class_docstr: Interface for object detection evalution classes.
  
  Example usage of the Evaluator:
  ------------------------------
  evaluator = DetectionEvaluator(categories)
  
  # Detections and groundtruth for image 1.
  evaluator.add_single_groundtruth_image_info(...)
  evaluator.add_single_detected_image_info(...)
  
  # Detections and groundtruth for image 2.
  evaluator.add_single_groundtruth_image_info(...)
  evaluator.add_single_detected_image_info(...)
  
  metrics_dict = evaluator.evaluate()
docstr: Adds groundtruth for a single image to be used for evaluation.
  
  Args:
    image_id: A unique string/integer identifier for the image.
    groundtruth_dict: A dictionary of groundtruth numpy arrays required
      for evaluations.
docstr_tok: ["Adds","groundtruth","for","a","single","image","to","be","used","for","evaluation",".","Args",":","image_id",":","A","unique","string\/integer","identifier","for","the","image",".","groundtruth_dict",":","A","dictionary","of","groundtruth","numpy","arrays","required","for","evaluations","."]
code: def add_single_ground_truth_image_info(
      self, image_id, groundtruth_dict
  ):
      """Adds groundtruth for a single image to be used for evaluation.
  
      Args:
        image_id: A unique string/integer identifier for the image.
        groundtruth_dict: A dictionary of groundtruth numpy arrays required
          for evaluations.
      """
      pass
  
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  import collections
  import logging
  import numpy
  from abc import ABCMeta, abstractmethod
  from .None import label_map_util, metrics, per_image_evaluation, standard_fields
label_desc: Use image node_id 2 for calling the DetectionEvaluator obj's underlying member method code with example usage: obj.add_single_ground_truth_image_info(image_id, groundtruth_dict) without return types