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[docs] VideoProcessor (#7965)

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Steven Liu
2024-05-20 19:48:21 -07:00
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8
docs/source/en/api/video_processor.md
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@@ -12,4 +12,10 @@ specific language governing permissions and limitations under the License.
# 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.
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
[[autodoc]] video_processor.VideoProcessor.preprocess_video
[[autodoc]] video_processor.VideoProcessor.postprocess_video

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src/diffusers/video_processor.py
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@@ -30,17 +30,19 @@ class VideoProcessor(VaeImageProcessor):
Preprocesses input video(s).
Args:
video: The input video. It can be one of the following:
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).
* 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.