class_docstr: The StanfordCars dataset, mapping images to their respective class
code: def _get_class_names(self):
      meta_data = io.loadmat(
          os.path.join(self.root, "devkit/cars_meta.mat")
      )
      class_names = meta_data["class_names"][0]
      return [
          # Format class names appropriately for directory creation.
          "{:03}".format(i)
          + "_"
          + class_name[0].replace(" ", "_").replace("/", "_")
          for i, class_name in enumerate(class_names)
      ]
  
imports: import argparse
  import os
  import shutil
  from scipy import io
  from torch.utils.data import DataLoader
  from tqdm import tqdm
  from vissl.utils.download import download_and_extract_archive, download_url
  from vissl.utils.io import cleanup_dir
label_desc: Use image node_id 3 for calling the StanfordCars obj's underlying member method code with example usage: obj._get_class_names() and returns: unknown