mirror of
https://github.com/invoke-ai/InvokeAI
synced 2024-08-30 20:32:17 +00:00
160267c71a
- Remove `ImageType` entirely, it is confusing - Create `ResourceOrigin`, may be `internal` or `external` - Revamp `ImageCategory`, may be `general`, `mask`, `control`, `user`, `other`. Expect to add more as time goes on - Update images `list` route to accept `include_categories` OR `exclude_categories` query parameters to afford finer-grained querying. All services are updated to accomodate this change. The new setup should account for our types of images, including the combinations we couldn't really handle until now: - Canvas init and masks - Canvas when saved-to-gallery or merged
75 lines
2.4 KiB
Python
75 lines
2.4 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 BaseModel, Field
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from invokeai.app.models.image import ImageCategory, ImageField, ResourceOrigin
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from .baseinvocation import BaseInvocation, InvocationContext, InvocationConfig
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from .image import ImageOutput
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class CvInvocationConfig(BaseModel):
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"""Helper class to provide all OpenCV invocations with additional config"""
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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": ["cv", "image"],
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},
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}
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class CvInpaintInvocation(BaseInvocation, CvInvocationConfig):
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"""Simple inpaint using opencv."""
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# fmt: off
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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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# fmt: on
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def invoke(self, context: InvocationContext) -> ImageOutput:
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image = context.services.images.get_pil_image(
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self.image.image_origin, self.image.image_name
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)
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mask = context.services.images.get_pil_image(
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self.mask.image_origin, self.mask.image_name
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)
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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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)
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return ImageOutput(
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image=ImageField(
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image_name=image_dto.image_name,
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image_origin=image_dto.image_origin,
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),
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width=image_dto.width,
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height=image_dto.height,
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)
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