class_docstr: BoxIOU.
code: def __init__(self, t=0.5, threed=False):
      self.labeled_boxes = {}
      self.predicted_boxes = {}
      self.threshold = t
      self.threed = threed
      self.get_iou_func = get_2d_bounding_box_iou
      if self.threed:
          self.get_iou_func = get_3d_bounding_box_iou
  
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 to create a new BoxIoUMetric object  with example: obj = BoxIoUMetric(t, threed)