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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, | |
) | |
class StableDiffusionSafePipelineOutput(BaseOutput): | |
""" | |
Output class for Safe 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)`. PIL images or numpy array present the denoised images of the diffusion pipeline. | |
nsfw_content_detected (`List[bool]`) | |
List of flags denoting whether the corresponding generated image likely represents "not-safe-for-work" | |
(nsfw) content, or `None` if safety checking could not be performed. | |
images (`List[PIL.Image.Image]` or `np.ndarray`) | |
List of denoised PIL images that were flagged by the safety checker any may contain "not-safe-for-work" | |
(nsfw) content, or `None` if no safety check was performed or no images were flagged. | |
applied_safety_concept (`str`) | |
The safety concept that was applied for safety guidance, or `None` if safety guidance was disabled | |
""" | |
images: Union[List[PIL.Image.Image], np.ndarray] | |
nsfw_content_detected: Optional[List[bool]] | |
unsafe_images: Optional[Union[List[PIL.Image.Image], np.ndarray]] | |
applied_safety_concept: Optional[str] | |