{"id":23397536,"url":"https://github.com/rishraks/face_recognition","last_synced_at":"2026-02-04T04:36:27.544Z","repository":{"id":268276738,"uuid":"903845237","full_name":"rishraks/Face_Recognition","owner":"rishraks","description":"A Python-based Face Recognition project utilizing OpenCV, MediaPipe, and a trained machine learning model for real-time face detection and recognition. The system identifies individuals from live camera feeds with high accuracy, leveraging facial landmarks and bounding boxes to provide seamless predictions.","archived":false,"fork":false,"pushed_at":"2024-12-27T07:13:45.000Z","size":16,"stargazers_count":2,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-02-14T14:25:54.511Z","etag":null,"topics":["ai","mediapipe-facemesh","opencv-python","python","scikitlearn-machine-learning"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/rishraks.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2024-12-15T17:45:35.000Z","updated_at":"2025-01-04T18:46:57.000Z","dependencies_parsed_at":"2024-12-16T00:50:28.814Z","dependency_job_id":null,"html_url":"https://github.com/rishraks/Face_Recognition","commit_stats":null,"previous_names":["rishraks/face_recognition"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rishraks%2FFace_Recognition","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rishraks%2FFace_Recognition/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rishraks%2FFace_Recognition/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rishraks%2FFace_Recognition/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/rishraks","download_url":"https://codeload.github.com/rishraks/Face_Recognition/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":247898520,"owners_count":21014722,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["ai","mediapipe-facemesh","opencv-python","python","scikitlearn-machine-learning"],"created_at":"2024-12-22T08:19:09.928Z","updated_at":"2026-02-04T04:36:22.524Z","avatar_url":"https://github.com/rishraks.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Face Recognition Project\n\nThis project is a Python-based real-time Face Recognition system that uses OpenCV, MediaPipe, and a machine learning model to detect and recognize faces. Users must collect data, process it, train the model, and then test it for face recognition.\n\n## Features\n- Real-time face detection using MediaPipe Face Detection.\n- Face landmark mapping with MediaPipe Face Mesh.\n- Accurate face recognition powered by a user-trained machine learning model.\n- Easily extensible for adding new individuals or improving recognition accuracy.\n\n## Installation\n\n1. **Clone the Repository:**\n   ```bash\n   git clone https://github.com/rishraks/Face_Recognition.git\n   cd face-recognition-project\n   ```\n\n2. **Set Up Virtual Environment:**\n   ```bash\n   python -m venv env\n   source env/bin/activate  # On Windows: env\\Scripts\\activate\n   ```\n\n3. **Install Dependencies:**\n   ```bash\n   pip install mediapipe opencv-python\n   ```\n\n4. **Organize Data for Training:**\n   - Create a folder `Data_Collection` with subfolders named after each person's name.\n   - Place corresponding images in each folder.\n\n5. **Train the Model:**\n   - Run the training script:\n     ```bash\n     python Data_Training.py\n     ```\n   - Save the generated model as `model.p` in the project directory.\n\n## Usage\n\n### Real-Time Face Recognition\nAfter training the model, run the following command to start the application:\n```bash\npython Data_Testing.py\n```\n- Press `Q` to quit the application.\n\n### Training a New Model\nTo train a new model with your dataset:\n1. Ensure the dataset is organized in the `Data_Collection` folder.\n2. Run the training script:\n   ```bash\n   python training.py\n   ```\n3. Save the generated model as `model.p`.\n\n## Requirements\n- Python 3.7+\n- OpenCV\n- MediaPipe\n- NumPy\n- Scikit-learn\n\n## File Structure\n```\nface-recognition-project/\n├── Data_Collection/       # Dataset folder with subfolders for each person\n├── model.p                # Trained model (generated by the user)\n├── Testing.py             # Script for real-time face recognition\n├── Data_Training.py       # Script for training the face recognition model\n├── Data_Collection.py     # Script for data collection\n├── Data_Processing.py     # Script for data processing\n└── README.md              # Project documentation\n```\n\n## Future Enhancements\n- Add support for multiple cameras.\n- Improve recognition accuracy with more training data.\n- Implement GUI for user-friendly interaction.\n\n## Acknowledgements\nThis project leverages the following libraries and tools:\n- [OpenCV](https://opencv.org/)\n- [MediaPipe](https://mediapipe.dev/)\n- [Scikit-learn](https://scikit-learn.org/)\n\n## License\nThis project is licensed under the MIT License. See `LICENSE` for more details.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Frishraks%2Fface_recognition","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Frishraks%2Fface_recognition","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Frishraks%2Fface_recognition/lists"}