mirror of
https://github.com/invoke-ai/InvokeAI
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044d4c107a
All invocation metadata (type, title, tags and category) are now defined in decorators.
The decorators add the `type: Literal["invocation_type"]: "invocation_type"` field to the invocation.
Category is a new invocation metadata, but it is not used by the frontend just yet.
- `@invocation()` decorator for invocations
```py
@invocation(
"sdxl_compel_prompt",
title="SDXL Prompt",
tags=["sdxl", "compel", "prompt"],
category="conditioning",
)
class SDXLCompelPromptInvocation(BaseInvocation, SDXLPromptInvocationBase):
...
```
- `@invocation_output()` decorator for invocation outputs
```py
@invocation_output("clip_skip_output")
class ClipSkipInvocationOutput(BaseInvocationOutput):
...
```
- update invocation docs
- add category to decorator
- regen frontend types
56 lines
1.9 KiB
Python
56 lines
1.9 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.primitives import ImageField, ImageOutput
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from invokeai.app.models.image import ImageCategory, ResourceOrigin
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from .baseinvocation import BaseInvocation, InputField, InvocationContext, invocation
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@invocation(
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"cv_inpaint",
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title="OpenCV Inpaint",
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tags=["opencv", "inpaint"],
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category="inpaint",
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)
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class CvInpaintInvocation(BaseInvocation):
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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.services.images.get_pil_image(self.image.image_name)
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mask = context.services.images.get_pil_image(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.services.images.create(
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image=image_inpainted,
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image_origin=ResourceOrigin.INTERNAL,
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image_category=ImageCategory.GENERAL,
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node_id=self.id,
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session_id=context.graph_execution_state_id,
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is_intermediate=self.is_intermediate,
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workflow=self.workflow,
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)
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return ImageOutput(
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image=ImageField(image_name=image_dto.image_name),
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width=image_dto.width,
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height=image_dto.height,
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)
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