用opencv的dnn模块做yolov5目标检测,包含C++和Python两个版本的程序

Overview

yolov5-dnn-cpp-py

yolov5s,yolov5l,yolov5m,yolov5x的onnx文件在百度云盘下载, 链接:https://pan.baidu.com/s/1d67LUlOoPFQy0MV39gpJiw 提取码:bayj

python版本的主程序是main_yolov5.py,C++版本的主程序是main_yolo.cpp

运行整套程序只需要安装opencv库(4.0以上版本的),彻底摆脱对深度学习框架的依赖

如果你想运行生成onnx文件的程序,那么就cd到convert-onnx文件夹,在百度云盘下载yolov5s,yolov5l,yolov5m,yolov5x的.pth文件放在该目录里, 百度云盘链接: https://pan.baidu.com/s/1oIdwpp6kuasANMInTpHnrw 密码: m3n1

这4个pth文件是从https://github.com/ultralytics/yolov5 的pth文件里抽取出参数,保存到顺序字典OrderedDict里,最后生成新的pth文件 在convert-onnx文件夹里,我把4种yolov5的网络结构全都定义在.py文件里,这样便于读者直观的了解网络结构以及层与层的连接关系。 下载完成pth文件后,运行convert_onnx.py就可以生成.onnx文件,这个程序需要依赖pytorch1.7.0框架,如果pytorch版本低了,程序运行会报错。 因为在yolov5里有新的激活函数,旧版本pytorch可能不支持的

在编写这套程序时,遇到的bug和解决办法,可以阅读我的csdn博客 https://blog.csdn.net/nihate/article/details/112731327

Owner
深度学习算法工程师
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