diff --git a/configs/rec/rec_r45_visionlan.yml b/configs/rec/rec_r45_visionlan.yml
index 4c3fb4a80b8e5b73cdb05c30054fda6420470801..f3a3661f5344f3c48b4948fb1037d185b94ad376 100644
--- a/configs/rec/rec_r45_visionlan.yml
+++ b/configs/rec/rec_r45_visionlan.yml
@@ -3,12 +3,12 @@ Global:
   epoch_num: 8
   log_smooth_window: 200
   print_batch_step: 200
-  save_model_dir: /paddle/backup/visionlan/LA_v2
+  save_model_dir: ./output/rec/r45_visionlan
   save_epoch_step: 1
   # evaluation is run every 2000 iterations
   eval_batch_step: [0, 2000]
   cal_metric_during_train: True
-  pretrained_model: ./pretrained_model/LF_2_ocr
+  pretrained_model:
   checkpoints: 
   save_inference_dir:
   use_visualdl: True
diff --git a/tools/infer/predict_rec.py b/tools/infer/predict_rec.py
index 2b92430623586724ebe82e346445998529752501..1da9f2572258e08e76b855d0ed9402fbc331ae86 100755
--- a/tools/infer/predict_rec.py
+++ b/tools/infer/predict_rec.py
@@ -157,17 +157,6 @@ class TextRecognizer(object):
         padding_im[:, :, 0:resized_w] = resized_image
         return padding_im
 
-    def resize_norm_img_svtr(self, img, image_shape):
-
-        imgC, imgH, imgW = image_shape
-        resized_image = cv2.resize(
-            img, (imgW, imgH), interpolation=cv2.INTER_LINEAR)
-        resized_image = resized_image.astype('float32')
-        resized_image = resized_image.transpose((2, 0, 1)) / 255
-        resized_image -= 0.5
-        resized_image /= 0.5
-        return resized_image
-
     def resize_norm_img_vl(self, img, image_shape):
 
         imgC, imgH, imgW = image_shape