feat(lab): present chronological perception evidence

2026-08-05 07:49:49 +03:00
parent 12c8a2d74c
commit 7a72a206f1
102 changed files with 20122 additions and 222 deletions
@@ -0,0 +1,155 @@
+import assert from "node:assert/strict";
+import { readFile } from "node:fs/promises";
+import test, { after, before } from "node:test";
+import { createServer } from "vite";
+
+let server;
+let fetchE46FDashCamBakeoff;
+
+before(async () => {
+  server = await createServer({
+    server: { middlewareMode: true },
+    appType: "custom",
+    logLevel: "silent",
+  });
+  ({ fetchE46FDashCamBakeoff } = await server.ssrLoadModule(
+    "/src/core/laboratory/e46fDashCamBakeoff.ts",
+  ));
+});
+
+after(async () => {
+  await server?.close();
+});
+
+function metrics(overrides = {}) {
+  return {
+    frame_count: 4489,
+    route_duration_seconds: 458.713353,
+    detection_observation_count: 23478,
+    track_observation_count: 24937,
+    detection_box_clipped_count: 0,
+    track_box_clipped_count: 1630,
+    unique_track_count: 545,
+    mean_tracked_objects_per_frame: 5.555135,
+    zero_detection_frame_count: 39,
+    zero_track_frame_count: 25,
+    tracker_recovered_frame_count: 29,
+    full_layer_blackout_event_count: 1,
+    route_id_gap_event_count: 0,
+    short_track_count: 37,
+    short_track_fraction: 0.06789,
+    track_class_switch_count: 0,
+    ...overrides,
+  };
+}
+
+test("E46F preserves temporal gains but admits the semantic rejection", async () => {
+  const resultId = `e46f-dashcam-bakeoff-${"a".repeat(64)}`;
+  const baselineId = `e46e-ready-stack-${"b".repeat(64)}`;
+  const identity = "c".repeat(64);
+  const fetcher = async () => new Response(JSON.stringify({
+    schema_version: "missioncore.e46f-dashcam-bakeoff-catalog/v1",
+    items: [{
+      schema_version: "missioncore.e46f-dashcam-bakeoff-view/v1",
+      result_id: resultId,
+      created_at_utc: "2026-08-04T09:00:00Z",
+      source_session_id: "20260720T065719Z_viewer_live",
+      camera_source_id: "sensor.camera.right",
+      metrics: metrics(),
+      acceptance: {
+        full_route_accounted: true,
+        stock_detector_tracker_executed: true,
+        controlled_detector_only_change: true,
+        visual_overlay_available: true,
+        independent_truth_available: false,
+        navigation_or_safety_accepted: false,
+      },
+      method: {
+        schema_version: "missioncore.laboratory-method/v1",
+        completeness: "complete",
+        execution_class: "hybrid",
+        pipeline_id: "e46f-deepstream-dashcamnet-detectnet-v2-nvdcf/v1",
+        components: [{
+          kind: "model",
+          name: "NVIDIA DashCamNet",
+          version: "pruned_onnx_v1.0.4",
+          role: "moving-camera traffic-object detection",
+          identity_sha256: identity,
+        }],
+      },
+      limitations: ["not independent truth"],
+      comparison: {
+        controlled_change: "detector-only",
+        baseline_result_id: baselineId,
+        baseline_metrics: metrics({
+          unique_track_count: 909,
+          zero_track_frame_count: 28,
+          full_layer_blackout_event_count: 2,
+          short_track_fraction: 0.093509,
+        }),
+        delta: {
+          zero_track_frame_count: -3,
+          full_layer_blackout_event_count: -1,
+          unique_track_count: -364,
+          short_track_fraction: -0.025619,
+        },
+        large_box_visual_triage: {
+          area_ratio_threshold: 0.2,
+          candidate: {
+            observation_count: 2912,
+            frame_count: 2173,
+            track_id_count: 23,
+            class_observations: { person: 2912 },
+          },
+          baseline: {
+            observation_count: 191,
+            frame_count: 191,
+            track_id_count: 4,
+            class_observations: { car: 191 },
+          },
+          interpretation: "diagnostic visual triage; not precision/recall",
+        },
+        visual_review: {
+          status: "rejected-semantic-regression",
+          sample_video_seconds: [4.2, 9, 22, 44, 264, 418],
+          finding: "fisheye rim becomes huge person tracks",
+          next_action: "rectify valid FOV and repeat A/B",
+        },
+        verdict: "reject-dashcamnet-on-unrectified-fisheye",
+      },
+      video: {
+        url: `/api/v1/laboratory/e46f/results/${resultId}/overlay.mp4`,
+        media_type: "video/mp4",
+        byte_length: 150513080,
+        sha256: identity,
+        width: 800,
+        height: 600,
+      },
+      ground_truth: false,
+    }],
+  }), { status: 200, headers: { "Content-Type": "application/json" } });
+
+  const result = await fetchE46FDashCamBakeoff({ fetcher });
+  assert.equal(result.resultId, resultId);
+  assert.equal(result.comparison.verdict, "reject-dashcamnet-on-unrectified-fisheye");
+  assert.equal(result.comparison.delta.zeroTrackFrameCount, -3);
+  assert.equal(result.comparison.largeBoxVisualTriage.candidate.observationCount, 2912);
+  assert.equal(result.comparison.visualReview.status, "rejected-semantic-regression");
+  assert.equal(result.acceptance.navigationOrSafetyAccepted, false);
+  assert.equal(result.video.sha256, identity);
+  assert.doesNotMatch(JSON.stringify(result), /Users|D:\\|runtime\/experiments/);
+});
+
+test("E46F uses the fixed LAB anatomy and exposes the frozen full video", async () => {
+  const [resultView, visual] = await Promise.all([
+    readFile(new URL("../src/workspaces/laboratory/E46FDashCamBakeoffResult.tsx", import.meta.url), "utf8"),
+    readFile(new URL("../src/workspaces/laboratory/E46EReadyStackVisual.tsx", import.meta.url), "utf8"),
+  ]);
+  assert.match(resultView, /LaboratorySummary/);
+  assert.match(resultView, /LaboratoryEvidence/);
+  assert.match(resultView, /LaboratoryResultSummary/);
+  assert.match(resultView, /semantic regression/);
+  assert.match(visual, /LaboratoryEvidenceViewer/);
+  assert.match(visual, /<video/);
+  assert.match(visual, /controls/);
+});