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Linzaer/Face-Track-Detect-Extract

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Linzaer/Face-Track-Detect-Extract has 622 GitHub stars and 205 forks. GitHot measured 0 stars in 24 hours. Last checked 2026-11-15 11:12 UTC. Last push 2019-06-01.

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What you can do

  • You can run it to extract the optimal face for everyone from a lot of videos and use it as a training set for CNN Training.
  • You can also send the extracted face to the backend for Face Recognition.

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Ãœber uns

💎 Detect , track and extract the optimal face in multi-target faces (exclude side face and select the optimal face).

Maschinelles Lernen

README.md

Original

Face Detection & Tracking & Extract

GitHub PyPI - Python Version

This project can detect , track and extract the optimal face in multi-target faces (exclude side face and select the optimal face).

Introduction

  • Dependencies:
    • Python 3.5+
    • Tensorflow
    • MTCNN
    • Scikit-learn
    • Numpy
    • Numba
    • Opencv-python
    • Filterpy

Run

  • To run the python version of the code :
python3 start.py
  • Then you can find faces extracted stored in the floder ./facepics .
  • If you want to draw 5 face landmarks on the face extracted,you just add the argument face_landmarks
python3 start.py --face_landmarks

What can this project do?

  • You can run it to extract the optimal face for everyone from a lot of videos and use it as a training set for CNN Training.
  • You can also send the extracted face to the backend for Face Recognition.

Results

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Special Thanks to:

License

MIT LICENSE