| | from dataclasses import dataclass |
| | from typing import List, Optional, Union |
| |
|
| | 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: 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] |
| |
|