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It is designed to provide a more efficient and accurate method of attendance tracking, reducing the need for manual input and minimizing errors.\n\n## Tools used\n\n- PyTorch\n- FastAPI\n- [FaceNet Torch](https://github.com/timesler/facenet-pytorch/)\n- MTCNN and VGGFace (Not really tools but deserve a mention)\n\n## Features\n\n- Face detection: The system uses advanced face detection algorithms to identify individuals.\n- Attendance tracking: Once a face is detected and recognized, the system automatically marks the individual as present.\n\n## Installation\n\n1. Clone the repository: `git clone https://github.com/AbhijithGanesh/Rekognize.git`\n2. Navigate to the project directory: `cd Rekognize`\n3. Install the required dependencies: `pip install -r src/requirements.txt`\n4. Run the application: `python main.py`\n\n## Usage\n\nTo use the system, simply start the application and position the camera to capture the faces of the individuals. The system will automatically detect the faces and mark the attendance.\n\n## Contributing\n\nContributions are welcome!\n\n## License\n\nThis project is licensed under the terms of the MIT license. See the [LICENSE](LICENSE.md) file for details.\n\n## Contributors\n\n- [Abhijith Ganesh](https://github.com/AbhijithGanesh)\n- [Allen Bijo T](https://github.com/AllenBijo)\n\n## Disclaimer\n\nThis is a public fork of a private repository we worked on. Please re-train/change the dataset according to your use case.","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fabhijithganesh%2Frekognize","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fabhijithganesh%2Frekognize","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fabhijithganesh%2Frekognize/lists"}