fix: use structured images in duplicate detection tests

tests/test_analyzer.py

@@ -49,21 +49,42 @@ def test_normal_image_is_neither(tmp_path):
 from analyzer import find_duplicates
 
 
+def make_gradient_image(tmp_path, name="gradient.jpg"):
+    from PIL import Image
+    img = Image.new("L", (100, 100))
+    pixels = img.load()
+    for y in range(100):
+        for x in range(100):
+            pixels[x, y] = x * 255 // 100
+    p = tmp_path / name
+    img.convert("RGB").save(p)
+    return str(p)
+
+
+def make_diagonal_image(tmp_path, name="diagonal.jpg"):
+    from PIL import Image
+    img = Image.new("L", (100, 100))
+    pixels = img.load()
+    for y in range(100):
+        for x in range(100):
+            pixels[x, y] = 255 if x > y else 0
+    p = tmp_path / name
+    img.convert("RGB").save(p)
+    return str(p)
+
+
 def test_identical_images_are_duplicates(tmp_path):
-    p1 = make_test_image(tmp_path, color=(100, 150, 200))
+    p1 = make_gradient_image(tmp_path, "img1.jpg")
     import shutil
     p2 = tmp_path / "copy.jpg"
     shutil.copy(p1, p2)
-    groups = find_duplicates([p1, str(p2)], threshold=0)
+    groups = find_duplicates([p1, str(p2)], threshold=8)
     assert len(groups) == 1
     assert len(groups[0]) == 2
 
 
 def test_different_images_are_not_duplicates(tmp_path):
-    from PIL import Image
-    p1 = make_test_image(tmp_path, color=(0, 0, 0))
-    img = Image.new("RGB", (100, 100), color=(255, 0, 0))
-    p2 = tmp_path / "red.jpg"
-    img.save(p2)
-    groups = find_duplicates([p1, str(p2)], threshold=0)
+    p1 = make_gradient_image(tmp_path, "gradient.jpg")
+    p2 = make_diagonal_image(tmp_path, "diagonal.jpg")
+    groups = find_duplicates([p1, p2], threshold=8)
     assert len(groups) == 0