ImageContainer

Documentation

• Class name: ImageContainer
• Category: image/container
• Output node: False

The ImageContainer node is designed to create a container image with specified dimensions and background color. It primarily serves the purpose of generating a base image layer, which can be further manipulated or used as a background in image processing tasks.

Input types

Required

• width
  • Specifies the width of the container image to be created. It determines the horizontal dimension of the resulting image.
  • Comfy dtype: INT
  • Python dtype: int
• height
  • Specifies the height of the container image to be created. It determines the vertical dimension of the resulting image.
  • Comfy dtype: INT
  • Python dtype: int
• red
  • Defines the red component of the background color of the container image.
  • Comfy dtype: INT
  • Python dtype: int
• green
  • Defines the green component of the background color of the container image.
  • Comfy dtype: INT
  • Python dtype: int
• blue
  • Defines the blue component of the background color of the container image.
  • Comfy dtype: INT
  • Python dtype: int
• alpha
  • Specifies the opacity level of the background color of the container image.
  • Comfy dtype: FLOAT
  • Python dtype: float

Output types

• image
  • Comfy dtype: IMAGE
  • The output is a tensor representation of the container image with the specified dimensions and background color.
  • Python dtype: torch.Tensor

Usage tips

• Infra type: GPU
• Common nodes: unknown

Source code

class ImageContainer:
    def __init__(self):
        pass

    @classmethod
    def INPUT_TYPES(cls):
        return {
            "required": {
                "width": ("INT", {
                    "default": 512,
                    "min": 1,
                    "step": 1
                }),
                "height": ("INT", {
                    "default": 512,
                    "min": 1,
                    "step": 1
                }),
                "red": ("INT", {
                    "default": 255,
                    "max": 255,
                    "step": 1
                }),
                "green": ("INT", {
                    "default": 255,
                    "max": 255,
                    "step": 1
                }),
                "blue": ("INT", {
                    "default": 255,
                    "max": 255,
                    "step": 1
                }),
                "alpha": ("FLOAT", {
                    "default": 0.0,
                    "max": 1.0,
                    "step": 0.01
                }),
            },
        }

    RETURN_TYPES = ("IMAGE",)
    FUNCTION = "node"
    CATEGORY = "image/container"

    def node(self, width, height, red, green, blue, alpha):
        return (create_rgba_image(width, height, (red, green, blue, int(alpha * 255))).image_to_tensor().unsqueeze(0),)