49 lines
1.2 KiB
Python
49 lines
1.2 KiB
Python
import cv2
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import torch
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class GaussianBlur:
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def __init__(self):
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pass
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@classmethod
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def INPUT_TYPES(s):
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return {
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"required": {
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"image": ("IMAGE",),
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"kernel_size": ("INT", {
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"default": 5,
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"min": 1,
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"max": 31,
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"step": 1
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}),
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"sigma": ("FLOAT", {
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"default": 1.0,
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"min": 0.1,
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"max": 10.0,
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"step": 0.1
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}),
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},
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}
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RETURN_TYPES = ("IMAGE",)
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FUNCTION = "blur"
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CATEGORY = "postprocessing"
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def blur(self, image: torch.Tensor, kernel_size: int, sigma: float):
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batch_size, height, width, _ = image.shape
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result = torch.zeros_like(image)
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for b in range(batch_size):
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tensor_image = image[b].numpy()
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blurred = cv2.GaussianBlur(tensor_image, (kernel_size, kernel_size), sigma)
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tensor = torch.from_numpy(blurred).unsqueeze(0)
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result[b] = tensor
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return (result,)
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NODE_CLASS_MAPPINGS = {
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"GaussianBlur": GaussianBlur
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}
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