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
102 lines
2.8 KiB
Python
102 lines
2.8 KiB
Python
#!/opt/homebrew/bin/python3.11
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"""
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Find BLUE stamps (Inverted Jenny) or Envelopes
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Filter: Blue Color + Small/Medium Size
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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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# Keyframes to check
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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_6756.jpg", # 112:36 (Dialogue: "Give me the stamp")
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"scan_6759.jpg", # 112:39
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]
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print("🔍 Analyzing Keyframes for BLUE Stamps...")
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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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h, w, _ = img.shape
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# Convert to HSV
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hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
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# Blue Mask (Hue ~100-130)
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# Adjusting for various shades of blue
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mask1 = cv2.inRange(hsv, np.array([90, 50, 50]), np.array([130, 255, 255]))
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# Optional: Also look for White/Paper (Envelope)
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# mask2 = cv2.inRange(hsv, np.array([0, 0, 200]), np.array([180, 30, 255]))
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# mask = mask1 + mask2
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mask = mask1
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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 Blue objects...")
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found_count = 0
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for cnt in contours:
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area = cv2.contourArea(cnt)
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# FILTER 1: Area Size
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# We want something stamp-sized or envelope-sized
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# Stamp: ~100 - 5000 px
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# Envelope: ~1000 - 20000 px
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if area < 100 or area > 20000:
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continue
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# FILTER 2: Aspect Ratio (Rectangular)
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x, y, w_box, h_box = cv2.boundingRect(cnt)
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aspect_ratio = float(w_box) / h_box
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# Check if it looks like a rectangle (0.5 to 2.0 ratio roughly)
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# But stamps can be small. Let's just check area mostly.
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# Filter out very long thin lines (likely text)
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if w_box < 5 or h_box < 5:
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continue
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# Filter out very large backgrounds
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if w_box > 300 and h_box > 300:
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continue
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print(
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f" ✅ Found Blue Candidate: Area={int(area)}, Size={w_box}x{h_box}, Pos=({x},{y})"
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)
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# Draw
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cv2.rectangle(img, (x, y), (x + w_box, y + h_box), (0, 255, 0), 2)
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cv2.putText(
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img,
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f"BLUE? ({int(area)})",
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(x, y - 10),
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cv2.FONT_HERSHEY_SIMPLEX,
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0.5,
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(0, 255, 0),
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1,
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)
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# Crop
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crop = img[y : y + h_box, x : x + w_box]
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crop_path = os.path.join(BASE_DIR, f"crop_blue_{frame_name}_{x}_{y}.jpg")
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cv2.imwrite(crop_path, crop)
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found_count += 1
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if found_count > 0:
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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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else:
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print(" ❌ No blue candidates found.")
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