Get Images From Batch Indexed

Documentation

• Class name: GetImagesFromBatchIndexed
• Category: KJNodes/image
• Output node: False

This node is designed to select and return specific images from a given batch based on the provided indices. It allows for the dynamic extraction of a subset of images from a larger collection, facilitating operations that require targeted manipulation or analysis of image batches.

Input types

Required

• images
  • Represents the batch of images from which specific items will be selected. It is crucial for determining the scope of images available for extraction.
  • Comfy dtype: IMAGE
  • Python dtype: torch.Tensor
• indexes
  • A string of comma-separated indices indicating which images to extract from the batch. This parameter directly influences which images are selected and returned.
  • Comfy dtype: STRING
  • Python dtype: str

Output types

• image
  • Comfy dtype: IMAGE
  • The output is a subset of images selected from the input batch based on the specified indices.
  • Python dtype: torch.Tensor

Usage tips

• Infra type: GPU
• Common nodes: unknown

Source code

class GetImagesFromBatchIndexed:

    RETURN_TYPES = ("IMAGE",)
    FUNCTION = "indexedimagesfrombatch"
    CATEGORY = "KJNodes/image"
    DESCRIPTION = """
Selects and returns the images at the specified indices as an image batch.
"""

    @classmethod
    def INPUT_TYPES(s):
        return {
            "required": {
                 "images": ("IMAGE",),
                 "indexes": ("STRING", {"default": "0, 1, 2", "multiline": True}),
        },
    } 

    def indexedimagesfrombatch(self, images, indexes):

        # Parse the indexes string into a list of integers
        index_list = [int(index.strip()) for index in indexes.split(',')]

        # Convert list of indices to a PyTorch tensor
        indices_tensor = torch.tensor(index_list, dtype=torch.long)

        # Select the images at the specified indices
        chosen_images = images[indices_tensor]

        return (chosen_images,)