mirror of
https://github.com/invoke-ai/InvokeAI
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58 lines
1.9 KiB
Python
58 lines
1.9 KiB
Python
# Copyright (c) 2022 Kyle Schouviller (https://github.com/kyle0654)
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from typing import Literal, Optional
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from pydantic import Field
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from invokeai.app.models.image import ImageCategory, ImageField, ResourceOrigin
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from .baseinvocation import BaseInvocation, InvocationContext, InvocationConfig
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from .image import ImageOutput
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class UpscaleInvocation(BaseInvocation):
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"""Upscales an image."""
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# fmt: off
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type: Literal["upscale"] = "upscale"
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# Inputs
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image: Optional[ImageField] = Field(description="The input image", default=None)
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strength: float = Field(default=0.75, gt=0, le=1, description="The strength")
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level: Literal[2, 4] = Field(default=2, description="The upscale level")
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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": ["upscaling", "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(self.image.image_name)
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results = context.services.restoration.upscale_and_reconstruct(
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image_list=[[image, 0]],
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upscale=(self.level, self.strength),
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strength=0.0, # 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_origin=ResourceOrigin.INTERNAL,
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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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is_intermediate=self.is_intermediate,
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)
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return ImageOutput(
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image=ImageField(image_name=image_dto.image_name),
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width=image_dto.width,
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height=image_dto.height,
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)
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