eroncero
432f0378bf
- Add Flask application with MJPEG video streaming - Implement OpenCV DNN face detection module - Add zone-based entry/exit tracking with cooldown mechanism - Create web interface with real-time WebSocket updates - Add model download script and comprehensive README - Include OpenCV DNN model files for face detection
79 lines
2.7 KiB
Python
79 lines
2.7 KiB
Python
#!/usr/bin/env python3
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"""
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Script to download OpenCV DNN face detection model files.
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Downloads the required prototxt and caffemodel files for face detection.
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"""
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import os
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import urllib.request
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from pathlib import Path
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def download_file(url, destination):
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"""Download a file from URL to destination."""
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print(f"Downloading {os.path.basename(destination)}...")
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try:
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urllib.request.urlretrieve(url, destination)
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print(f"✓ Successfully downloaded {os.path.basename(destination)}")
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return True
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except Exception as e:
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print(f"✗ Error downloading {os.path.basename(destination)}: {e}")
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return False
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def main():
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"""Main function to download model files."""
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# Create models directory if it doesn't exist
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models_dir = Path("models")
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models_dir.mkdir(exist_ok=True)
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# Model file URLs
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prototxt_url = "https://raw.githubusercontent.com/opencv/opencv/master/samples/dnn/face_detector/deploy.prototxt"
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model_url = "https://raw.githubusercontent.com/opencv/opencv_3rdparty/dnn_samples_face_detector_20170830/res10_300x300_ssd_iter_140000.caffemodel"
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# Destination paths
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prototxt_path = models_dir / "deploy.prototxt"
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model_path = models_dir / "res10_300x300_ssd_iter_140000.caffemodel"
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print("=" * 60)
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print("OpenCV DNN Face Detection Model Downloader")
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print("=" * 60)
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print()
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# Check if files already exist
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if prototxt_path.exists():
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print(f"⚠ {prototxt_path.name} already exists. Skipping download.")
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else:
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success = download_file(prototxt_url, prototxt_path)
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if not success:
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print("\nAlternative: You can manually download deploy.prototxt from:")
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print("https://github.com/opencv/opencv/blob/master/samples/dnn/face_detector/deploy.prototxt")
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print()
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if model_path.exists():
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print(f"⚠ {model_path.name} already exists. Skipping download.")
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else:
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success = download_file(model_url, model_path)
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if not success:
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print("\n⚠ Warning: The caffemodel file is large (~10MB) and may require manual download.")
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print("Alternative download methods:")
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print("1. Using wget:")
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print(f" wget -O {model_path} {model_url}")
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print("2. Using curl:")
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print(f" curl -L -o {model_path} {model_url}")
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print("3. Direct browser download:")
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print(f" {model_url}")
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print()
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print()
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print("=" * 60)
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if prototxt_path.exists() and model_path.exists():
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print("✓ All model files are ready!")
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else:
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print("⚠ Some files may be missing. Please check the files above.")
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print("=" * 60)
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if __name__ == "__main__":
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main()
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