mirror of
https://github.com/invoke-ai/InvokeAI
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52 lines
1.7 KiB
Python
52 lines
1.7 KiB
Python
# Copyright (c) 2022 Kyle Schouviller (https://github.com/kyle0654)
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from typing import Literal
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import cv2 as cv
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import numpy
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from PIL import Image, ImageOps
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from pydantic import Field
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from ..services.image_storage import ImageType
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from .baseinvocation import BaseInvocation, InvocationContext
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from .image import ImageField, ImageOutput
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class CvInpaintInvocation(BaseInvocation):
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"""Simple inpaint using opencv."""
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type: Literal["cv_inpaint"] = "cv_inpaint"
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# Inputs
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image: ImageField = Field(default=None, description="The image to inpaint")
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mask: ImageField = Field(
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default=None, description="The mask to use when inpainting"
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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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mask = context.services.images.get(self.mask.image_type, self.mask.image_name)
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# Convert to cv image/mask
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# TODO: consider making these utility functions
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cv_image = cv.cvtColor(numpy.array(image.convert("RGB")), cv.COLOR_RGB2BGR)
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cv_mask = numpy.array(ImageOps.invert(mask))
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# Inpaint
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cv_inpainted = cv.inpaint(cv_image, cv_mask, 3, cv.INPAINT_TELEA)
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# Convert back to Pillow
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# TODO: consider making a utility function
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image_inpainted = Image.fromarray(cv.cvtColor(cv_inpainted, cv.COLOR_BGR2RGB))
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image_type = ImageType.INTERMEDIATE
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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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context.services.images.save(image_type, image_name, image_inpainted)
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return ImageOutput(
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image=ImageField(image_type=image_type, image_name=image_name)
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)
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