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The Pytorch implementation is ultralytics/yolov5.
Currently, we support yolov5 v1.0(yolov5s only), v2.0, v3.0 and v3.1.
NET
macro in yolov5.cpp1. generate yolov5s.wts from pytorch with yolov5s.pt, or download .wts from model zoo
git clone https://github.com/wang-xinyu/tensorrtx.git
git clone https://github.com/ultralytics/yolov5.git
// download its weights 'yolov5s.pt'
// copy tensorrtx/yolov5/gen_wts.py into ultralytics/yolov5
// ensure the file name is yolov5s.pt and yolov5s.wts in gen_wts.py
// go to ultralytics/yolov5
python gen_wts.py
// a file 'yolov5s.wts' will be generated.
2. build tensorrtx/yolov5 and run
// put yolov5s.wts into tensorrtx/yolov5
// go to tensorrtx/yolov5
// ensure the macro NET in yolov5.cpp is s
mkdir build
cd build
cmake ..
make
sudo ./yolov5 -s // serialize model to plan file i.e. 'yolov5s.engine'
sudo ./yolov5 -v // deserialize plan file and run inference with camera or video.
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