Machine Learning for human detection on encrypted video streams 🧠
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The goal of this project is to analyze the traffic generated by a webcam call and, from such traffic, identify whether a person or only the background is recorded in the video. The problem is approached by a Machine Learning (ML) standpoint, acquiring data and creating a labelled dataset as a ground truth.
Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.
If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag "enhancement". Don't forget to give the project a star! Thanks again!
- Fork the Project
- Create your Feature Branch (
git checkout -b feature/AmazingFeature) - Commit your Changes (
git commit -m 'Add some AmazingFeature') - Push to the Branch (
git push origin feature/AmazingFeature) - Open a Pull Request
Distributed under the GPLv3 License. See LICENSE for more information.
Giovanni Baccichet - @Giovanni_Bacci - github[at]baccichet.org