class_docstr: Stanford Cars dataset.
  homepage="https://ai.stanford.edu/~jkrause/cars/car_dataset.html",
  dependencies=scipy
class_docstr_tok: ["Stanford","Cars","dataset",".","homepage=","''","https",":","\/\/ai.stanford.edu\/~jkrause\/cars\/car_dataset.html","''",",","dependencies=scipy"]
code: def _generate_categories(self) -> List[str]:
      resources = self._resources()
  
      devkit_dp = resources[1].load(self._root)
      meta_dp = Filter(
          devkit_dp, path_comparator("name", "cars_meta.mat")
      )
      _, meta_file = next(iter(meta_dp))
  
      return list(read_mat(meta_file, squeeze_me=True)["class_names"])
  
imports: import pathlib
  from typing import Any, BinaryIO, Dict, Iterator, List, Tuple, Union
  from torchdata.datapipes.iter import Filter, IterDataPipe, Mapper, Zipper
  from torchvision.prototype.datasets.utils import Dataset, EncodedImage, HttpResource, OnlineResource
  from torchvision.prototype.datasets.utils._internal import hint_sharding, hint_shuffling, path_comparator, read_categories_file, read_mat
  from torchvision.prototype.tv_tensors import Label
  from torchvision.tv_tensors import BoundingBoxes
  from .._api import register_dataset, register_info
label_desc: Use image node_id 5 for calling the StanfordCars obj's underlying member method code with example usage: obj._generate_categories() and returns: list