feat(perception): integrate vegetation policy review

tests/test_vegetation_shadow_lab.py

@@ -2,6 +2,7 @@ from __future__ import annotations
 
 import hashlib
 import json
+import shutil
 import zipfile
 from pathlib import Path
 from types import SimpleNamespace
@@ -9,9 +10,11 @@ from types import SimpleNamespace
 from fastapi import FastAPI
 from fastapi.testclient import TestClient
 
-from k1link.laboratory import LaboratoryEvidenceRegistry
+import k1link.laboratory.vegetation_policy_review as policy_review_module
 import k1link.laboratory.vegetation_shadow_lab as vegetation_lab_module
+from k1link.laboratory import LaboratoryEvidenceRegistry
 from k1link.laboratory.evidence_report import verify_laboratory_evidence_result
+from k1link.laboratory.vegetation_policy_review import seal_vegetation_policy_review
 from k1link.laboratory.vegetation_shadow_lab import seal_vegetation_shadow_lab
 from k1link.web.vegetation_shadow_lab_api import build_vegetation_shadow_lab_router
 
@@ -229,3 +232,95 @@ def test_vegetation_shadow_lab_seals_autonomous_visual_evidence(
         client.get(f"/api/v1/laboratory/vegetation-shadow/{result_root.name}").status_code
         == 503
     )
+
+
+def test_policy_review_reuses_sealed_video_and_links_yolox_tgs(
+    tmp_path: Path,
+    monkeypatch,
+) -> None:
+    roots = {}
+    for candidate, vegetation_iou in (("ddrnet", 0.64), ("ppliteseg", 0.61)):
+        for mode in ("goose", "ravnoves"):
+            root = tmp_path / "worker" / f"{candidate}-{mode}"
+            _worker_result(root, candidate=candidate, mode=mode, vegetation_iou=vegetation_iou)
+            roots[(candidate, mode)] = root
+    video_root = tmp_path / "worker" / "ddrnet-ravnoves-video"
+    _video_worker_result(video_root)
+    m47_root = tmp_path / f"m47-reference-graph-lab-{'a' * 64}"
+    m47_root.mkdir()
+    base_m4_result_id = f"m4-threat-replay-{'f' * 64}"
+    monkeypatch.setattr(
+        vegetation_lab_module,
+        "read_m47_reference_graph_lab",
+        lambda _root: SimpleNamespace(
+            result_id=m47_root.name,
+            report={
+                "source": {"source_id": "RAVNOVES00"},
+                "visual_evidence": {
+                    "linked_result_id": base_m4_result_id,
+                    "timeline_frames": 4489,
+                },
+            },
+        ),
+    )
+    base_root = seal_vegetation_shadow_lab(
+        ddrnet_goose_root=roots[("ddrnet", "goose")],
+        ppliteseg_goose_root=roots[("ppliteseg", "goose")],
+        ddrnet_ravnoves_root=roots[("ddrnet", "ravnoves")],
+        ppliteseg_ravnoves_root=roots[("ppliteseg", "ravnoves")],
+        output_root=tmp_path / "results",
+        ddrnet_ravnoves_video_root=video_root,
+        m47_reference_graph_lab_root=m47_root,
+    )
+    tgs_result_id = f"m49-tgs-full-shadow-{'9' * 64}"
+    monkeypatch.setattr(
+        policy_review_module,
+        "read_m49_tgs_full_shadow",
+        lambda _root: SimpleNamespace(
+            result_id=tgs_result_id,
+            report={
+                "source": {
+                    "source_id": "RAVNOVES00",
+                    "linked_visual_result_id": base_m4_result_id,
+                },
+                "timeline": {"frame_count": 4489},
+            },
+        ),
+    )
+
+    def fake_policy_archive(**kwargs) -> list[int]:
+        shutil.copyfile(kwargs["source_archive"], kwargs["destination_archive"])
+        return [4489 * 800 * 600, *([0] * 8)]
+
+    monkeypatch.setattr(policy_review_module, "build_policy_mask_archive", fake_policy_archive)
+    result_root = seal_vegetation_policy_review(
+        base_lab_root=base_root,
+        mission_policy_path=REPOSITORY_ROOT
+        / "config/perception/lab-v1-vegetation-mission-policy-v1.json",
+        provider_label_map_path=REPOSITORY_ROOT
+        / "config/perception/lab-v1-vegetation-provider-label-map-v1.json",
+        m49_tgs_full_shadow_root=tmp_path / "sealed-tgs",
+        output_root=tmp_path / "results",
+        created_at_utc="2026-08-28T08:00:00+00:00",
+    )
+    manifest = json.loads((result_root / "result.json").read_text("utf-8"))
+    route = manifest["route_video"]
+    assert route["view_kind"] == "coarse-material-policy-review"
+    assert route["linked_tgs_result_id"] == tgs_result_id
+    assert route["fusion"]["pixel_raster_fusion"] is False
+    assert route["fusion"]["camera_semantic_temporal_filter"] == "none"
+    assert route["taxonomy"]["schema_version"] == (
+        "missioncore.lab-v1-terrain-policy-taxonomy/v1"
+    )
+    assert len(route["taxonomy"]["classes"]) == 9
+    assert len(manifest["artifacts"]) == 79
+    assert manifest["authority"]["commands_enabled"] is False
+    assert manifest["decision"]["multilayer_policy_review_ready"] is True
+
+    app = FastAPI()
+    app.include_router(build_vegetation_shadow_lab_router(root_provider=lambda: result_root.parent))
+    response = TestClient(app).get(
+        f"/api/v1/laboratory/vegetation-shadow/{result_root.name}/masks/0"
+    )
+    assert response.status_code == 200
+    assert response.content == b"\x89PNG\r\n\x1a\n"