yolov8 TensorRT

The Pytorch implementation is https://github.com/ultralytics/ultralytics.

onnx model

step1. install yolov8

 pip install ultralytics

step2. download yolov8 model from https://github.com/ultralytics/assets/releases

step3. convert yolov8 model to onnx

yolo mode=export model=yolov8n.pt format=onnx simplify=True

or you can download onnx model from here z16b

How to Run, yolov8n as example

1. Modify the tensorrt cuda opencv path in CMakeLists.txt

   #cuda 
   include_directories(/mnt/Gu/softWare/cuda-11.0/targets/x86_64-linux/include)
   link_directories(/mnt/Gu/softWare/cuda-11.0/targets/x86_64-linux/lib)
   
   #tensorrt 
   include_directories(/mnt/Gpan/tensorRT/TensorRT-8.2.0.6/include/)
   link_directories(/mnt/Gpan/tensorRT/TensorRT-8.2.0.6/lib/)
   

2. build

   1. mkdir build
   2. cd build
   3. cmake ..
   4. make
   
   

3. onnx to tensorrt model

   ./onnx2trt/onnx2trt  ../onnx_model/yolov8n.onnx ./yolov8n.trt  1
   
   

4. inference

   ./yolov8 ./yolov8n.trt  ../samples/
   

   The results are saved in the build folder.

   

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