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CarlaStereo

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

Carla simulator data linked in the CREStereo github repo.

The dataset is expected to have the following structure:

root
    carla-highres
        trainingF
            scene1
                img0.png
                img1.png
                disp0GT.pfm
                disp1GT.pfm
                calib.txt
            scene2
                img0.png
                img1.png
                disp0GT.pfm
                disp1GT.pfm
                calib.txt
            ...
Parameters:
  • root (str or pathlib.Path) – Root directory where carla-highres is located.

  • 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][source]

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

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