feat(lab): visualize semantic SLAM shadow
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DCCONSTRUCTIONS
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import assert from "node:assert/strict";
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import { after, before, test } from "node:test";
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import { createServer } from "vite";
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let server;
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let fetchE47SemanticSlamResult;
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let fetchE47SemanticTimelineChunk;
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let e47SemanticMaskUrl;
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const resultId = `e47-semantic-slam-${"a".repeat(64)}`;
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const baseM4ResultId = `m4-threat-replay-${"b".repeat(64)}`;
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before(async () => {
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server = await createServer({
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appType: "custom",
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logLevel: "silent",
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server: { middlewareMode: true },
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});
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({
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fetchE47SemanticSlamResult,
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fetchE47SemanticTimelineChunk,
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e47SemanticMaskUrl,
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} = await server.ssrLoadModule("/src/core/laboratory/e47SemanticSlam.ts"));
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});
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after(async () => {
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await server?.close();
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});
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function resultView(overrides = {}) {
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return {
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schema_version: "missioncore.e47-semantic-slam-view/v1",
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result_id: resultId,
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created_at_utc: "2026-08-06T10:00:00.000Z",
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status: "diagnostic-semantic-slam-shadow",
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profile_id: "ravnoves00-eomt-kb4-slam-shadow/v1",
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base_m4_result_id: baseM4ResultId,
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semantic_result_id: `result-${"c".repeat(64)}`,
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geometry_result_id: `m4-geometry-replay-${"d".repeat(64)}`,
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source_pack_id: `e10-lidar-pack-${"e".repeat(64)}`,
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calibration_content_sha256: "f".repeat(64),
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provider: {
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provider_id: "eomt-cityscapes-semantic-control/v1",
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model_id: "tue-mps/cityscapes_semantic_eomt_large_1024",
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model_revision: "revision-1",
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model_weights_sha256: "1".repeat(64),
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preprocess_id: "raw-kb4-valid-fov-semantic/v1",
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},
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temporal_binding: {
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semantic_to_camera: "exact-sequence-and-session-time",
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camera_to_lidar: "accepted-e6-nearest-host-arrival-best-effort",
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clock_basis: "recorded-host-monotonic-arrival",
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maximum_lidar_camera_delta_ms: 100,
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maximum_pose_point_delta_ms: 100,
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physical_synchronization_proven: false,
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},
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taxonomy: [
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{
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class_id: 0,
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label: "outside_valid_fov",
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disposition: "ambiguous",
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color_rgb: [0, 0, 0],
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},
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{
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class_id: 7,
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label: "paved_road",
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disposition: "labeled",
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color_rgb: [128, 64, 128],
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},
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],
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metrics: {
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frames: { total: 4489, mask_available: 4489, source_available: 4489 },
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points: {
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total: 4,
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projected: 2,
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labeled: 1,
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ambiguous: 1,
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unprojected: 2,
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absent: 0,
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},
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observations: {
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total: 2,
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labeled: 1,
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ambiguous: 0,
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unprojected: 1,
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absent: 0,
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},
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runtime: { elapsed_ms: 1000, frames_per_second: 4.489 },
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},
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acceptance: {
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artifact_contract_passed: true,
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frame_accounting_passed: true,
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point_accounting_passed: true,
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observation_binding_passed: true,
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temporal_binding_passed: true,
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independent_semantic_truth_passed: false,
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provider_promoted: false,
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},
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limitations: ["diagnostic only"],
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ground_truth: false,
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semantic_authority: "diagnostic-only",
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navigation_or_safety_accepted: false,
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actuation_allowed: false,
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...overrides,
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};
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}
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test("E47 accepts only a fully accounted diagnostic semantic/SLAM view", async () => {
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const result = await fetchE47SemanticSlamResult({
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fetcher: async () => new Response(JSON.stringify({
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schema_version: "missioncore.e47-semantic-slam-catalog/v1",
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items: [resultView()],
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})),
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});
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assert.equal(result.resultId, resultId);
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assert.equal(result.baseM4ResultId, baseM4ResultId);
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assert.equal(result.metrics.points.projected, 2);
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assert.equal(result.acceptance.independentSemanticTruthPassed, false);
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assert.equal(result.temporalBinding.physicalSynchronizationProven, false);
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assert.equal(result.temporalBinding.maximumLidarCameraDeltaMs, 100);
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assert.equal(result.acceptance.temporalBindingPassed, true);
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assert.equal(result.taxonomy[0].disposition, "ambiguous");
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assert.equal(
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e47SemanticMaskUrl(resultId, 14),
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`/api/v1/laboratory/e47-semantic-slam/results/${resultId}/masks/14`,
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);
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});
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test("E47 rejects result-level point accounting drift", async () => {
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await assert.rejects(
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fetchE47SemanticSlamResult({
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fetcher: async () => new Response(JSON.stringify({
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schema_version: "missioncore.e47-semantic-slam-catalog/v1",
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items: [resultView({
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metrics: {
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...resultView().metrics,
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points: {
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...resultView().metrics.points,
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total: 5,
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},
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},
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})],
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})),
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}),
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/point accounting/,
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);
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});
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test("E47 chunk preserves unavailable sentinel and verifies the status histogram", async () => {
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const validFrame = {
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schema_version: "missioncore.e47-semantic-slam-frame/v1",
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sequence: 14,
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source_point_count: 4,
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class_ids: [7, 0, -1, -1],
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status_codes: [3, 2, 1, 1],
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counts: { labeled: 1, ambiguous: 1, unprojected: 2, absent: 0 },
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};
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const chunk = await fetchE47SemanticTimelineChunk(resultId, 14, 1, {
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taxonomy: [
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{ classId: 0, label: "outside_valid_fov", disposition: "ambiguous", colorRgb: [0, 0, 0] },
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{ classId: 7, label: "paved_road", disposition: "labeled", colorRgb: [128, 64, 128] },
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],
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fetcher: async () => new Response(JSON.stringify({
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schema_version: "missioncore.e47-semantic-slam-chunk/v1",
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result_id: resultId,
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start_sequence: 14,
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frame_count: 1,
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next_sequence: 15,
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frames: [validFrame],
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})),
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});
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assert.deepEqual(chunk.frames[0].classIds, [7, 0, -1, -1]);
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await assert.rejects(
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fetchE47SemanticTimelineChunk(resultId, 14, 1, {
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taxonomy: [
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{ classId: 0, label: "outside_valid_fov", disposition: "ambiguous", colorRgb: [0, 0, 0] },
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{ classId: 7, label: "paved_road", disposition: "labeled", colorRgb: [128, 64, 128] },
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],
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fetcher: async () => new Response(JSON.stringify({
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schema_version: "missioncore.e47-semantic-slam-chunk/v1",
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result_id: resultId,
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start_sequence: 14,
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frame_count: 1,
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next_sequence: 15,
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frames: [{ ...validFrame, class_ids: [7, 0, 7, -1] }],
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})),
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}),
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/class\/status binding/,
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);
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});
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@@ -0,0 +1,69 @@
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import assert from "node:assert/strict";
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import { readFile } from "node:fs/promises";
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import { test } from "node:test";
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const component = (name) => new URL(`../src/components/laboratory/${name}`, import.meta.url);
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test("semantic evidence mask is decoded, cached, cancelled and object-contained client-side", async () => {
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const source = await readFile(component("RecordedEvidenceSemanticMaskOverlay.tsx"), "utf8");
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assert.match(source, /decodedMaskCache/);
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assert.match(source, /pendingMaskCache/);
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assert.match(source, /AbortController/);
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assert.match(source, /getImageData/);
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assert.match(source, /8-bit grayscale class-id PNG/);
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assert.match(source, /ResizeObserver/);
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assert.match(source, /Math\.min\(width \/ imageWidth, height \/ imageHeight\)/);
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assert.match(source, /decoded\.key !== expectedKey/);
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assert.match(source, /mask\?\.key === expectedKey/);
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assert.match(source, /необъявленный class ID/);
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assert.match(source, /recorded-evidence-semantic-mask-overlay__error/);
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assert.match(source, /role="alert"/);
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});
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test("shared recorded scenes place optional semantic masks beneath boxes", async () => {
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const [imageScene, videoScene] = await Promise.all([
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readFile(component("RecordedEvidenceImageScene.tsx"), "utf8"),
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readFile(component("RecordedEvidenceVideoScene.tsx"), "utf8"),
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]);
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for (const source of [imageScene, videoScene]) {
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assert.match(source, /semanticOverlay\?: RecordedEvidenceSemanticOverlay/);
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assert.ok(
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source.indexOf("<RecordedEvidenceSemanticMaskOverlay")
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< source.indexOf("<RecordedEvidenceBoxOverlay"),
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);
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}
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});
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test("metric evidence keeps missing semantic assignments as context and exposes a taxonomy legend", async () => {
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const source = await readFile(component("LaboratoryMetricEvidenceScene.tsx"), "utf8");
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assert.match(source, /pointSemanticClassIds\?: readonly \(number \| null\)\[\]/);
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assert.match(source, /pointSemanticClassIds\.length === pointCloudBodyXyzM\.length/);
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assert.match(source, /classId === null \? undefined : colorsByClassId\.get\(classId\)/);
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assert.match(source, /data-decision="semantic"/);
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assert.match(source, /recordedEvidenceSemanticCssColor/);
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});
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test("semantic point alignment is enforced only when M4 exposes the exact spatial increment", async () => {
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const source = await readFile(
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new URL("../src/workspaces/laboratory/M4ReplayThreatVisual.tsx", import.meta.url),
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"utf8",
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);
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assert.match(source, /semantic && frame\?\.spatialAvailable && semanticFrame/);
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assert.match(source, /\|\| !frame\.spatialAvailable\s*\|\| !semanticFrame/);
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assert.match(source, /semanticFrame\.sourcePointCount !== frame\.pointCloudSourceCount/);
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});
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test("M4 mounts semantic mask overlays only for the active VIDEO or CAMERA layer", async () => {
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const source = await readFile(
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new URL("../src/workspaces/laboratory/M4ReplayThreatVisual.tsx", import.meta.url),
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"utf8",
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);
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assert.match(
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source,
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/semanticOverlay=\{mode === "video" \? semanticOverlay : undefined\}/,
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);
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assert.match(
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source,
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/semanticOverlay=\{mode === "camera" \? semanticOverlay : undefined\}/,
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);
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});
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