`nnUNetv2_plan_and_preprocess`: hasattr(): attribute name must be string for overwrite_image_reader_writer

Hi, I'm trying to run the following command:

nnUNetv2_plan_and_preprocess -d 777 --verify_dataset_integrity --verbose --clean

This is my dataset.json:

{
    "channel_names": {
        "0000": "ciss",
        "0001": "t2_n4"
    },
    "file_ending": ".nii.gz",
    "tensor_image_size": "3D",
    "numTraining": 32,
    "dataset_name": "Dataset777_MyDataset",
    "license": "Not licensed",
    "description": "Segmentation dataset",
    "reference": "Add reference if applicable",
    "modality": {
        "0000": "ciss",
        "0001": "t2_n4"
    },
    "overwrite_image_reader_writer": null,
    "labels": {
        "background": 0,
        "Cortex Gray Matter": 1,
        "Normal-Appearing White Matter": 2,
        "White Matter Hyperintensities": 3,
        "Subcortical/limbic gray matter": 4,
        "Other/Artifact": 5
    }
}

I've previously run this code:

dataset_name = 'Dataset777_MyDataset'

# Create necessary directories
imagesTr_dir = os.path.join(nnUNet_raw, dataset_name, 'imagesTr')
labelsTr_dir = os.path.join(nnUNet_raw, dataset_name, 'labelsTr')
os.makedirs(imagesTr_dir, exist_ok=True)
os.makedirs(labelsTr_dir, exist_ok=True)

# Map modalities to four-digit indices
modality_mapping = {
    'ciss': '0000',
    't2_n4': '0001'
}

# Initialize case ID counter and mapping
case_counter = 1
case_id_mapping = {}

# Define source directory
source_dir = 'Training Patches 10062024'

# List all files in the source directory
files = [f for f in os.listdir(source_dir) if f.endswith('.nii.gz')]

for file in files:
    # Extract information using regex
    match = re.match(r'subj(\d+)_team(\d+)_patch(\d+)_(\w+).nii.gz', file)
    if match:
        subject, team, patch, modality = match.groups()
        case_key = f'subj{subject}_team{team}_patch{patch}'

        # Assign a unique case ID
        if case_key not in case_id_mapping:
            case_id = f'{case_counter:03d}'
            case_id_mapping[case_key] = case_id
            case_counter += 1
        else:
            case_id = case_id_mapping[case_key]

        # Determine destination filename
        if modality in modality_mapping:
            modality_index = modality_mapping[modality]
            dest_filename = f'case_{case_id}_{modality_index}.nii.gz'
            dest_path = os.path.join(imagesTr_dir, dest_filename)
        elif modality == 'final':
            dest_filename = f'case_{case_id}.nii.gz'
            dest_path = os.path.join(labelsTr_dir, dest_filename)
        else:
            continue  # Skip unrecognized modalities

        # Copy and rename the file
        shutil.copyfile(os.path.join(source_dir, file), dest_path)
    else:
        print(f"File did not match pattern: {file}")

# Prepare the dataset.json
channel_names = {
    "0000": "ciss",
    "0001": "t2_n4"
}

dataset_info = {
    "channel_names": channel_names,
    "file_ending": ".nii.gz",
    "tensor_image_size": "3D",
    "numTraining": len(case_id_mapping),
    "dataset_name": "Dataset777_MyDataset",
    "license": "Not licensed",
    "description": "Segmentation dataset",
    "reference": "Add reference if applicable",
    "modality": channel_names,
    "overwrite_image_reader_writer": None,
    "labels": {
        "background": 0,
        "Cortex Gray Matter": 1,
        "Normal-Appearing White Matter": 2,
        "White Matter Hyperintensities": 3,
        "Subcortical/limbic gray matter": 4,
        "Other/Artifact": 5,
    }

}

# Save dataset.json
with open(os.path.join(nnUNet_raw, dataset_name, 'dataset.json'), 'w') as f:
    json.dump(dataset_info, f, indent=4)

This is what I get as an error:

Fingerprint extraction...
Dataset777_MyDataset
Traceback (most recent call last):
  File "/Users/georgeaidinis/miniconda3/envs/BIA_1/bin/nnUNetv2_plan_and_preprocess", line 8, in <module>
    sys.exit(plan_and_preprocess_entry())
  File "/Users/georgeaidinis/miniconda3/envs/BIA_1/lib/python3.10/site-packages/nnunetv2/experiment_planning/plan_and_preprocess_entrypoints.py", line 180, in plan_and_preprocess_entry
    extract_fingerprints(args.d, args.fpe, args.npfp, args.verify_dataset_integrity, args.clean, args.verbose)
  File "/Users/georgeaidinis/miniconda3/envs/BIA_1/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 "/Users/georgeaidinis/miniconda3/envs/BIA_1/lib/python3.10/site-packages/nnunetv2/experiment_planning/plan_and_preprocess_api.py", line 30, in extract_fingerprint_dataset
    verify_dataset_integrity(join(nnUNet_raw, dataset_name), num_processes)
  File "/Users/georgeaidinis/miniconda3/envs/BIA_1/lib/python3.10/site-packages/nnunetv2/experiment_planning/verify_dataset_integrity.py", line 200, in verify_dataset_integrity
    reader_writer_class = determine_reader_writer_from_dataset_json(dataset_json, dataset[dataset.keys().__iter__().__next__()]['images'][0])
  File "/Users/georgeaidinis/miniconda3/envs/BIA_1/lib/python3.10/site-packages/nnunetv2/imageio/reader_writer_registry.py", line 31, in determine_reader_writer_from_dataset_json
    ret = recursive_find_reader_writer_by_name(ioclass_name)
  File "/Users/georgeaidinis/miniconda3/envs/BIA_1/lib/python3.10/site-packages/nnunetv2/imageio/reader_writer_registry.py", line 74, in recursive_find_reader_writer_by_name
    ret = recursive_find_python_class(join(nnunetv2.__path__[0], "imageio"), rw_class_name, 'nnunetv2.imageio')
  File "/Users/georgeaidinis/miniconda3/envs/BIA_1/lib/python3.10/site-packages/nnunetv2/utilities/find_class_by_name.py", line 13, in recursive_find_python_class
    if hasattr(m, class_name):
TypeError: hasattr(): attribute name must be string

I'm on a Mac(M1), running (conda):

python version : 3.10.14.final.0 nnunetv2 : 2.5.1

Any ideas as to why this might happen?

MIC-DKFZ / nnUNet

`nnUNetv2_plan_and_preprocess`: hasattr(): attribute name must be string for overwrite_image_reader_writer #2539