feat(perception): add full camera-first shadow

2026-07-30 23:15:06 +03:00
parent dee6d57133
commit dc6f9b66da
12 changed files with 1932 additions and 29 deletions
@@ -0,0 +1,96 @@
+from __future__ import annotations
+
+from typing import Any
+
+from k1link.compute.e53_camera_first_shadow import (
+    _Profile,
+    adjacent_family_matches,
+    select_candidate_detections,
+)
+
+
+def _profile() -> _Profile:
+    return _Profile(
+        raw={},
+        expected_source_pack_id="source",
+        expected_local_surface_id="surface",
+        expected_detector_result_id="detector",
+        expected_baseline_e29_id="baseline",
+        target_labels=frozenset({"person", "car", "truck"}),
+        label_groups={
+            "person": ("person",),
+            "vehicle": ("car", "truck"),
+        },
+        minimum_detector_score=0.5,
+        maximum_bbox_image_fraction=0.25,
+        adjacent_family_iou=0.25,
+        baseline_family_iou=0.25,
+        maximum_latency_p95_ms=50.0,
+        maximum_rss_growth_mib=512.0,
+    )
+
+
+def test_candidate_filter_keeps_camera_semantics_and_rejects_large_box() -> None:
+    selected, counts = select_candidate_detections(
+        [
+            {
+                "instance_id": 1,
+                "label": "person",
+                "score": 0.99,
+                "box_xyxy": [100.0, 100.0, 180.0, 300.0],
+                "mask_pixels": 4000,
+            },
+            {
+                "instance_id": 2,
+                "label": "car",
+                "score": 0.95,
+                "box_xyxy": [0.0, 0.0, 800.0, 600.0],
+                "mask_pixels": 480000,
+            },
+            {
+                "instance_id": 3,
+                "label": "laptop",
+                "score": 0.98,
+                "box_xyxy": [10.0, 10.0, 100.0, 100.0],
+            },
+        ],
+        width=800,
+        height=600,
+        profile=_profile(),
+    )
+
+    assert len(selected) == 1
+    assert selected[0]["label"] == "person"
+    assert selected[0]["association_group"] == "person"
+    assert selected[0]["cuboid_status"] == "camera-candidate-no-cuboid"
+    assert counts["pathological_large_box"] == 1
+    assert counts["non_target"] == 1
+
+
+def test_adjacent_matching_is_family_aware_and_one_to_one() -> None:
+    previous: list[dict[str, Any]] = [
+        {
+            "association_group": "vehicle",
+            "bbox_xyxy": [10.0, 10.0, 110.0, 110.0],
+        },
+        {
+            "association_group": "person",
+            "bbox_xyxy": [200.0, 20.0, 240.0, 120.0],
+        },
+    ]
+    current: list[dict[str, Any]] = [
+        {
+            "association_group": "vehicle",
+            "bbox_xyxy": [12.0, 12.0, 112.0, 112.0],
+        },
+        {
+            "association_group": "vehicle",
+            "bbox_xyxy": [14.0, 14.0, 114.0, 114.0],
+        },
+        {
+            "association_group": "person",
+            "bbox_xyxy": [202.0, 22.0, 242.0, 122.0],
+        },
+    ]
+
+    assert adjacent_family_matches(previous, current, minimum_iou=0.25) == 2
@@ -0,0 +1,95 @@
+from __future__ import annotations
+
+import pytest
+
+from k1link.compute.rig_geometry import (
+    RIG_GEOMETRY_SCHEMA,
+    RigGeometryError,
+    parse_rig_geometry,
+)
+
+
+def _unbound() -> dict[str, object]:
+    return {
+        "schema_version": RIG_GEOMETRY_SCHEMA,
+        "profile_id": "portable-k1/unbound-v1",
+        "rig_kind": "portable",
+        "qualification": {
+            "state": "unbound",
+            "reason": "no measured mount",
+            "evidence_sha256": [],
+        },
+        "coordinate_frames": {
+            "lidar_frame": "k1-lidar",
+            "body_frame": None,
+            "body_from_lidar": None,
+        },
+        "vehicle_body": None,
+        "authority": {
+            "commands_enabled": False,
+            "navigation_or_safety_accepted": False,
+        },
+    }
+
+
+def test_unbound_portable_rig_fails_closed_without_inventing_geometry() -> None:
+    geometry = parse_rig_geometry(_unbound())
+
+    assert geometry.metric_body_geometry_available is False
+    assert geometry.collision_geometry_qualified is False
+    assert geometry.collision_contract()["state"] == "unavailable"
+    assert geometry.collision_contract()["recent_collision_publishable"] is False
+
+
+def test_unbound_rig_rejects_hidden_physical_values() -> None:
+    value = _unbound()
+    value["coordinate_frames"] = {
+        "lidar_frame": "k1-lidar",
+        "body_frame": "vehicle-body",
+        "body_from_lidar": None,
+    }
+
+    with pytest.raises(RigGeometryError, match="must not contain physical values"):
+        parse_rig_geometry(value)
+
+
+def test_measured_mount_does_not_grant_collision_authority() -> None:
+    value = _unbound()
+    value.update(
+        {
+            "profile_id": "measured-rig/v1",
+            "rig_kind": "vehicle-mounted",
+            "qualification": {
+                "state": "measured",
+                "reason": "bench measurement only",
+                "evidence_sha256": ["a" * 64],
+                "uncertainty": {
+                    "translation_1sigma_m": 0.01,
+                    "rotation_1sigma_deg": 0.2,
+                    "body_dimension_1sigma_m": 0.01,
+                },
+            },
+            "coordinate_frames": {
+                "lidar_frame": "k1-lidar",
+                "body_frame": "vehicle-body",
+                "body_from_lidar": {
+                    "from_frame": "k1-lidar",
+                    "to_frame": "vehicle-body",
+                    "translation_m": [0.0, 0.0, 1.0],
+                    "quaternion_xyzw": [0.0, 0.0, 0.0, 1.0],
+                },
+            },
+            "vehicle_body": {
+                "frame": "vehicle-body",
+                "shape": "axis-aligned-box",
+                "minimum_xyz_m": [-1.0, -0.5, -0.2],
+                "maximum_xyz_m": [1.0, 0.5, 1.2],
+            },
+        }
+    )
+
+    geometry = parse_rig_geometry(value)
+
+    assert geometry.metric_body_geometry_available is True
+    assert geometry.collision_geometry_qualified is False
+    assert geometry.collision_contract()["state"] == "unavailable"