Get Mask Size & Count

Documentation

• Class name: GetMaskSizeAndCount
• Category: KJNodes/masking
• Output node: False

This node is designed to analyze the dimensions and batch size of a given mask, returning its width, height, and count while passing the mask through unchanged. It serves as a utility for understanding and processing mask dimensions within a workflow.

Input types

Required

• mask
  • The mask input is crucial for determining the dimensions and batch size of the mask. It directly influences the node's output by providing the necessary data for calculation.
  • Comfy dtype: MASK
  • Python dtype: torch.Tensor

Output types

• mask
  • Comfy dtype: MASK
  • The original mask passed through unchanged, facilitating further processing or analysis.
  • Python dtype: torch.Tensor
• width
  • Comfy dtype: INT
  • The width of the mask, providing insight into its dimensions.
  • Python dtype: int
• height
  • Comfy dtype: INT
  • The height of the mask, offering information on its size.
  • Python dtype: int
• count
  • Comfy dtype: INT
  • The batch size of the mask, indicating how many masks are processed.
  • Python dtype: int
• ui
  • A textual representation of the mask's dimensions and count, enhancing readability and understanding.

Usage tips

• Infra type: CPU
• Common nodes: unknown

Source code

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

    RETURN_TYPES = ("MASK","INT", "INT", "INT",)
    RETURN_NAMES = ("mask", "width", "height", "count",)
    FUNCTION = "getsize"
    CATEGORY = "KJNodes/masking"
    DESCRIPTION = """
Returns the width, height and batch size of the mask,  
and passes it through unchanged.  

"""

    def getsize(self, mask):
        width = mask.shape[2]
        height = mask.shape[1]
        count = mask.shape[0]
        return {"ui": {
            "text": [f"{count}x{width}x{height}"]}, 
            "result": (mask, width, height, count) 
        }