mirror of
https://github.com/invoke-ai/InvokeAI
synced 2024-08-30 20:32:17 +00:00
39 lines
1.6 KiB
Python
39 lines
1.6 KiB
Python
|
# Copyright (c) 2022 Kyle Schouviller (https://github.com/kyle0654)
|
||
|
|
|
||
|
|
from datetime import datetime, timezone
|
||
|
|
from typing import Literal, Union
|
||
|
|
from pydantic import Field
|
||
|
|
from .image import ImageField, ImageOutput
|
||
|
|
from .baseinvocation import BaseInvocation, InvocationContext
|
||
|
|
from ..services.image_storage import ImageType
|
||
|
|
from ..services.invocation_services import InvocationServices
|
||
|
|
|
||
|
|
|
||
|
|
class UpscaleInvocation(BaseInvocation):
|
||
|
|
"""Upscales an image."""
|
||
|
|
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")
|
||
|
|
|
||
|
|
def invoke(self, context: InvocationContext) -> ImageOutput:
|
||
|
|
image = context.services.images.get(self.image.image_type, self.image.image_name)
|
||
|
|
results = context.services.generate.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_type = ImageType.RESULT
|
||
|
|
image_name = context.services.images.create_name(context.graph_execution_state_id, self.id)
|
||
|
|
context.services.images.save(image_type, image_name, results[0][0])
|
||
|
|
return ImageOutput(
|
||
|
|
image = ImageField(image_type = image_type, image_name = image_name)
|
||
|
|
)
|