39 lines
1.3 KiB
Python
39 lines
1.3 KiB
Python
from dataclasses import dataclass
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from typing import List, Optional, Union
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import numpy as np
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import PIL
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from ...utils import (
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BaseOutput,
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OptionalDependencyNotAvailable,
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is_torch_available,
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is_transformers_available,
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)
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@dataclass
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class StableDiffusionXLPipelineOutput(BaseOutput):
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"""
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Output class for Stable Diffusion pipelines.
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Args:
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images (`List[PIL.Image.Image]` or `np.ndarray`)
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List of denoised PIL images of length `batch_size` or numpy array of shape `(batch_size, height, width,
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num_channels)`. PIL images or numpy array present the denoised images of the diffusion pipeline.
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"""
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images: Union[List[PIL.Image.Image], np.ndarray]
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try:
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if not (is_transformers_available() and is_torch_available()):
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raise OptionalDependencyNotAvailable()
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except OptionalDependencyNotAvailable:
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from ...utils.dummy_torch_and_transformers_objects import * # noqa F403
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else:
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from .pipeline_stable_diffusion_xl import StableDiffusionXLPipeline
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from .pipeline_stable_diffusion_xl_img2img import StableDiffusionXLImg2ImgPipeline
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from .pipeline_stable_diffusion_xl_inpaint import StableDiffusionXLInpaintPipeline
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from .pipeline_stable_diffusion_xl_instruct_pix2pix import StableDiffusionXLInstructPix2PixPipeline
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