Buckets:

hf-doc-build/doc-dev / diffusers /pr_12411 /en /api /video_processor.md
rtrm's picture
|
download
raw
2.32 kB
# 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_video[[diffusers.video_processor.VideoProcessor.preprocess_video]]
[Source](https://github.com/huggingface/diffusers/blob/vr_12411/src/diffusers/video_processor.py#L29)
Preprocesses input video(s).
**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.
#### diffusers.video_processor.VideoProcessor.postprocess_video[[diffusers.video_processor.VideoProcessor.postprocess_video]]
[Source](https://github.com/huggingface/diffusers/blob/vr_12411/src/diffusers/video_processor.py#L90)
Converts a video tensor to a list of frames for export.
**Parameters:**
video (`torch.Tensor`) : The video as a tensor.
output_type (`str`, defaults to `"np"`) : Output type of the postprocessed `video` tensor.

Xet Storage Details

Size:
2.32 kB
·
Xet hash:
29249eb96debcf1013a0989a4390a3e5595219976b81cc16838f91d187e3252f

Xet efficiently stores files, intelligently splitting them into unique chunks and accelerating uploads and downloads. More info.