tensorflow-MTCNN:人脸检测MTCNN算法,采用tensorflow框架编写,从理解到训练,中文注释完全,含测试和训练,支持摄像头-源码

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张量流 人脸检测MTCNN算法,采用tensorflow框架编写,从理解到训练,中文注释完全,含测试和训练,支持摄像头,代码参考 ,相应地减少了尺寸和优化。 模型理解 是目前比较流行的人脸检测方法,通过人脸检测可以进行更精准的人脸识别。模型主要通过PNet,RNet,ONet三个网络级联,一步一步精调来对人脸进行更准确的检测。论文中的模型图如下: 接下来我会从我在训练中的理解来解释MTCNN模型都干了什么。三个模型要按顺序训练,首先是PNet,然后RNet,最后ONet。 PNet: PNet是全卷积网络,主要为了应对不同输入尺度,层数很浅,主要作用是重新多的把人脸框都选进来,宁愿错误拿来好

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