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Serving PyTorch Models in C++ on Windows10 platforms

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How to use

Prepare Data

examples/data/train/

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examples/data/test/

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Train Model

cd examples && python train.py

Transform Model

cd examples && python transform_model.py

Test Model

cd makefile/pytorch
mkdir build && cd build && cmake -A x64 ..

or

mkdir build && cd build && cmake -G "Visual Studio 15 2017 Win64" ..

set Command Arguments -> ..\..\..\examples\checkpoint ..\..\..\examples\images
set Environment -> path=%path%;../../../thirdparty/libtorch/lib;../../../thirdparty/opencv/build/x64/vc15/bin;

Test CUDA Softmax

cd makefile/cuda
mkdir build && cd build && cmake -A x64 ..

or

mkdir build && cd build && cmake -G "Visual Studio 15 2017 Win64" ..

Inference onnx model

cd makefile/tensorRT/classification
mkdir build && cd build && cmake -A x64 ..

or

mkdir build && cd build && cmake -G "Visual Studio 15 2017 Win64" ..
set Environment -> path=%path%;../../../../thirdparty/TensorRT/lib;

Inference caffe model for faster-rcnn

cd makefile/tensorRT/detection
mkdir build && cd build && cmake -A x64 ..

or

mkdir build && cd build && cmake -G "Visual Studio 15 2017 Win64" ..
set Environment -> path=%path%;../../../../thirdparty/TensorRT/lib;

download VGG16_faster_rcnn_final.caffemodel

Thirdparty

thirdparty/
	- libtorch  
	- opencv 
	- CUDA
	- TensorRT
	

download thirdparty from here.

Docker

docker pull zccyman/deepframe
nvidia-docker run -it --name=mydocker zccyman/deepframe /bin/bash
cd workspace && git clone https://github.com/zccyman/pytorch-inference.git

Environment

Todo List

Notes

Acknowledgement