49 lines
1.8 KiB
Python
49 lines
1.8 KiB
Python
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import torch
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import comfy.model_management
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from kornia.morphology import dilation, erosion, opening, closing, gradient, top_hat, bottom_hat
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class Morphology:
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@classmethod
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def INPUT_TYPES(s):
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return {"required": {"image": ("IMAGE",),
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"operation": (["erode", "dilate", "open", "close", "gradient", "bottom_hat", "top_hat"],),
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"kernel_size": ("INT", {"default": 3, "min": 3, "max": 999, "step": 1}),
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}}
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RETURN_TYPES = ("IMAGE",)
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FUNCTION = "process"
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CATEGORY = "image/postprocessing"
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def process(self, image, operation, kernel_size):
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device = comfy.model_management.get_torch_device()
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kernel = torch.ones(kernel_size, kernel_size, device=device)
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image_k = image.to(device).movedim(-1, 1)
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if operation == "erode":
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output = erosion(image_k, kernel)
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elif operation == "dilate":
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output = dilation(image_k, kernel)
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elif operation == "open":
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output = opening(image_k, kernel)
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elif operation == "close":
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output = closing(image_k, kernel)
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elif operation == "gradient":
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output = gradient(image_k, kernel)
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elif operation == "top_hat":
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output = top_hat(image_k, kernel)
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elif operation == "bottom_hat":
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output = bottom_hat(image_k, kernel)
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else:
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raise ValueError(f"Invalid operation {operation} for morphology. Must be one of 'erode', 'dilate', 'open', 'close', 'gradient', 'tophat', 'bottomhat'")
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img_out = output.to(comfy.model_management.intermediate_device()).movedim(1, -1)
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return (img_out,)
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NODE_CLASS_MAPPINGS = {
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"Morphology": Morphology,
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}
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NODE_DISPLAY_NAME_MAPPINGS = {
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"Morphology": "ImageMorphology",
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}
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