Masks to Mask List

Documentation

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

The MasksToMaskList node is designed to transform a collection of individual masks into a list of masks, applying a 3D mask transformation to each mask in the process. This operation is essential for preparing mask data for further processing or analysis within a pipeline that requires masks in a standardized format.

Input types

Required

• masks
  • The 'masks' parameter represents the collection of masks to be transformed. It is crucial for the node's operation as it provides the raw data that will be processed into a standardized list format.
  • Comfy dtype: MASK
  • Python dtype: Optional[List[torch.Tensor]]

Output types

• mask
  • Comfy dtype: MASK
  • The output is a list of masks, each transformed into a 3D format, ready for further processing or analysis.
  • Python dtype: List[torch.Tensor]

Usage tips

• Infra type: CPU
• Common nodes: unknown

Source code

class MasksToMaskList:
    @classmethod
    def INPUT_TYPES(s):
        return {"required": {
                        "masks": ("MASK", ),
                      }
                }

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

    CATEGORY = "ImpactPack/Operation"

    def doit(self, masks):
        if masks is None:
            empty_mask = torch.zeros((64, 64), dtype=torch.float32, device="cpu")
            return ([empty_mask], )

        res = []

        for mask in masks:
            res.append(mask)

        print(f"mask len: {len(res)}")

        res = [make_3d_mask(x) for x in res]

        return (res, )