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            "License :: OSI Approved :: Apache Software License",
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        "description": "[![Python 3.6](https://img.shields.io/badge/python-3.6-blue.svg)](https://www.python.org/downloads/release/python-360/)\n[![License](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://opensource.org/licenses/Apache-2.0)\n\n# Access Face Vision\n\nFace detection and recognition Application.\n\n### With pip\n - ##### Installation\n```bash\npip install access-face-vision\n```\n\n- ##### Training/Creating FaceGroup\n```bash\npython -m access_face_vision --mode train --img_dir samples/celebrities --face_group celebrities\n\n# Directory structure\n# **/Images/\n#          A/\n#           A_K_01.jpg\n#           A_K_02.jpg\n#          B/\n#           B_S_01.jpg\n#           B_S_02.jpg\n```\n\n- ##### Running Inferences\n```bash\n# Live video feed\n>python -m access_face_vision --mode live-video --camera-index 0 --camera_wait 30 --face_group celebrities\n\n# server mode\npython -m access_face_vision --mode server\n```\nUse [access-client](https://github.com/accessai/access-client) to make requests to this server\n\n\n### Docker image\n\n- Docker Image build\n```bash\ndocker build -t access_face_vision:latest .\n```\n\n - Docker run\n ```bash\n# we will use it as root directory for access_face_vision application\nmkdir -p accessai/afv\n\n# Start server\ndocker run -v $(pwd)/afv:/accessai/afv python -m access_face_vision --mode server\n\n# Start camera feed processor\ndocker run -v $(pwd)/afv:/accessai/af v python -m access_face_vision --mode server\n```\n\n## Contribution\n Contributions are welcome. Feel free to raise PRs! with any improvements.\n\n\n## Credit\nFace Encoder model: https://github.com/nyoki-mtl/keras-facenet",
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