The algorithm failed on one or more cases

Hi, could you please send me the logs of my Docker submission. Thank you very much.

Hi,

your algorithm gave the following output:

2023-07-24T20:04:48.175000+00:00 nnUNet_raw is not defined and nnU-Net can only be used on data for which preprocessed files are already present on your system. nnU-Net cannot be used for experiment planning and preprocessing like this. If this is not intended, please read documentation/setting_up_paths.md for information on how to set this up properly. 2023-07-24T20:04:48.175000+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. 2023-07-24T20:04:48.175000+00:00 nnUNet_results is not defined and nnU-Net cannot be used for training or inference. If this is not intended behavior, please read documentation/setting_up_paths.md for information on how to set this up. 2023-07-24T20:04:48.175000+00:00 use_folds is None, attempting to auto detect available folds 2023-07-24T20:04:48.175000+00:00 found the following folds: [0] 2023-07-24T20:04:48.175000+00:00 There are 1 cases in the source folder 2023-07-24T20:04:48.175000+00:00 I am process 0 out of 1 (max process ID is 0, we start counting with 0!) 2023-07-24T20:04:48.175000+00:00 There are 1 cases that I would like to predict 2023-07-24T20:05:35.190000+00:00 nnUNet_raw is not defined and nnU-Net can only be used on data for which preprocessed files are already present on your system. nnU-Net cannot be used for experiment planning and preprocessing like this. If this is not intended, please read documentation/setting_up_paths.md for information on how to set this up properly. 2023-07-24T20:05:35.190000+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. 2023-07-24T20:05:35.190000+00:00 nnUNet_results is not defined and nnU-Net cannot be used for training or inference. If this is not intended behavior, please read documentation/setting_up_paths.md for information on how to set this up. 2023-07-24T20:05:35.190000+00:00 nnUNet_raw is not defined and nnU-Net can only be used on data for which preprocessed files are already present on your system. nnU-Net cannot be used for experiment planning and preprocessing like this. If this is not intended, please read documentation/setting_up_paths.md for information on how to set this up properly. 2023-07-24T20:05:35.190000+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. 2023-07-24T20:05:35.190000+00:00 nnUNet_results is not defined and nnU-Net cannot be used for training or inference. If this is not intended behavior, please read documentation/setting_up_paths.md for information on how to set this up.

and the following error:

2023-07-24T20:05:35.190000+00:00 Traceback (most recent call last): 2023-07-24T20:05:35.190000+00:00 File "/usr/local/lib/python3.9/runpy.py", line 197, in _run_module_as_main 2023-07-24T20:05:35.190000+00:00 return _run_code(code, main_globals, None, 2023-07-24T20:05:35.190000+00:00 File "/usr/local/lib/python3.9/runpy.py", line 87, in _run_code 2023-07-24T20:05:35.190000+00:00 exec(code, run_globals) 2023-07-24T20:05:35.190000+00:00 File "/opt/app/process.py", line 125, in 2023-07-24T20:05:35.190000+00:00 Segaalgorithm().process() 2023-07-24T20:05:35.190000+00:00 File "/home/user/.local/lib/python3.9/site-packages/evalutils/evalutils.py", line 183, in process 2023-07-24T20:05:35.190000+00:00 self.process_cases() 2023-07-24T20:05:35.190000+00:00 File "/opt/app/process.py", line 105, in process_cases 2023-07-24T20:05:35.190000+00:00 self.predictor.predict_from_files(str(self.temp_path), 2023-07-24T20:05:35.190000+00:00 File "/home/user/.local/lib/python3.9/site-packages/nnunetv2/inference/predict_from_raw_data.py", line 258, in predict_from_files 2023-07-24T20:05:35.190000+00:00 return self.predict_from_data_iterator(data_iterator, save_probabilities, num_processes_segmentation_export) 2023-07-24T20:05:35.190000+00:00 File "/home/user/.local/lib/python3.9/site-packages/nnunetv2/inference/predict_from_raw_data.py", line 351, in predict_from_data_iterator 2023-07-24T20:05:35.190000+00:00 for preprocessed in data_iterator: 2023-07-24T20:05:35.190000+00:00 File "/home/user/.local/lib/python3.9/site-packages/nnunetv2/inference/data_iterators.py", line 109, in preprocessing_iterator_fromfiles 2023-07-24T20:05:35.190000+00:00 raise RuntimeError('Background workers died. Look for the error message further up! If there is ' 2023-07-24T20:05:35.190000+00:00 RuntimeError: Background workers died. Look for the error message further up! If there is none then your RAM was full and the worker was killed by the OS. Use fewer workers or get more RAM in that case!

Hi, thanks. Aktually that looks lika a ram issue for me. What is the test image size?

Best Constantin