Channel issue with ACDC dataset

[amitojdeep]

I downloaded the provided ACDC dataset and when I tried to run the code, I got the following error (channels issue)

Traceback (most recent call last):
File "main.py", line 87, in
main()
File "main.py", line 73, in main
model.train(args)
File "/project/6037231/amitoj/cycleGAN/model.py", line 362, in train
fake_gt = self.Gsi(unl_img.float()) ### having 21 channels
File "/home/amitoj/.local/lib/python3.7/site-packages/torch/nn/modules/module.py", line 547, in call
result = self.forward(*input, **kwargs)
File "/project/6037231/amitoj/cycleGAN/arch/generators.py", line 431, in forward
x = self.conv1(x)
File "/home/amitoj/.local/lib/python3.7/site-packages/torch/nn/modules/module.py", line 547, in call
result = self.forward(*input, **kwargs)
File "/home/amitoj/.local/lib/python3.7/site-packages/torch/nn/modules/conv.py", line 343, in forward
return self.conv2d_forward(input, self.weight)
File "/home/amitoj/.local/lib/python3.7/site-packages/torch/nn/modules/conv.py", line 340, in conv2d_forward
self.padding, self.dilation, self.groups)
RuntimeError: Given groups=1, weight of size 64 3 7 7, expected input[5, 1, 256, 256] to have 3 channels, but got 1 channels instead

Any fix for this or do I need to manually edit all the code?

[kevinkwshin]

ACDC dataset has only 1 input_channel.

Thus, in "dataloader.py",
I add this line after line 383 to append image in 3 channels.

img = Image.open(img_path)
img = img.convert('RGB') # <-- added

[amitojdeep]

ACDC dataset has only 1 input_channel.

Thus, in "dataloader.py",
I add this line after line 383 to append image in 3 channels.

img = Image.open(img_path)
img = img.convert('RGB') # <-- added

I also tried this as a quick and dirty fix. But using thrice the amount of memory isn’t the best thing. Any better option?

[sajjadafridi]

ACDC dataset has only 1 input_channel.

Thus, in "dataloader.py",
I add this line after line 383 to append image in 3 channels.

img = Image.open(img_path)
img = img.convert('RGB') # <-- added

This fix the issue but it show another error when creating one_hot_encodding