mirror of
https://github.com/invoke-ai/InvokeAI
synced 2024-08-30 20:32:17 +00:00
162bcda49e
- `MetadataModule` is stateless and needed in places where the `InvocationContext` is not available, so have not made it a `service` - Handles loading/parsing/building metadata, and creating png info objects - added tests for MetadataModule - Lifted thumbnail stuff to util
57 lines
1.9 KiB
Python
57 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 ImageField, ImageType
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from invokeai.app.modules.metadata import MetadataModule
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from .baseinvocation import BaseInvocation, InvocationContext, InvocationConfig
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from .image import ImageOutput, build_image_output
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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(
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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_type = ImageType.RESULT
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image_name = context.services.images.create_name(
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context.graph_execution_state_id, self.id
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)
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metadata = MetadataModule.build_metadata(
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session_id=context.graph_execution_state_id, invocation=self
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)
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context.services.images.save(image_type, image_name, results[0][0], metadata)
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return build_image_output(
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image_type=image_type,
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image_name=image_name,
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image=results[0][0]
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) |