mirror of
https://github.com/invoke-ai/InvokeAI
synced 2024-08-30 20:32:17 +00:00
63 lines
2.0 KiB
Python
63 lines
2.0 KiB
Python
# 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, ImageType
|
|
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_type, 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_type=ImageType.RESULT,
|
|
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_type=image_dto.image_type,
|
|
),
|
|
width=image_dto.width,
|
|
height=image_dto.height,
|
|
)
|