content: import shutil
  from copy import deepcopy
  
  from batchgenerators.utilities.file_and_folder_operations import join, maybe_mkdir_p, isdir, load_json, save_json
  from nnunetv2.paths import nnUNet_raw
  
  
  def convert(source_folder, target_dataset_name):
      """
      remember that old tasks were called TaskXXX_YYY and new ones are called DatasetXXX_YYY
      source_folder
      """
      if isdir(join(nnUNet_raw, target_dataset_name)):
          raise RuntimeError(f'Target dataset name {target_dataset_name} already exists. Aborting... '
                             f'(we might break something). If you are sure you want to proceed, please manually '
                             f'delete {join(nnUNet_raw, target_dataset_name)}')
      maybe_mkdir_p(join(nnUNet_raw, target_dataset_name))
      shutil.copytree(join(source_folder, 'imagesTr'), join(nnUNet_raw, target_dataset_name, 'imagesTr'))
      shutil.copytree(join(source_folder, 'labelsTr'), join(nnUNet_raw, target_dataset_name, 'labelsTr'))
      if isdir(join(source_folder, 'imagesTs')):
          shutil.copytree(join(source_folder, 'imagesTs'), join(nnUNet_raw, target_dataset_name, 'imagesTs'))
      if isdir(join(source_folder, 'labelsTs')):
          shutil.copytree(join(source_folder, 'labelsTs'), join(nnUNet_raw, target_dataset_name, 'labelsTs'))
      if isdir(join(source_folder, 'imagesVal')):
          shutil.copytree(join(source_folder, 'imagesVal'), join(nnUNet_raw, target_dataset_name, 'imagesVal'))
      if isdir(join(source_folder, 'labelsVal')):
          shutil.copytree(join(source_folder, 'labelsVal'), join(nnUNet_raw, target_dataset_name, 'labelsVal'))
      shutil.copy(join(source_folder, 'dataset.json'), join(nnUNet_raw, target_dataset_name))
  
      dataset_json = load_json(join(nnUNet_raw, target_dataset_name, 'dataset.json'))
      del dataset_json['tensorImageSize']
      del dataset_json['numTest']
      del dataset_json['training']
      del dataset_json['test']
      dataset_json['channel_names'] = deepcopy(dataset_json['modality'])
      del dataset_json['modality']
  
      dataset_json['labels'] = {j: int(i) for i, j in dataset_json['labels'].items()}
      dataset_json['file_ending'] = ".nii.gz"
      save_json(dataset_json, join(nnUNet_raw, target_dataset_name, 'dataset.json'), sort_keys=False)
  
  
  def convert_entry_point():
      import argparse
      parser = argparse.ArgumentParser()
      parser.add_argument("input_folder", type=str,
                          help='Raw old nnUNet dataset. This must be the folder with imagesTr,labelsTr etc subfolders! '
                               'Please provide the PATH to the old Task, not just the task name. nnU-Net V2 does not '
                               'know where v1 tasks are.')
      parser.add_argument("output_dataset_name", type=str,
                          help='New dataset NAME (not path!). Must follow the DatasetXXX_NAME convention!')
      args = parser.parse_args()
      convert(args.input_folder, args.output_dataset_name)
  