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https://github.com/invoke-ai/InvokeAI
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34e3aa1f88
author Kyle Schouviller <kyle0654@hotmail.com> 1669872800 -0800 committer Kyle Schouviller <kyle0654@hotmail.com> 1676240900 -0800 Adding base node architecture Fix type annotation errors Runs and generates, but breaks in saving session Fix default model value setting. Fix deprecation warning. Fixed node api Adding markdown docs Simplifying Generate construction in apps [nodes] A few minor changes (#2510) * Pin api-related requirements * Remove confusing extra CORS origins list * Adds response models for HTTP 200 [nodes] Adding graph_execution_state to soon replace session. Adding tests with pytest. Minor typing fixes [nodes] Fix some small output query hookups [node] Fixing some additional typing issues [nodes] Move and expand graph code. Add base item storage and sqlite implementation. Update startup to match new code [nodes] Add callbacks to item storage [nodes] Adding an InvocationContext object to use for invocations to provide easier extensibility [nodes] New execution model that handles iteration [nodes] Fixing the CLI [nodes] Adding a note to the CLI [nodes] Split processing thread into separate service [node] Add error message on node processing failure Removing old files and duplicated packages Adding python-multipart
43 lines
1.7 KiB
Python
43 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 numpy
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from pydantic import Field
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from PIL import Image, ImageOps
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import cv2 as cv
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from .image import ImageField, ImageOutput
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from .baseinvocation import BaseInvocation, InvocationContext
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from ..services.image_storage import ImageType
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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(default=None, description="The mask to use when inpainting")
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def invoke(self, context: InvocationContext) -> ImageOutput:
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image = context.services.images.get(self.image.image_type, self.image.image_name)
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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(context.graph_execution_state_id, self.id)
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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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