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