Channel mismatch error when converting the code to do multi-class segmentation.

[srivastavashobhit]

I have made changes to your code to do multiclass segmentation. I have taken care that labels are read right. I have already done this job successfully for your last masterpiece, U2NET. In ISNET, I am getting this error when giving a four-channel multiclass label.

RuntimeError: Given groups=1, weight of size [16, 1, 3, 3], expected input[1, 4, 256, 256] to have 1 channels, but got 4 channels instead

I faced the same error in U2Net, but then this code fix at line 354 and line 459 in https://github.com/xuebinqin/U-2-Net/blob/master/model/u2net.py solved it -

   -  self.outconv = nn.Conv2d(6,out_ch,1)
   + self.outconv = nn.Conv2d(6*out_ch,out_ch,1)

Please check if ISNet needs a similar fix.

Thankful for your incredible work.

End notes
I have set out_channel to 4
I am taking care of gt_preprocess and ensuring it returns a four-channel label.

[srivastavashobhit]

The issue is resolved. Error is due to not passing the correct number of out_ch in net = ISNetGTEncoder(in_ch=4, out_ch=4).

[kabbas570]

@srivastavashobhit can you please explain how you managed to make a 4-channel label? Thanks

[srivastavashobhit]

@kabbas570
In my case, I was first incorrectly not passing out_ch=4 when creating an object of ISNetGTEncoder at line 38 of train_valid_inference_main.py

The default value of out_ch is 1. You can check this in the constructor of ISNetGTEncoder

Later, I also had to make changes to the data_loader_cache.py in im_preprocess and/or gt_preprocess to deal with 4 channels. I do not remember the changes now and do not have the files to refer.

[kabbas570]

@srivastavashobhit, thanks for the reply. Yes, I changed the gt_prrprocess file and the corresponding number of classes in ISNetGTEncoder,and fortunately, it working now,
Cheers
Abbas