About train GlaS Dataset

[kirk0221]

I had a problem learning XNet, your great research. The GlaS dataset, a 2D image, was preprocessed using wavelet2D.py to obtain LF and HF images of [1,128,128] testers, respectively. After passing through the XNet model, are the shapes of outputs_train1 and outputs_train2 [2,128,128] respectively?

And when we learn GlaS dataset on branch1 and branch2 on the XNet model, will 3 and 1 channels be right?

# branch 1
self.b1_1_1 = nn.Sequential(
conv3x3(in_channels, l1c), #in_channels = 3
conv3x3(l1c, l1c),
BasicBlock(l1c, l1c)

# branch 2
self.b2_1_1 = nn.Sequential(
conv3x3(1, l1c),
conv3x3(l1c, l1c),
BasicBlock(l1c, l1c)

Thank you for your answers!!