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from dataclasses import dataclass |
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from typing import List, Union |
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import numpy as np |
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import PIL.Image |
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import torch |
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from ...utils import BaseOutput |
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@dataclass |
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class AnimateDiffPipelineOutput(BaseOutput): |
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r""" |
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Output class for AnimateDiff pipelines. |
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Args: |
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frames (`torch.Tensor`, `np.ndarray`, or List[List[PIL.Image.Image]]): |
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List of video outputs - It can be a nested list of length `batch_size,` with each sub-list containing denoised |
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PIL image sequences of length `num_frames.` It can also be a NumPy array or Torch tensor of shape |
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`(batch_size, num_frames, channels, height, width)` |
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""" |
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frames: Union[torch.Tensor, np.ndarray, List[List[PIL.Image.Image]]] |
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