8f05a7c188
- Update ASR, face, OCR, pose processors - Add release pre-flight check script - Add synonym generation, chunk processing scripts - Add face recognition, stamp search utilities
73 lines
2.4 KiB
Python
73 lines
2.4 KiB
Python
#!/opt/homebrew/bin/python3.11
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"""
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Scan key stamp scenes from Charade (1963) for stamp-related objects
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Looking for: envelopes, letters, stamp albums, small rectangular paper objects
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"""
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import cv2
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import numpy as np
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import os
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import glob
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BASE_DIR = "output/384b0ff44aaaa1f1/stamp_scenes"
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OUTPUT_DIR = "output/384b0ff44aaaa1f1/stamp_scenes_crops"
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os.makedirs(OUTPUT_DIR, exist_ok=True)
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frames = sorted(glob.glob(os.path.join(BASE_DIR, "scene_*.jpg")))
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print(f"🎬 Scanning {len(frames)} key stamp scene frames...")
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for frame_path in frames:
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img = cv2.imread(frame_path)
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if img is None:
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continue
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gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
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# 1. Look for rectangular objects (edges + contours)
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edges = cv2.Canny(gray, 50, 150)
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contours, _ = cv2.findContours(edges, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
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frame_crops = 0
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for contour in contours:
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area = cv2.contourArea(contour)
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if area < 500 or area > 100000:
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continue
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# Approximate polygon
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epsilon = 0.02 * cv2.arcLength(contour, True)
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approx = cv2.approxPolyDP(contour, epsilon, True)
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# Look for 4-sided shapes (rectangles)
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if len(approx) == 4:
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x, y, w, h = cv2.boundingRect(contour)
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aspect = w / h if h > 0 else 0
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# Stamp/letter/envelope proportions
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if 0.3 < aspect < 3.0:
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# Check if it's paper-like (light colored)
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roi = gray[y : y + h, x : x + w]
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mean_val = np.mean(roi)
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# Paper is typically light (high pixel values)
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if mean_val > 120:
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frame_crops += 1
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crop = img[y : y + h, x : x + w]
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basename = os.path.basename(frame_path).replace(".jpg", "")
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crop_path = os.path.join(
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OUTPUT_DIR, f"paper_{basename}_{x}_{y}.jpg"
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)
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cv2.imwrite(crop_path, crop)
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# Draw on full frame
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cv2.rectangle(img, (x, y), (x + w, y + h), (0, 255, 0), 2)
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if frame_crops > 0:
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print(
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f" 📍 {os.path.basename(frame_path)}: {frame_crops} paper-like rectangles"
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)
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ann_path = os.path.join(OUTPUT_DIR, f"annotated_{os.path.basename(frame_path)}")
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cv2.imwrite(ann_path, img)
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print(f"\n🏁 Done. Check {OUTPUT_DIR} for paper object crops.")
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