diff --git a/deploy/pdserving/ocr_reader.py b/deploy/pdserving/ocr_reader.py
index 75f0f3d5c3aea488f82ec01a72e20310663d565b..d488cc0920391eded6c08945597b5c938b7c7a42 100644
--- a/deploy/pdserving/ocr_reader.py
+++ b/deploy/pdserving/ocr_reader.py
@@ -339,7 +339,7 @@ class CharacterOps(object):
 class OCRReader(object):
     def __init__(self,
                  algorithm="CRNN",
-                 image_shape=[3, 32, 320],
+                 image_shape=[3, 48, 320],
                  char_type="ch",
                  batch_num=1,
                  char_dict_path="./ppocr_keys_v1.txt"):
@@ -356,7 +356,7 @@ class OCRReader(object):
     def resize_norm_img(self, img, max_wh_ratio):
         imgC, imgH, imgW = self.rec_image_shape
         if self.character_type == "ch":
-            imgW = int(32 * max_wh_ratio)
+            imgW = int(imgH * max_wh_ratio)
         h = img.shape[0]
         w = img.shape[1]
         ratio = w / float(h)
@@ -377,7 +377,7 @@ class OCRReader(object):
     def preprocess(self, img_list):
         img_num = len(img_list)
         norm_img_batch = []
-        max_wh_ratio = 0
+        max_wh_ratio = 320/48.
         for ino in range(img_num):
             h, w = img_list[ino].shape[0:2]
             wh_ratio = w * 1.0 / h
diff --git a/deploy/pdserving/web_service.py b/deploy/pdserving/web_service.py
index f05806ce030238144568a3ca137798a9132027e4..d8491dc572fa2c5c4186a426ce689254d312cb45 100644
--- a/deploy/pdserving/web_service.py
+++ b/deploy/pdserving/web_service.py
@@ -63,7 +63,6 @@ class DetOp(Op):
         dt_boxes_list = self.post_func(det_out, [ratio_list])
         dt_boxes = self.filter_func(dt_boxes_list[0], [self.ori_h, self.ori_w])
         out_dict = {"dt_boxes": dt_boxes, "image": self.raw_im}
-
         return out_dict, None, ""
 
 
@@ -86,7 +85,7 @@ class RecOp(Op):
         dt_boxes = copy.deepcopy(self.dt_list)
         feed_list = []
         img_list = []
-        max_wh_ratio = 0
+        max_wh_ratio = 320/48.
         ## Many mini-batchs, the type of feed_data is list.
         max_batch_size = 6  # len(dt_boxes)
 
@@ -150,7 +149,8 @@ class RecOp(Op):
         for i in range(dt_num):
             text = rec_list[i]
             dt_box = self.dt_list[i]
-            result_list.append([text, dt_box.tolist()])
+            if text[1] >= 0.5:
+                result_list.append([text, dt_box.tolist()])
         res = {"result": str(result_list)}
         return res, None, ""