83 lines
2.2 KiB
Markdown
83 lines
2.2 KiB
Markdown
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# Documentation
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- Class name: BlurImageFast
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- Category: image/filters
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- Output node: False
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BlurImageFast节点提供了一种快速高效的方法来对图像应用高斯模糊。它通过指定x和y方向上的模糊半径来模糊图像，从而实现可自定义的模糊效果。
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# Input types
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## Required
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- images
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- images参数代表要进行模糊处理的图像。它对于定义将应用高斯模糊效果的输入图像至关重要。
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- Comfy dtype: IMAGE
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- Python dtype: torch.Tensor
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- radius_x
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- radius_x参数指定高斯模糊的水平半径。它决定了图像x轴方向上的模糊程度。
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- Comfy dtype: INT
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- Python dtype: int
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- radius_y
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- radius_y参数指定高斯模糊的垂直半径。它决定了图像y轴方向上的模糊程度。
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- Comfy dtype: INT
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- Python dtype: int
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# Output types
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- image
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- 输出是输入图像的模糊版本，通过根据radius_x和radius_y参数指定的高斯模糊实现。
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- Comfy dtype: IMAGE
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- Python dtype: torch.Tensor
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## Usage tips
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- Infra type: `GPU`
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- Common nodes: unknown
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## Source code
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```python
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class BlurImageFast:
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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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"images": ("IMAGE",),
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"radius_x": ("INT", {
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"default": 1,
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"min": 0,
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"max": 1023,
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"step": 1
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}),
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"radius_y": ("INT", {
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"default": 1,
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"min": 0,
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"max": 1023,
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"step": 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_image"
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CATEGORY = "image/filters"
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def blur_image(self, images, radius_x, radius_y):
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if radius_x + radius_y == 0:
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return (images,)
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dx = radius_x * 2 + 1
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dy = radius_y * 2 + 1
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dup = copy.deepcopy(images.cpu().numpy())
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for index, image in enumerate(dup):
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dup[index] = cv2.GaussianBlur(image, (dx, dy), 0)
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return (torch.from_numpy(dup),)
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```
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