FallingThingsStereo

class torchvision.datasets.FallingThingsStereo(root: Union[str, Path], variant: str = 'single', transforms: Optional[Callable] = None)

FallingThings dataset.

The dataset is expected to have the following structure:

root
    FallingThings
        single
            dir1
                scene1
                    _object_settings.json
                    _camera_settings.json
                    image1.left.depth.png
                    image1.right.depth.png
                    image1.left.jpg
                    image1.right.jpg
                    image2.left.depth.png
                    image2.right.depth.png
                    image2.left.jpg
                    image2.right
                    ...
                scene2
            ...
        mixed
            scene1
                _object_settings.json
                _camera_settings.json
                image1.left.depth.png
                image1.right.depth.png
                image1.left.jpg
                image1.right.jpg
                image2.left.depth.png
                image2.right.depth.png
                image2.left.jpg
                image2.right
                ...
            scene2
            ...

Parameters:

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

• variant (string) – Which variant to use. Either “single”, “mixed”, 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], ndarray]

Return example at given index.

Parameters:

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

Returns:

A 3-tuple with (img_left, img_right, disparity). The disparity is a numpy array of shape (1, H, W) and the images are PIL images. If a valid_mask is generated within the transforms parameter, a 4-tuple with (img_left, img_right, disparity, valid_mask) is returned.

Return type:

tuple