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As a series of tutorials on the most popular deep learning algorithms for new-entry deep learning research engineers, MTCNN has been widely adopted in industry for human face detection task which is an essential step for subsquential face recognition and facial expression analysis. This tutorial is designed to explain how to implement the algorithm. In this tutorial, developers will learn how to build MTCNN model for face detection task.

Python 6.49% Jupyter Notebook 93.51%

mtcnn_tutorial's Introduction

MTCNN_Tutorial-

As a series of tutorials on the most popular deep learning algorithms for new-entry deep learning research engineers, MTCNN has been widely adopted in industry for human face detection task which is an essential step for subsquential face recognition and facial expression analysis. This tutorial is designed to explain how to implement the algorithm. In this tutorial, developers will learn how to build MTCNN model for face detection task.

Results

Test Image

python MTCNN.py --test_image 'images/s_l.jpg' --mini_face 20

Test Video

python Video.py --scale 1 --mini_face 32

How to implement MTCNN

Please go through the details on MTCNN_Step_by_Step.ipynb

How to train MTCNN

Please go through the details on MTCNN_Training_Step_by_Step.ipynb

Reference

  1. Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks
  2. Coding is heavily based on Dface

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