ImageFilterBlur

Documentation

• Class name: ImageFilterBlur
• Category: image/filter
• Output node: False

The ImageFilterBlur node applies a simple blurring effect to images using a specified horizontal and vertical size. This node is designed to soften images, reducing detail and noise by averaging the pixels within the defined kernel size.

Input types

Required

• images
  • The input images to be blurred. This parameter is crucial for defining the source images on which the blur effect will be applied.
  • Comfy dtype: IMAGE
  • Python dtype: torch.Tensor
• size_x
  • Specifies the horizontal size of the blur kernel. This size influences the extent of blurring in the horizontal direction.
  • Comfy dtype: INT
  • Python dtype: int
• size_y
  • Specifies the vertical size of the blur kernel. This size influences the extent of blurring in the vertical direction.
  • Comfy dtype: INT
  • Python dtype: int

Output types

• image
  • Comfy dtype: IMAGE
  • The output images after applying the blur effect. This shows the result of the blurring process on the input images.
  • Python dtype: torch.Tensor

Usage tips

• Infra type: GPU
• Common nodes: unknown

Source code

class ImageFilterBlur:
    def __init__(self):
        pass

    @classmethod
    def INPUT_TYPES(cls):
        return {
            "required": {
                "images": ("IMAGE",),
                "size_x": ("INT", {
                    "default": 10,
                    "min": 1,
                }),
                "size_y": ("INT", {
                    "default": 10,
                    "min": 1,
                }),
            },
        }

    RETURN_TYPES = ("IMAGE",)
    FUNCTION = "node"
    CATEGORY = "image/filter"

    def node(self, images, size_x, size_y):
        return (cv2_layer(images, lambda x: cv2.blur(x, (size_x, size_y))),)