VOCSegmentation

class torchvision.datasets.VOCSegmentation(root: Union[str, Path], 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 (str or pathlib.Path) – 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 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.

• 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