Sintel¶
-
class
torchvision.datasets.
Sintel
(root, split='train', pass_name='clean', transforms=None)[source]¶ Sintel Dataset for optical flow.
The dataset is expected to have the following structure:
root Sintel testing clean scene_1 scene_2 ... final scene_1 scene_2 ... training clean scene_1 scene_2 ... final scene_1 scene_2 ... flow scene_1 scene_2 ...
- Parameters
root (string) – Root directory of the Sintel Dataset.
split (string, optional) – The dataset split, either “train” (default) or “test”
pass_name (string, optional) – The pass to use, either “clean” (default), “final”, or “both”. See link above for details on the different passes.
transforms (callable, optional) – A function/transform that takes in
img1, img2, flow, valid_flow_mask
and returns a transformed version.valid_flow_mask
is expected for consistency with other datasets which return a built-in valid mask, such asKittiFlow
.
- Special-members
-
__getitem__
(index)[source]¶ Return example at given index.
- Parameters
index (int) – The index of the example to retrieve
- Returns
A 3-tuple with
(img1, img2, flow)
. The flow is a numpy array of shape (2, H, W) and the images are PIL images.flow
is None ifsplit="test"
. If a valid flow mask is generated within thetransforms
parameter, a 4-tuple with(img1, img2, flow, valid_flow_mask)
is returned.- Return type