Closed wjcheon closed 10 months ago
In this thread: https://github.com/MIC-DKFZ/nnUNet/issues/132
This error was solved by changing OS from windows to linux. I am also on Windows 11.
Can we solved this problem? @Karol-G
Hey,
I recommend to use nnU-Net v2 which also works on Windows. nnU-Net v1 only works on Linux and is not maintained anymore.
Best, Karol
Dear Karol-G
I solved the problem by changing the operating system (OS) from Windows to Ubuntu on WSL2.
Thus, the preprocessing procedure is working well. but, in the middle of the preprocessing procedure was stopped without error.
My environment condition (RAM and STORAGE) is enough.
Do you know the reason?
PS. when I removed the file and changed "dataset.json", the issue still occurred in another file.
Best regards
Wonjoong Cheon
Hey @wjcheon,
Sorry, but I won't be able to help you with any problems that happen within WSL2. WSL2 is only a virtual machine and not a bare metal Linux OS. We support only the latter.
Best, Karol
I have research project on nnUNet v1.
doing:
However, the --verify dataset integrity exam was passed. the following procedure is not working with Are we using the nonzero mask for normalization? OrderedDict([(0, False)]) ValueError: need at least one array to concatenate
Plz help.
Best regards Wonjoong Cheon
If you have questions or suggestions, feel free to open an issue at https://github.com/MIC-DKFZ/nnUNet
Expected label values are [0, 1, 2] Labels OK Verifying test set Dataset OK
Please cite the following paper when using nnUNet:
Isensee, F., Jaeger, P.F., Kohl, S.A.A. et al. "nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation." Nat Methods (2020). https://doi.org/10.1038/s41592-020-01008-z
If you have questions or suggestions, feel free to open an issue at https://github.com/MIC-DKFZ/nnUNet
Please cite the following paper when using nnUNet:
Isensee, F., Jaeger, P.F., Kohl, S.A.A. et al. "nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation." Nat Methods (2020). https://doi.org/10.1038/s41592-020-01008-z
If you have questions or suggestions, feel free to open an issue at https://github.com/MIC-DKFZ/nnUNet
Please cite the following paper when using nnUNet:
Isensee, F., Jaeger, P.F., Kohl, S.A.A. et al. "nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation." Nat Methods (2020). https://doi.org/10.1038/s41592-020-01008-z
If you have questions or suggestions, feel free to open an issue at https://github.com/MIC-DKFZ/nnUNet
H:\workspace\nnUNet_raw_data_base\nnUNet_raw_data\Task003_KiTs2023_nnUNetv1\imagesTr\train_1 H:\workspace\nnUNet_raw_data_base\nnUNet_raw_data\Task003_KiTs2023_nnUNetv1\imagesTr\train_2 H:\workspace\nnUNet_raw_data_base\nnUNet_raw_data\Task003_KiTs2023_nnUNetv1\imagesTr\train_3
Task003_KiTs2023_nnUNetv1 number of threads: (8, 8)
Are we using the nonzero mask for normalization? OrderedDict([(0, False)]) Traceback (most recent call last): File "\?\D:\anaconda_env\nnunetv1\Scripts\nnUNet_plan_and_preprocess-script.py", line 33, in
sys.exit(load_entry_point('nnunet', 'console_scripts', 'nnUNet_plan_and_preprocess')())
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "c:\users\user\dropbox\research\개인연구\903_nnunet_gui\code\nnunet-v1-wjcheon\nnunet\nnunet\experiment_planning\nnUNet_plan_and_preprocess.py", line 159, in main
exp_planner.plan_experiment()
File "c:\users\user\dropbox\research\개인연구\903_nnunet_gui\code\nnunet-v1-wjcheon\nnunet\nnunet\experiment_planning\experiment_planner_baseline_3DUNet.py", line 257, in plan_experiment
target_spacing = self.get_target_spacing()
^^^^^^^^^^^^^^^^^^^^^^^^^
File "c:\users\user\dropbox\research\개인연구\903_nnunet_gui\code\nnunet-v1-wjcheon\nnunet\nnunet\experiment_planning\experiment_planner_baseline_3DUNet_v21.py", line 51, in get_target_spacing
target = np.percentile(np.vstack(spacings), self.target_spacing_percentile, 0)
^^^^^^^^^^^^^^^^^^^
File "D:\anaconda_env\nnunetv1\Lib\site-packages\numpy\core\shape_base.py", line 289, in vstack
return _nx.concatenate(arrs, 0, dtype=dtype, casting=casting)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
ValueError: need at least one array to concatenate