ImageFilterMin

Documentation

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

The ImageFilterMin node applies a minimum filter to images, effectively enhancing dark areas and potentially reducing noise. This filter selects the minimum pixel value in a neighborhood defined by the filter size, making it useful for image processing tasks where reducing high-frequency noise or emphasizing darker regions is desired.

Input types

Required

• images
  • Specifies the images to be processed. This parameter is crucial as it determines the input on which the minimum filter will be applied, directly affecting the output.
  • Comfy dtype: IMAGE
  • Python dtype: torch.Tensor
• size
  • Defines the size of the neighborhood around each pixel to consider for the minimum filter. A larger size can lead to more pronounced smoothing and noise reduction effects.
  • Comfy dtype: INT
  • Python dtype: int

Output types

• image
  • Comfy dtype: IMAGE
  • The processed images after applying the minimum filter, which emphasizes darker areas and reduces noise.
  • Python dtype: torch.Tensor

Usage tips

• Infra type: GPU
• Common nodes: unknown

Source code

class ImageFilterMin:
    def __init__(self):
        pass

    @classmethod
    def INPUT_TYPES(cls):
        return {
            "required": {
                "images": ("IMAGE",),
                "size": ("INT", {
                    "default": 2,
                    "min": 0,
                    "step": 2
                }),
            },
        }

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

    def node(self, images, size):
        return applyImageFilter(images, ImageFilter.MinFilter(int(size) + 1))