОРОД · EoMT",
|
||||
resultId,
|
||||
spatialResultId: null,
|
||||
taxonomy: review.city.taxonomy,
|
||||
maskUrl: (sequence) => vegetationFullRouteMaskUrl(resultId, "city", sequence),
|
||||
label: review.city.name,
|
||||
maskAriaLabel: "EoMT city semantic prediction",
|
||||
},
|
||||
{
|
||||
id: "vegetation",
|
||||
controlLabel: "ПРИРОДА · DDRNet",
|
||||
resultId,
|
||||
spatialResultId: null,
|
||||
taxonomy: review.vegetation.taxonomy,
|
||||
maskUrl: (sequence) => vegetationFullRouteMaskUrl(resultId, "vegetation", sequence),
|
||||
label: review.vegetation.name,
|
||||
maskAriaLabel: "DDRNet nature semantic prediction",
|
||||
},
|
||||
]), [resultId, review.city, review.vegetation]);
|
||||
const sealedSpatialGap = useMemo<M4ReplayClassifiedSpatialLayer>(() => ({
|
||||
label: "RAVNOVES004TREE",
|
||||
pointLayerLabel: "SOURCE POINTS",
|
||||
cellLayerLabel: "TGS COSTMAP",
|
||||
cellLayerAvailable: false,
|
||||
expectedAtSequence: false,
|
||||
frame: null,
|
||||
loading: false,
|
||||
error: null,
|
||||
replacePointCloud: false,
|
||||
}), []);
|
||||
|
||||
return (
|
||||
<CanonicalRecordedLabReplay
|
||||
label="RAVNOVES004TREE full recorded review"
|
||||
mediaMode={mediaMode ?? "none"}
|
||||
mediaModes={FULL_ROUTE_MEDIA_MODES}
|
||||
spatialMode={spatialMode ?? "none"}
|
||||
spatialModes={FULL_ROUTE_SPATIAL_MODES}
|
||||
expanded={expanded}
|
||||
splitPrimarySize={splitPrimarySize}
|
||||
splitOrientation={splitOrientation}
|
||||
mediaAriaLabel={mediaMode === "camera" ? "Камера" : "Видео"}
|
||||
spatialAriaLabel={spatialMode === "3d" ? "Трёхмерная сцена" : "Вид сверху"}
|
||||
mediaLayerControls={mediaLayerControls}
|
||||
spatialLayerControls={spatialLayerControls}
|
||||
spatialLeadingControl={resetSpatialView}
|
||||
mediaMultiLayer
|
||||
mediaContent={mediaContent}
|
||||
spatialContent={spatialContent}
|
||||
emptyMessage="Выберите VIDEO/CAMERA или 3D/PLAN. Общий таймлайн останется на месте."
|
||||
overlay={overlay}
|
||||
transport={transport}
|
||||
trailingActions={!splitView && spatialMode ? resetSpatialView : null}
|
||||
onMediaModeChange={handleMediaModeChange}
|
||||
onSpatialModeChange={handleSpatialModeChange}
|
||||
onExpandedChange={setExpanded}
|
||||
onSplitPrimarySizeChange={setSplitPrimarySize}
|
||||
<M4ReplayThreatVisual
|
||||
resultId={resultId}
|
||||
timelineEndpointRoot={VEGETATION_TIMELINE_ENDPOINT}
|
||||
semanticLayers={semanticLayers}
|
||||
initialSemanticLayerId="vegetation"
|
||||
initialSpatialMode="3d"
|
||||
classifiedSpatialLayer={sealedSpatialGap}
|
||||
evidenceLabel="RAVNOVES004TREE"
|
||||
playbackTransport="segmented"
|
||||
recoverTimestampStalls
|
||||
showReferenceMediaLayers
|
||||
showSpatialOverlaySummary
|
||||
/>
|
||||
);
|
||||
}
|
||||
@@ -575,32 +101,32 @@ function FullRouteReviewResult({
|
||||
summary={(
|
||||
<LaboratorySummary
|
||||
title="LAB V1 · RAVNOVES004TREE · полный маршрут"
|
||||
description="Общий recorded-LAB шаблон воспроизводит запись с травой и оврагами: RIGHT camera, исходное облако, ограниченный Local SLAM, два независимых semantic-слоя и десять реально просчитанных TGS-якорей."
|
||||
description="Принятый recorded-LAB инструмент воспроизводит RAV004 без отдельного viewer: одна media-clock timeline, RIGHT camera, source points, bounded Local SLAM и переключаемые EoMT/DDRNet."
|
||||
status="FULL RECORDED REVIEW · truth отсутствует · commands OFF"
|
||||
statusTone="warning"
|
||||
facts={[
|
||||
{ label: "Источник", value: `${review.sourceId} · ${review.frameCount}/${review.frameCount} frames` },
|
||||
{ label: "3D", value: "1437 source point chunks · 2825 SLAM poses · recorded RRD" },
|
||||
{ label: "Источник", value: `${review.sourceId} · ${review.frameCount}/${review.frameCount} camera frames` },
|
||||
{ label: "3D", value: "1444 source cloud increments · gravity-stable RFU → body" },
|
||||
{ label: "Город", value: `${review.city.name} · ${decimal(review.city.inferenceFps, 2)} fps` },
|
||||
{ label: "Природа", value: `${review.vegetation.name} · ${decimal(review.vegetation.inferenceFps, 2)} fps` },
|
||||
{ label: "TGS", value: "10 sealed causal anchors · continuous costmap отсутствует" },
|
||||
{ label: "TGS", value: "10 review anchors существуют · full-route artifact отсутствует" },
|
||||
{ label: "Authority", value: `${rigLabel} · VISUAL REVIEW ONLY · commands OFF` },
|
||||
]}
|
||||
brief={{
|
||||
question: "Что реально видно на полном RAV004-прогоне с высокой травой, оврагами и переходом к городу?",
|
||||
approach: "Одна recorded timeline открывается общим LAB viewer. Camera и RRD синхронизированы; EoMT/DDRNet переключаются на камере, source points и 5-секундный Local SLAM — в 3D, TGS — только в доказанном окне десяти запечатанных якорей.",
|
||||
principalResult: "RAV004 больше не подменяется RAV00: доступна полная исходная запись и её реальные пространственные слои.",
|
||||
limitation: "Ручной truth, continuous TGS и point-aligned 3D semantics отсутствуют. Один повреждённый H.264-пакет на позиции 6092 заменён предыдущим декодированным кадром и отражён в proof.",
|
||||
approach: "RAV004 поставляет только data/provider configuration в тот же M4 recorded viewer. Видеодекодер владеет clock; новые source increments проецируются в gravity-stable forward/left/up frame, Local SLAM ограничен пятью секундами.",
|
||||
principalResult: "RAV004 больше не имеет отдельной логики окон, таймера, seek, cache или 3D controls. Модели и подписи меняются конфигурацией, архитектура переключения остаётся общей.",
|
||||
limitation: "Full-route TGS, независимый person/vehicle detector, ручной truth и point-aligned 3D semantics пока не запечатаны. Semantic-derived рамки диагностические и не являются STOP-authority.",
|
||||
}}
|
||||
method={{
|
||||
completeness: "complete",
|
||||
executionClass: "ai-inference",
|
||||
pipelineId: "ravnoves004tree-full-eomt-ddrnet-recorded-review/v1",
|
||||
pipelineId: "canonical-recorded-lab-rav004tree/v3",
|
||||
components: [
|
||||
{ kind: "algorithm", name: "Recorded source points + bounded Local SLAM", version: "source-paced-ground-v2", role: "spatial source evidence", identitySha256: null },
|
||||
{ kind: "algorithm", name: "Canonical recorded replay", version: "media-clock / one viewer", role: "shared camera + spatial transport", identitySha256: null },
|
||||
{ kind: "algorithm", name: "Recorded source points + bounded Local SLAM", version: "source-paced-ground-v3", role: "gravity-stable spatial evidence", identitySha256: null },
|
||||
{ kind: "model", name: review.city.name, version: "sealed Worker 006 run", role: "urban semantic review", identitySha256: null },
|
||||
{ kind: "model", name: review.vegetation.name, version: "GOOSE DDRNet-39", role: "vegetation semantic review", identitySha256: null },
|
||||
{ kind: "algorithm", name: "Causal TGS", version: "10 linked route anchors", role: "bounded geometric evidence", identitySha256: null },
|
||||
],
|
||||
}}
|
||||
/>
|
||||
@@ -617,19 +143,19 @@ function FullRouteReviewResult({
|
||||
)}
|
||||
result={(
|
||||
<LaboratoryResultSummary
|
||||
title="Полный RAV004 visual review восстановлен; управление не авторизовано"
|
||||
status="Recorded evidence ready · navigation/actuation OFF"
|
||||
title="RAV004 переведён на общий replay-каркас; safety evidence ещё не полно"
|
||||
status="Recorded evidence · navigation/actuation OFF"
|
||||
statusTone="warning"
|
||||
metrics={[
|
||||
{ label: "Route masks", value: "6830/6830 × 2", hint: "sealed local archives · Worker не требуется" },
|
||||
{ label: "EoMT throughput", value: `${decimal(review.city.inferenceFps, 2)} fps`, hint: "изолированный полный прогон" },
|
||||
{ label: "DDRNet throughput", value: `${decimal(review.vegetation.inferenceFps, 2)} fps`, hint: "изолированный полный прогон" },
|
||||
{ label: "Spatial evidence", value: "RRD + 10 TGS anchors", hint: "continuous TGS и 3D semantics отсутствуют" },
|
||||
{ label: "Camera timeline", value: "6830 frames · ≈9.51 Hz", hint: "media clock owns video, overlays and spatial" },
|
||||
{ label: "Source geometry", value: "1444 increments · ≈2 Hz", hint: "last proven spatial frame is held between source arrivals" },
|
||||
{ label: "EoMT throughput", value: `${decimal(review.city.inferenceFps, 2)} fps`, hint: "изолированный full pass; не realtime stack" },
|
||||
{ label: "DDRNet throughput", value: `${decimal(review.vegetation.inferenceFps, 2)} fps`, hint: "изолированный full pass; temporal stability не принята" },
|
||||
]}
|
||||
conclusion={{
|
||||
proved: "Полный RAV004 открывается в каноническом recorded viewer с camera, source points, bounded Local SLAM, EoMT, DDRNet и связанными TGS-якорями.",
|
||||
notProved: "Не доказаны truth accuracy, временная стабильность DDRNet, continuous negative-obstacle detection и безопасное управление ровером.",
|
||||
decision: "Использовать как visual audit. Следующий gate — truth-набор овраг/трава/дерево/яма и motion-aware temporal evaluation при целевых ≥10 FPS; navigation/actuation оставить OFF.",
|
||||
proved: "Camera, seek, spatial layers and semantic switching use one accepted reusable viewer and one media clock; RFU source geometry no longer inherits LiDAR roll/pitch.",
|
||||
notProved: "Не доказаны continuous TGS, независимый detector/STOP, truth accuracy, temporal stability DDRNet и ≥10 FPS совместного live stack.",
|
||||
decision: "Продолжать как visual audit. До запечатанного full-route TGS и detector/load gate navigation/actuation остаются OFF.",
|
||||
}}
|
||||
/>
|
||||
)}
|
||||
@@ -754,27 +280,9 @@ export function VegetationShadowResultView({
|
||||
executionClass: "ai-inference",
|
||||
pipelineId: "ravnoves-eomt-ddrnet-yolox-causal-tgs-recorded-review/v1",
|
||||
components: [
|
||||
{
|
||||
kind: "model",
|
||||
name: "EoMT Cityscapes semantic",
|
||||
version: "sealed E47 archive",
|
||||
role: "urban semantic review",
|
||||
identitySha256: null,
|
||||
},
|
||||
{
|
||||
kind: "model",
|
||||
name: selected.loadedModelName,
|
||||
version: selected.candidate,
|
||||
role: "vegetation material candidate",
|
||||
identitySha256: selected.checkpointSha256,
|
||||
},
|
||||
{
|
||||
kind: "algorithm",
|
||||
name: "Frozen YOLOX + causal TGS",
|
||||
version: "linked M4/M4.9 archives",
|
||||
role: "independent object and geometry veto",
|
||||
identitySha256: null,
|
||||
},
|
||||
{ kind: "model", name: "EoMT Cityscapes semantic", version: "sealed E47 archive", role: "urban semantic review", identitySha256: null },
|
||||
{ kind: "model", name: selected.loadedModelName, version: selected.candidate, role: "vegetation material candidate", identitySha256: selected.checkpointSha256 },
|
||||
{ kind: "algorithm", name: "Frozen YOLOX + causal TGS", version: "linked M4/M4.9 archives", role: "independent object and geometry veto", identitySha256: null },
|
||||
],
|
||||
}}
|
||||
/>
|
||||
@@ -795,26 +303,10 @@ export function VegetationShadowResultView({
|
||||
status="Semantics advisory · YOLOX/TGS veto cannot be cleared"
|
||||
statusTone="warning"
|
||||
metrics={[
|
||||
{
|
||||
label: "Route masks",
|
||||
value: `${route.frameCount}/${route.frameCount}`,
|
||||
hint: "sealed local playback · Worker для открытия не нужен",
|
||||
},
|
||||
{
|
||||
label: "Semantic sources",
|
||||
value: "2 independent layers",
|
||||
hint: "EoMT CITY / DDRNet VEGETATION · display switches, evidence does not fuse",
|
||||
},
|
||||
{
|
||||
label: "Vegetation worker p95",
|
||||
value: `${decimal(selected.shadowLatencyP95Ms, 2)} ms`,
|
||||
hint: "изолированный DDRNet inference; не совместный realtime stack",
|
||||
},
|
||||
{
|
||||
label: "Vegetation peak VRAM",
|
||||
value: `${decimal(selected.peakReservedVramBytes / 1024 ** 3, 2)} GiB`,
|
||||
hint: "DDRNet candidate на Worker 006",
|
||||
},
|
||||
{ label: "Route masks", value: `${route.frameCount}/${route.frameCount}`, hint: "sealed local playback · Worker для открытия не нужен" },
|
||||
{ label: "Semantic sources", value: "2 independent layers", hint: "EoMT CITY / DDRNet VEGETATION · display switches, evidence does not fuse" },
|
||||
{ label: "Vegetation worker p95", value: `${decimal(selected.shadowLatencyP95Ms, 2)} ms`, hint: "изолированный DDRNet inference; не совместный realtime stack" },
|
||||
{ label: "Vegetation peak VRAM", value: `${decimal(selected.peakReservedVramBytes / 1024 ** 3, 2)} GiB`, hint: "DDRNet candidate на Worker 006" },
|
||||
]}
|
||||
conclusion={{
|
||||
proved: "На одной recorded timeline доступны городской EoMT, природный DDRNet, YOLOX detections и causal TGS; LAB автономна от Worker.",
|
||||
|
||||
@@ -18,6 +18,7 @@ import {
|
||||
|
||||
const REQUESTED_CHUNK_FRAMES = 24;
|
||||
const RETAINED_CHUNK_COUNT = 4;
|
||||
const RETAINED_CHUNKS_BEHIND = 1;
|
||||
const PREFETCH_CHUNKS_AHEAD = 1;
|
||||
const RETAINED_CAMERA_POINT_OVERLAYS = 12;
|
||||
|
||||
@@ -31,10 +32,17 @@ export function m4ThreatChunkWindowStarts(
|
||||
frameCount: number,
|
||||
): readonly number[] {
|
||||
if (chunkSize < 1 || frameCount < 1) return [];
|
||||
return Array.from(
|
||||
{ length: PREFETCH_CHUNKS_AHEAD + 1 },
|
||||
(_, index) => activeChunkStart + index * chunkSize,
|
||||
).filter((start) => start >= 0 && start < frameCount);
|
||||
return [
|
||||
activeChunkStart,
|
||||
...Array.from(
|
||||
{ length: RETAINED_CHUNKS_BEHIND },
|
||||
(_, index) => activeChunkStart - (index + 1) * chunkSize,
|
||||
),
|
||||
...Array.from(
|
||||
{ length: PREFETCH_CHUNKS_AHEAD },
|
||||
(_, index) => activeChunkStart + (index + 1) * chunkSize,
|
||||
),
|
||||
].filter((start) => start >= 0 && start < frameCount);
|
||||
}
|
||||
|
||||
export function cancelM4ThreatChunkRequestsOutsideWindow<T extends { abort(): void }>(
|
||||
|
||||
Reference in New Issue
Block a user