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BaofengZan 3d2228d7a9 hrnet classification trt 加速		2020-11-06 23:22:11 +08:00
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CMakeLists.txt	hrnet clasification trt 加速	2020-11-06 23:19:23 +08:00
demo.py	hrnet clasification trt 加速	2020-11-06 23:19:23 +08:00
hrnet.cpp	hrnet classification trt 加速	2020-11-06 23:22:11 +08:00
logging.h	hrnet clasification trt 加速	2020-11-06 23:19:23 +08:00
readme.md	hrnet classification trt 加速	2020-11-06 23:22:11 +08:00

readme.md

HRNet

The Pytorch implementation is HRNet-Image-Classification.

How to Run

1. generate .wts
Download code and model from HRNet-Image-Classification and config your environments.

Put demo.py in the YOUR_ROOT_DIR\HRNet-Image-Classification\tools folder, set savewts in main() as True, and run, the .wts will be generated.

cmake and make

mkdir build
cd build
cmake ..
make
sudo ./dbnet -s             // serialize model to plan file i.e. 'hrnet.engine'
sudo ./dbnet -d  ../samples // deserialize plan file and run inference, the images in samples will be processed.

Result

The test img:

Pytorch Result:

TRT Result: