SintelStereo — Torchvision 0.22 documentation (original) (raw)
class torchvision.datasets.SintelStereo(root: Union[str, Path], pass_name: str = 'final', transforms: Optional[Callable] = None)[source]¶
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 (str or
pathlib.Path) – 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]][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) 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: