code: def predict(self, image_file):
          
          image = misc.imread(image_file)
          gray_image = image
          if len(image.shape) > 2:
              gray_image = cv2.cvtColor(image, code=cv2.COLOR_BGR2GRAY)
          resized_image = cv2.resize(gray_image, self.target_dimensions, interpolation=cv2.INTER_LINEAR)
          final_image = np.array([np.array([resized_image]).reshape(list(self.target_dimensions)+[self.channels])])
          prediction = self.model.predict(final_image)
          # Return the dominant expression
          dominant_expression = self._print_prediction(prediction[0])
          return dominant_expression
docs: Predicts discrete emotion for given image.
  
          :param images: image file (jpg or png format)