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 _resources(self) -> List[OnlineResource]:
      resources: List[OnlineResource] = [
          HttpResource(
              self._URLS[self._split],
              sha256=self._CHECKSUM[self._split],
          )
      ]
      if self._split == "train":
          resources.append(
              HttpResource(
                  url=self._URLS["car_devkit"],
                  sha256=self._CHECKSUM["car_devkit"],
              )
          )
  
      else:
          resources.append(
              HttpResource(
                  self._URLS["cars_test_annos_withlabels"],
                  sha256=self._CHECKSUM["cars_test_annos_withlabels"],
              )
          )
      return resources
  
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 2 for calling the StanfordCars obj's underlying member method code with example usage: obj._resources() and returns: resources