update

doc/doc_ch/android_demo.md

-# Android Demo 快速测试
-
-
-### 1. 安装最新版本的Android Studio
-
-可以从 https://developer.android.com/studio 下载。本Demo使用是4.0版本Android Studio编写。
-
-### 2. 创建新项目
-
-Demo测试的时候使用的是NDK 20b版本，20版本以上均可以支持编译成功。
-
-如果您是初学者，可以用以下方式安装和测试NDK编译环境。
-点击 File -> New ->New Project，  新建  "Native C++" project
-
-
-1. Start a new Android Studio project
-    在项目模版中选择 Native C++ 选择PaddleOCR/deploy/android_demo 路径
-    进入项目后会自动编译，第一次编译会花费较长的时间，建议添加代理加速下载。
-
-**代理添加：**
-
-选择 Android Studio -> Preferences -> Appearance & Behavior -> System Settings -> HTTP Proxy -> Manual proxy configuration
-
-![](../demo/proxy.png)
-
-2. 开始编译
-
-点击编译按钮，连接手机，跟着Android Studio的引导完成操作。
-
-在 Android Studio 里看到下图，表示编译完成：
-
-![](../demo/build.png)
-
-**提示:** 此时如果出现下列找不到OpenCV的报错信息，请重新点击编译，编译完成后退出项目，再次进入。
-
-![](../demo/error.png)
-
-### 3. 发送到手机端
-
-完成编译，点击运行，在手机端查看效果。
-
-### 4. 如何自定义demo图片
-
-1. 图片存放路径:android_demo/app/src/main/assets/images
-
-   将自定义图片放置在该路径下
-
-2. 配置文件: android_demo/app/src/main/res/values/strings.xml
-
-   修改 IMAGE_PATH_DEFAULT 为自定义图片名即可
-
-
-# 获得更多支持
-前往[端计算模型生成平台EasyEdge](https://ai.baidu.com/easyedge/app/open_source_demo?referrerUrl=paddlelite)，获得更多开发支持：
-
-- Demo APP：可使用手机扫码安装，方便手机端快速体验文字识别
-- SDK：模型被封装为适配不同芯片硬件和操作系统SDK，包括完善的接口，方便进行二次开发

doc/doc_en/android_demo_en.md

-# Android Demo quick start
-
-### 1. Install the latest version of Android Studio
-
-It can be downloaded from https://developer.android.com/studio . This Demo is written by Android Studio version 4.0.
-
-### 2. Create a new project
-
-The NDK version 20b is used in the demo test, and the compilation can be successfully supported for version 20 and above.
-
-If you are a beginner, you can install and test the NDK compilation environment in the following ways.
-
-File -> New ->New Project  to create  "Native C++" project
-
-1. Start a new Android Studio project
-
-   Select Native C++ in the project template, select Paddle OCR/deploy/android_demo path
-   After entering the project, it will be automatically compiled. The first compilation
-   will take a long time. It is recommended to add an agent to speed up the download.
-
-**Agent add:**
-
-  Android Studio -> Preferences -> Appearance & Behavior -> System Settings -> HTTP Proxy -> Manual proxy configuration
-
-![](../demo/proxy.png)
-
-2. Start compilation
-
-Click the compile button, connect the phone, and follow the instructions of Android Studio to complete the operation.
-
-When you see the following picture in Android Studio, the compilation is complete:
-
-![](../demo/build.png)
-
-**Tip:** At this time, if the following error message that OpenCV cannot be found appears, please re-click compile,
-exit the project after compiling, and enter again.
-
-![](../demo/error.png)
-
-### 3. Send to mobile
-
-Complete the compilation, click Run, and check the effect on the mobile phone.
-
-### 4. How to customize the demo picture
-
-1. Image storage path: android_demo/app/src/main/assets/images
-
-   Place the custom picture under this path
-
-2. Configuration file: android_demo/app/src/main/res/values/strings.xml
-
-   Modify IMAGE_PATH_DEFAULT to a custom picture name
-
-# Get more support
-
-Go to [EasyEdge](https://ai.baidu.com/easyedge/app/open_source_demo?referrerUrl=paddlelite) to get more development support:
-
-- Demo APP: You can use your mobile phone to scan the code to install, which is convenient for the mobile terminal to quickly experience text recognition
-
-- SDK: The model is packaged to adapt to different chip hardware and operating system SDKs, including a complete interface to facilitate secondary development

doc/doc_en/paddleOCR_overview_en.md → doc/doc_en/clone_en.md

-# PaddleOCR Overview and Project Clone
+# Project Clone
 
-## 1. PaddleOCR Overview
+## 1. Clone PaddleOCR
 
-PaddleOCR contains rich text detection, text recognition and end-to-end algorithms. With the experience from real world scenarios and the industry, PaddleOCR chooses DB and CRNN as the basic detection and recognition models, and proposes a series of models, named PP-OCR, for industrial applications after a series of optimization strategies. The PP-OCR model is aimed at general scenarios and forms a model library of different languages. Based on the capabilities of PP-OCR, PaddleOCR releases the PP-Structure toolkit for document scene tasks, including two major tasks: layout analysis and table recognition. In order to get through the entire process of industrial landing, PaddleOCR provides large-scale data production tools and a variety of prediction deployment tools to help developers quickly turn ideas into reality.
-
-<div align="center">
-    <img src="../overview_en.png">
-</div>
-
-
-
-## 2. Project Clone
-
-### **2.1 Clone PaddleOCR repo**
-
-```
+```bash
 # Recommend
 git clone https://github.com/PaddlePaddle/PaddleOCR
 
@@ -25,9 +13,9 @@ git clone https://gitee.com/paddlepaddle/PaddleOCR
 # Note: The mirror on Gitee may not keep in synchronization with the latest project on GitHub. There might be a delay of 3-5 days. Please try GitHub at first.
 ```
 
-### **2.2 Install third-party libraries**
+## 2. Install third-party libraries
 
-```
+```bash
 cd PaddleOCR
 pip3 install -r requirements.txt
 ```