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ETH3DStereo

class torchvision.datasets.ETH3DStereo(root: Union[str, Path], split: str = 'train', transforms: Optional[Callable] = None)[source]

ETH3D Low-Res Two-View dataset.

The dataset is expected to have the following structure:

root
    ETH3D
        two_view_training
            scene1
                im1.png
                im0.png
                images.txt
                cameras.txt
                calib.txt
            scene2
                im1.png
                im0.png
                images.txt
                cameras.txt
                calib.txt
            ...
        two_view_training_gt
            scene1
                disp0GT.pfm
                mask0nocc.png
            scene2
                disp0GT.pfm
                mask0nocc.png
            ...
        two_view_testing
            scene1
                im1.png
                im0.png
                images.txt
                cameras.txt
                calib.txt
            scene2
                im1.png
                im0.png
                images.txt
                cameras.txt
                calib.txt
            ...
Parameters:
  • root (str or pathlib.Path) – Root directory of the ETH3D Dataset.

  • 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]][source]

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

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