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# UniformTemporalSubsample

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

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

  Note

  The UniformTemporalSubsample transform is in Beta stage, and while we do not expect disruptive breaking changes, some APIs may slightly change according to user feedback. Please submit any feedback you may have in this issue: https://github.com/pytorch/vision/issues/6753.

  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

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