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Support CPU and GPU inference, and the pruned model can also be used for inference.

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YINYIPENG-EN/YOLOv4_libtorch

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pth权重转为pt,将权重放在与main.cpp同一路径下(放在别的地方也可用,但需要将路径填写正确,建议绝对路径且不要有中文),同时填写类的txt文件路径,比如我这里用的coco_classes.txt。mode是预测模式,如果是image,表示预测图像,并在image_path填写路径,如果是video,为视频预测,填写image_path视频路径。

环境

windows 10

pytorch:1.7.0(低版本应该也可以)

libtorch 1.7 Debug版

cuda 10.2

VS 2017

英伟达 1650 4G

环境配置可见:https://blog.csdn.net/z240626191s/article/details/124341346 如果本项目对你有帮助,麻烦点个star~

其他细节:https://blog.csdn.net/z240626191s/article/details/125491741

权重: 链接:https://pan.baidu.com/s/1AMUSnVqMO3ERyH9cPV_5jw 提取码:yypn

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Support CPU and GPU inference, and the pruned model can also be used for inference.

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