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
117 lines
3.8 KiB
Python
117 lines
3.8 KiB
Python
#!/opt/homebrew/bin/python3.11
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"""
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Find Stamps by detecting Hands first
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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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UUID = "384b0ff44aaaa1f1"
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BASE_DIR = f"output/{UUID}/florence2_results"
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# Frames to check
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FRAMES = [
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"scan_6756.jpg", # 112:36
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"scan_6763.jpg", # 112:43
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"scan_6790.jpg", # 113:10
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"scan_6813.jpg", # 113:33
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"scan_6832.jpg", # 113:52
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]
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print("🖐️ Searching for Stamps via Hand Detection...")
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for frame_name in FRAMES:
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img_path = os.path.join(BASE_DIR, frame_name)
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if not os.path.exists(img_path):
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continue
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img = cv2.imread(img_path)
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hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
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# Skin Color Range (Approximate for Caucasian skin)
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# Hue: 0-30 (Red/Orange/Yellowish), Sat: 30-200, Val: 50-255
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mask = cv2.inRange(hsv, np.array([0, 30, 50]), np.array([30, 200, 255]))
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# Morphological operations to clean up
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kernel = np.ones((5, 5), np.uint8)
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mask = cv2.morphologyEx(mask, cv2.MORPH_CLOSE, kernel)
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mask = cv2.morphologyEx(mask, cv2.MORPH_OPEN, kernel)
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# Find contours (Hands)
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contours, _ = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
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print(f"\n🎞️ Scanning {frame_name} for hands...")
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hand_count = 0
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for cnt in contours:
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area = cv2.contourArea(cnt)
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x, y, w, h = cv2.boundingRect(cnt)
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# Filter for hand-like size and shape
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# Hand area: 1000 - 20000 pixels
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# Aspect ratio: roughly 1:1 to 2:3
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if 1000 < area < 30000:
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aspect_ratio = float(w) / h
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if 0.3 < aspect_ratio < 2.5:
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hand_count += 1
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print(
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f" 🖐️ Hand Candidate found: Area={int(area)}, Pos=({x},{y}), Size={w}x{h}"
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)
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# Crop Hand
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hand_crop = img[y : y + h, x : x + w]
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hand_crop_path = os.path.join(
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BASE_DIR, f"hand_{frame_name}_{hand_count}.jpg"
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)
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cv2.imwrite(hand_crop_path, hand_crop)
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# Draw on main image
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cv2.rectangle(img, (x, y), (x + w, y + h), (255, 0, 0), 3)
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# Analyze Hand for Stamp Colors
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# Stamp is Inverted Jenny: Blue Background, Red Plane
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# Look for Blue or Pink/Red blobs inside the hand
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hand_hsv = cv2.cvtColor(hand_crop, cv2.COLOR_BGR2HSV)
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# 1. Look for Blue (Background)
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blue_mask = cv2.inRange(
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hand_hsv, np.array([90, 50, 50]), np.array([130, 255, 255])
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)
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# 2. Look for Pink/Red (Plane)
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pink_mask = cv2.inRange(
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hand_hsv, np.array([150, 50, 50]), np.array([179, 255, 255])
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)
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blue_area = cv2.countNonZero(blue_mask)
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pink_area = cv2.countNonZero(pink_mask)
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# Heuristic: If we find significant Blue and Pink areas in the hand
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if blue_area > 50 and pink_area > 20:
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print(
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f" ✅ Potential Stamp in Hand! (Blue={blue_area}, Pink={pink_area})"
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)
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cv2.putText(
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img,
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f"STAMP? ({blue_area})",
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(x, y + h + 20),
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cv2.FONT_HERSHEY_SIMPLEX,
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1,
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(0, 255, 0),
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2,
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)
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cv2.imwrite(
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os.path.join(
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BASE_DIR, f"found_stamp_hand_{frame_name}_{hand_count}.jpg"
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),
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hand_crop,
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)
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if hand_count == 0:
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print(" ❌ No hands found.")
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res_path = os.path.join(BASE_DIR, f"result_hands_{frame_name}")
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cv2.imwrite(res_path, img)
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