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yolov5-tensorrt-inference's Introduction

YoloV5-TensorRT-inference

这是一个使用C++推理的tensorRT引擎文件的案例。

系统：Ubuntu 编译：VScode + Cmake

使用步骤

一、onnx文件准备

运行原作者yolov5项目下的export.py，导出所需onnx文件
python export.py --weights yolov5s.pt --include onnx



二、onnx转engine(trt)文件

使用官方转换器trtexec(文件填写自己对应的路径)
sudo ./trtexec --onnx=yolov5s.onnx --saveEngine=yolov5s.trt
trtexec文件在TensorRT目录下的bin文件。

yolov5s.trt文件百度云下载：链接: https://pan.baidu.com/s/1nmrxr7n19ZxwldBJw64USA?pwd=QWER 提取码: QWER

三、Cmake

CMakeLists.txt 路径依赖替换成自己的路径
代码中图片、engine(trt)文件、保存路径 替换成自己路径
VScode项目中按ctrl+shift+P，选择Cmake配置，此时生成build文件夹
cd ./build/
cmake ..
make
现在build文件夹中生成一个可执行文件infer
在sample_photo中：
命令行输入./infer 运行即可完成推理输出
在sample_video中：命令行输入需要添加视频源文件路径和输出路径两个参数
例： ./infer /dev/video0 /home/zc/C++_TensorRT_inference/sample_video/video/0_0.mp4
./infer /home/zc/C++_TensorRT_inference/sample_video/video/0.mp4 /home/zc/C++_TensorRT_inference/sample_video/video/0_0.mp4

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