Masks Combine Batch

Documentation

• Class name: Masks Combine Batch
• Category: WAS Suite/Image/Masking
• Output node: False

This node is designed to combine multiple mask tensors into a single mask tensor by summing them up. It ensures that the resulting mask values are clamped between 0 and 1, maintaining the integrity of mask data.

Input types

Required

• masks
  • The 'masks' input consists of a batch of mask tensors to be combined. It plays a crucial role in the node's operation by providing the raw data that will be processed into a single, unified mask.
  • Comfy dtype: MASK
  • Python dtype: List[torch.Tensor]

Output types

• mask
  • Comfy dtype: MASK
  • The output is a single mask tensor that represents the combined effect of the input masks, with values clamped between 0 and 1.
  • Python dtype: torch.Tensor

Usage tips

• Infra type: GPU
• Common nodes: unknown

Source code

class WAS_Mask_Combine_Batch:

    def __init__(self):
        self.WT = WAS_Tools_Class()

    @classmethod
    def INPUT_TYPES(cls):
        return {
                    "required": {
                        "masks": ("MASK",),
                    },
                }

    CATEGORY = "WAS Suite/Image/Masking"

    RETURN_TYPES = ("MASK",)

    FUNCTION = "combine_masks"

    def combine_masks(self, masks):
        combined_mask = torch.sum(torch.stack([mask.unsqueeze(0) for mask in masks], dim=0), dim=0)
        combined_mask = torch.clamp(combined_mask, 0, 1)  # Ensure values are between 0 and 1
        return (combined_mask, )