                  input_image_bgr=cv2.imread(x),
                  detector='dlib-cnn',
                  verbose=True,
                  input_is_predetected_face=True).landmarks
              img_list.append([x, np.array(d[0][1])
                               if len(d) > 0
                               else np.zeros((68, 2)), 0])
  
          img_list_len = len(img_list)
          for i in tqdm(range(0, img_list_len - 1),
                        desc="Sorting",
 
</s> remove             img_list.append([x, np.array(d[0][1])
                             if len(d) > 0
 </s> add             img_list.append([img, np.array(landmarks[0][1])
                             if landmarks </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             [x, cv2.calcHist([cv2.imread(x)], [0], None, [256], [0, 256])]
            for x in
 </s> add             [img, cv2.calcHist([cv2.imread(img)], [0], None, [256], [0, 256])]
            for img in </s> remove         for x in tqdm(self.find_images(input_dir),
                      desc="Loading",
                      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="Loading",
                        file=sys.stdout):
            landmarks = face_alignment.Extract(
                input_image_bgr=cv2.imread(img), </s> remove         for x in tqdm(self.find_images(input_dir),
                      desc="Loading",
                      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="Loading",
                        file=sys.stdout):
            landmarks = face_alignment.Extract(
                input_image_bgr=cv2.imread(img),
            img_list.append([img, np.array(landmarks[0][1])
                             if landmarks
                  input_image_bgr=cv2.imread(x),
                  detector='dlib-cnn',
                  verbose=True,
                  input_is_predetected_face=True).landmarks
            img_list.append([img, np.array(landmarks[0][1])
                             if landmarks
            img_list.append([img, np.array(landmarks[0][1])
                             if landmarks
                               else np.zeros((68, 2)), 0])
  
          img_list_len = len(img_list)
          for i in tqdm(range(0, img_list_len - 1),
                        desc="Sorting",
keep keep keep keep replace replace keep keep keep keep keep
 Sort tool bugfixes and linting 
tools/sort.py