Kitti2015Stereo

class torchvision.datasets.Kitti2015Stereo(root: Union[str, Path], split: str = 'train', transforms: Optional[Callable] = None)

KITTI dataset from the 2015 stereo evaluation benchmark.

The dataset is expected to have the following structure:

root
    Kitti2015
        testing
            image_2
                img1.png
                img2.png
                ...
            image_3
                img1.png
                img2.png
                ...
        training
            image_2
                img1.png
                img2.png
                ...
            image_3
                img1.png
                img2.png
                ...
            disp_occ_0
                img1.png
                img2.png
                ...
            disp_occ_1
                img1.png
                img2.png
                ...
            calib

Parameters:

• root (str or pathlib.Path) – Root directory where Kitti2015 is located.

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

• 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 4-tuple with (img_left, img_right, disparity, valid_mask). The disparity is a numpy array of shape (1, H, W) and the images are PIL images. valid_mask is implicitly None if the transforms parameter does not generate a valid mask. Both disparity and valid_mask are None if the dataset split is test.

Return type:

tuple