new_contents: import argparse
  import json
  import tensorflow as tf
  
  from aovek.preprocess.download_dataset import download_dataset
  from aovek.preprocess.data_processing import DataProcessing
  from aovek.training.train import Train
  from aovek.visualization.predict import Predict
  from aovek.validate.eval_metrics import EvalMetrics
  
  parser = argparse.ArgumentParser(description='4ovek')
  parser._action_groups.pop()
  
  required = parser.add_argument_group('required arguments')
  optional = parser.add_argument_group('optional arguments')
  
  optional.add_argument('-dataset_download', help='Download dataset.',
                        action='store_true')
  optional.add_argument('-processes_dataset', help='Processes dataset.',
                        action='store_true')
  optional.add_argument('-train', help='Train convolutional neural network.',
                        action='store_true')
  optional.add_argument('-predict', help='Make predictions for entire dataset.',
                        action='store_true')
  optional.add_argument('-evaluate', help='Evaluate trained model.',
                        action='store_true')
  
  required.add_argument('-config_file', help='Path to config file.',
                        required=True)
  
  
  def dataset_download(config):
      download_dataset(config)
  
  
  def processes_dataset(config):
      dp = DataProcessing(config)
      dp.set_normalizer(1)
      dp.pickle_dataset()
  
      print('Taken time: {}'.format(str(dp.get_time())))
  
  
  def train(config):
      config['network']['model_binary_data_file'] = './model/54/model.h5'
      config['network']['json_model_structure'] = './model/54/model.json'
  
      train = Train(config)
  
  
  def predict(config):
      with tf.Session():
          predict = Predict(config)
  
          predict.make_predictions_for_optimizers()
  
  
  def evaluate(config):
      with tf.Session():
          eval_metrics = EvalMetrics(config)
          eval_metrics.eval_pickles_metrics()
  
  
  if __name__ == '__main__':
      args = parser.parse_args()
  
      config_file = args.config_file
  
      with open(config_file) as c_f:
          config = json.load(c_f)
  
      if args.dataset_download:
          dataset_download(config)
      elif args.processes_dataset:
          processes_dataset(config)
      elif args.train:
          train(config)
      elif args.predict:
          predict(config)
      elif args.evaluate:
          evaluate(config)
  
subject: Add file for control person detection