29 lines
1.1 KiB
Python
29 lines
1.1 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.Image
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from ...utils import BaseOutput
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@dataclass
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class IFPipelineOutput(BaseOutput):
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r"""
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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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nsfw_detected (`List[bool]`):
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List of flags denoting whether the corresponding generated image likely represents "not-safe-for-work"
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(nsfw) content or a watermark. `None` if safety checking could not be performed.
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watermark_detected (`List[bool]`):
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List of flags denoting whether the corresponding generated image likely has a watermark. `None` if safety
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checking could not be performed.
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"""
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images: Union[List[PIL.Image.Image], np.ndarray]
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nsfw_detected: Optional[List[bool]]
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watermark_detected: Optional[List[bool]]
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