code: def xywh2xyxy(x: np.ndarray):
      # Convert nx4 boxes from [x, y, w, h] to [x1, y1, x2, y2] where xy1=top-left, xy2=bottom-right
      y = np.zeros_like(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
  
file_path: deep-learning-for-image-processing/pytorch_object_detection/yolov3_spp/load_onnx_test.py
imports: import time
  import cv2
  import onnx
  import onnxruntime
  import numpy
  from matplotlib import pyplot
  from draw_box_utils import draw_box
label_desc: Use image node_id 5 for calling a global function with example usage: xywh2xyxy(x) and returns: y