e75c4d6f07
- Remove session-ses_2f27.md (161KB raw session log) - Remove 49 ROOT_* duplicate files across REFERENCE/ - Remove 14 duplicate files between REFERENCE/ root and history/ - Remove asr_legacy.rs (dead code, replaced by asr.rs) - Remove src/core/worker/ (duplicate JobWorker) - Remove src/core/layers/ (empty directory) - Remove 4 .bak files in src/ - Remove 7 dead private methods in worker/processor.rs - Remove backup directory from git tracking
101 lines
3.2 KiB
Python
101 lines
3.2 KiB
Python
#!/opt/homebrew/bin/python3.11
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"""
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Find Inverted Jenny Stamp (Blue Rectangle in Hands)
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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 SMALL BLUE RECTANGLES in hands (Inverted Jenny)...")
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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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# 1. Hand Detection (Skin Tone) - Broad range
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skin_mask = cv2.inRange(hsv, np.array([0, 20, 40]), np.array([25, 150, 255]))
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# Clean up mask
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kernel = np.ones((5, 5), np.uint8)
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skin_mask = cv2.morphologyEx(skin_mask, cv2.MORPH_CLOSE, kernel)
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skin_mask = cv2.morphologyEx(skin_mask, cv2.MORPH_OPEN, kernel)
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# 2. Blue Detection (Stamp Background)
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# Inverted Jenny is Blue and Red. We look for the Blue part.
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blue_mask = cv2.inRange(hsv, np.array([90, 40, 40]), np.array([130, 255, 255]))
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# 3. Intersection: Blue INSIDE/NEAR Hands
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# We dilate the skin mask to include things held IN the hand
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skin_dilated = cv2.dilate(skin_mask, kernel, iterations=3)
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# Find blue things touching hands
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stamp_candidate_mask = cv2.bitwise_and(blue_mask, skin_dilated)
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# 4. Find contours in the intersection
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contours, _ = cv2.findContours(
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stamp_candidate_mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE
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)
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print(f"\n🎞️ Scanning {frame_name}...")
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found_count = 0
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for cnt in contours:
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x, y, w, h = cv2.boundingRect(cnt)
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area = cv2.contourArea(cnt)
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# Stamp size: Small rectangle (bigger than a dot, smaller than a face)
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# Area: 200 - 5000 pixels
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if 200 < area < 5000:
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aspect_ratio = float(w) / h
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# Check if it looks like a stamp (rectangular, aspect ratio 0.8 - 1.5 roughly)
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if 0.6 < aspect_ratio < 1.8:
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found_count += 1
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print(f" ✅ Candidate: Area={int(area)}, Pos=({x},{y}), Size={w}x{h}")
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# Crop with padding
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pad = 5
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crop = img[
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max(0, y - pad) : min(img.shape[0], y + h + pad),
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max(0, x - pad) : min(img.shape[1], x + w + pad),
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]
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crop_path = os.path.join(
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BASE_DIR, f"blue_stamp_{frame_name}_{x}_{y}.jpg"
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)
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cv2.imwrite(crop_path, crop)
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# Draw on main image
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cv2.rectangle(img, (x, y), (x + w, y + h), (0, 255, 0), 3)
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cv2.putText(
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img,
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"BLUE STAMP?",
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(x, y - 10),
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cv2.FONT_HERSHEY_SIMPLEX,
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0.6,
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(0, 255, 0),
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2,
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)
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if found_count == 0:
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print(" ❌ No blue stamp candidates found in hands.")
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else:
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res_path = os.path.join(BASE_DIR, f"result_blue_{frame_name}")
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cv2.imwrite(res_path, img)
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