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Sync the split MiniMax-H3 Spaces (part 3)
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from dataclasses import dataclass
import numpy as np
import PIL.Image
from ....utils import (
BaseOutput,
)
@dataclass
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: list[PIL.Image.Image] | np.ndarray
nsfw_content_detected: list[bool] | None
unsafe_images: list[PIL.Image.Image] | np.ndarray | None
applied_safety_concept: str | None