feat: blur detection via Laplacian variance

analyzer.py

@@ -0,0 +1,11 @@
+import cv2
+import numpy as np
+
+
+def is_blurry(path: str, threshold: float = 100.0) -> bool:
+    """Gibt True zurueck, wenn das Bild unscharf ist (Laplacian Variance < threshold)."""
+    img = cv2.imread(path, cv2.IMREAD_GRAYSCALE)
+    if img is None:
+        return False
+    variance = cv2.Laplacian(img, cv2.CV_64F).var()
+    return bool(variance < threshold)

tests/test_analyzer.py

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+import pytest
+from pathlib import Path
+from analyzer import is_blurry
+
+
+def make_test_image(tmp_path, color=(200, 200, 200)):
+    from PIL import Image
+    img = Image.new("RGB", (100, 100), color=color)
+    p = tmp_path / "test.jpg"
+    img.save(p)
+    return str(p)
+
+
+def test_solid_color_image_is_blurry(tmp_path):
+    path = make_test_image(tmp_path)
+    assert is_blurry(path, threshold=100) is True
+
+
+def test_normal_image_is_not_blurry(tmp_path):
+    from PIL import Image, ImageDraw
+    img = Image.new("RGB", (100, 100), color=(255, 255, 255))
+    draw = ImageDraw.Draw(img)
+    for i in range(0, 100, 2):
+        draw.line([(i, 0), (i, 100)], fill=(0, 0, 0), width=1)
+    p = tmp_path / "sharp.jpg"
+    img.save(p)
+    assert is_blurry(str(p), threshold=100) is False