feat(perception): split vegetation evidence layers

tests/test_vegetation_shadow_lab.py

@@ -1,16 +1,20 @@
 from __future__ import annotations
 
 import hashlib
+import io
 import json
 import shutil
 import zipfile
 from pathlib import Path
 from types import SimpleNamespace
 
+import numpy as np
 from fastapi import FastAPI
 from fastapi.testclient import TestClient
+from PIL import Image
 
 import k1link.laboratory.vegetation_policy_review as policy_review_module
+import k1link.laboratory.vegetation_policy_video as policy_video_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
@@ -21,6 +25,45 @@ from k1link.web.vegetation_shadow_lab_api import build_vegetation_shadow_lab_rou
 REPOSITORY_ROOT = Path(__file__).resolve().parents[1]
 
 
+def test_coarse_policy_masks_mark_every_outside_fov_pixel_undefined(
+    tmp_path: Path,
+    monkeypatch,
+) -> None:
+    monkeypatch.setattr(policy_video_module, "FRAME_COUNT", 1)
+    monkeypatch.setattr(
+        policy_video_module,
+        "fine_to_policy_lut",
+        lambda _taxonomy, _provider_map: np.full(256, 4, dtype=np.uint8),
+    )
+    source = tmp_path / "fine.zip"
+    fine_buffer = io.BytesIO()
+    Image.new("L", (800, 600), color=1).save(fine_buffer, format="PNG")
+    with zipfile.ZipFile(source, "w") as archive:
+        archive.writestr("masks/frame-000001.png", fine_buffer.getvalue())
+
+    valid_fov = np.zeros((600, 800), dtype=np.uint8)
+    valid_fov[:, :400] = 255
+    valid_fov_path = tmp_path / "valid-fov.png"
+    Image.fromarray(valid_fov, mode="L").save(valid_fov_path)
+    destination = tmp_path / "coarse.zip"
+    counts = policy_video_module.build_policy_mask_archive(
+        source_archive=source,
+        destination_archive=destination,
+        fine_taxonomy={},
+        provider_label_map={},
+        valid_fov_mask=valid_fov_path,
+    )
+    with (
+        zipfile.ZipFile(destination) as archive,
+        Image.open(io.BytesIO(archive.read("masks/frame-000001.png"))) as image,
+    ):
+        coarse = np.asarray(image.convert("L"))
+    assert np.all(coarse[:, :400] == 4)
+    assert np.all(coarse[:, 400:] == 9)
+    assert counts[4] == 600 * 400
+    assert counts[9] == 600 * 400
+
+
 def _sha256(path: Path) -> str:
     return hashlib.sha256(path.read_bytes()).hexdigest()
 
@@ -290,9 +333,12 @@ def test_policy_review_reuses_sealed_video_and_links_yolox_tgs(
 
     def fake_policy_archive(**kwargs) -> list[int]:
         shutil.copyfile(kwargs["source_archive"], kwargs["destination_archive"])
-        return [4489 * 800 * 600, *([0] * 8)]
+        assert kwargs["valid_fov_mask"].is_file()
+        return [4489 * 800 * 600, *([0] * 9)]
 
     monkeypatch.setattr(policy_review_module, "build_policy_mask_archive", fake_policy_archive)
+    valid_fov_mask = tmp_path / "valid-fov-mask.png"
+    Image.new("L", (800, 600), color=255).save(valid_fov_mask)
     result_root = seal_vegetation_policy_review(
         base_lab_root=base_root,
         mission_policy_path=REPOSITORY_ROOT
@@ -300,6 +346,7 @@ def test_policy_review_reuses_sealed_video_and_links_yolox_tgs(
         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",
+        valid_fov_mask_path=valid_fov_mask,
         output_root=tmp_path / "results",
         created_at_utc="2026-08-28T08:00:00+00:00",
     )
@@ -312,8 +359,9 @@ def test_policy_review_reuses_sealed_video_and_links_yolox_tgs(
     assert route["taxonomy"]["schema_version"] == (
         "missioncore.lab-v1-terrain-policy-taxonomy/v1"
     )
-    assert len(route["taxonomy"]["classes"]) == 9
-    assert len(manifest["artifacts"]) == 79
+    assert len(route["taxonomy"]["classes"]) == 10
+    assert route["valid_fov"]["outside_valid_fov_class_id"] == 9
+    assert len(manifest["artifacts"]) == 80
     assert manifest["authority"]["commands_enabled"] is False
     assert manifest["decision"]["multilayer_policy_review_ready"] is True