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feat: Add Mask from ID Node
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@ -967,3 +967,56 @@ class CanvasPasteBackInvocation(BaseInvocation, WithMetadata, WithBoard):
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image_dto = context.images.save(image=source_image)
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return ImageOutput.build(image_dto)
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@invocation(
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"mask_from_id",
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title="Mask from ID",
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tags=["image", "mask", "id"],
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category="image",
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version="1.0.0",
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)
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class MaskFromIDInvocation(BaseInvocation, WithMetadata, WithBoard):
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"""Generate a mask for a particular color in an ID Map"""
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image: ImageField = InputField(description="The image to create the mask from")
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color: ColorField = InputField(description="ID color to mask")
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threshold: int = InputField(default=100, description="Threshold for color detection")
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invert: bool = InputField(default=False, description="Whether or not to invert the mask")
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def rgba_to_hex(self, rgba_color: tuple[int, int, int, int]):
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r, g, b, a = rgba_color
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hex_code = "#{:02X}{:02X}{:02X}{:02X}".format(r, g, b, int(a * 255))
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return hex_code
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def id_to_mask(self, id_mask: Image.Image, color: tuple[int, int, int, int], threshold: int = 100):
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if id_mask.mode != "RGB":
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id_mask = id_mask.convert("RGB")
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# Can directly just use the tuple but I'll leave this rgba_to_hex here
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# incase anyone prefers using hex codes directly instead of the color picker
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hex_color_str = self.rgba_to_hex(color)
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rgb_color = numpy.array([int(hex_color_str[i : i + 2], 16) for i in (1, 3, 5)])
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# Maybe there's a faster way to calculate this distance but I can't think of any right now.
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color_distance = numpy.linalg.norm(id_mask - rgb_color, axis=-1)
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# Create a mask based on the threshold and the distance calculated above
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binary_mask = (color_distance < threshold).astype(numpy.uint8) * 255
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# Convert the mask back to PIL
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binary_mask_pil = Image.fromarray(binary_mask)
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return binary_mask_pil
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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 = self.id_to_mask(image, self.color.tuple(), self.threshold)
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if self.invert:
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mask = ImageOps.invert(mask)
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image_dto = context.images.save(image=mask, image_category=ImageCategory.MASK)
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return ImageOutput.build(image_dto)
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