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TRTForYolov3

Desc

tensorRT for Yolov3

alt tag

Test Enviroments

Ubuntu  16.04
TensorRT 4.0.1.6
CUDA 9.0

Models

Download the caffe model converted by official model:

Run Sample

#build source code
git submodule update --init --recursive
mkdir build
cd build && cmake .. && make && make install
cd ..

#for mobilenet-yolov3-608

> sh demo.sh

Performance

Model GPU Mode Inference Time
mobilenet-yolov3-608 GTX 1080 float32 12.655ms
mobilenet-yolov3-608 Jetson nano float32 247.655ms
mobilenet-yolov3-lite-320 Jetson nano float32 114.055ms
mobilenet-yolov3-lite-320 Jetson nano float16 97.189 ms
  • The performance in jetson nano was not satisfactory , I will try to optimize it

Details About Wrapper

see link TensorRTWrapper

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TensorRT for Yolov3

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  • C++ 76.8%
  • Cuda 14.5%
  • Python 4.9%
  • CMake 3.4%
  • Shell 0.4%