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# Kitti2015Stereo

class torchvision.datasets.Kitti2015Stereo(root: str, 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 (string) – 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

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