fix doc style for ocr

doc/COMPILE.md

@@ -119,6 +119,7 @@ you can execute `make install` to put targets under directory `./output`, you ne
 
 ### Compile C++ Server under the condition of WITH_OPENCV=ON
 First of all , opencv library should be installed, if not, please refer to the `Compile and install opencv` section later in this article.
+
 In the compile command, add `DOPENCV_DIR=${OPENCV_DIR}` and `DWITH_OPENCV=ON`，for example：
 ``` shell
 OPENCV_DIR=your_opencv_dir #`your_opencv_dir` is the installation path of OpenCV library。

doc/COMPILE_CN.md

@@ -118,6 +118,7 @@ make -j10
 
 ### 开启WITH_OPENCV选项编译C++ Server
 编译Serving C++ Server部分，开启WITH_OPENCV选项时，需要安装安装openCV库，若没有可参考本文档后面的说明编译安装openCV库。
+
 在编译命令中，加入`DOPENCV_DIR=${OPENCV_DIR}` 和 `DWITH_OPENCV=ON`选项，例如：
 ``` shell
 OPENCV_DIR=your_opencv_dir #`your_opencv_dir`为opencv库的安装路径。

python/examples/ocr/README.md

@@ -19,6 +19,7 @@ tar xf test_imgs.tar
 
 ### Start Service
 Select a startup mode according to CPU / GPU device
+
 After the -- model parameter, the folder path of multiple model files is passed in to start the prediction service of multiple model concatenation.
 ```
 #for cpu user
@@ -28,8 +29,10 @@ python -m paddle_serving_server_gpu.serve --model ocr_det_model ocr_rec_model --
 ```
 
 ### Client Prediction
-The pre-processing and post-processing is in the C + + server part, the image's Base64 encoded string is passed into the C + + server
+The pre-processing and post-processing is in the C + + server part, the image's Base64 encoded string is passed into the C + + server.
+
 so the value of parameter `feed_var` which is in the file `ocr_det_client/serving_client_conf.prototxt` should be changed.
+
 for this case, `feed_type` should be 3(which means the data type is string),`shape` should be 1.
 
 By passing in multiple client folder paths, the client can be started for multi model prediction.

python/examples/ocr/README_CN.md

@@ -19,6 +19,7 @@ tar xf test_imgs.tar
 
 ### 启动服务
 根据CPU/GPU设备选择一种启动方式
+
 通过--model后，指定多个模型文件的文件夹路径来启动多模型串联的预测服务。
 ```
 #for cpu user
@@ -29,8 +30,11 @@ python -m paddle_serving_server_gpu.serve --model ocr_det_model ocr_rec_model --
 
 ### 启动客户端
 由于需要在C++Server部分进行前后处理，传入C++Server的仅仅是图片的base64编码的字符串，故第一个模型的Client配置需要修改
+
 即`ocr_det_client/serving_client_conf.prototxt`中`feed_var`字段
+
 对于本示例而言，`feed_type`应修改为3(数据类型为string),`shape`为1.
+
 通过在客户端启动后加入多个client模型的client配置文件夹路径，启动client进行预测。
 ```
 python ocr_c_client_bytes.py ocr_det_client ocr_rec_client