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1e4b953ccd
This class works the same way as `WithMetadata` - it simply adds a `board` field to the node. The context wrapper function is able to pull the board id from this. This allows image-outputting nodes to get a board field "for free", and have their outputs automatically saved to it. This is a breaking change for node authors who may have a field called `board`, because it makes `board` a reserved field name. I'll look into how to avoid this - maybe by naming this invoke-managed field `_board` to avoid collisions? Supporting changes: - `WithBoard` is added to all image-outputting nodes, giving them the ability to save to board. - Unused, duplicate `WithMetadata` and `WithWorkflow` classes are deleted from `baseinvocation.py`. The "real" versions are in `fields.py`. - Remove `LinearUIOutputInvocation`. Now that all nodes that output images also have a `board` field by default, this node is no longer necessary. See comment here for context: https://github.com/invoke-ai/InvokeAI/pull/5491#discussion_r1480760629 - Without `LinearUIOutputInvocation`, the `ImagesInferface.update` method is no longer needed, and removed. Note: This commit does not bump all node versions. I will ensure that is done correctly before merging the PR of which this commit is a part. Note: A followup commit will implement the frontend changes to support this change.
42 lines
1.6 KiB
Python
42 lines
1.6 KiB
Python
# Copyright (c) 2022 Kyle Schouviller (https://github.com/kyle0654)
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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 invokeai.app.invocations.fields import ImageField
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from invokeai.app.invocations.primitives import ImageOutput
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from invokeai.app.services.shared.invocation_context import InvocationContext
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from .baseinvocation import BaseInvocation, invocation
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from .fields import InputField, WithBoard, WithMetadata
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@invocation("cv_inpaint", title="OpenCV Inpaint", tags=["opencv", "inpaint"], category="inpaint", version="1.2.1")
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class CvInpaintInvocation(BaseInvocation, WithMetadata, WithBoard):
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"""Simple inpaint using opencv."""
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image: ImageField = InputField(description="The image to inpaint")
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mask: ImageField = InputField(description="The mask to use when inpainting")
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def invoke(self, context: InvocationContext) -> ImageOutput:
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image = context.images.get_pil(self.image.image_name)
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mask = context.images.get_pil(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.convert("L")))
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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_dto = context.images.save(image=image_inpainted)
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return ImageOutput.build(image_dto)
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