guard norfair distance against non-finite and zero-area boxes that could crash autotracking cameras (#23475)

frigate/test/test_norfair_distance.py

@@ -0,0 +1,91 @@
+import math
+import unittest
+
+import numpy as np
+from norfair.camera_motion import (
+    HomographyTransformation,
+    TranslationTransformation,
+)
+
+from frigate.ptz.autotrack import transform_is_finite
+from frigate.track.norfair_tracker import distance
+
+
+class TestNorfairDistance(unittest.TestCase):
+    """Regression tests for the tracker distance guard.
+
+    norfair raises a hard ValueError on any nan distance, which kills the camera
+    process. During autotracking, an ill-conditioned homography can hand the
+    tracker a non-finite or degenerate estimate box, so distance() must never
+    return nan for any input.
+    """
+
+    def setUp(self) -> None:
+        # boxes are [[x1, y1], [x2, y2]]
+        self.detection = np.array([[805.0, 402.0], [864.0, 521.0]])
+        self.estimate = np.array([[800.0, 400.0], [860.0, 520.0]])
+
+    def test_finite_boxes_give_finite_distance(self) -> None:
+        d = distance(self.detection, self.estimate)
+        self.assertTrue(math.isfinite(d))
+
+    def test_inf_estimate_corner_does_not_return_nan(self) -> None:
+        estimate = np.array([[np.inf, 400.0], [860.0, 520.0]])
+        d = distance(self.detection, estimate)
+        self.assertFalse(math.isnan(d))
+        self.assertEqual(d, float("inf"))
+
+    def test_nan_estimate_corner_does_not_return_nan(self) -> None:
+        # the actual autotracking crash: a positive-only guard would miss this
+        # because nan <= 0 is False
+        estimate = np.array([[np.nan, 400.0], [860.0, 520.0]])
+        d = distance(self.detection, estimate)
+        self.assertFalse(math.isnan(d))
+        self.assertEqual(d, float("inf"))
+
+    def test_zero_area_estimate_does_not_return_nan(self) -> None:
+        estimate = np.array([[900.0, 500.0], [900.0, 500.0]])
+        d = distance(self.detection, estimate)
+        self.assertFalse(math.isnan(d))
+        self.assertEqual(d, float("inf"))
+
+    def test_zero_area_detection_does_not_return_nan(self) -> None:
+        detection = np.array([[805.0, 402.0], [805.0, 521.0]])
+        d = distance(detection, self.estimate)
+        self.assertFalse(math.isnan(d))
+        self.assertEqual(d, float("inf"))
+
+    def test_inverted_estimate_corners_do_not_return_nan(self) -> None:
+        # Kalman estimates can occasionally cross corners (x2 < x1)
+        estimate = np.array([[860.0, 520.0], [800.0, 400.0]])
+        d = distance(self.detection, estimate)
+        self.assertFalse(math.isnan(d))
+        self.assertEqual(d, float("inf"))
+
+
+class TestTransformIsFinite(unittest.TestCase):
+    def test_finite_homography_is_finite(self) -> None:
+        matrix = np.array([[1.0, 0.0, 5.0], [0.0, 1.0, 3.0], [0.0, 0.0, 1.0]])
+        self.assertTrue(transform_is_finite(HomographyTransformation(matrix)))
+
+    def test_finite_translation_is_finite(self) -> None:
+        self.assertTrue(
+            transform_is_finite(TranslationTransformation(np.array([12.0, -4.0])))
+        )
+
+    def test_non_finite_homography_is_not_finite(self) -> None:
+        transform = HomographyTransformation(np.eye(3))
+        # simulate accumulation overflowing to a non-finite matrix
+        transform.homography_matrix = np.array(
+            [[1.0, 0.0, np.inf], [0.0, 1.0, 0.0], [0.0, 0.0, 1.0]]
+        )
+        self.assertFalse(transform_is_finite(transform))
+
+    def test_nan_translation_is_not_finite(self) -> None:
+        self.assertFalse(
+            transform_is_finite(TranslationTransformation(np.array([np.nan, 0.0])))
+        )
+
+
+if __name__ == "__main__":
+    unittest.main()