# 68-Retinaface-Pytorch-version

**Repository Path**: jiangvshine/Retinaface-Pytorch-version

## Basic Information

- **Project Name**: 68-Retinaface-Pytorch-version
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 1
- **Forks**: 0
- **Created**: 2020-04-24
- **Last Updated**: 2022-04-29

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# Retinaface-Pytorch-version
### It's not the best version of my model due to confidentiality
Thanks to Alvin Yang (https://github.com/supernotman/RetinaFace_Pytorch)

This is the branch for 68 landmarks detection, the pre-trained model is in ./out 

Working on 96 landmarks detection( refer to the other branch)

<p align="center"><img src="assets/1.jpg" width="200"\></p>
<p align="center"><img src="assets/2.jpg" width="200"\></p>
<p align="center"><img src="assets/3.jpg" width="200"\></p>



Based on RetinaFace 
### current model 
mobileNet V1+FPN+context module+ regressor  1.6MB
CPU～10FPS GPU 50FPU



### Train：（ Please refer to dataloader.py to change the file location）
python3 train.py -train
This model use LS3D-W dataset，or change your dataset to the format of demo.pt/ demo.jpg（68*2 tensor）


### Use local camera ：
python3 video_detect.py （ need to delete all 'cuda()', and run locally with a CPU）


### Eval Model：
python3 train.py -train False

## Todo: 
- [ ] Use SBR and BFLD to improve performance

If you have train a model with this code, welcome to discuss with me at elvishelvis6@gmail.com