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 +1,169 @@
+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 fetchE46JRawFisheyeRealtime;
+
+before(async () => {
+  server = await createServer({
+    server: { middlewareMode: true },
+    appType: "custom",
+    logLevel: "silent",
+  });
+  ({ fetchE46JRawFisheyeRealtime } = await server.ssrLoadModule(
+    "/src/core/laboratory/e46jRawFisheyeRealtime.ts",
+  ));
+});
+
+after(async () => {
+  await server?.close();
+});
+
+test("E46J binds full raw fisheye capacity to an honest visual exception", async () => {
+  const identity = "b".repeat(64);
+  const resultId = `e46j-raw-fisheye-realtime-${"a".repeat(64)}`;
+  const payload = {
+    schema_version: "missioncore.e46j-raw-fisheye-realtime-catalog/v1",
+    items: [{
+      schema_version: "missioncore.e46j-raw-fisheye-realtime-view/v1",
+      result_id: resultId,
+      created_at_utc: "2026-08-04T18:20:00.000Z",
+      status: "realtime-capacity-passed-awaiting-temporal-layer",
+      source: {
+        camera_source_id: "sensor.camera.right",
+        session_id: "20260720T065719Z_viewer_live",
+        resolution: [800, 600],
+        frame_count: 4489,
+        frame_rate: 10.003944527024467,
+        calibration_model: "KB4",
+      },
+      detector: {
+        architecture: "YOLOX-S",
+        source: "Megvii-BaseDetection/YOLOX release 0.1.1rc0",
+        license: "Apache-2.0",
+        runtime: "NVIDIA Triton 2.70.0 ONNX Runtime GPU backend",
+      },
+      detection: { minimum_score: 0.5, nms_iou_threshold: 0.45 },
+      metrics: {
+        frame_count: 4489,
+        failed_frame_count: 0,
+        detection_observation_count: 15499,
+        class_observation_counts: { car: 14229, person: 625, truck: 608 },
+        mean_detections_per_frame: 3.452662,
+        max_detections_per_frame: 9,
+        zero_detection_frame_count: 181,
+        longest_zero_detection_run_frames: 24,
+        core_capacity_fps: 47.84049,
+        core_path_mean_ms: 20.902796,
+        core_path_p95_ms: 25.355265,
+        inference_request_mean_ms: 12.437504,
+        inference_request_p95_ms: 16.414979,
+        gpu_utilization_mean_percent: 26.396947,
+        operator_shadow_window_frame_count: 75,
+        operator_shadow_person_frame_count: 35,
+      },
+      visual_review: {
+        reviewed_video_range_seconds: [0, 448.723],
+        verdict: "realtime-detector-progress-with-known-shadow-exception",
+        review_windows: [
+          ["wall", 6, 10.9, "legacy-background-false-positive-suppressed"],
+          ["shrub", 178.6, 180.3, "legacy-background-false-positive-suppressed"],
+          ["ground", 250.7, 265.6, "legacy-background-false-positive-suppressed"],
+          ["road", 392.2, 400.6, "legacy-background-false-positive-suppressed"],
+          ["shadow", 419.4, 426.9, "operator-shadow-person-false-positive-observed"],
+          ["terrace", 440.8, 448.4, "legacy-background-false-positive-suppressed"],
+        ].map(([id, start, end, verdict]) => ({
+          id,
+          label: `${start}–${end}`,
+          start_seconds: start,
+          end_seconds: end,
+          verdict,
+        })),
+        finding: "full raw fisheye retained",
+        known_error: "operator shadow becomes person",
+      },
+      acceptance: {
+        ten_hz_capacity_gate_passed: true,
+        latency_gate_passed: true,
+        full_raw_fisheye_retained: true,
+      },
+      decision: {
+        selected_provider: "megvii-yolox-s-0.1.1rc0",
+        realtime_capacity_passed: true,
+        ready_for_temporal_bakeoff: true,
+        provider_promoted: false,
+        next_action: "attach ready temporal tracker",
+      },
+      method: {
+        schema_version: "missioncore.laboratory-method/v1",
+        completeness: "complete",
+        execution_class: "hybrid",
+        pipeline_id: "e46j-k1-right-raw-kb4-yolox-s-one-pass/v1",
+        components: [{
+          kind: "model",
+          name: "YOLOX-S",
+          version: "0.1.1rc0",
+          role: "ready detector",
+          identity_sha256: identity,
+        }],
+      },
+      limitations: ["not truth", "no temporal identity"],
+      video: {
+        url: `/api/v1/laboratory/e46j/results/${resultId}/overlay.mp4`,
+        media_type: "video/mp4",
+        byte_length: 150563706,
+        sha256: identity,
+        width: 800,
+        height: 600,
+        frame_rate: 10.003944527024467,
+        frame_count: 4489,
+        duration_seconds: 448.723,
+      },
+      visuals: Object.fromEntries(
+        ["full_route", "targeted_windows", "operator_shadow"].map((key) => [key, {
+          url: `/visual/${key}.png`,
+          media_type: "image/png",
+          byte_length: 1000,
+          sha256: identity,
+        }]),
+      ),
+      ground_truth: false,
+      authority: {
+        ground_truth: false,
+        provider_promoted: false,
+        commands_enabled: false,
+        navigation_or_safety_accepted: false,
+      },
+    }],
+  };
+  const result = await fetchE46JRawFisheyeRealtime({
+    fetcher: async () => new Response(JSON.stringify(payload), {
+      status: 200,
+      headers: { "Content-Type": "application/json" },
+    }),
+  });
+  assert.equal(result.source.frameCount, 4489);
+  assert.equal(result.source.resolution.join("x"), "800x600");
+  assert.equal(result.metrics.coreCapacityFps, 47.84049);
+  assert.equal(result.metrics.operatorShadowPersonFrameCount, 35);
+  assert.equal(result.visualReview.reviewWindows.length, 6);
+  assert.equal(result.decision.providerPromoted, false);
+  assert.doesNotMatch(JSON.stringify(result), /Users|D:\\|runtime\/experiments/);
+});
+
+test("E46J uses the fixed LAB anatomy and seekable full video", async () => {
+  const [resultView, visual] = await Promise.all([
+    readFile(new URL("../src/workspaces/laboratory/E46JRawFisheyeRealtimeResult.tsx", import.meta.url), "utf8"),
+    readFile(new URL("../src/workspaces/laboratory/E46JRawFisheyeRealtimeVisual.tsx", import.meta.url), "utf8"),
+  ]);
+  assert.match(resultView, /LaboratorySummary/);
+  assert.match(resultView, /LaboratoryEvidence/);
+  assert.match(resultView, /LaboratoryResultSummary/);
+  assert.match(resultView, /full raw fisheye realtime gate/);
+  assert.match(visual, /LaboratoryEvidenceViewer/);
+  assert.match(visual, /operator-shadow/);
+  assert.match(visual, /<video/);
+  assert.match(visual, /\[mode, selectedWindow\]/);
+});