mirror of
https://github.com/invoke-ai/InvokeAI
synced 2024-08-30 20:32:17 +00:00
37 lines
1.5 KiB
Python
37 lines
1.5 KiB
Python
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from datetime import datetime, timezone
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from typing import Literal, Union
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from pydantic import Field
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from .image import ImageField, ImageOutput
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from .baseinvocation import BaseInvocation, InvocationContext
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from ..services.image_storage import ImageType
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from ..services.invocation_services import InvocationServices
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class RestoreFaceInvocation(BaseInvocation):
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"""Restores faces in an image."""
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type: Literal['restore_face'] = 'restore_face'
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# Inputs
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image: Union[ImageField,None] = Field(description="The input image")
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strength: float = Field(default=0.75, gt=0, le=1, description="The strength of the restoration")
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def invoke(self, context: InvocationContext) -> ImageOutput:
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image = context.services.images.get(self.image.image_type, self.image.image_name)
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results = context.services.generate.upscale_and_reconstruct(
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image_list = [[image, 0]],
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upscale = None,
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strength = self.strength, # GFPGAN strength
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save_original = False,
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image_callback = None,
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)
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# Results are image and seed, unwrap for now
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# TODO: can this return multiple results?
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image_type = ImageType.RESULT
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image_name = context.services.images.create_name(context.graph_execution_state_id, self.id)
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context.services.images.save(image_type, image_name, results[0][0])
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return ImageOutput(
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image = ImageField(image_type = image_type, image_name = image_name)
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)
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