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35 lines
1.4 KiB
Python
35 lines
1.4 KiB
Python
import cv2
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from invokeai.app.invocations.baseinvocation import BaseInvocation, invocation
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from invokeai.app.invocations.fields import ImageField, InputField, WithBoard, WithMetadata
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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 invokeai.backend.image_util.util import cv2_to_pil, pil_to_cv2
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@invocation(
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"canny_edge_detection",
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title="Canny Edge Detection",
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tags=["controlnet", "canny"],
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category="controlnet_preprocessors",
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version="1.0.0",
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)
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class CannyEdgeDetectionInvocation(BaseInvocation, WithMetadata, WithBoard):
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"""Geneartes an edge map using a cv2's Canny algorithm."""
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image: ImageField = InputField(description="The image to process")
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low_threshold: int = InputField(
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default=100, ge=0, le=255, description="The low threshold of the Canny pixel gradient (0-255)"
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)
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high_threshold: int = InputField(
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default=200, ge=0, le=255, description="The high threshold of the Canny pixel gradient (0-255)"
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)
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def invoke(self, context: InvocationContext) -> ImageOutput:
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image = context.images.get_pil(self.image.image_name, "RGB")
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np_img = pil_to_cv2(image)
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edge_map = cv2.Canny(np_img, self.low_threshold, self.high_threshold)
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edge_map_pil = cv2_to_pil(edge_map)
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image_dto = context.images.save(image=edge_map_pil)
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return ImageOutput.build(image_dto)
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