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 detections for a single image to be used for evaluation.
  
  Args:
    image_id: A unique string/integer identifier for the image.
    detections_dict: A dictionary of detection numpy arrays required
      for evaluation.
docstr_tok: ["Adds","detections","for","a","single","image","to","be","used","for","evaluation",".","Args",":","image_id",":","A","unique","string\/integer","identifier","for","the","image",".","detections_dict",":","A","dictionary","of","detection","numpy","arrays","required","for","evaluation","."]
code: def add_single_detected_image_info(self, image_id, detections_dict):
      """Adds detections for a single image to be used for evaluation.
  
      Args:
        image_id: A unique string/integer identifier for the image.
        detections_dict: A dictionary of detection numpy arrays required
          for evaluation.
      """
      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 3 for calling the DetectionEvaluator obj's underlying member method code with example usage: obj.add_single_detected_image_info(image_id, detections_dict) without return types