code: def _prepare_synset_to_human(self):
      SIZE = 2655750
      URL = "https://heibox.uni-heidelberg.de/f/9f28e956cd304264bb82/?dl=1"
      self.human_dict = os.path.join(self.root, "synset_human.txt")
      if (
          not os.path.exists(self.human_dict)
          or not os.path.getsize(self.human_dict) == SIZE
      ):
          download(URL, self.human_dict)
  
imports: import glob
  import os
  import pickle
  import shutil
  import tarfile
  from functools import partial
  import albumentations
  import cv2
  import numpy
  import PIL
  import taming.data.utils
  import torchvision.transforms.functional
  import yaml
  from ldm.modules.image_degradation import degradation_fn_bsr, degradation_fn_bsr_light
  from omegaconf import OmegaConf
  from PIL import Image
  from taming.data.imagenet import ImagePaths, download, give_synsets_from_indices, retrieve, str_to_indices
  from torch.utils.data import Dataset, Subset
  from tqdm import tqdm
label_desc: Use image node_id 6 for calling the ImageNetBase obj's underlying member method code with example usage: obj._prepare_synset_to_human() without return types