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# SintelStereo

class torchvision.datasets.SintelStereo(root: str, 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 (string) – 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

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