class_docstr: The Lung cornavirus dataset is ...(todo: add link and description)
  
  Args:
      dataset_root (str): The dataset directory. Default: None
      result_root(str): The directory to save the result file. Default: None
      transforms (list): Transforms for image.
      mode (str, optional): Which part of dataset to use. it is one of ('train', 'val'). Default: 'train'.
  
      Examples:
  
          transforms=[]
          dataset_root = "data/lung_coronavirus/lung_coronavirus_phase0/"
          dataset = LungCoronavirus(dataset_root=dataset_root, transforms=[], num_classes=3, mode="train")
  
          for data in dataset:
              img, label = data
              print(img.shape, label.shape) # (1, 128, 128, 128) (128, 128, 128)
              print(np.unique(label))
code: def __init__(
      self,
      dataset_root=None,
      result_dir=None,
      transforms=None,
      num_classes=None,
      mode="train",
      ignore_index=255,
      dataset_json_path="",
  ):
      super(LungCoronavirus, self).__init__(
          dataset_root,
          result_dir,
          transforms,
          num_classes,
          mode,
          ignore_index,
          data_URL=URL,
          dataset_json_path=dataset_json_path,
      )
  
file_path: PaddleSeg/contrib/MedicalSeg/medicalseg/datasets/lung_coronavirus.py
imports: import os
  import sys
  import numpy
  from medicalseg.cvlibs import manager
  from medicalseg.transforms import Compose
  from medicalseg.datasets import MedicalDataset
label_desc: Use image node_id 1 to create a new LungCoronavirus object from inherited base classes: MedicalDataset with example: obj = LungCoronavirus(dataset_root, result_dir, transforms, num_classes, mode, ignore_index, dataset_json_path)