code: def xywh2xyxy(x: torch.Tensor | NDArray[t.Any]):
      # Convert nx4 boxes from [x, y, w, h] to [x1, y1, x2, y2] where xy1=top-left, xy2=bottom-right
      y = x.clone() if isinstance(x, torch.Tensor) else np.copy(x)
      y[..., 0] = x[..., 0] - x[..., 2] / 2  # top left x
      y[..., 1] = x[..., 1] - x[..., 3] / 2  # top left y
      y[..., 2] = x[..., 0] + x[..., 2] / 2  # bottom right x
      y[..., 3] = x[..., 1] + x[..., 3] / 2  # bottom right y
      return y
  
imports: from __future__ import annotations
  import json
  import os
  import time
  import typing
  from pathlib import Path
  import attr
  import cv2
  import numpy
  import torch
  import torchvision
  from PIL import Image
label_desc: Use image node_id 7 for calling a global function with example usage: xywh2xyxy(x) and returns: y