Bitwise(MASK & MASK)

Documentation

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

The BitwiseAndMask node performs a bitwise AND operation between two masks, resulting in a new mask that represents the intersection of the input masks. This operation is useful for combining or filtering mask data based on overlapping regions.

Input types

Required

• mask1
  • The first input mask for the bitwise AND operation. It plays a crucial role in determining the resulting mask by intersecting its content with the second mask.
  • Comfy dtype: MASK
  • Python dtype: torch.Tensor
• mask2
  • The second input mask for the bitwise AND operation. It intersects with the first mask to produce the resulting mask that highlights the overlapping areas.
  • Comfy dtype: MASK
  • Python dtype: torch.Tensor

Output types

• mask
  • Comfy dtype: MASK
  • The output mask resulting from the bitwise AND operation between the two input masks, highlighting the areas where both masks overlap.
  • Python dtype: torch.Tensor

Usage tips

• Infra type: CPU
• Common nodes: unknown

Source code

class BitwiseAndMask:
    @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 = bitwise_and_masks(mask1, mask2)
        return (mask,)