Monailabel issue - Internal Server Error

Support
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1

Facing a few issues while using monailabel training.
1)
[Python] Failed to run inference in MONAI Label Server.
[Python] Message: Status: 500; Response: Internal Server Error

Traceback (most recent call last):
File “C:/Users/admin/AppData/Local/slicer.org/Slicer 5.6.2/slicer.org/Extensions-32448/MONAILabel/lib/Slicer-5.6/qt-scripted-modules/MONAILabel.py”, line 1545, in onClickSegmentation
result_file, params = self.logic.infer(model, image_file, params, session_id=self.getSessionId())
File “C:/Users/admin/AppData/Local/slicer.org/Slicer 5.6.2/slicer.org/Extensions-32448/MONAILabel/lib/Slicer-5.6/qt-scripted-modules/MONAILabel.py”, line 2321, in infer
result_file, params = client.infer(model, image_in, params, label_in, file, session_id)
File “C:\Users\admin\AppData\Local\slicer.org\Slicer 5.6.2\slicer.org\Extensions-32448\MONAILabel\lib\Slicer-5.6\qt-scripted-modules\MONAILabelLib\client.py”, line 344, in infer
raise MONAILabelClientException(
MONAILabelLib.client.MONAILabelClientException: (1, ‘Status: 500; Response: Internal Server Error’)

  1. training bar and accuracy bar shows training error and accuracy 0.
    image
    image1503×831 250 KB

3)happens during training
RuntimeError: Error(s) in loading state_dict for SegResNet:
size mismatch for conv_final.2.conv.weight: copying a param with shape torch.Size([26, 32, 1, 1, 1]) from checkpoint, the shape in current model is torch.Size([3, 32, 1, 1, 1]).
size mismatch for conv_final.2.conv.bias: copying a param with shape torch.Size([26]) from checkpoint, the shape in current model is torch.Size([3]).

2

Hi @Daniel_Lo,

It looks like the issue might be related to a mismatch between the number of labels the model was trained on and those defined in the config file. Could you please share a bit more detail so we can help replicate the issue?

Also, for any questions specifically about MONAI Label, it might be helpful to comment directly on the MONAI Label repository: GitHub - Project-MONAI/MONAILabel: MONAI Label is an intelligent open source image labeling and learning tool.

Best,