diff --git a/tools/infer/utility.py b/tools/infer/utility.py
index 1bb34990f2000e7294f8ecbda7da2fb6f19b3336..72b19b9198163751423f5b34880ddc0acc6fbbdf 100755
--- a/tools/infer/utility.py
+++ b/tools/infer/utility.py
@@ -84,19 +84,29 @@ def parse_args():
 
     parser.add_argument("--enable_mkldnn", type=str2bool, default=False)
     parser.add_argument("--use_zero_copy_run", type=str2bool, default=False)
-    
+
     parser.add_argument("--use_pdserving", type=str2bool, default=False)
-    
+
     return parser.parse_args()
 
 
 def create_predictor(args, mode):
+    """
+    create predictor for inference
+    :param args: params for prediction engine
+    :param mode: mode
+    :return: predictor
+    """
     if mode == "det":
         model_dir = args.det_model_dir
     elif mode == 'cls':
         model_dir = args.cls_model_dir
-    else:
+    elif mode == 'rec':
         model_dir = args.rec_model_dir
+    else:
+        raise ValueError(
+            "'mode' of create_predictor() can only be one of ['det', 'cls', 'rec']"
+        )
 
     if model_dir is None:
         logger.info("not find {} model file path {}".format(mode, model_dir))
@@ -144,6 +154,12 @@ def create_predictor(args, mode):
 
 
 def draw_text_det_res(dt_boxes, img_path):
+    """
+    Visualize the results of detection
+    :param dt_boxes: The boxes predicted by detection model
+    :param img_path: Image path
+    :return: Visualized image
+    """
     src_im = cv2.imread(img_path)
     for box in dt_boxes:
         box = np.array(box).astype(np.int32).reshape(-1, 2)