UniformTemporalSubsample

class torchvision.transforms.v2.UniformTemporalSubsample(num_samples: int)

[BETA] Uniformly subsample num_samples indices from the temporal dimension of the video.

Warning

The UniformTemporalSubsample transform is in Beta stage, and while we do not expect major breaking changes, some APIs may still change according to user feedback. Please submit any feedback you may have in this issue: https://github.com/pytorch/vision/issues/6753, and you can also check out https://github.com/pytorch/vision/issues/7319 to learn more about the APIs that we suspect might involve future changes.

Videos are expected to be of shape [..., T, C, H, W] where T denotes the temporal dimension.

When num_samples is larger than the size of temporal dimension of the video, it will sample frames based on nearest neighbor interpolation.

Parameters:

num_samples (int) – The number of equispaced samples to be selected