code: def wh_iou(wh1, wh2):
      # Returns the nxm IoU matrix. wh1 is nx2, wh2 is mx2
      wh1 = wh1[:, None]  # [N,1,2]
      wh2 = wh2[None]  # [1,M,2]
      inter = torch.min(wh1, wh2).prod(2)  # [N,M]
      return inter / (wh1.prod(2) + wh2.prod(2) - inter)
  
imports: import glob
  import math
  import os
  import random
  import time
  import cv2
  import matplotlib
  import numpy
  import torch
  import torch.nn
  import torchvision
  from tqdm import tqdm
  from build_utils import torch_utils
label_desc: Use image node_id 9 for calling a global function with example usage: wh_iou(wh1, wh2) and returns: unknown