  
                  if score < min_score:
                      min_score = score
                      j_min_score = j
              img_list[i + 1] = img_list[j_min_score]
              img_list[j_min_score] = img_list[i + 1]
  
          return img_list
  
      def sort_face_cnn_dissim(self):
          input_dir = self.args.input_dir
  
 
</s> remove             img_list[i + 1] = img_list[j_min_score]
            img_list[j_min_score] = img_list[i + 1]

 </s> add             (img_list[i + 1],
             img_list[j_min_score]) = (img_list[j_min_score],
                                       img_list[i + 1]) </s> remove             img_list[i + 1] = img_list[j_min_score]
            img_list[j_min_score] = img_list[i + 1]

 </s> add             (img_list[i + 1],
             img_list[j_min_score]) = (img_list[j_min_score],
                                       img_list[i + 1]) </s> remove                 if f1encs is not None and f2encs is not None and len(
                        f1encs) > 0 and len(f2encs) > 0:
 </s> add                 if f1encs and f2encs: </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
            (img_list[i + 1],
             img_list[j_min_score]) = (img_list[j_min_score],
                                       img_list[i + 1])
  
                  if score < min_score:
                      min_score = score
                      j_min_score = j
            (img_list[i + 1],
             img_list[j_min_score]) = (img_list[j_min_score],
                                       img_list[i + 1])
            (img_list[i + 1],
             img_list[j_min_score]) = (img_list[j_min_score],
                                       img_list[i + 1])
            (img_list[i + 1],
             img_list[j_min_score]) = (img_list[j_min_score],
                                       img_list[i + 1])
          return img_list
  
      def sort_face_cnn_dissim(self):
          input_dir = self.args.input_dir
  
keep keep keep keep replace replace replace keep keep keep keep keep
 Sort tool bugfixes and linting 
tools/sort.py