mirror of
https://github.com/invoke-ai/InvokeAI
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60 lines
1.9 KiB
Python
60 lines
1.9 KiB
Python
from typing import Literal, Union
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from pydantic import Field
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from invokeai.app.models.image import ImageCategory, ImageField, ImageType
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from .baseinvocation import BaseInvocation, InvocationContext, InvocationConfig
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from .image import ImageOutput
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class RestoreFaceInvocation(BaseInvocation):
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"""Restores faces in an image."""
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# fmt: off
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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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# fmt: on
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# Schema customisation
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class Config(InvocationConfig):
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schema_extra = {
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"ui": {
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"tags": ["restoration", "image"],
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},
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}
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def invoke(self, context: InvocationContext) -> ImageOutput:
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image = context.services.images.get_pil_image(
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self.image.image_type, self.image.image_name
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)
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results = context.services.restoration.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_dto = context.services.images.create(
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image=results[0][0],
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image_type=ImageType.INTERMEDIATE,
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image_category=ImageCategory.GENERAL,
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node_id=self.id,
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session_id=context.graph_execution_state_id,
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)
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return ImageOutput(
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image=ImageField(
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image_name=image_dto.image_name,
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image_type=image_dto.image_type,
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),
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width=image_dto.width,
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height=image_dto.height,
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)
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