Bitwise(MASK - MASK)

Documentation

• Class name: SubtractMask
• Category: ImpactPack/Operation
• Output node: False

The SubtractMask node is designed to perform subtraction operations between two mask inputs, resulting in a single mask output that represents the difference between the two input masks. This operation is useful in scenarios where the removal of certain areas or features from a mask is required, effectively highlighting disparities or changes between the two masks.

Input types

Required

• mask1
  • The first mask input for the subtraction operation. It serves as the base mask from which the second mask will be subtracted.
  • Comfy dtype: MASK
  • Python dtype: torch.Tensor
• mask2
  • The second mask input for the subtraction operation. This mask is subtracted from the first mask, effectively removing its features from the first mask.
  • Comfy dtype: MASK
  • Python dtype: torch.Tensor

Output types

• mask
  • Comfy dtype: MASK
  • The resulting mask after subtracting the second mask from the first. This output highlights the differences or changes between the two input masks.
  • Python dtype: torch.Tensor

Usage tips

• Infra type: CPU
• Common nodes: unknown

Source code

class SubtractMask:
    @classmethod
    def INPUT_TYPES(s):
        return {"required": {
                        "mask1": ("MASK", ),
                        "mask2": ("MASK", ),
                      }
                }

    RETURN_TYPES = ("MASK",)
    FUNCTION = "doit"

    CATEGORY = "ImpactPack/Operation"

    def doit(self, mask1, mask2):
        mask = subtract_masks(mask1, mask2)
        return (mask,)