| import torch
|
| import comfy.model_management
|
|
|
| from kornia.morphology import dilation, erosion, opening, closing, gradient, top_hat, bottom_hat
|
| import kornia.color
|
|
|
|
|
| class Morphology:
|
| @classmethod
|
| def INPUT_TYPES(s):
|
| return {"required": {"image": ("IMAGE",),
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| "operation": (["erode", "dilate", "open", "close", "gradient", "bottom_hat", "top_hat"],),
|
| "kernel_size": ("INT", {"default": 3, "min": 3, "max": 999, "step": 1}),
|
| }}
|
|
|
| RETURN_TYPES = ("IMAGE",)
|
| FUNCTION = "process"
|
|
|
| CATEGORY = "image/postprocessing"
|
|
|
| def process(self, image, operation, kernel_size):
|
| device = comfy.model_management.get_torch_device()
|
| kernel = torch.ones(kernel_size, kernel_size, device=device)
|
| image_k = image.to(device).movedim(-1, 1)
|
| if operation == "erode":
|
| output = erosion(image_k, kernel)
|
| elif operation == "dilate":
|
| output = dilation(image_k, kernel)
|
| elif operation == "open":
|
| output = opening(image_k, kernel)
|
| elif operation == "close":
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| output = closing(image_k, kernel)
|
| elif operation == "gradient":
|
| output = gradient(image_k, kernel)
|
| elif operation == "top_hat":
|
| output = top_hat(image_k, kernel)
|
| elif operation == "bottom_hat":
|
| output = bottom_hat(image_k, kernel)
|
| else:
|
| raise ValueError(f"Invalid operation {operation} for morphology. Must be one of 'erode', 'dilate', 'open', 'close', 'gradient', 'tophat', 'bottomhat'")
|
| img_out = output.to(comfy.model_management.intermediate_device()).movedim(1, -1)
|
| return (img_out,)
|
|
|
|
|
| class ImageRGBToYUV:
|
| @classmethod
|
| def INPUT_TYPES(s):
|
| return {"required": { "image": ("IMAGE",),
|
| }}
|
|
|
| RETURN_TYPES = ("IMAGE", "IMAGE", "IMAGE")
|
| RETURN_NAMES = ("Y", "U", "V")
|
| FUNCTION = "execute"
|
|
|
| CATEGORY = "image/batch"
|
|
|
| def execute(self, image):
|
| out = kornia.color.rgb_to_ycbcr(image.movedim(-1, 1)).movedim(1, -1)
|
| return (out[..., 0:1].expand_as(image), out[..., 1:2].expand_as(image), out[..., 2:3].expand_as(image))
|
|
|
| class ImageYUVToRGB:
|
| @classmethod
|
| def INPUT_TYPES(s):
|
| return {"required": {"Y": ("IMAGE",),
|
| "U": ("IMAGE",),
|
| "V": ("IMAGE",),
|
| }}
|
|
|
| RETURN_TYPES = ("IMAGE",)
|
| FUNCTION = "execute"
|
|
|
| CATEGORY = "image/batch"
|
|
|
| def execute(self, Y, U, V):
|
| 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)
|
| out = kornia.color.ycbcr_to_rgb(image.movedim(-1, 1)).movedim(1, -1)
|
| return (out,)
|
|
|
| NODE_CLASS_MAPPINGS = {
|
| "Morphology": Morphology,
|
| "ImageRGBToYUV": ImageRGBToYUV,
|
| "ImageYUVToRGB": ImageYUVToRGB,
|
| }
|
|
|
| NODE_DISPLAY_NAME_MAPPINGS = {
|
| "Morphology": "ImageMorphology",
|
| }
|
|
|
