code: def get_2d_bounding_box_iou(box1, box2):
      """Compute IoU between two 2D bounding boxes.
  
      Args:
        box1: Input tensor with shape [4] [x_min, y_min, x_max, y_max]
        box2: Input tensor with shape [4] [x_min, y_min, x_max, y_max]
  
      Returns:
        The intersection over union as a float.
      """
      x_min1, y_min1, x_max1, y_max1 = box1
      x_min2, y_min2, x_max2, y_max2 = box2
      ma = np.maximum
      mi = np.minimum
      intersection = ma(
          0, mi(x_max1, x_max2) - ma(x_min1, x_min2)
      ) * ma(0, mi(y_max1, y_max2) - ma(y_min1, y_min2))
      area1 = (x_max1 - x_min1) * (y_max1 - y_min1)
      area2 = (x_max2 - x_min2) * (y_max2 - y_min2)
      union = area1 + area2 - intersection
      print(intersection / union)
      return intersection / (union + 1e-5)
  
imports: import os
  import pickle
  from absl import logging
  import matplotlib.pyplot
  import numpy
  import tensorflow
  from tensorflow_graphics.geometry.representation import grid
  from tensorflow_graphics.math.interpolation import trilinear
  from tensorflow_graphics.projects.points_to_3Dobjects.models import centernet_utils
  from tensorflow_graphics.projects.points_to_3Dobjects.utils import tf_utils
  from google3.pyglib import gfile
  from google3.third_party.google_research.google_research.tf3d.object_detection.box_utils import np_box_ops
label_desc: Use image node_id 1 for calling a global function with example usage: get_2d_bounding_box_iou(box1, box2) and returns: unknown