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使用ONNXRuntime部署鲁棒性视频抠图,包含C++和Python两种版本的程序

C++ 82.94% Python 17.06%

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robustvideomatting-onnxruntime

使用ONNXRuntime部署鲁棒性视频抠图,包含C++和Python两种版本的程序

在PeterL1n的github仓库里有一套很火的开源代码BackgroundMattingV2,在这个算法里,有两个输入, 一个是带人物的图片,另一个是不带人物的纯背景图片,有了背景作为一个很强的先验指导,使得BMV2在4K高分率的图片上以很快的性能跑出较高的抠图精度, 但是对于用户来讲,这是一个很不友好的。因为用户在实际拍摄时很少会刻意再去拍一个背景图,这就导致BackgroundMattingV2的应用场景很受限。 不过在最近,PeterL1n发布了一套新的视频抠图开源程序,这时的输入只有一张RGB图,这个就很好。因此我决定编写一套视频抠图的推理程序。 起初,我想使用opencv的dnn模块作为推理引擎,但是程序运行到cv2.dnn.readNet(modelpath) 这里时报错,因此我决定使用onnxruntime 作为推理引擎,程序能正常运行

模型文件在百度网盘,链接:https://pan.baidu.com/s/1dnbmmjrztex64xDjMzHSUA 提取码:616v

下载完模型文件后,就可以运行程序里,C++版本的主程序是main.cpp,Python版本的主程序是main.py

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