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# StanfordCars

class torchvision.datasets.StanfordCars(root: str, split: str = 'train', transform: Optional[Callable] = None, target_transform: Optional[Callable] = None, download: bool = False)

  Stanford Cars Dataset

  The Cars dataset contains 16,185 images of 196 classes of cars. The data is split into 8,144 training images and 8,041 testing images, where each class has been split roughly in a 50-50 split

  Note

  This class needs scipy to load target files from .mat format.

  Parameters:

    - root (string) – Root directory of dataset

    - split (string, optional) – The dataset split, supports `"train"` (default) or `"test"`.

    - transform (callable, optional) – A function/transform that takes in an PIL image and returns a transformed version. E.g, `transforms.RandomCrop`

    - target_transform (callable, optional) – A function/transform that takes in the target and transforms it.

    - download (bool, optional) – If True, downloads the dataset from the internet and puts it in root directory. If dataset is already downloaded, it is not downloaded again.

  Special-members:

  __getitem__(idx: int) → Tuple[Any, Any]

    Returns pil_image and class_id for given index

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