# mtcnn-pytorch

**Repository Path**: anold/mtcnn-pytorch

## Basic Information

- **Project Name**: mtcnn-pytorch
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2019-11-05
- **Last Updated**: 2020-12-19

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# mtcnn-pytorch
# Descriptions in chinese
  https://blog.csdn.net/Sierkinhane/article/details/83308658

# results:

![](https://github.com/Sierkinhane/mtcnn-pytorch/blob/master/results/r_1.jpg)
![](https://github.com/Sierkinhane/mtcnn-pytorch/blob/master/results/r_2.jpg)
![](https://github.com/Sierkinhane/mtcnn-pytorch/blob/master/results/r_3.jpg)
![](https://github.com/Sierkinhane/mtcnn-pytorch/blob/master/results/r_4.jpg)



# Test an image
  * run > python mtcnn_test.py
 
# Training data prepraring
  * download [WIDER FACE](https://pan.baidu.com/s/1sJTO7TcQ2576RUqR_IIhbQ) (passcode:lsl3) face detection data then store it into ./data_set/face_detection
    * run > python ./anno_store/tool/format/transform.py change .mat(wider_face_train.mat) into .txt(anno_train.txt)
  * download [CNN_FacePoint](http://mmlab.ie.cuhk.edu.hk/archive/CNN_FacePoint.htm) face detection and landmark data then store it into ./data_set/face_landmark

# Training
  * preparing data for P-Net
    * run > python mtcnn/data_preprocessing/gen_Pnet_train_data.py
    * run > python mtcnn/data_preprocessing/assemble_pnet_imglist.py
  * train P-Net
    * run > python mtcnn/train_net/train_p_net.py
    
  * preparing data for R-Net
    * run > python mtcnn/data_preprocessing/gen_Rnet_train_data.py (maybe you should change the pnet model path)
    * run > python mtcnn/data_preprocessing/assemble_rnet_imglist.py
  * train R-Net
    * run > python mtcnn/train_net/train_r_net.py
  
  * preparing data for O-Net
    * run > python mtcnn/data_preprocessing/gen_Onet_train_data.py
    * run > python mtcnn/data_preprocessing/gen_landmark_48.py
    * run > python mtcnn/data_preprocessing/assemble_onet_imglist.py
  * train O-Net
    * run > python mtcnn/train_net/train_o_net.py
    
 # Citation
   [DFace](https://github.com/kuaikuaikim/DFace)