code: def __init__(self, task_id):
      task_name = list(tasks[task_id].keys())[0].split(".")[0]
      print(f"Preparing task {task_id} {task_name}")
      super().__init__(
          dataset_root=f"data/{task_name}",
          raw_dataset_dir=f"{task_name}_raw/",
          images_dir=f"{task_name}/{task_name}/imagesTr",
          labels_dir=f"{task_name}/{task_name}/labelsTr",
          phase_dir=f"{task_name}_phase0/",
          urls=tasks[task_id],
          valid_suffix=("nii.gz", "nii.gz"),
          filter_key=(None, None),
          uncompress_params={"format": "tar", "num_files": 1},
      )
      self.preprocess = {"images": [], "labels": []}
  
file_path: PaddleSeg/contrib/MedicalSeg/tools/prepare_msd_brain_seg.py
imports: import os
  import os.path
  import sys
  import time
  import numpy
  import nibabel
  import SimpleITK
  from tqdm import tqdm
  from prepare import Prep
  from tools.preprocess_utils import join_paths
label_desc: Use image node_id 1 to create a new PrepMSDBrain object from inherited base classes: Prep with example: obj = PrepMSDBrain(task_id)