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from dataclasses import dataclass |
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from typing import List, Optional, Union |
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import numpy as np |
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import PIL.Image |
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from ...utils import BaseOutput, is_flax_available |
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@dataclass |
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class StableDiffusionPipelineOutput(BaseOutput): |
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""" |
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Output class for Stable Diffusion pipelines. |
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Args: |
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images (`List[PIL.Image.Image]` or `np.ndarray`) |
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List of denoised PIL images of length `batch_size` or NumPy array of shape `(batch_size, height, width, |
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num_channels)`. |
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nsfw_content_detected (`List[bool]`) |
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List indicating whether the corresponding generated image contains "not-safe-for-work" (nsfw) content or |
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`None` if safety checking could not be performed. |
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""" |
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images: Union[List[PIL.Image.Image], np.ndarray] |
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nsfw_content_detected: Optional[List[bool]] |
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if is_flax_available(): |
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import flax |
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@flax.struct.dataclass |
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class FlaxStableDiffusionPipelineOutput(BaseOutput): |
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""" |
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Output class for Flax-based Stable Diffusion pipelines. |
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Args: |
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images (`np.ndarray`): |
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Denoised images of array shape of `(batch_size, height, width, num_channels)`. |
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nsfw_content_detected (`List[bool]`): |
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List indicating whether the corresponding generated image contains "not-safe-for-work" (nsfw) content |
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or `None` if safety checking could not be performed. |
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""" |
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images: np.ndarray |
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nsfw_content_detected: List[bool] |
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