VOCSegmentation — Torchvision 0.22 documentation (original) (raw)

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)[source]¶

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". Ifyear=="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][source]¶

Parameters:

index (int) – Index

Returns:

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

Return type:

tuple