Questions about training datasets about mtcnn_face_detection_alignment HOT 5 OPEN

Hi @sparrow0629,

Unfortunately, we haven't heard from @kpzhang93 about training much. I will try to answer your questions to the best of my knowledge and my experience with playing code.

He trains the networks both on WIDER and AFLW. WIDER is a nice large dataset good for face detection and AFLW has landmarks (WIDER does not).

The inputs must be square. In the training time I believe he is turning the rectangle to square, maybe smallest enclosing square. He is not distorting/rescaling the rectangle region to a square one.

A box is a true box if it has intersection over union ratio larger than 0.5. See III.A. in the paper for details.

Best,
Cha.

from mtcnn_face_detection_alignment.

Thank you so much @cdicle
really helps me a lot

from mtcnn_face_detection_alignment.

Hi, @cdicle
I'm also trying the training process of mtcnn, I guess there are many details and tricks that I don't know, expecially for landmark localization regression in multi-task training, it's really hard for me to find out, but it's really a fantastic projects, this is my trial: github.com/daikankan/mtcnn, hard to reach the author's precision ~~

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I think we can't reach the author. Until now to be honest I still want to know how they train it.

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@cdicle why is used the pnet to generate train datas for rnet? Whether can I use the train datas used in pnet to train rnet?

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