we0091234/yolov7-face-tensorrt

yolov7-face tensorrt

yolov7-face TensorRT

yolov7-face

The Pytorch implementation is yolov7-face.

onnx export

step1. git clone https://github.com/derronqi/yolov7-face

step2. modify models/export.py

 #line 72
 #output_names = None
 # modified into:
 output_names = ["output"]

step3. modify models/yolo.py class IKeypoint

#line 308
# return x if self.training else (torch.cat(z, 1), x)
# modified into:
return x if self.training else torch.cat(z, 1)

step4. Export to onnx model

 cd yolov7-face
 python models/export.py --weights yolov7s-face.pt --grid 

How to Run, yolov7s-face 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/yolov7s-face.onnx ./yolov7s-face.trt  1
   
   

4. inference

   ./yolov7_face yolov7s-face.trt ../images
   

   The results are saved in the build folder.

   

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