diff --git a/deploy/cpp_infer/docs/windows_vs2019_build.md b/deploy/cpp_infer/docs/windows_vs2019_build.md
index bcaefa46f83a30a4c232add78dc2e9f521b9f84f..2f5c5818d7d977c78c15e29d7c1bbebd98ce99bf 100644
--- a/deploy/cpp_infer/docs/windows_vs2019_build.md
+++ b/deploy/cpp_infer/docs/windows_vs2019_build.md
@@ -121,7 +121,7 @@ CUDA_LIB、CUDNN_LIB、TENSORRT_DIR、WITH_GPU、WITH_TENSORRT
 ```
 cd /d D:\projects\cpp\PaddleOCR\deploy\cpp_infer
 ```
-可执行文件`ppocr.exe`即为样例的预测程序，其主要使用方法如下，更多使用方法可以参考[说明文档](../readme.md)`运行demo`部分。
+可执行文件`ppocr.exe`即为样例的预测程序，其主要使用方法如下，更多使用方法可以参考[说明文档](../readme_ch.md)`运行demo`部分。
 
 ```shell
 # 切换终端编码为utf8
diff --git a/ppocr/postprocess/db_postprocess.py b/ppocr/postprocess/db_postprocess.py
index dfe107816c195b36bf06568843b008bf66ff24c7..244825b76a47162419b4ae68103b182331be1791 100755
--- a/ppocr/postprocess/db_postprocess.py
+++ b/ppocr/postprocess/db_postprocess.py
@@ -144,9 +144,9 @@ class DBPostProcess(object):
                 np.round(box[:, 0] / width * dest_width), 0, dest_width)
             box[:, 1] = np.clip(
                 np.round(box[:, 1] / height * dest_height), 0, dest_height)
-            boxes.append(box.astype(np.int16))
+            boxes.append(box.astype("int32"))
             scores.append(score)
-        return np.array(boxes, dtype=np.int16), scores
+        return np.array(boxes, dtype="int32"), scores
 
     def unclip(self, box, unclip_ratio):
         poly = Polygon(box)
@@ -185,15 +185,15 @@ class DBPostProcess(object):
         '''
         h, w = bitmap.shape[:2]
         box = _box.copy()
-        xmin = np.clip(np.floor(box[:, 0].min()).astype(np.int), 0, w - 1)
-        xmax = np.clip(np.ceil(box[:, 0].max()).astype(np.int), 0, w - 1)
-        ymin = np.clip(np.floor(box[:, 1].min()).astype(np.int), 0, h - 1)
-        ymax = np.clip(np.ceil(box[:, 1].max()).astype(np.int), 0, h - 1)
+        xmin = np.clip(np.floor(box[:, 0].min()).astype("int32"), 0, w - 1)
+        xmax = np.clip(np.ceil(box[:, 0].max()).astype("int32"), 0, w - 1)
+        ymin = np.clip(np.floor(box[:, 1].min()).astype("int32"), 0, h - 1)
+        ymax = np.clip(np.ceil(box[:, 1].max()).astype("int32"), 0, h - 1)
 
         mask = np.zeros((ymax - ymin + 1, xmax - xmin + 1), dtype=np.uint8)
         box[:, 0] = box[:, 0] - xmin
         box[:, 1] = box[:, 1] - ymin
-        cv2.fillPoly(mask, box.reshape(1, -1, 2).astype(np.int32), 1)
+        cv2.fillPoly(mask, box.reshape(1, -1, 2).astype("int32"), 1)
         return cv2.mean(bitmap[ymin:ymax + 1, xmin:xmax + 1], mask)[0]
 
     def box_score_slow(self, bitmap, contour):
@@ -214,7 +214,7 @@ class DBPostProcess(object):
         contour[:, 0] = contour[:, 0] - xmin
         contour[:, 1] = contour[:, 1] - ymin
 
-        cv2.fillPoly(mask, contour.reshape(1, -1, 2).astype(np.int32), 1)
+        cv2.fillPoly(mask, contour.reshape(1, -1, 2).astype("int32"), 1)
         return cv2.mean(bitmap[ymin:ymax + 1, xmin:xmax + 1], mask)[0]
 
     def __call__(self, outs_dict, shape_list):