ImageColorToMask

Documentation

• Class name: ImageColorToMask
• Category: mask
• Output node: False

The ImageColorToMask node is designed to convert a specified color in an image to a mask. It processes an image and a target color, generating a mask where the specified color is highlighted, facilitating operations like color-based segmentation or object isolation.

Input types

Required

• image
  • The 'image' parameter represents the input image to be processed. It is crucial for determining the areas of the image that match the specified color to be converted into a mask.
  • Comfy dtype: IMAGE
  • Python dtype: torch.Tensor
• color
  • The 'color' parameter specifies the target color in the image to be converted into a mask. It plays a key role in identifying the specific color areas to be highlighted in the resulting mask.
  • Comfy dtype: INT
  • Python dtype: int

Output types

• mask
  • Comfy dtype: MASK
  • The output is a mask highlighting the areas of the input image that match the specified color. This mask can be used for further image processing tasks, such as segmentation or object isolation.
  • Python dtype: torch.Tensor

Usage tips

• Infra type: GPU
• Common nodes: unknown

Source code

class ImageColorToMask:
    @classmethod
    def INPUT_TYPES(s):
        return {
                "required": {
                    "image": ("IMAGE",),
                    "color": ("INT", {"default": 0, "min": 0, "max": 0xFFFFFF, "step": 1, "display": "color"}),
                }
        }

    CATEGORY = "mask"

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

    def image_to_mask(self, image, color):
        temp = (torch.clamp(image, 0, 1.0) * 255.0).round().to(torch.int)
        temp = torch.bitwise_left_shift(temp[:,:,:,0], 16) + torch.bitwise_left_shift(temp[:,:,:,1], 8) + temp[:,:,:,2]
        mask = torch.where(temp == color, 255, 0).float()
        return (mask,)