dataset

[YING1992]

thanks for share your code.
I have few questions for training the model.
I try to train P/R/O net with 100000 dataset which include pos, part and neg(2:3:6). However, the results seems bad. I just change the learning rate to 0.00001, other params are keeped. Is my dataset is too small for this problem? If it is possible, can you share your dataset?

[Seanlinx]

@YING1992 How did you get your data set, did you follow the instructions in README to generate training set for Rnet and Onet?

[YING1992]

thanks for your reply.
At first, in my training, i follow the instructions in README. when i generate onet training set, i get nothing with default params. then, i just use method like gen_pnet_data.py to generate rnet and onet training set.

[gehaocool]

Hi, @Seanlinx , I have some questions about preparing the training data from WiderFace.

I followed the data preparation instruction in README

1. generate data for pnet
2. use gen_hard_example.py to get data for rnet and onet

After these 2 steps, the amount of rnet training data is:
pos: 93576, neg: 4856413, part: 279664, is the pos data enough?

and for onet, pos: 167997, neg:34483, part: 79545, is the negative data and part data enough?
I read in another issue that you said 60w false positive is needed for rnet, and 8w for onet. I don't know if I get it right, or I set the wrong params in gen_hard_example.py. Shoud I use the similar method of gen_pnet_data.py to generate some 'easy' samples for rnet and onet?

please give me some instruction, thanks!