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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_flax_available,
is_onnx_available,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
@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_cycle_diffusion import CycleDiffusionPipeline
from .pipeline_stable_diffusion import StableDiffusionPipeline
from .pipeline_stable_diffusion_img2img import StableDiffusionImg2ImgPipeline
from .pipeline_stable_diffusion_inpaint import StableDiffusionInpaintPipeline
from .pipeline_stable_diffusion_inpaint_legacy import StableDiffusionInpaintPipelineLegacy
from .pipeline_stable_diffusion_upscale import StableDiffusionUpscalePipeline
from .safety_checker import StableDiffusionSafetyChecker
if is_transformers_available() and is_torch_available() and is_transformers_version(">=", "4.25.0.dev0"):
from .pipeline_stable_diffusion_image_variation import StableDiffusionImageVariationPipeline
else:
from ...utils.dummy_torch_and_transformers_objects import StableDiffusionImageVariationPipeline
if is_transformers_available() and is_onnx_available():
from .pipeline_onnx_stable_diffusion import OnnxStableDiffusionPipeline, StableDiffusionOnnxPipeline
from .pipeline_onnx_stable_diffusion_img2img import OnnxStableDiffusionImg2ImgPipeline
from .pipeline_onnx_stable_diffusion_inpaint import OnnxStableDiffusionInpaintPipeline
from .pipeline_onnx_stable_diffusion_inpaint_legacy import OnnxStableDiffusionInpaintPipelineLegacy
if is_transformers_available() and is_flax_available():
import flax
@flax.struct.dataclass
class FlaxStableDiffusionPipelineOutput(BaseOutput):
"""
Output class for Stable Diffusion pipelines.
Args:
images (`np.ndarray`)
Array of shape `(batch_size, height, width, num_channels)` with images from 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.
"""
images: np.ndarray
nsfw_content_detected: List[bool]
from ...schedulers.scheduling_pndm_flax import PNDMSchedulerState
from .pipeline_flax_stable_diffusion import FlaxStableDiffusionPipeline
from .safety_checker_flax import FlaxStableDiffusionSafetyChecker
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