class_docstr: This class represents the application logic for evaluating a set of
  results inferred within NiftyNet (or externally generated)
code: def __init__(self):
      self.app = None
      self.model_dir = None
      self.summary_dir = None
      self.session_prefix = None
  
      self.outputs_collector = None
      self.gradients_collector = None
  
file_path: NiftyNet/niftynet/evaluation/evaluation_application_driver.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import os
  import time
  import itertools
  import pandas
  import tensorflow
  from niftynet.engine.application_factory import ApplicationFactory
  from niftynet.io.misc_io import touch_folder
  from niftynet.io.image_sets_partitioner import ImageSetsPartitioner
label_desc: Use image node_id 1 to create a new EvaluationApplicationDriver object from inherited base classes: object with example: obj = EvaluationApplicationDriver()