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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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import kornia.color |
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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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class ImageRGBToYUV: |
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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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}} |
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RETURN_TYPES = ("IMAGE", "IMAGE", "IMAGE") |
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RETURN_NAMES = ("Y", "U", "V") |
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FUNCTION = "execute" |
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CATEGORY = "image/batch" |
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def execute(self, image): |
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out = kornia.color.rgb_to_ycbcr(image.movedim(-1, 1)).movedim(1, -1) |
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return (out[..., 0:1].expand_as(image), out[..., 1:2].expand_as(image), out[..., 2:3].expand_as(image)) |
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class ImageYUVToRGB: |
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@classmethod |
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def INPUT_TYPES(s): |
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return {"required": {"Y": ("IMAGE",), |
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"U": ("IMAGE",), |
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"V": ("IMAGE",), |
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}} |
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RETURN_TYPES = ("IMAGE",) |
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FUNCTION = "execute" |
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CATEGORY = "image/batch" |
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def execute(self, Y, U, V): |
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image = torch.cat([torch.mean(Y, dim=-1, keepdim=True), torch.mean(U, dim=-1, keepdim=True), torch.mean(V, dim=-1, keepdim=True)], dim=-1) |
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out = kornia.color.ycbcr_to_rgb(image.movedim(-1, 1)).movedim(1, -1) |
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return (out,) |
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NODE_CLASS_MAPPINGS = { |
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"Morphology": Morphology, |
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"ImageRGBToYUV": ImageRGBToYUV, |
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"ImageYUVToRGB": ImageYUVToRGB, |
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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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