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# VOCSegmentation

class torchvision.datasets.VOCSegmentation(root: str, year: str = '2012', image_set: str = 'train', download: bool = False, transform: Optional[Callable] = None, target_transform: Optional[Callable] = None, transforms: Optional[Callable] = None)

  Pascal VOC Segmentation Dataset.

  Parameters:

    - root (string) – Root directory of the VOC Dataset.

    - year (string, optional) – The dataset year, supports years `"2007"` to `"2012"`.

    - image_set (string, optional) – Select the image_set to use, `"train"`, `"trainval"` or `"val"`. If `year=="2007"`, can also be `"test"`.

    - 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.

    - 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.

    - transforms (callable, optional) – A function/transform that takes input sample and its target as entry and returns a transformed version.

  Special-members:

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

      index (int) – Index

    Returns:

      (image, target) where target is the image segmentation.

    Return type:

      tuple

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