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

Infra type: GPU
Common nodes:
- ImageBatch
- IPAdapterApply
- [CR Batch Process Switch](../../ComfyUI_Comfyroll_CustomNodes/Nodes/CR Batch Process Switch.md)
- PreviewImage
- [Preview Chooser](../../cg-image-picker/Nodes/Preview Chooser.md)

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,)

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