Closed Arimitsu06 closed 1 week ago
Thanks for your attention. We use ignore_mask_cutmixed1
here to remain consistency with confidence map filter and loss function, which indeed has the potential to result in more pixels being ignored in the non-cutmixed prediction.
In fact, since the ignore mask for the unlabeled image is primarily generated by random cropping, using ignore_mask
instead of ignore_mask_cutmixed1
would not affect the distribution of the predictions and hence the threshold update.
Thanks for your quick reply and clarification!
Hello, thank you for this great work! I was looking at your dynamic threshold function and when you call it in line 200-201 of corrmatch.py, it is
thresh_controller.thresh_update(pred_u_w.detach(), ignore_mask_cutmixed1, update_g=True)
thresh_global = thresh_controller.get_thresh_global()
I was wondering why you are using
ignore_mask_cutmixed1
instead ofignore_mask
since wouldn't this entail using the cutmixed ignore mask for the non-cutmixed unlabeled weakly augmented image?