Video Processor

The VideoProcessor provides a unified API for video pipelines to prepare inputs for VAE encoding and post-processing outputs once they’re decoded. The class inherits VaeImageProcessor so it includes transformations such as resizing, normalization, and conversion between PIL Image, PyTorch, and NumPy arrays.

VideoProcessor

diffusers.video_processor.VideoProcessor.preprocess_video

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( video height: int | None = None width: int | None = None **kwargs ) → torch.Tensor of shape (batch_size, num_channels, num_frames, height, width)

Parameters

  • video (list[PIL.Image], list[list[PIL.Image]], torch.Tensor, np.array, list[torch.Tensor], list[np.array]) — The input video. It can be one of the following:
    • list of the PIL images.
    • list of list of PIL images.
    • 4D Torch tensors (expected shape for each tensor (num_frames, num_channels, height, width)).
    • 4D NumPy arrays (expected shape for each array (num_frames, height, width, num_channels)).
    • list of 4D Torch tensors (expected shape for each tensor (num_frames, num_channels, height, width)).
    • list of 4D NumPy arrays (expected shape for each array (num_frames, height, width, num_channels)).
    • 5D NumPy arrays: expected shape for each array (batch_size, num_frames, height, width, num_channels).
    • 5D Torch tensors: expected shape for each array (batch_size, num_frames, num_channels, height, width).
  • height (int, optional, defaults to None) — The height in preprocessed frames of the video. If None, will use the get_default_height_width() to get default height.
  • width (int, optional, defaults to None) -- The width in preprocessed frames of the video. If None, will use get_default_height_width() to get the default width.

Returns

torch.Tensor of shape (batch_size, num_channels, num_frames, height, width)

A 5D tensor holding the batched channels-first video(s).

Preprocesses input video(s). Keyword arguments will be forwarded to VaeImageProcessor.preprocess.

diffusers.video_processor.VideoProcessor.postprocess_video

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( video: Tensor output_type: str = 'np' **kwargs )

Parameters

  • video (torch.Tensor) — The video as a tensor.
  • output_type (str, defaults to "np") — Output type of the postprocessed video tensor.

Converts a video tensor to a list of frames for export. Keyword arguments will be forwarded to VaeImageProcessor.postprocess.

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