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
97 lines
2.8 KiB
Python
97 lines
2.8 KiB
Python
#!/opt/homebrew/bin/python3.11
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"""
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Batch Scan Keyframes for SMALL red stamps
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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 json
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UUID = "384b0ff44aaaa1f1"
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BASE_DIR = f"output/{UUID}/florence2_results"
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# The keyframes we extracted
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FRAMES = [
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"scan_6751.jpg", # 112:31
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"scan_6755.jpg", # 112:35
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"scan_6759.jpg", # 112:39
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]
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def find_small_stamps_in_frame(img_path):
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if not os.path.exists(img_path):
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return []
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img = cv2.imread(img_path)
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if img is None:
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return []
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h, w, _ = img.shape
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hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
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# Red Mask
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mask1 = cv2.inRange(hsv, np.array([0, 70, 50]), np.array([10, 255, 255]))
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mask2 = cv2.inRange(hsv, np.array([170, 70, 50]), np.array([180, 255, 255]))
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mask = mask1 + mask2
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contours, _ = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
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found = []
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# Constraint: Stamp must be small.
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# If the image is 1080p, a stamp held in hand is likely < 200x200 pixels?
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# Let's say Area < 30,000 pixels (approx 5% of width * 5% of height).
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MAX_STAMP_AREA = 30000
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for cnt in contours:
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area = cv2.contourArea(cnt)
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if area > MAX_STAMP_AREA:
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continue
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# Shape Constraint: Triangle or Rectangle
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peri = cv2.arcLength(cnt, True)
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approx = cv2.approxPolyDP(cnt, 0.04 * peri, True)
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vertices = len(approx)
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# Check for Triangle (3) or Rectangle (4)
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if vertices in [3, 4]:
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x, y, w_box, h_box = cv2.boundingRect(approx)
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# Aspect ratio check? Stamps are usually rectangular or square.
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# Triangles are rare for stamps unless folded.
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# Let's just return everything small and triangular/rectangular for now.
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found.append((x, y, w_box, h_box, area, approx))
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return found, img
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print("🔍 Scanning Keyframes for Small Stamps...")
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for frame_name in FRAMES:
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frame_path = os.path.join(BASE_DIR, frame_name)
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result, img = find_small_stamps_in_frame(frame_path)
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print(f"\n🎞️ Analyzing {frame_name}...")
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if result:
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print(f" ✅ Found {len(result)} potential small stamps!")
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# Draw them
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for x, y, w_box, h_box, area, approx in result:
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print(f" 📍 Box: ({x},{y}), Size: {w_box}x{h_box}, Area: {area}")
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cv2.rectangle(img, (x, y), (x + w_box, y + h_box), (0, 255, 0), 2)
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# Save crop
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crop_name = f"crop_{frame_name}_{x}_{y}.jpg"
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crop_path = os.path.join(BASE_DIR, crop_name)
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crop = img[y : y + h_box, x : x + w_box]
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cv2.imwrite(crop_path, crop)
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# Save result image
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res_name = f"result_opencv_{frame_name}"
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cv2.imwrite(os.path.join(BASE_DIR, res_name), img)
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else:
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print(f" ❌ No small stamps found.")
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