class_docstr: Evaluator for specified metrics.
docstr: Runs metrics over provided pairs and returns metric dict.
docstr_tok: ["Runs","metrics","over","provided","pairs","and","returns","metric","dict","."]
code: def evaluate(self):
      """Runs metrics over provided pairs and returns metric dict."""
      metrics = {}
      for name, metric in self.metrics.items():
          metrics[name] = metric.evaluate()
      return metrics
  
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 Evaluator obj's underlying member method code with example usage: obj.evaluate() and returns: metrics