ImageFilterMedianBlur

Documentation

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

The ImageFilterMedianBlur node applies a median blur filter to images, effectively reducing noise and smoothing the image while preserving edges. This filter is particularly useful for removing salt-and-pepper noise from images.

Input types

Required

• images
  • Specifies the images to be processed. This parameter is crucial as it determines the input on which the median blur effect will be applied.
  • Comfy dtype: IMAGE
  • Python dtype: torch.Tensor
• size
  • Defines the size of the kernel used for the median blur. A larger size will result in a more pronounced blurring effect.
  • Comfy dtype: INT
  • Python dtype: int

Output types

• image
  • Comfy dtype: IMAGE
  • Returns the images after applying the median blur filter, showcasing a smoother appearance with reduced noise.
  • Python dtype: torch.Tensor

Usage tips

• Infra type: GPU
• Common nodes: unknown

Source code

class ImageFilterMedianBlur:
    def __init__(self):
        pass

    @classmethod
    def INPUT_TYPES(cls):
        return {
            "required": {
                "images": ("IMAGE",),
                "size": ("INT", {
                    "default": 10,
                    "min": 1,
                    "step": 2
                }),
            },
        }

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

    def node(self, images, size):
        size -= 1

        img = images.clone().detach()
        img = (img * 255).to(torch.uint8)

        return ((cv2_layer(img, lambda x: cv2.medianBlur(x, size)) / 255),)