class_docstr: The StanfordCars dataset, mapping images to their respective class
code: def __init__(self, root: str, split: str):
      assert split in {"train", "test"}
      self.root = root
      self.split = split
      self.annotations = self._open_annotations()
      self.image_folder = os.path.join(self.root, f"cars_{split}")
      self.class_names = self._get_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 1 to create a new StanfordCars object  with example: obj = StanfordCars(root, split)