RepeatImageBatch

Documentation

Class name: RepeatImageBatch
Category: image/batch
Output node: False

The RepeatImageBatch node is designed to duplicate a given image a specified number of times, creating a batch of identical images. This functionality is essential for operations that require multiple instances of the same image for batch processing or augmentation purposes.

Input types

Required

image
- The 'image' parameter represents the image to be duplicated. It is crucial for determining the content of the output batch.
- Comfy dtype: IMAGE
- Python dtype: torch.Tensor
amount
- The 'amount' parameter specifies the number of times the input image should be repeated. It directly influences the size of the output batch.
- Comfy dtype: INT
- Python dtype: int

Output types

image
- Comfy dtype: IMAGE
- The output is a batch of images, each identical to the input image, repeated the specified number of times.
- Python dtype: torch.Tensor

Usage tips

Infra type: GPU
Common nodes: unknown

Source code

class RepeatImageBatch:
    @classmethod
    def INPUT_TYPES(s):
        return {"required": { "image": ("IMAGE",),
                              "amount": ("INT", {"default": 1, "min": 1, "max": 4096}),
                              }}
    RETURN_TYPES = ("IMAGE",)
    FUNCTION = "repeat"

    CATEGORY = "image/batch"

    def repeat(self, image, amount):
        s = image.repeat((amount, 1,1,1))
        return (s,)

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