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Batch Images

Documentation

  • Class name: ImageBatch
  • Category: image
  • Output node: False

The ImageBatch node is designed for combining two images into a single batch. If the dimensions of the images do not match, it automatically rescales the second image to match the first one's dimensions before combining them.

Input types

Required

  • image1
    • The first image to be combined into the batch. It serves as the reference for the dimensions to which the second image will be adjusted if necessary.
    • Comfy dtype: IMAGE
    • Python dtype: torch.Tensor
  • image2
    • The second image to be combined into the batch. It is automatically rescaled to match the dimensions of the first image if they differ.
    • Comfy dtype: IMAGE
    • Python dtype: torch.Tensor

Output types

  • image
    • Comfy dtype: IMAGE
    • The combined batch of images, with the second image rescaled to match the first one's dimensions if needed.
    • Python dtype: torch.Tensor

Usage tips

Source code

class ImageBatch:

    @classmethod
    def INPUT_TYPES(s):
        return {"required": { "image1": ("IMAGE",), "image2": ("IMAGE",)}}

    RETURN_TYPES = ("IMAGE",)
    FUNCTION = "batch"

    CATEGORY = "image"

    def batch(self, image1, image2):
        if image1.shape[1:] != image2.shape[1:]:
            image2 = comfy.utils.common_upscale(image2.movedim(-1,1), image1.shape[2], image1.shape[1], "bilinear", "center").movedim(1,-1)
        s = torch.cat((image1, image2), dim=0)
        return (s,)