ImageBatchRemove

Documentation

• Class name: ImageBatchRemove
• Category: image/batch
• Output node: False

The ImageBatchRemove node is designed for selectively removing an image from a batch based on its index. This functionality is crucial for operations where specific images need to be excluded from further processing, thereby enabling dynamic manipulation of image collections.

Input types

Required

• images
  • The 'images' parameter represents the batch of images from which one will be removed. It is essential for specifying the group of images subject to modification.
  • Comfy dtype: IMAGE
  • Python dtype: torch.Tensor
• index
  • The 'index' parameter determines the position of the image to be removed from the batch. It plays a critical role in identifying the specific image to exclude, ensuring precise manipulation of the image collection.
  • Comfy dtype: INT
  • Python dtype: int

Output types

• image
  • Comfy dtype: IMAGE
  • Returns a new batch of images with the specified image removed, facilitating the dynamic adjustment of image collections.
  • Python dtype: torch.Tensor

Usage tips

• Infra type: GPU
• Common nodes: unknown

Source code

class ImageBatchRemove:
    def __init__(self):
        pass

    @classmethod
    def INPUT_TYPES(cls):
        return {
            "required": {
                "images": ("IMAGE",),
                "index": ("INT", {
                    "default": 1,
                    "min": 1,
                    "step": 1
                }),
            },
        }

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

    def node(self, images, index):
        batch = images.shape[0]
        index = min(batch, index - 1)

        return (torch.cat((images[:index], images[index + 1:]), dim=0),)