By: qqqwwwee on July 6, 2023, 9:37 a.m.
Dear organizers,
Thanks for hosting this challenge.
I encountered the problem "The algorithm failed on one or more cases." when my submit was going processing.
The test has passed offline. And I cannot get any error information of this problem.
Could you help me to solve the problem?
Best regards, Eugene
By: giansteve on July 6, 2023, 11:06 a.m.
Dear qqqwwwee,
We found two submissions from you. The first one was created on July 6, 2023, at 11:02 a.m. and gave as error "Time limit exceeded". The second one was created on July 6, 2023, at 12:06 p.m. and gave as error "AssertionError".
We hope this helps Best SEG.A. Team
By: qqqwwwee on July 6, 2023, 12:26 p.m.
Dear organizers,
Thanks for your reply.
May I ask for the detail of the time limit for Seg.A.?
If no time limit, how can I pass the test within the time limit on the grand-challenge platform?
Best regards, Eugene
By: giansteve on July 6, 2023, 12:56 p.m.
Due to the many failed submissions, we are working on this topic to solve the issue and probably increase the time limit. New updates will follow as soon as possible.
Thank you for being so patient
SEG.A. Team
By: giansteve on July 10, 2023, 8:01 a.m.
Dear Eugene,
The failed submission submitted 4 hours ago gave as error the following message: "RuntimeError: data type not supported".
I paste here the Stdout and the Stderr, hoping they will be helpful:
2023-07-10T03:25:59.376000+00:00
2023-07-10T03:25:59.376000+00:00
2023-07-10T03:25:59.376000+00:00 Please cite the following paper when using nnUNet:
2023-07-10T03:25:59.376000+00:00
2023-07-10T03:25:59.376000+00:00 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
2023-07-10T03:25:59.376000+00:00
2023-07-10T03:25:59.376000+00:00
2023-07-10T03:25:59.376000+00:00 If you have questions or suggestions, feel free to open an issue at https://github.com/MIC-DKFZ/nnUNet
2023-07-10T03:25:59.376000+00:00
2023-07-10T03:25:59.376000+00:00 nnUNet_preprocessed is not defined and nnU-Net can not be used for preprocessing or training. If this is not intended, please read documentation/setting_up_paths.md for information on how to set this up.
2023-07-10T03:25:59.376000+00:00 emptying cuda cache
2023-07-10T03:25:59.376000+00:00 loading parameters for folds, 0
2023-07-10T03:25:59.377000+00:00 using the following model files: ['/opt/app/checkpoints/nnUNet/3d_fullres/Task700_SEG_A_2023/BigResUNetTrainerV4_base_lr0001_00001_ft__nnUNetPlansv2.1/fold_0/model_final_checkpoint.model']
2023-07-10T03:25:59.377000+00:00 starting prediction...
2023-07-10T03:25:59.377000+00:00 preprocessing [PosixPath('/input/images/ct/bc5eae0e-1bc8-468a-98a2-00547e42ed2c.mha')]
2023-07-10T03:25:59.377000+00:00 using preprocessor GenericPreprocessor
2023-07-10T03:25:59.377000+00:00 before crop: (1, 399, 512, 512) after crop: (1, 399, 512, 512) spacing: [1.5 0.828125 0.828125]
2023-07-10T03:25:59.377000+00:00
2023-07-10T03:25:59.377000+00:00 separate z, order in z is 0 order inplane is 3
2023-07-10T03:25:59.377000+00:00 separate z, order in z is 0 order inplane is 1
2023-07-10T03:25:59.377000+00:00 before: {'spacing': array([1.5 , 0.828125, 0.828125]), 'spacing_transposed': array([1.5 , 0.828125, 0.828125]), 'data.shape (data is transposed)': (1, 399, 512, 512)}
2023-07-10T03:25:59.377000+00:00 after: {'spacing': array([2.98504508, 0.73242188, 0.73242188]), 'data.shape (data is resampled)': (1, 200, 579, 579)}
2023-07-10T03:25:59.377000+00:00
2023-07-10T03:25:59.377000+00:00 (1, 200, 579, 579)
2023-07-10T03:25:59.377000+00:00 Preprocess_patient time: 42.972883224487305
2023-07-10T03:25:59.377000+00:00 predicting /output/images/aorta-segmentation/BigResUNetTrainerV4_base_lr0001_00001_ft__nnUNetPlansv2.1/bc5eae0e-1bc8-468a-98a2-00547e42ed2c.mha
2023-07-10T03:25:59.377000+00:00 patch_size: [ 64 160 160]
2023-07-10T03:25:59.377000+00:00 debug: mirroring True mirror_axes (0, 1, 2)
2023-07-10T03:25:59.377000+00:00 step_size: 0.5
2023-07-10T03:25:59.377000+00:00 do mirror: True
2023-07-10T03:25:59.377000+00:00 data shape: (1, 200, 579, 579)
2023-07-10T03:25:59.377000+00:00 patch size: [ 64 160 160]
2023-07-10T03:25:59.377000+00:00 steps (x, y, and z): [[0, 27, 54, 82, 109, 136], [0, 70, 140, 210, 279, 349, 419], [0, 70, 140, 210, 279, 349, 419]]
2023-07-10T03:25:59.377000+00:00 number of tiles: 294
2023-07-10T03:25:59.377000+00:00 computing Gaussian
2023-07-10T03:25:59.377000+00:00 done
2023-07-10T03:25:59.377000+00:00 initializing result array (on GPU)
2023-07-10T03:25:59.377000+00:00 moving data to GPU
2023-07-10T03:25:59.377000+00:00 initializing result_numsamples (on GPU)
2023-07-10T03:25:59.377000+00:00 copying results to CPU
2023-07-10T03:25:59.377000+00:00 prediction done
2023-07-10T03:25:59.377000+00:00 force_separate_z: None interpolation order: 1
2023-07-10T03:25:59.377000+00:00 separate z: True lowres axis [0]
2023-07-10T03:25:59.377000+00:00 separate z, order in z is 0 order inplane is 1
2023-07-10T03:25:59.376000+00:00 Traceback (most recent call last):
2023-07-10T03:25:59.376000+00:00 File "/opt/conda/lib/python3.8/runpy.py", line 194, in _run_module_as_main
2023-07-10T03:25:59.376000+00:00 return _run_code(code, main_globals, None,
2023-07-10T03:25:59.376000+00:00 File "/opt/conda/lib/python3.8/runpy.py", line 87, in _run_code
2023-07-10T03:25:59.376000+00:00 exec(code, run_globals)
2023-07-10T03:25:59.376000+00:00 File "/opt/app/process.py", line 167, in <module>
2023-07-10T03:25:59.376000+00:00 Segaalgorithm().process()
2023-07-10T03:25:59.376000+00:00 File "/home/user/.local/lib/python3.8/site-packages/evalutils/evalutils.py", line 183, in process
2023-07-10T03:25:59.376000+00:00 self.process_cases()
2023-07-10T03:25:59.376000+00:00 File "/opt/app/process.py", line 121, in process_cases
2023-07-10T03:25:59.376000+00:00 predict_cases(model_folder_name, list_of_lists, output_dir, folds,
2023-07-10T03:25:59.376000+00:00 File "/opt/app/predict.py", line 263, in predict_cases
2023-07-10T03:25:59.376000+00:00 results.append(save_segmentation_nifti_from_softmax(softmax, output_filename, dct, interpolation_order,
2023-07-10T03:25:59.376000+00:00 File "/home/user/.local/lib/python3.8/site-packages/nnunet/inference/segmentation_export.py", line 107, in save_segmentation_nifti_from_softmax
2023-07-10T03:25:59.376000+00:00 seg_old_spacing = resample_data_or_seg(segmentation_softmax, shape_original_after_cropping, is_seg=False,
2023-07-10T03:25:59.376000+00:00 File "/home/user/.local/lib/python3.8/site-packages/nnunet/preprocessing/preprocessing.py", line 173, in resample_data_or_seg
2023-07-10T03:25:59.376000+00:00 reshaped_final_data.append(map_coordinates(reshaped_data, coord_map, order=order_z,
2023-07-10T03:25:59.376000+00:00 File "/home/user/.local/lib/python3.8/site-packages/scipy/ndimage/_interpolation.py", line 459, in map_coordinates
2023-07-10T03:25:59.376000+00:00 _nd_image.geometric_transform(filtered, None, coordinates, None, None,
2023-07-10T03:25:59.376000+00:00 RuntimeError: data type not supported
Best SEG.A. Team