text: 
  from tensorflow.python.keras.callbacks import TensorBoard
  from Model import Recognizer
  from PIL import Image
  import numpy as np
  import time
  import tensorflow as tf
  
  data_dimension = 48
  
  X1 = np.load( 'processed_data/x1.npy')
  X2 = np.load( 'processed_data/x2.npy')
  Y = np.load( 'processed_data/y.npy')
  
  X1 = X1.reshape( ( X1.shape[0]  , data_dimension**2 * 3  ) ).astype( np.float32 )
  X2 = X2.reshape( ( X2.shape[0]  , data_dimension**2 * 3  ) ).astype( np.float32 )
  
  print( X1.shape )
  print( X2.shape )
  print( Y.shape )
  
  recognizer = Recognizer()
  #recognizer.load_model('models/model.h5')
  
  parameters = {
      'batch_size' : 750 ,
      'epochs' : 5 ,
      'callbacks' : None , # [ TensorBoard( log_dir='logs/{}'.format( time.time() ) ) ] ,
      'val_data' : None
  }
  
  recognizer.fit( [ X1 , X2 ], Y, hyperparameters=parameters)
  recognizer.save_model('models/model.h5')
  
  print( Y[ 100 : 110 ] )
  print( recognizer.predict( [ X1[100 : 110] , X2[ 100 : 110 ] ] ))
  
  
  