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It utilizes OpenCV for image processing, Dlib for facial landmark detection, and Pygame for alarm notifications. The application is built on Flask for easy web streaming of the video feed.\n\n## Features\n- Real-time drowsiness detection using webcam feed.\n- Facial landmark analysis to detect eyes, mouth, and nose positions.\n- Eye Aspect Ratio (EAR) algorithm for detecting closed eyes.\n- Audio alerts for detected drowsiness.\n- Web interface for streaming the video feed.\n\n## Installation\n\n### Prerequisites\n- Python 3.x\n- OpenCV\n- Dlib\n- Pygame\n- Pillow\n- Flask\n\n### Setup\n1. Clone the repository:\n\n```bash\ngit clone https://github.com/hitthecodelabs/DrowsinessDetectorStream.git\n```\n2. Install the required packages:\n```bash\npip install -r requirements.txt\n```\n\n## Usage\nTo start the application, run the following command in your terminal:\n```bash\npython app_cv2.py\n```\n\nOpen a web browser and navigate to `http://localhost:5000` to view the streaming video feed.\n\n## Contribution\nContributions to DrowsinessDetectorStream are welcome. Please ensure to follow best practices and code standards when contributing.\n\n## License\n[MIT License](LICENSE)\n\n## Acknowledgments\n- Haar Cascades for face and eye detection.\n- Dlib's facial landmark predictor.\n- Pygame for audio playback.\n- Flask for web framework capabilities.\n\n## Contact\nFor any inquiries, please contact [e-mail](mailto:jpaul@hitthecodelabs.com).\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fhitthecodelabs%2Fdrowsinessdetectorstream","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fhitthecodelabs%2Fdrowsinessdetectorstream","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fhitthecodelabs%2Fdrowsinessdetectorstream/lists"}