code: def interpret_output(self, batch_output):
      if self.is_training:
          return True
      return self.output_decoder.decode_batch(
          {"window_resampled": batch_output["resampled_moving_image"]},
          batch_output["locations"],
      )
  
imports: from __future__ import absolute_import, division, print_function
  import tensorflow
  from niftynet.application.base_application import BaseApplication
  from niftynet.io.image_reader import ImageReader
  from niftynet.contrib.sampler_pairwise.sampler_pairwise_uniform import PairwiseUniformSampler
  from niftynet.contrib.sampler_pairwise.sampler_pairwise_resize import PairwiseResizeSampler
  from niftynet.engine.application_factory import OptimiserFactory, ApplicationNetFactory
  from niftynet.engine.application_variables import NETWORK_OUTPUT, CONSOLE, TF_SUMMARIES
  from niftynet.engine.windows_aggregator_resize import ResizeSamplesAggregator
  from niftynet.layer.resampler import ResamplerLayer
  from niftynet.layer.pad import PadLayer
  from niftynet.layer.loss_segmentation import LossFunction
label_desc: Use image node_id 6 for calling the RegApp obj's underlying member method code with example usage: obj.interpret_output(batch_output) and returns: self, True