          """
          input_dir = self.args.input_dir
          print("Preparing to group...")
          if group_method == 'group_blur':
              temp_list = [[x, self.estimate_blur(cv2.imread(x))]
                           for x in
                           tqdm(self.find_images(input_dir),
                                desc="Reloading",
                                file=sys.stdout)]
          elif group_method == 'group_face':
              temp_list = [[x, face_recognition.face_encodings(cv2.imread(x))]
 
</s> remove             temp_list = [[x, face_recognition.face_encodings(cv2.imread(x))]
                         for x in
                         tqdm(self.find_images(input_dir),
                              desc="Reloading",
                              file=sys.stdout)]
 </s> add             temp_list = [
                [img, face_recognition.face_encodings(cv2.imread(img))]
                for img in tqdm(self.find_images(input_dir),
                                desc="Reloading",
                                file=sys.stdout)] </s> remove             for x in tqdm(self.find_images(input_dir),
                          desc="Reloading",
                          file=sys.stdout):
                d = face_alignment.Extract(
                    input_image_bgr=cv2.imread(x),
 </s> add             for img in tqdm(self.find_images(input_dir),
                            desc="Reloading",
                            file=sys.stdout):
                landmarks = face_alignment.Extract(
                    input_image_bgr=cv2.imread(img), </s> remove                 temp_list.append([x, np.array(d[0][1])
                                  if len(d) > 0
 </s> add                 temp_list.append([img, np.array(landmarks[0][1])
                                  if landmarks </s> remove             for x in tqdm(self.find_images(input_dir),
                          desc="Reloading",
                          file=sys.stdout):
                d = face_alignment.Extract(
                    input_image_bgr=cv2.imread(x),
 </s> add             for img in tqdm(self.find_images(input_dir),
                            desc="Reloading",
                            file=sys.stdout):
                landmarks = face_alignment.Extract(
                    input_image_bgr=cv2.imread(img), </s> remove                     [x, self.calc_landmarks_face_yaw(np.array(d[0][1]))])
 </s> add                     [img,
                     self.calc_landmarks_face_yaw(np.array(landmarks[0][1]))])
            temp_list = [[img, self.estimate_blur(cv2.imread(img))]
                         for img in
          """
          input_dir = self.args.input_dir
          print("Preparing to group...")
          if group_method == 'group_blur':
            temp_list = [[img, self.estimate_blur(cv2.imread(img))]
                         for img in
            temp_list = [[img, self.estimate_blur(cv2.imread(img))]
                         for img in
                           tqdm(self.find_images(input_dir),
                                desc="Reloading",
                                file=sys.stdout)]
          elif group_method == 'group_face':
              temp_list = [[x, face_recognition.face_encodings(cv2.imread(x))]
keep keep keep keep replace replace keep keep keep keep keep
 Sort tool bugfixes and linting 
tools/sort.py