描述如何在Deepstream 5.0中使用yolov5.zip

# 0.Instruction This Repos contains how to run yolov5 model in DeepStream 5.0 # 1.Geneate yolov5 engine model We can use https://github.com/wang-xinyu/tensorrtx yolov5 to generate engine model ### Important Note: You should replace yololayer.cu and hardswish.cu file in tensorrtx/yolov5 ### How to Run, yolov5s as example -- a). generate yolov5s.wts from pytorch with yolov5s.pt ``` 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. ``` -- b). 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' ``` We can get 'yolov5s.engine' and 'libmyplugin.so' here for the future use. # 2.Build DeepStream 5.0 nvdsinfer_custom_impl_yolo plugin In Deepstream 5.0/nvdsinfer_custom_impl_Yolo Directory, exec 'make' command. We can get libnvdsinfer_custom_impl_Yolo.so here. # 3.Modify configure file After build yolov5 plugin, modify 'config_infer_primary_yoloV5.txt' in Deepstream 5.0 Directory. -- a).In Line 58. "parse-bbox-func-name=NvDsInferParseCustomYoloV5" // This is the bbox parse function name. -- b).In Line 59. "custom-lib-path" // This is DeepStream plugin path. -- c).In Line 56. Comment "#cluster-mode=2". Becase we use custom NMS function. # 4. How to run it Running the application as ``` LD_PRELOAD=./libcustomOp.so deepstream-app -c <app-config> ```