rough playable version finished

locate_finders.py

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+from PIL import Image
+import numpy as np
+from numpy.lib.stride_tricks import sliding_window_view
+
+def load_bw(path):
+    # Black=1, White=0
+    im = Image.open(path).convert("L")
+    bw = (np.array(im) < 128).astype(np.uint8)
+    return bw
+
+def finder_template(box_size=2):
+    # 7x7 finder: outer black, inner white (5x5), center black (3x3)
+    F = np.array([
+        [1,1,1,1,1,1,1],
+        [1,0,0,0,0,0,1],
+        [1,0,1,1,1,0,1],
+        [1,0,1,1,1,0,1],
+        [1,0,1,1,1,0,1],
+        [1,0,0,0,0,0,1],
+        [1,1,1,1,1,1,1],
+    ], dtype=np.uint8)
+    # upscale to pixels
+    return np.kron(F, np.ones((box_size, box_size), dtype=np.uint8))
+
+def count_finders(img_path, box_size=2, max_mismatch=0):
+    bw = load_bw(img_path)
+    T = finder_template(box_size=box_size)
+    h, w = T.shape
+    # slide 14x14 window over the image
+    win = sliding_window_view(bw, (h, w))
+    # Hamming distance to template per window
+    mismatches = (win ^ T).sum(axis=(-2, -1))
+    hits = mismatches <= max_mismatch
+    # Optional: suppress overlapping duplicates by non-maximum suppression on exact matches
+    ys, xs = np.where(hits)
+    # Convert to center coordinates
+    centers = [(int(y + h/2), int(x + w/2)) for y, x in zip(ys, xs)]
+
+    # Greedy dedup within ~half a finder width
+    deduped = []
+    r = max(2, h//2)
+    for cy, cx in centers:
+        if all((abs(cy - y) > r) or (abs(cx - x) > r) for y, x in deduped):
+            deduped.append((cy, cx))
+
+    return len(deduped), deduped
+
+if __name__ == "__main__":
+    n, centers = count_finders("./scrambled_test_qr_code.png", box_size=2, max_mismatch=0)
+    print("Finder count:", n, "centers:", centers, "Exactly three?", n == 3)
+