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# PCAM

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

  PCAM Dataset.

  The PatchCamelyon dataset is a binary classification dataset with 327,680 color images (96px x 96px), extracted from histopathologic scans of lymph node sections. Each image is annotated with a binary label indicating presence of metastatic tissue.

  This dataset requires the `h5py` package which you can install with `pip install h5py`.

  Parameters:

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

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

    - transform (callable, optional) – A function/transform that takes in a 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 into `root/pcam`. If dataset is already downloaded, it is not downloaded again.

  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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