Initial project import

tests/test_fingerprinting.py

@@ -0,0 +1,112 @@
+"""
+tests/test_fingerprinting.py — Unit tests for src/cv/fingerprinting.py
+
+Tests run WITHOUT requiring real video files.
+"""
+
+from __future__ import annotations
+
+import numpy as np
+import pytest
+
+from src.cv.fingerprinting import (
+    text_safe_crop,
+    extract_hs_histograms,
+    compare_histograms,
+    hist_to_bytes,
+    bytes_to_hist,
+)
+
+
+# ---------------------------------------------------------------------------
+# Fixtures
+# ---------------------------------------------------------------------------
+
+@pytest.fixture
+def solid_blue_frame() -> np.ndarray:
+    """256×256 solid blue BGR frame."""
+    frame = np.zeros((256, 256, 3), dtype=np.uint8)
+    frame[:, :] = (255, 0, 0)  # BGR blue
+    return frame
+
+
+@pytest.fixture
+def solid_red_frame() -> np.ndarray:
+    """256×256 solid red BGR frame."""
+    frame = np.zeros((256, 256, 3), dtype=np.uint8)
+    frame[:, :] = (0, 0, 255)  # BGR red
+    return frame
+
+
+# ---------------------------------------------------------------------------
+# text_safe_crop
+# ---------------------------------------------------------------------------
+
+class TestTextSafeCrop:
+    def test_removes_correct_rows(self, solid_blue_frame: np.ndarray) -> None:
+        cropped = text_safe_crop(solid_blue_frame, crop_top=0.15, crop_bottom=0.30)
+        h = solid_blue_frame.shape[0]  # 256
+        expected_h = int(h * (1.0 - 0.30)) - int(h * 0.15)
+        assert cropped.shape[0] == expected_h
+
+    def test_zero_crop_returns_same_size(self, solid_blue_frame: np.ndarray) -> None:
+        cropped = text_safe_crop(solid_blue_frame, crop_top=0.0, crop_bottom=0.0)
+        assert cropped.shape == solid_blue_frame.shape
+
+    def test_invalid_top_raises(self, solid_blue_frame: np.ndarray) -> None:
+        with pytest.raises(ValueError, match="crop_top"):
+            text_safe_crop(solid_blue_frame, crop_top=1.0, crop_bottom=0.0)
+
+    def test_invalid_bottom_raises(self, solid_blue_frame: np.ndarray) -> None:
+        with pytest.raises(ValueError, match="crop_bottom"):
+            text_safe_crop(solid_blue_frame, crop_top=0.0, crop_bottom=-0.1)
+
+    def test_overlapping_crops_raise(self, solid_blue_frame: np.ndarray) -> None:
+        with pytest.raises(ValueError, match="must be < 1.0"):
+            text_safe_crop(solid_blue_frame, crop_top=0.6, crop_bottom=0.5)
+
+
+# ---------------------------------------------------------------------------
+# Histograms
+# ---------------------------------------------------------------------------
+
+class TestHistograms:
+    def test_output_shape(self, solid_blue_frame: np.ndarray) -> None:
+        luma, sat = extract_hs_histograms(solid_blue_frame, bins_hue=50, bins_sat=60)
+        assert luma.shape == (50,)
+        assert sat.shape  == (60,)
+
+    def test_normalised(self, solid_blue_frame: np.ndarray) -> None:
+        import numpy as np
+        luma, sat = extract_hs_histograms(solid_blue_frame, bins_hue=50, bins_sat=60)
+        # L2-normalised → norm ≈ 1.0
+        assert np.linalg.norm(luma) == pytest.approx(1.0, abs=1e-5)
+        assert np.linalg.norm(sat)  == pytest.approx(1.0, abs=1e-5)
+
+    def test_same_frame_correl_is_one(self, solid_blue_frame: np.ndarray) -> None:
+        import cv2
+        luma, _ = extract_hs_histograms(solid_blue_frame, bins_hue=50, bins_sat=60)
+        score = compare_histograms(luma, luma, method=cv2.HISTCMP_CORREL)
+        assert score == pytest.approx(1.0, abs=1e-5)
+
+    def test_different_frames_correl_lower(
+        self,
+        solid_blue_frame: np.ndarray,
+        solid_red_frame: np.ndarray,
+    ) -> None:
+        import cv2
+        luma_b, _ = extract_hs_histograms(solid_blue_frame, 50, 60)
+        luma_r, _ = extract_hs_histograms(solid_red_frame,  50, 60)
+        score = compare_histograms(luma_b, luma_r, method=cv2.HISTCMP_CORREL)
+        assert score < 1.0
+
+
+# ---------------------------------------------------------------------------
+# Serialisation round-trip
+# ---------------------------------------------------------------------------
+
+class TestSerialisation:
+    def test_round_trip(self, solid_blue_frame: np.ndarray) -> None:
+        luma, _ = extract_hs_histograms(solid_blue_frame, 50, 60)
+        restored = bytes_to_hist(hist_to_bytes(luma))
+        np.testing.assert_array_almost_equal(luma, restored)