Open Yangr116 opened 2 years ago
Another question about BoxInst. In the pairwise term, the the probability of making the same prediction = p_i p_j + (1 - p_i) (1 - p_j). However, lines 41-45 in 'adet/modeling/condinst/dynamic_mask_head.py' use the max to calculate this probability.
max_ = torch.max(log_same_fg_prob, log_same_bg_prob)
log_same_prob = torch.log(torch.exp(log_same_fg_prob - max_) +torch.exp(log_same_bg_prob - max_)) + max_
Why does not use
log_same_prob = torch.log(torch.exp(log_same_fg_prob)+torch.exp(log_same_bg_prob))
, directly? Looking forward to your reply~
Have you solved the above problems? I have the same questions.
@xulinxulin same question
@engrjav @engrjav From my experiments, the default settings are best. However, the second question is still not solved.
@Yangr116 i am facing an issue in training, which i posted as Issue no 572 (https://github.com/aim-uofa/AdelaiDet/issues/572) i get zero AP after training my custom dataset for 90 k iterations with the error No weights in checkpoint matched with model. Some model parameters or buffers are not found in the checkpoint:
can you guide
Thanks for your great work! In the paper, Table1(a) shows that the color similarity threshold of 0.1 catches the best performance. However, it is set to 0.3 in the configs(line 25). I would like to know what color similarity threshold could obtain the best performance.