🔧 Mask Smooth

Documentation

• Class name: MaskSmooth+
• Category: essentials
• Output node: False

The MaskSmooth node is designed to apply a Gaussian blur to a given mask, with the intensity of the blur adjustable by the user. This process smooths the edges of the mask, creating a more visually appealing and less jagged appearance.

Input types

Required

• mask
  • The mask input represents the binary or grayscale image to which the Gaussian blur will be applied. It is central to achieving the smoothing effect.
  • Comfy dtype: MASK
  • Python dtype: torch.Tensor
• amount
  • The amount parameter controls the intensity of the Gaussian blur applied to the mask. A higher value results in a more pronounced smoothing effect.
  • Comfy dtype: INT
  • Python dtype: int

Output types

• mask
  • Comfy dtype: MASK
  • The output is a modified version of the input mask, having undergone Gaussian blurring to smooth its edges.
  • Python dtype: torch.Tensor

Usage tips

• Infra type: CPU
• Common nodes: unknown

Source code

class MaskSmooth:
    @classmethod
    def INPUT_TYPES(s):
        return {
            "required": {
                "mask": ("MASK",),
                "amount": ("INT", { "default": 0, "min": 0, "max": 127, "step": 1, }),
            }
        }

    RETURN_TYPES = ("MASK",)
    FUNCTION = "execute"
    CATEGORY = "essentials"

    def execute(self, mask, amount):
        if amount == 0:
            return (mask,)

        if amount % 2 == 0:
            amount += 1

        mask = mask > 0.5
        mask = T.functional.gaussian_blur(mask.unsqueeze(1), amount).squeeze(1).float()

        return (mask,)