Skip to content

Latest commit

 

History

History
49 lines (36 loc) · 1.75 KB

README.md

File metadata and controls

49 lines (36 loc) · 1.75 KB
Raw

RetinaFace

The pytorch implementation is biubug6/Pytorch_Retinaface, I forked it into wang-xinyu/Pytorch_Retinaface and add genwts.py

This branch is using TensorRT 7 API, branch trt4->retinaface is using TensorRT 4.

Run

1. generate retinaface.wts from pytorch implementation https://github.com/wang-xinyu/Pytorch_Retinaface

git clone https://github.com/wang-xinyu/Pytorch_Retinaface.git
// download its weights 'Resnet50_Final.pth', put it in Pytorch_Retinaface/weights
cd Pytorch_Retinaface
python detect.py --save_model
python genwts.py
// a file 'retinaface.wts' will be generated.

2. put retinaface.wts into tensorrtx/retinaface, build and run

git clone https://github.com/wang-xinyu/tensorrtx.git
cd tensorrtx/retinaface
// put retinaface.wts here
mkdir build
cd build
cmake ..
make
sudo ./retina_r50 -s  // build and serialize model to file i.e. 'retina_r50.engine'
wget https://github.com/Tencent/FaceDetection-DSFD/raw/master/data/worlds-largest-selfie.jpg
sudo ./retina_r50 -d  // deserialize model file and run inference.

3. check the images generated, as follows. result.jpg

Config

  • Input shape INPUT_H, INPUT_W defined in decode.h
  • FP16/FP32 can be selected by the macro USE_FP16 in retina_r50.cpp
  • GPU id can be selected by the macro DEVICE in retina_r50.cpp
  • Batchsize can be selected by the macro BATCHSIZE in retina_r50.cpp

More Information

See the readme in home page.