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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,
OptionalDependencyNotAvailable,
is_flax_available,
is_k_diffusion_available,
is_k_diffusion_version,
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]]
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ...utils.dummy_torch_and_transformers_objects import * # noqa F403
else:
from .pipeline_cycle_diffusion import CycleDiffusionPipeline
from .pipeline_stable_diffusion import StableDiffusionPipeline
from .pipeline_stable_diffusion_attend_and_excite import StableDiffusionAttendAndExcitePipeline
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_instruct_pix2pix import StableDiffusionInstructPix2PixPipeline
from .pipeline_stable_diffusion_latent_upscale import StableDiffusionLatentUpscalePipeline
from .pipeline_stable_diffusion_ldm3d import StableDiffusionLDM3DPipeline
from .pipeline_stable_diffusion_model_editing import StableDiffusionModelEditingPipeline
from .pipeline_stable_diffusion_panorama import StableDiffusionPanoramaPipeline
from .pipeline_stable_diffusion_paradigms import StableDiffusionParadigmsPipeline
from .pipeline_stable_diffusion_sag import StableDiffusionSAGPipeline
from .pipeline_stable_diffusion_upscale import StableDiffusionUpscalePipeline
from .pipeline_stable_unclip import StableUnCLIPPipeline
from .pipeline_stable_unclip_img2img import StableUnCLIPImg2ImgPipeline
from .safety_checker import StableDiffusionSafetyChecker
from .stable_unclip_image_normalizer import StableUnCLIPImageNormalizer
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version(">=", "4.25.0")):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ...utils.dummy_torch_and_transformers_objects import StableDiffusionImageVariationPipeline
else:
from .pipeline_stable_diffusion_image_variation import StableDiffusionImageVariationPipeline
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version(">=", "4.26.0")):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ...utils.dummy_torch_and_transformers_objects import (
StableDiffusionDepth2ImgPipeline,
StableDiffusionDiffEditPipeline,
StableDiffusionPix2PixZeroPipeline,
)
else:
from .pipeline_stable_diffusion_depth2img import StableDiffusionDepth2ImgPipeline
from .pipeline_stable_diffusion_diffedit import StableDiffusionDiffEditPipeline
from .pipeline_stable_diffusion_pix2pix_zero import StableDiffusionPix2PixZeroPipeline
try:
if not (
is_torch_available()
and is_transformers_available()
and is_k_diffusion_available()
and is_k_diffusion_version(">=", "0.0.12")
):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ...utils.dummy_torch_and_transformers_and_k_diffusion_objects import * # noqa F403
else:
from .pipeline_stable_diffusion_k_diffusion import StableDiffusionKDiffusionPipeline
try:
if not (is_transformers_available() and is_onnx_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ...utils.dummy_onnx_objects import * # noqa F403
else:
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
from .pipeline_onnx_stable_diffusion_upscale import OnnxStableDiffusionUpscalePipeline
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 .pipeline_flax_stable_diffusion_img2img import FlaxStableDiffusionImg2ImgPipeline
from .pipeline_flax_stable_diffusion_inpaint import FlaxStableDiffusionInpaintPipeline
from .safety_checker_flax import FlaxStableDiffusionSafetyChecker
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