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
68 lines
1.9 KiB
Python
68 lines
1.9 KiB
Python
#!/opt/homebrew/bin/python3.11
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"""
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Export Person Thumbnails
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職責：從聚類後的數據中提取每個 Person 的臉部截圖，用於確認身份。
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"""
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import cv2
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import json
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import os
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import sys
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# 設定
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OUTPUT_DIR = "output/quick_preview"
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VIDEO_PATH = os.path.join(OUTPUT_DIR, "preview.mp4")
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JSON_PATH = os.path.join(OUTPUT_DIR, "preview.face_clustered.json")
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def main():
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if not os.path.exists(VIDEO_PATH):
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print("❌ Video not found.")
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return
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if not os.path.exists(JSON_PATH):
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print("❌ Clustered JSON not found.")
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return
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print(f"🔍 Extracting person thumbnails from {JSON_PATH}...")
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with open(JSON_PATH) as f:
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data = json.load(f)
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cap = cv2.VideoCapture(VIDEO_PATH)
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saved_persons = set()
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for frame_obj in data.get("frames", []):
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ts = frame_obj.get("timestamp")
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faces = frame_obj.get("faces", [])
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for face in faces:
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pid = face.get("person_id")
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# 如果這個 Person ID 還沒被存過
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if pid and pid not in saved_persons:
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# 定位到該時間點
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cap.set(cv2.CAP_PROP_POS_MSEC, ts * 1000)
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ret, frame = cap.read()
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if ret:
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x, y, w, h = face["x"], face["y"], face["width"], face["height"]
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# 稍微擴大裁剪範圍以包含完整臉部特徵
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margin = 5
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crop = frame[
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max(0, y - margin) : y + h + margin,
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max(0, x - margin) : x + w + margin,
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]
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out_path = os.path.join(OUTPUT_DIR, f"{pid}.jpg")
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cv2.imwrite(out_path, crop)
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print(f"✅ Saved {pid} to {out_path}")
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saved_persons.add(pid)
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cap.release()
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print(f"\n🎉 Finished! Saved {len(saved_persons)} unique person thumbnails.")
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if __name__ == "__main__":
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main()
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