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VOCDetection

class torchvision.datasets.VOCDetection(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)[source]

Pascal VOC Detection 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. (default: alphabetic indexing of VOC’s 20 classes).

  • transform (callable, optional) – A function/transform that takes in a PIL image and returns a transformed version. E.g, transforms.RandomCrop

  • target_transform (callable, required) – 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 a dictionary of the XML tree.

Return type:

tuple

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