SintelStereo

class torchvision.datasets.SintelStereo(root: Union[str, Path], pass_name: str = 'final', transforms: Optional[Callable] = None)

Sintel Stereo Dataset.

The dataset is expected to have the following structure:

root
    Sintel
        training
            final_left
                scene1
                    img1.png
                    img2.png
                    ...
                ...
            final_right
                scene2
                    img1.png
                    img2.png
                    ...
                ...
            disparities
                scene1
                    img1.png
                    img2.png
                    ...
                ...
            occlusions
                scene1
                    img1.png
                    img2.png
                    ...
                ...
            outofframe
                scene1
                    img1.png
                    img2.png
                    ...
                ...

Parameters:

• root (str or pathlib.Path) – Root directory where Sintel Stereo is located.

• pass_name (string) – The name of the pass to use, either “final”, “clean” or “both”.

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

Special-members:

__getitem__(index: int) → 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 (img_left, img_right, disparity, valid_mask) is returned. The disparity is a numpy array of shape (1, H, W) and the images are PIL images whilst the valid_mask is a numpy array of shape (H, W).

Return type:

tuple