CelebA

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

Large-scale CelebFaces Attributes (CelebA) Dataset Dataset.

Parameters:

• root (string) – Root directory where images are downloaded to.

• split (string) – One of {‘train’, ‘valid’, ‘test’, ‘all’}. Accordingly dataset is selected.

• target_type (string or list, optional) –

  Type of target to use, attr, identity, bbox, or landmarks. Can also be a list to output a tuple with all specified target types. The targets represent:

  • attr (np.array shape=(40,) dtype=int): binary (0, 1) labels for attributes

  • identity (int): label for each person (data points with the same identity are the same person)

  • bbox (np.array shape=(4,) dtype=int): bounding box (x, y, width, height)

  • landmarks (np.array shape=(10,) dtype=int): landmark points (lefteye_x, lefteye_y, righteye_x, righteye_y, nose_x, nose_y, leftmouth_x, leftmouth_y, rightmouth_x, rightmouth_y)

  Defaults to attr. If empty, None will be returned as target.

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

• 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 in root directory. If dataset is already downloaded, it is not downloaded again.

Special-members:

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

Parameters:

index (int) – Index

Returns:

Sample and meta data, optionally transformed by the respective transforms.

Return type:

(Any)