wip: [01-stabilize] paused at task 1/1 - OCR Hallucination Immune logic via Semantic delta window and fret-isolation

verify_pdf.py

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+import fitz
+import cv2
+import numpy as np
+
+def _get_ocr_reader():
+    import easyocr
+    return easyocr.Reader(['en'])
+
+def verify_pdf_with_ocr(pdf_path):
+    print(f"Opening PDF for OCR Verification: {pdf_path}")
+    doc = fitz.open(pdf_path)
+    print(f"Total Pages: {len(doc)}")
+    
+    reader = _get_ocr_reader()
+    
+    for i in range(len(doc)):
+        page = doc[i]
+        pix = page.get_pixmap(dpi=150)
+        img = np.frombuffer(pix.samples, dtype=np.uint8).reshape(pix.height, pix.width, pix.n)
+        
+        if pix.n == 4:
+            img = cv2.cvtColor(img, cv2.COLOR_BGRA2BGR)
+        elif pix.n == 1:
+            img = cv2.cvtColor(img, cv2.COLOR_GRAY2BGR)
+            
+        gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
+        h, w = gray.shape
+        
+        # Count staff lines
+        _, thresh = cv2.threshold(gray, 200, 255, cv2.THRESH_BINARY_INV)
+        row_sums = np.sum(thresh, axis=1) / 255.0
+        staff_rows = np.where(row_sums > w * 0.4)[0]
+        
+        # Group them
+        staff_blocks = []
+        if len(staff_rows) > 0:
+            c = [staff_rows[0]]
+            for r in staff_rows[1:]:
+                if r - c[-1] < 10:
+                    c.append(r)
+                else:
+                    staff_blocks.append(c)
+                    c = [r]
+            staff_blocks.append(c)
+
+        print(f"\n[Page {i+1}] (Shape: {w}x{h})")
+        print(f" - Found {len(staff_blocks)} horizontal staff lines/blocks.")
+        
+        # Read measure number using OCR from top left
+        if len(staff_blocks) > 0:
+            top_y = staff_blocks[0][0]
+        else:
+            top_y = 100
+        
+        crop_y1 = max(0, top_y - 60)
+        crop_y2 = top_y + 10
+        crop_x2 = int(w * 0.15)
+        
+        crop = gray[crop_y1:crop_y2, :crop_x2]
+        upscaled = cv2.resize(crop, (0,0), fx=3.0, fy=3.0, interpolation=cv2.INTER_CUBIC)
+        _, upscaled_thresh = cv2.threshold(upscaled, 150, 255, cv2.THRESH_BINARY_INV)
+        
+        results = reader.readtext(upscaled_thresh, allowlist='0123456789')
+        if results:
+            print(f" - OCR Candidate Measure Numbers: {[r[1] for r in results]}")
+        else:
+            print(f" - No Measure Number Detected.")
+
+if __name__ == "__main__":
+    verify_pdf_with_ocr("output/shintakarajima_perfect.pdf")