          return sum(scores) / len(scores)
  
      @staticmethod
      def get_avg_score_faces_cnn(fl1, references):
          scores = []
          for fl2 in references:
              score = np.sum(np.absolute((fl2 - fl1).flatten()))
              scores.append(score)
 
</s> remove 
            return renaming
 </s> add         return renaming </s> remove     def calc_landmarks_face_pitch(fl):  # unused
        t = ((fl[6][1] - fl[8][1]) + (fl[10][1] - fl[8][1])) / 2.0
        b = fl[8][1]
        return b - t
 </s> add     def calc_landmarks_face_pitch(flm):
        """ UNUSED - Calculate the amount of pitch in a face """
        var_t = ((flm[6][1] - flm[8][1]) + (flm[10][1] - flm[8][1])) / 2.0
        var_b = flm[8][1]
        return var_b - var_t </s> remove     def calc_landmarks_face_yaw(fl):
        var_l = ((fl[27][0] - fl[0][0])
                 + (fl[28][0] - fl[1][0])
                 + (fl[29][0] - fl[2][0])) / 3.0
        var_r = ((fl[16][0] - fl[27][0])
                 + (fl[15][0] - fl[28][0])
                 + (fl[14][0] - fl[29][0])) / 3.0
 </s> add     def calc_landmarks_face_yaw(flm):
        """ Calculate the amount of yaw in a face """
        var_l = ((flm[27][0] - flm[0][0])
                 + (flm[28][0] - flm[1][0])
                 + (flm[29][0] - flm[2][0])) / 3.0
        var_r = ((flm[16][0] - flm[27][0])
                 + (flm[15][0] - flm[28][0])
                 + (flm[14][0] - flm[29][0])) / 3.0
        """ Return the average dlib CNN similarity score
            between a face and reference image """
          return sum(scores) / len(scores)
  
      @staticmethod
      def get_avg_score_faces_cnn(fl1, references):
        """ Return the average dlib CNN similarity score
            between a face and reference image """
          scores = []
          for fl2 in references:
              score = np.sum(np.absolute((fl2 - fl1).flatten()))
              scores.append(score)
keep keep keep add keep keep keep keep
 Sort tool bugfixes and linting 
tools/sort.py