| from dataclasses import dataclass |
| from typing import List, Optional, Union |
|
|
| import numpy as np |
|
|
| import PIL |
| from PIL import Image |
|
|
| from ..utils import ( |
| BaseOutput, |
| is_torch_available, |
| is_transformers_available, |
| ) |
|
|
|
|
| @dataclass |
| 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)`. 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: Union[List[PIL.Image.Image], np.ndarray] |
| nsfw_content_detected: Optional[List[bool]] |
|
|
|
|
| if is_transformers_available() and is_torch_available(): |
| from .pipeline_stable_diffusion import StableDiffusionPipeline |
|
|
