feat(v1): add pose quality evidence

v1/tests/test_evidence.py

@@ -0,0 +1,76 @@
+from v1.pose import Keypoint, PersonPose
+from v1.evidence import assess_pose_quality, extract_evidence
+from v1.tracking import PersonTracker
+
+
+def _pose(box=(20.0, 20.0, 60.0, 140.0), horizontal=False, missing_ankles=False):
+    points = [Keypoint(float(index), float(index), 0.9) for index in range(17)]
+    if horizontal:
+        points[5] = Keypoint(20.0, 50.0, 0.9)
+        points[6] = Keypoint(30.0, 50.0, 0.9)
+        points[11] = Keypoint(70.0, 53.0, 0.9)
+        points[12] = Keypoint(80.0, 53.0, 0.9)
+    if missing_ankles:
+        points[15] = Keypoint(35.0, 120.0, 0.1)
+        points[16] = Keypoint(45.0, 120.0, 0.1)
+    return PersonPose(box_xyxy=box, box_confidence=0.9, keypoints=tuple(points))
+
+
+def test_tracker_keeps_id_for_nearby_person_in_next_frame():
+    tracker = PersonTracker(max_match_distance_ratio=0.2)
+
+    first = tracker.update([_pose()], detected_at_monotonic=1.0, frame_size=(200, 200))
+    second = tracker.update(
+        [_pose(box=(23.0, 22.0, 63.0, 142.0))],
+        detected_at_monotonic=1.1,
+        frame_size=(200, 200),
+    )
+
+    assert first[0].track_id == second[0].track_id
+
+
+def test_missing_ankles_rejects_pose():
+    quality = assess_pose_quality(_pose(missing_ankles=True), threshold=0.4)
+
+    assert quality.accepted is False
+    assert quality.reason == "required_joint_low_confidence"
+
+
+def test_horizontal_body_is_evidence_not_event():
+    pose = _pose(horizontal=True)
+    quality = assess_pose_quality(pose, threshold=0.4)
+
+    evidence = extract_evidence(pose, quality=quality, previous=None)
+
+    assert evidence.accepted is True
+    assert evidence.horizontal_pose is True
+    assert evidence.rapid_vertical_change is False
+
+
+def test_missing_pose_cannot_create_usable_evidence():
+    quality = assess_pose_quality(None, threshold=0.4)
+
+    evidence = extract_evidence(None, quality=quality, previous=None)
+
+    assert quality.accepted is False
+    assert evidence.accepted is False
+
+
+def test_large_hip_drop_is_normalized_as_rapid_vertical_evidence():
+    previous_pose = _pose()
+    current_points = list(previous_pose.keypoints)
+    current_points[11] = Keypoint(11.0, 100.0, 0.9)
+    current_points[12] = Keypoint(12.0, 100.0, 0.9)
+    current_pose = PersonPose(
+        box_xyxy=previous_pose.box_xyxy,
+        box_confidence=previous_pose.box_confidence,
+        keypoints=tuple(current_points),
+    )
+    previous_quality = assess_pose_quality(previous_pose, threshold=0.4)
+    current_quality = assess_pose_quality(current_pose, threshold=0.4)
+    previous = extract_evidence(previous_pose, quality=previous_quality, previous=None)
+
+    evidence = extract_evidence(current_pose, quality=current_quality, previous=previous)
+
+    assert evidence.accepted is True
+    assert evidence.rapid_vertical_change is True