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I am using U-mamba to segment brain regions, I am doing this in linux. I have also prepared the dataset in nnUNet format and set the correct directories for nnUNet_raw, nnUNet_preprocessed and nnUNet_results.
Here is the structure:
Inside nnUNet_raw, I have a folder named Dataset701_AbdomenCT .
Within Dataset701_AbdomenCT , there are imagesTr, imagesTs, labelsTr, and dataset.json.
I followed the nnUNet formatting guidelines when preparing the data and the dataset.json file.
{
"channel_names": {
"0": "CT"
},
"labels": {
"background": 0,
"liver": 1,
"right kidney": 2,
"spleen": 3,
"pancreas": 4,
"aorta": 5,
"inferior vena cava": 6,
"right adrenal gland": 7,
"left adrenal gland": 8,
"gallbladder": 9,
"esophagus": 10,
"stomach": 11,
"duodenum": 12,
"left kidney": 13
},
"numTraining": 50,
"file_ending": ".nii.gz",
"name": "Dataset701_AbdomenCT",
"description": "This dataset was from MICCAI FLARE 2022 Challenge. The training set contained 50 CT scans that were from the MSD Pancreas dataset and the annotations were from AbdomenCT-1K. Another 50 validation cases were from TCIA and the annotations were provided by the challenge organizers."
}
I got the error when running the following command.
Fingerprint extraction...
Traceback (most recent call last):
File "/home/zrh/ENTER/envs/mamba-env/bin/nnUNetv2_plan_and_preprocess", line 8, in
sys.exit(plan_and_preprocess_entry())
File "/home/zrh/ENTER/envs/mamba-env/lib/python3.10/site-packages/nnunetv2/experiment_planning/plan_and_preprocess_entrypoints.py", line 182, in plan_and_preprocess_entry
extract_fingerprints(args.d, args.fpe, args.npfp, args.verify_dataset_integrity, args.clean, args.verbose)
File "/home/zrh/ENTER/envs/mamba-env/lib/python3.10/site-packages/nnunetv2/experiment_planning/plan_and_preprocess_api.py", line 47, in extract_fingerprints
extract_fingerprint_dataset(d, fingerprint_extractor_class, num_processes, check_dataset_integrity, clean,
File "/home/zrh/ENTER/envs/mamba-env/lib/python3.10/site-packages/nnunetv2/experiment_planning/plan_and_preprocess_api.py", line 26, in extract_fingerprint_dataset
dataset_name = convert_id_to_dataset_name(dataset_id)
File "/home/zrh/ENTER/envs/mamba-env/lib/python3.10/site-packages/nnunetv2/utilities/dataset_name_id_conversion.py", line 48, in convert_id_to_dataset_name
raise RuntimeError(f"Could not find a dataset with the ID {dataset_id}. Make sure the requested dataset ID "
RuntimeError: Could not find a dataset with the ID 701. Make sure the requested dataset ID exists and that nnU-Net knows where raw and preprocessed data are located (see Documentation - Installation). Here are your currently defined folders:
nnUNet_preprocessed=/home/zrh/PycharmProjects/pythonProject/U-Mamba/data/nnUNet_preprocessed
nnUNet_results=/home/zrh/PycharmProjects/pythonProject/U-Mamba/data/nnUNet_trained_models
nnUNet_raw=/home/zrh/PycharmProjects/pythonProject/U-Mamba/data/nnUNet_raw
If something is not right, adapt your environment variables.
Thank you very much
The text was updated successfully, but these errors were encountered:
I am using U-mamba to segment brain regions, I am doing this in linux. I have also prepared the dataset in nnUNet format and set the correct directories for nnUNet_raw, nnUNet_preprocessed and nnUNet_results.
Here is the structure:
Inside nnUNet_raw, I have a folder named Dataset701_AbdomenCT .
Within Dataset701_AbdomenCT , there are imagesTr, imagesTs, labelsTr, and dataset.json.
I followed the nnUNet formatting guidelines when preparing the data and the dataset.json file.
{
"channel_names": {
"0": "CT"
},
"labels": {
"background": 0,
"liver": 1,
"right kidney": 2,
"spleen": 3,
"pancreas": 4,
"aorta": 5,
"inferior vena cava": 6,
"right adrenal gland": 7,
"left adrenal gland": 8,
"gallbladder": 9,
"esophagus": 10,
"stomach": 11,
"duodenum": 12,
"left kidney": 13
},
"numTraining": 50,
"file_ending": ".nii.gz",
"name": "Dataset701_AbdomenCT",
"description": "This dataset was from MICCAI FLARE 2022 Challenge. The training set contained 50 CT scans that were from the MSD Pancreas dataset and the annotations were from AbdomenCT-1K. Another 50 validation cases were from TCIA and the annotations were provided by the challenge organizers."
}
I got the error when running the following command.
Fingerprint extraction...
Traceback (most recent call last):
File "/home/zrh/ENTER/envs/mamba-env/bin/nnUNetv2_plan_and_preprocess", line 8, in
sys.exit(plan_and_preprocess_entry())
File "/home/zrh/ENTER/envs/mamba-env/lib/python3.10/site-packages/nnunetv2/experiment_planning/plan_and_preprocess_entrypoints.py", line 182, in plan_and_preprocess_entry
extract_fingerprints(args.d, args.fpe, args.npfp, args.verify_dataset_integrity, args.clean, args.verbose)
File "/home/zrh/ENTER/envs/mamba-env/lib/python3.10/site-packages/nnunetv2/experiment_planning/plan_and_preprocess_api.py", line 47, in extract_fingerprints
extract_fingerprint_dataset(d, fingerprint_extractor_class, num_processes, check_dataset_integrity, clean,
File "/home/zrh/ENTER/envs/mamba-env/lib/python3.10/site-packages/nnunetv2/experiment_planning/plan_and_preprocess_api.py", line 26, in extract_fingerprint_dataset
dataset_name = convert_id_to_dataset_name(dataset_id)
File "/home/zrh/ENTER/envs/mamba-env/lib/python3.10/site-packages/nnunetv2/utilities/dataset_name_id_conversion.py", line 48, in convert_id_to_dataset_name
raise RuntimeError(f"Could not find a dataset with the ID {dataset_id}. Make sure the requested dataset ID "
RuntimeError: Could not find a dataset with the ID 701. Make sure the requested dataset ID exists and that nnU-Net knows where raw and preprocessed data are located (see Documentation - Installation). Here are your currently defined folders:
nnUNet_preprocessed=/home/zrh/PycharmProjects/pythonProject/U-Mamba/data/nnUNet_preprocessed
nnUNet_results=/home/zrh/PycharmProjects/pythonProject/U-Mamba/data/nnUNet_trained_models
nnUNet_raw=/home/zrh/PycharmProjects/pythonProject/U-Mamba/data/nnUNet_raw
If something is not right, adapt your environment variables.
Thank you very much
The text was updated successfully, but these errors were encountered: