class_docstr: Evaluator for specified metrics.
code: def __init__(self, metrics, split, shapenet_dir):
      self.metrics = metrics
      self.split = split
      self.shapenet_dir = shapenet_dir
  
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 Evaluator object  with example: obj = Evaluator(metrics, split, shapenet_dir)