code: def scale_boxes(
      boxes: Tensor, image_size: torch.Size, new_size: torch.Size
  ) -> Tensor:
      """Scale bbox coordinates to a new image size.
  
      Args:
          boxes (Tensor): Boxes of shape (N, 4) - (x1, y1, x2, y2).
          image_size (Size): Size of the original image in which the bbox coordinates were retrieved.
          new_size (Size): New image size to which the bbox coordinates will be scaled.
  
      Returns:
          Tensor: Updated boxes of shape (N, 4) - (x1, y1, x2, y2).
      """
      scale = Tensor([*new_size]) / Tensor([*image_size])
      return boxes * scale.repeat(2).to(boxes.device)
  
file_path: anomalib/src/anomalib/data/utils/boxes.py
imports: from __future__ import annotations
  import torch
  from torch import Tensor
  from anomalib.utils.cv import connected_components_cpu, connected_components_gpu
label_desc: Use image node_id 4 for calling a global function with example usage: scale_boxes(boxes, image_size, new_size) and returns: unknown