HD1K

class torchvision.datasets.HD1K(root: Union[str, Path], split: str = 'train', transforms: Optional[Callable] = None)

HD1K dataset for optical flow.

The dataset is expected to have the following structure:

root
    hd1k
        hd1k_challenge
            image_2
        hd1k_flow_gt
            flow_occ
        hd1k_input
            image_2

Parameters:

• root (str or pathlib.Path) – Root directory of the HD1K Dataset.

• split (string, optional) – The dataset split, either “train” (default) or “test”

• transforms (callable, optional) – A function/transform that takes in img1, img2, flow, valid_flow_mask and returns a transformed version.

Special-members:

__getitem__(index: int) → Union[Tuple[Image, Image, Optional[ndarray], Optional[ndarray]], Tuple[Image, Image, Optional[ndarray]]]

Return example at given index.

Parameters:

index (int) – The index of the example to retrieve

Returns:

A 4-tuple with (img1, img2, flow, valid_flow_mask) where valid_flow_mask is a numpy boolean mask of shape (H, W) indicating which flow values are valid. The flow is a numpy array of shape (2, H, W) and the images are PIL images. flow and valid_flow_mask are None if split="test".

Return type:

tuple