class_docstr: IoU metric.
code: def __init__(
      self,
      max_num_classes=6,
      resolution=128,
      tol=0.05,
      slave=False,
      path=None,
  ):
      self.max_num_classes = max_num_classes
      self.iou_per_class = {i: [] for i in range(self.max_num_classes)}
      self.resolution = resolution
      self.slave = slave
      self.path = path
      self.tol = tol
  
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 IoUMetric object  with example: obj = IoUMetric(max_num_classes, resolution, tol, slave, path)