diffusers/pr_12595/en/api/video_processor.md

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]]

diffusers.video_processor.VideoProcessor.preprocess_videodiffusers.video_processor.VideoProcessor.preprocess_videohttps://github.com/huggingface/diffusers/blob/vr_12595/src/diffusers/video_processor.py#L29[{"name": "video", "val": ""}, {"name": "height", "val": ": typing.Optional[int] = None"}, {"name": "width", "val": ": typing.Optional[int] = None"}]- 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.0

Preprocesses input video(s).

diffusers.video_processor.VideoProcessor.postprocess_videodiffusers.video_processor.VideoProcessor.postprocess_videohttps://github.com/huggingface/diffusers/blob/vr_12595/src/diffusers/video_processor.py#L90[{"name": "video", "val": ": Tensor"}, {"name": "output_type", "val": ": str = 'np'"}]- video (torch.Tensor) -- The video as a tensor.

• output_type (str, defaults to "np") -- Output type of the postprocessed video tensor.0

Converts a video tensor to a list of frames for export.