Kitti2015Stereo — Torchvision 0.22 documentation (original) (raw)
class torchvision.datasets.Kitti2015Stereo(root: Union[str, Path], split: str = 'train', transforms: Optional[Callable] = None)[source]¶
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 (str or
pathlib.Path) – 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][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: