mirror of
https://github.com/invoke-ai/InvokeAI
synced 2024-08-30 20:32:17 +00:00
a1773197e9
- remove `image_origin` from most places where we interact with images - consolidate image file storage into a single `images/` dir Images have an `image_origin` attribute but it is not actually used when retrieving images, nor will it ever be. It is still used when creating images and helps to differentiate between internally generated images and uploads. It was included in eg API routes and image service methods as a holdover from the previous app implementation where images were not managed in a database. Now that we have images in a db, we can do away with this and simplify basically everything that touches images. The one potentially controversial change is to no longer separate internal and external images on disk. If we retain this separation, we have to keep `image_origin` around in a number of spots and it getting image paths on disk painful. So, I am have gotten rid of this organisation. Images are now all stored in `images`, regardless of their origin. As we improve the image management features, this change will hopefully become transparent.
68 lines
2.2 KiB
Python
68 lines
2.2 KiB
Python
# Copyright (c) 2022 Kyle Schouviller (https://github.com/kyle0654)
|
|
|
|
from typing import Literal
|
|
|
|
import cv2 as cv
|
|
import numpy
|
|
from PIL import Image, ImageOps
|
|
from pydantic import BaseModel, Field
|
|
|
|
from invokeai.app.models.image import ImageCategory, ImageField, ResourceOrigin
|
|
from .baseinvocation import BaseInvocation, InvocationContext, InvocationConfig
|
|
from .image import ImageOutput
|
|
|
|
|
|
class CvInvocationConfig(BaseModel):
|
|
"""Helper class to provide all OpenCV invocations with additional config"""
|
|
|
|
# Schema customisation
|
|
class Config(InvocationConfig):
|
|
schema_extra = {
|
|
"ui": {
|
|
"tags": ["cv", "image"],
|
|
},
|
|
}
|
|
|
|
|
|
class CvInpaintInvocation(BaseInvocation, CvInvocationConfig):
|
|
"""Simple inpaint using opencv."""
|
|
|
|
# fmt: off
|
|
type: Literal["cv_inpaint"] = "cv_inpaint"
|
|
|
|
# Inputs
|
|
image: ImageField = Field(default=None, description="The image to inpaint")
|
|
mask: ImageField = Field(default=None, description="The mask to use when inpainting")
|
|
# fmt: on
|
|
|
|
def invoke(self, context: InvocationContext) -> ImageOutput:
|
|
image = context.services.images.get_pil_image(self.image.image_name)
|
|
mask = context.services.images.get_pil_image(self.mask.image_name)
|
|
|
|
# Convert to cv image/mask
|
|
# TODO: consider making these utility functions
|
|
cv_image = cv.cvtColor(numpy.array(image.convert("RGB")), cv.COLOR_RGB2BGR)
|
|
cv_mask = numpy.array(ImageOps.invert(mask.convert("L")))
|
|
|
|
# Inpaint
|
|
cv_inpainted = cv.inpaint(cv_image, cv_mask, 3, cv.INPAINT_TELEA)
|
|
|
|
# Convert back to Pillow
|
|
# TODO: consider making a utility function
|
|
image_inpainted = Image.fromarray(cv.cvtColor(cv_inpainted, cv.COLOR_BGR2RGB))
|
|
|
|
image_dto = context.services.images.create(
|
|
image=image_inpainted,
|
|
image_origin=ResourceOrigin.INTERNAL,
|
|
image_category=ImageCategory.GENERAL,
|
|
node_id=self.id,
|
|
session_id=context.graph_execution_state_id,
|
|
is_intermediate=self.is_intermediate,
|
|
)
|
|
|
|
return ImageOutput(
|
|
image=ImageField(image_name=image_dto.image_name),
|
|
width=image_dto.width,
|
|
height=image_dto.height,
|
|
)
|