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Example workflow for detecting unique faces in videos

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Extracting unique faces in a video

This is an example project that discover and return any unique faces in a given video, using deepface.

Features

  • Face Detection: Locate faces in any given image.
  • Face Recognition: Verify the identity of individuals by comparing faces against known identities.
  • Anti-Spoofing: Optional anti-spoofing feature to enhance security by preventing fake identity verification.

Getting Started

Prerequisites

  • Python 3.x
  • Necessary Python packages as listed in requirements.txt. Install them using the command:
    pip install -r requirements.txt

Installation

git clone https://github.com/dannykok/deepface-example.git
pip install -r requirements.txt

Usage

To run the face detection and recognition:

python main.py path/to/video

Configuration

The project allows for various configurations, including the choice of face recognition model and similarity metric. These can be adjusted in the main.py script.

Output

Images of unique faces found will be output into the output_faces directory.

Contributing

Contributions to improve the project are welcome. Please follow the standard fork-and-pull request workflow.

License

This project is licensed under the MIT License - see the LICENSE file for details. However, it's important to note that this project depends on the DeepFace library. You should review its license and terms of use before using this project.

Acknowledgments

Thanks to the open-source community for providing the tools and libraries used in this project.

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Example workflow for detecting unique faces in videos

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