Jakob Wasserthal

Thanks for the feedback. For all the MR images we tried it worked well. Maybe there is some other problem. What is the command you used? Would it be possible...

You need to manually annotate the training data (available on zenodo) and then train a nnU-Net (see nnU-Net documentation).

You can try `--output_type dicom`.

I use the following library for dicom to nifti conversion: https://github.com/icometrix/dicom2nifti They would have to fix this problem and then it also works in TotalSegmentator.

I also have this issue. When you install pytorch (`pip install torch`) you can not use nnunet anymore. Because this will automatically install pytorch 2.6. It seems that the easiest...

I just tried it. If you change to ``` checkpoint = torch.load(join(model_training_output_dir, f'fold_{f}', checkpoint_name), map_location=torch.device('cpu'), weights_only=False) ``` in `nnunetv2/inference/predict_from_raw_data.py` then it works again.

I created a PR with this fix.

I still get the same error when trying to run on windows.

It happens for different nnunet models. I created a small reproducible example here: Test code: https://github.com/wasserth/TotalSegmentator/blob/update_mr_model/tests/tests_nnunet.py Github action to automatically run it on mac + ubuntu + windows: https://github.com/wasserth/TotalSegmentator/blob/update_mr_model/.github/workflows/run_tests_nnunet.yml Result...

I also do not have a Windows Machine available. I only see the windows results from the github action (and from user issues who report problems). I will create a...