class_docstr: You need to to download and convert the [India Driving Dataset](https://idd.insaan.iiit.ac.in/evaluation/autonue21/#bm5)
  following the instructions of Segmentation Track. IDD_Dectection dataset also need for pseudo-labeling.
  
  And then, you need to organize data following the below structure.
  
  IDD_Segmentation
  |
  |--leftImg8bit
  |  |--train
  |  |--val
  |  |--test
  |
  |--gtFine
  |  |--train
  |  |--val
  |  |--test
  
  Args:
      transforms (list): Transforms for image.
      dataset_root (str): Cityscapes dataset directory.
      mode (str, optional): Which part of dataset to use. it is one of ('train', 'val', 'test'). Default: 'train'.
      coarse_multiple (float|int, optional): Multiple of the amount of coarse data relative to fine data. Default: 1
      add_val (bool, optional): Whether to add val set in training. Default: False
code: def __getitem__(self, idx):
      if self.mode == "test":
          image_path, label_path = self.file_list[idx]
          im, _ = self.transforms(im=image_path)
          im = im[np.newaxis, ...]
          return im, image_path
      elif self.mode == "val":
          image_path, label_path = self.file_list[idx]
          im, _ = self.transforms(im=image_path)
          label = np.asarray(Image.open(label_path))
          #             label = cv2.resize(label, (1280, 720), interpolation=cv2.INTER_NEAREST)
          label = label[np.newaxis, :, :]
          return im, label
      else:
          if idx >= self.num_files:
              image_path, label_path = self.coarse_file_list[
                  idx - self.num_files
              ]
          else:
              image_path, label_path = self.file_list[idx]
  
          im, label = self.transforms(im=image_path, label=label_path)
          return im, label
  
file_path: PaddleSeg/contrib/AutoNUE/datasets/auto_nue.py
imports: import os
  import glob
  import random
  import cv2
  import paddle
  import numpy
  from PIL import Image
  from paddleseg.cvlibs import manager
  from paddleseg.transforms import Compose
label_desc: Use image node_id 2 for calling the AutoNue obj's underlying member method code with example usage: obj.__getitem__(idx) and returns: im,  image_path, im,  label, im,  label