code: def __getitem__(self, index):
      base_img_fn = "{}.png".format(self.img_ids[index])
      if self.is_train[index]:  # self.train_mode:
          img_fn = os.path.join(TRAIN_IMG_DIR, base_img_fn)
      else:
          img_fn = os.path.join(TEST_IMG_DIR, base_img_fn)
      img = self.load_image(img_fn)
  
      if self.train_mode:
          base_mask_fn = "{}.png".format(self.img_ids[index])
          if self.is_train[index]:
              mask_fn = os.path.join(TRAIN_MASK_DIR, base_mask_fn)
          else:
              mask_fn = os.path.join(TEST_DIR, "masks", base_mask_fn)
          mask = self.load_image(mask_fn, True)
          img, mask = self.aug_image(img, mask)
          return img, mask, self.salt_exists[index]
      else:
          img = self.aug_image(img)
          return [img]
  
imports: import os, cv2, glob
  import numpy
  from PIL import Image
  import torch
  import torch.utils.data
  from torchvision import datasets, models, transforms
  from utils import read_masks, get_test_meta, get_nfold_split
  import augmentation
  from settings import *
label_desc: Use image node_id 2 for calling the ImageDataset obj's underlying member method code with example usage: obj.__getitem__(index) and returns: img,  mask,  self, list