JoinImageBatch

Documentation

• Class name: easy joinImageBatch
• Category: EasyUse/Image
• Output node: False

This node is designed to merge a batch of images into a single large image, either by stacking them horizontally or vertically based on the specified mode. It abstracts the complexity of image manipulation and resizing, providing a straightforward way to create composite images from multiple inputs.

Input types

Required

• images
  • A batch of images to be joined into a single image. The importance of this parameter lies in its role as the primary input that determines the content and structure of the output image.
  • Comfy dtype: IMAGE
  • Python dtype: torch.Tensor
• mode
  • Specifies the orientation for joining images, either 'horizontal' or 'vertical'. This affects the final layout of the composite image, influencing its visual presentation and dimensions.
  • Comfy dtype: ['horizontal', 'vertical']
  • Python dtype: Tuple[str, Dict[str, Any]]

Output types

• image
  • Comfy dtype: IMAGE
  • The resulting single large image created by joining the input batch of images according to the specified mode.
  • Python dtype: torch.Tensor

Usage tips

• Infra type: GPU
• Common nodes: unknown

Source code

class JoinImageBatch:
  """Turns an image batch into one big image."""

  @classmethod
  def INPUT_TYPES(s):
    return {
      "required": {
        "images": ("IMAGE",),
        "mode": (("horizontal", "vertical"), {"default": "horizontal"}),
      },
    }

  RETURN_TYPES = ("IMAGE",)
  RETURN_NAMES = ("image",)
  FUNCTION = "join"
  CATEGORY = "EasyUse/Image"

  def join(self, images, mode):
    n, h, w, c = images.shape
    image = None
    if mode == "vertical":
      # for vertical we can just reshape
      image = images.reshape(1, n * h, w, c)
    elif mode == "horizontal":
      # for horizontal we have to swap axes
      image = torch.transpose(torch.transpose(images, 1, 2).reshape(1, n * w, h, c), 1, 2)
    return (image,)