Open sparrow0629 opened 7 years ago
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.
Thank you so much @cdicle really helps me a lot
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 ~~
I think we can't reach the author. Until now to be honest I still want to know how they train it.
@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?
Hello, thanks for sharing your code. I have some questions about training.