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# Food101

class torchvision.datasets.Food101(root: str, split: str = 'train', transform: Optional[Callable] = None, target_transform: Optional[Callable] = None, download: bool = False)

  The Food-101 Data Set.

  The Food-101 is a challenging data set of 101 food categories with 101,000 images. For each class, 250 manually reviewed test images are provided as well as 750 training images. On purpose, the training images were not cleaned, and thus still contain some amount of noise. This comes mostly in the form of intense colors and sometimes wrong labels. All images were rescaled to have a maximum side length of 512 pixels.

  Parameters:

    - root (string) – Root directory of the dataset.

    - split (string, optional) – The dataset split, supports `"train"` (default) and `"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. Default is False.

  Special-members:

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

      index (int) – Index

    Returns:

      Sample and meta data, optionally transformed by the respective transforms.

    Return type:

      (Any)

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