text: from keras.models import Sequential, model_from_json, load_model
  from keras import backend as K
  K.set_image_dim_ordering('tf')
  import sys
  import json
  import numpy as np
  import tensorflow as tf
  from Computer.NN_Trainer.Util import *
  from Computer.Autonomous.KerasNetworkModel import KerasNetworkModel
  
  class KerasSteeringAngleModel(KerasNetworkModel):
      def predict(self, img):
          '''
          :param img: size 240,320,3.
          :return: type = numpy.float32, prediction of steering angle between -10 to +10
          '''
  
          x = img.reshape((1, img.shape[0], img.shape[1], img.shape[2])) #TODO: make it more dynamic, it should reshape based on the input shape of network
          prediction = self.model.predict(x, batch_size=1, verbose=0)
          return prediction[0][0] #prediction looks something like this --> [[2.424]], so we take the [0][0]