diff --git a/fluid/PaddleCV/rcnn/README.md b/fluid/PaddleCV/rcnn/README.md
index 80d389ec3e1b797b96e62dc040f34744b6fc54cb..97d1736f2b25bd6baa5ab5142be18544c9d63b85 100644
--- a/fluid/PaddleCV/rcnn/README.md
+++ b/fluid/PaddleCV/rcnn/README.md
@@ -12,7 +12,7 @@
 
 ## Installation
 
-Running sample code in this directory requires PaddelPaddle Fluid v.1.0.0 and later. If the PaddlePaddle on your device is lower than this version, please follow the instructions in [installation document](http://www.paddlepaddle.org/documentation/docs/zh/0.15.0/beginners_guide/install/install_doc.html#paddlepaddle) and make an update.
+Running sample code in this directory requires PaddelPaddle Fluid v.1.3.0 and later. If the PaddlePaddle on your device is lower than this version, please follow the instructions in [installation document](http://paddlepaddle.org/documentation/docs/en/1.3/beginners_guide/install/index_en.html) and make an update.
 
 ## Introduction
 
@@ -37,6 +37,25 @@ Train the model on [MS-COCO dataset](http://cocodataset.org/#download), download
     cd dataset/coco
     ./download.sh
 
+The data catalog structure is as follows:
+
+  ```
+  data/coco/
+  ├── annotations
+  │   ├── instances_train2014.json
+  │   ├── instances_train2017.json
+  │   ├── instances_val2014.json
+  │   ├── instances_val2017.json
+  |   ...
+  ├── train2017
+  │   ├── 000000000009.jpg
+  │   ├── 000000580008.jpg
+  |   ...
+  ├── val2017
+  │   ├── 000000000139.jpg
+  │   ├── 000000000285.jpg
+  |   ...
+  ```
 
 ## Training
 
@@ -174,7 +193,7 @@ python infer.py \
     --draw_threshold=0.6
 ```
 
-Please set the model path and image path correctly.
+Please set the model path and image path correctly. GPU device is used by default, you can set `--use_gpu=False` to switch to CPU device. And you can set `draw_threshold` to tune score threshold to control the number of output detection boxes.
 
 Visualization of infer result is shown as below:
 <p align="center">
diff --git a/fluid/PaddleCV/rcnn/README_cn.md b/fluid/PaddleCV/rcnn/README_cn.md
index b7577a858edc135a23ad6d9c3252318e9847aca5..3d45de1c5845727d0b942f9ba5a4bf5216985af9 100644
--- a/fluid/PaddleCV/rcnn/README_cn.md
+++ b/fluid/PaddleCV/rcnn/README_cn.md
@@ -12,7 +12,7 @@
 
 ## 安装
 
-在当前目录下运行样例代码需要PadddlePaddle Fluid的v.1.0.0或以上的版本。如果你的运行环境中的PaddlePaddle低于此版本，请根据[安装文档](http://www.paddlepaddle.org/documentation/docs/zh/0.15.0/beginners_guide/install/install_doc.html#paddlepaddle)中的说明来更新PaddlePaddle。
+在当前目录下运行样例代码需要PadddlePaddle Fluid的v.1.3.0或以上的版本。如果你的运行环境中的PaddlePaddle低于此版本，请根据[安装文档](http://www.paddlepaddle.org/)中的说明来更新PaddlePaddle。
 
 ## 简介
 区域卷积神经网络（RCNN）系列模型为两阶段目标检测器。通过对图像生成候选区域，提取特征，判别特征类别并修正候选框位置。
@@ -37,6 +37,27 @@ Mask RCNN同样为两阶段框架，第一阶段扫描图像生成候选框；
     cd dataset/coco
     ./download.sh
 
+数据目录结构如下：
+
+```
+data/coco/
+├── annotations
+│   ├── instances_train2014.json
+│   ├── instances_train2017.json
+│   ├── instances_val2014.json
+│   ├── instances_val2017.json
+|   ...
+├── train2017
+│   ├── 000000000009.jpg
+│   ├── 000000580008.jpg
+|   ...
+├── val2017
+│   ├── 000000000139.jpg
+│   ├── 000000000285.jpg
+|   ...
+
+```
+
 ## 模型训练
 
 **下载预训练模型：** 本示例提供Resnet-50预训练模型，该模性转换自Caffe，并对批标准化层(Batch Normalization Layer)进行参数融合。采用如下命令下载预训练模型：
@@ -170,7 +191,7 @@ python infer.py \
     --draw_threshold=0.6
 ```
 
-注意，请正确设置`${path_to_trained_model}`模型和预测图片的路径。
+注意，请正确设置模型路径`${path_to_trained_model}`和预测图片路径。默认使用GPU设备，也可通过设置`--use_gpu=False`使用CPU设备。可通过设置`draw_threshold`调节得分阈值控制检测框的个数。
 
 下图为模型可视化预测结果：
 <p align="center">
diff --git a/fluid/PaddleCV/rcnn/infer.py b/fluid/PaddleCV/rcnn/infer.py
index 416d51caf71c7cb0f3860ad3397528d327128842..0c66ec08cf63cbf25df0959a5c082838965d7597 100644
--- a/fluid/PaddleCV/rcnn/infer.py
+++ b/fluid/PaddleCV/rcnn/infer.py
@@ -33,8 +33,8 @@ def infer():
         }
         labels_map[0] = 'background'
     except:
-        print("The COCO dataset is not exist, use the defalut mapping of class "
-              "index and real category name on COCO17.")
+        print("The COCO dataset or COCO API is not exist, use the default "
+              "mapping of class index and real category name on COCO17.")
         assert cfg.dataset == 'coco2017'
         labels_map = coco17_labels()