kirk0221

Thank you for your kind answer. Also, if you import and use a mask from GlaS Dataset, it comes out as a [128,128] tensor, so I can't calculate Dice loss...

This is my tensor shape for training. inputs_train_shape1 = torch.Size([2, 1, 128, 128]) inputs_train_shape2 = torch.Size([2, 1, 128, 128]) outputs_train_shape1 = torch.Size([2, 2, 128, 128]) outputs_train_shape2 = torch.Size([2, 2, 128,...

I check it, then i have same error input_train_shape1 = torch.Size([2, 1, 128, 128]) input_train_shape2 = torch.Size([2, 1, 128, 128]) mask_train = torch.Size([2, 128, 128]) outputs_train_shape1 = torch.Size([2, 2, 128,...

I have one more question from the author. I wonder why the output channel comes out as 2 according to NUM_CLASSES in For the GlaS data set, the input is...

So how do you do additional preprocessing on the GlaS mask? The background of my GlaS mask is 0, and the number of each class is going up in order...

Then, isn't it the shape of the tensor of [2,128,128] corresponding to NUM_CLASSES?? If you need to make it in that shape, please tell me how to pre-process it. thank...

Author, the problem I asked earlier has been solved. I have a new question. In wavelet2D, is it possible for us to change the threshold other than specifying --wavelet_type?