# Copyright (c) 2022 Kyle Schouviller (https://github.com/kyle0654) from typing import Literal, Union from pydantic import Field from invokeai.app.models.image import ImageCategory, ImageField, ResourceOrigin from .baseinvocation import BaseInvocation, InvocationContext, InvocationConfig from .image import ImageOutput class UpscaleInvocation(BaseInvocation): """Upscales an image.""" # fmt: off type: Literal["upscale"] = "upscale" # Inputs image: Union[ImageField, None] = Field(description="The input image", default=None) strength: float = Field(default=0.75, gt=0, le=1, description="The strength") level: Literal[2, 4] = Field(default=2, description="The upscale level") # fmt: on # Schema customisation class Config(InvocationConfig): schema_extra = { "ui": { "tags": ["upscaling", "image"], }, } def invoke(self, context: InvocationContext) -> ImageOutput: image = context.services.images.get_pil_image( self.image.image_origin, self.image.image_name ) results = context.services.restoration.upscale_and_reconstruct( image_list=[[image, 0]], upscale=(self.level, self.strength), strength=0.0, # GFPGAN strength save_original=False, image_callback=None, ) # Results are image and seed, unwrap for now # TODO: can this return multiple results? image_dto = context.services.images.create( image=results[0][0], image_origin=ResourceOrigin.INTERNAL, image_category=ImageCategory.GENERAL, node_id=self.id, session_id=context.graph_execution_state_id, is_intermediate=self.is_intermediate, ) return ImageOutput( image=ImageField( image_name=image_dto.image_name, image_origin=image_dto.image_origin, ), width=image_dto.width, height=image_dto.height, )