class_docstr: IoU metric.
docstr: Evaluate.
docstr_tok: ["Evaluate","."]
code: def evaluate(self):
      """Evaluate."""
      if self.slave:
          data = self.iou_per_class
          with gfile.Open(self.path, "wb") as file:
              pickle.dump(data, file)
          logging.info(file)
          return
      else:
          iou_per_class_means = []
          for _, v in self.iou_per_class.items():
              if v:
                  iou_per_class_means.append(np.mean(v))
          return np.mean(iou_per_class_means)
  
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 3 for calling the IoUMetric obj's underlying member method code with example usage: obj.evaluate() and returns: np