mirror of
https://github.com/invoke-ai/InvokeAI
synced 2024-08-30 20:32:17 +00:00
45 lines
1.5 KiB
Python
45 lines
1.5 KiB
Python
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 ..services.image_storage import ImageType
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from ..services.invocation_services import InvocationServices
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from .baseinvocation import BaseInvocation, InvocationContext
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from .image import ImageField, ImageOutput
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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(
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default=0.75, gt=0, le=1, description="The strength of the restoration"
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)
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def invoke(self, context: InvocationContext) -> ImageOutput:
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image = context.services.images.get(
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self.image.image_type, self.image.image_name
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)
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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(
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context.graph_execution_state_id, self.id
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)
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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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