使用OpenCV部署YOLOX,支持YOLOX-S、YOLOX-M、YOLOX-L、YOLOX-X、YOLOX-Darknet53五种结构,包含C++和Python两种版本的程序

Overview

yolox-opencv-dnn

使用OpenCV部署YOLOX,支持YOLOX-S、YOLOX-M、YOLOX-L、YOLOX-X、YOLOX-Darknet53五种结构,包含C++和Python两种版本的程序

onnx文件在百度云盘,下载链接:https://pan.baidu.com/s/11UAVSPWbDKY_LmmoHlUQXw 提取码:147w

下载完成后,把文件放在代码文件所在目录里,就可以运行程序了。如果出现读取onnx文件失败, 那很有可能是你的opencv版本低了,需要升级到4.5以上的

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Comments
  • 你好除了YOLOX-S 其他模型都报错,这是什么原因?谢谢

    你好除了YOLOX-S 其他模型都报错,这是什么原因?谢谢

    Traceback (most recent call last): File "main.py", line 153, in net = yolox(args.model, p6=args.with_p6, confThreshold=args.score_thr) File "main.py", line 9, in init self.net = cv2.dnn.readNet(model) cv2.error: OpenCV(4.5.3) C:\Users\runneradmin\AppData\Local\Temp\pip-req-build-q3d_8t8e\opencv\modules\dnn\src\onnx\onnx_importer.cpp:78: error: (-5:Bad argument) Can't read ONNX file: yolox_m.onnx in function 'cv::dnn::dnn4_v20210608::ONNXImporter::ONNXImporter'

    opened by vc815 2
  • 您好,我跑通了opencv dnn推理yolox-tiny

    您好,我跑通了opencv dnn推理yolox-tiny

    我如你所说注释掉了均值那些(void yolox::normalize(Mat& img)) 然后就跑通了,但是我感觉AP好像没有ncnn高(threshold阈值都是0.25),当然速度确实比ncnn快了一倍(i3-8100 cpu)。 请问是不是要改如下几处? 也就是说yolox-tiny不能沿用你在cpp里预设好的值?

    const int stride[3] = { 8, 16, 32 }; const float mean[3] = { 0.485, 0.456, 0.406 }; const float std[3] = { 0.229, 0.224, 0.225 };

    opened by wwzh2015 0
  • 关于opencv dnn实现神经网络的问题

    关于opencv dnn实现神经网络的问题

    关注了你在CSDN的博客,工作很棒,请继续加油! 另外我有个不情之请,能不能写一篇关于opencv dnn实现神经网络的文章呢? 比如,有些网络结构中的某些层,在opencv自己的定义中没有,需要自行改动layer的定义,能否结合一个实例,给介绍一下如何实现?需要注意的问题有哪些? 不情之请,还望百忙之中抽时间给与支持!

    再谢再盼!

    opened by opentld 1
Owner
深度学习算法工程师
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