PaddlePaddle · luotao1 · Jan 19, 2018 · Dec 14, 2017 · Dec 14, 2017 · Dec 14, 2017
diff --git a/Demo/iOS/AICamera/README_cn.md → Demo/iOS/AICamera/README.cn.md b/Demo/iOS/AICamera/README_cn.md → Demo/iOS/AICamera/README.cn.md
@@ -51,9 +51,9 @@ App模型需要开启摄像头权限。启动App后，点击屏幕，将会出
 
 ## 快速安装
 
-如果你想快速地体验PDCamera，可通过扫描以下二维码进行安装。成功识别二维码之后，会自动跳转到安装页面，点击“Install PDCamera”链接，App会自动下载并安装到你的iOS设备上。
+如果你想快速地体验PDCamera，可通过扫描以下二维码进行安装。成功识别二维码之后，会自动跳转到安装页面，点击**“Install PDCamera”**链接，App会自动下载并安装到你的iOS设备上。
 
-成功安装App后，你还需要安装如下步骤进一步设置：设置 → 通用 → 设备管理 → Baidu USA llc → 信任“Baidu USA llc”。
+成功安装App后，你还需要按照如下步骤设置你的iOS设备：**设置 → 通用 → 设备管理 → Baidu USA llc → 信任“Baidu USA llc”**。
 
 <p align="center">
 <img src="assets/qr_code_ios.png" width = "30%"/>
@@ -71,6 +71,8 @@ Github上面只维护了该Demo相关的源码文件和项目配置。用户可
 
 VGG模型的识别精度高，但由于模型较大（104.3MB），需要占用较高的内存（\~800MB），并且识别速度慢（每帧~1.5秒），因此对设备的计算能力要求较高（iPhone6s以上），默认没有添加到项目中。用户也可自行下载[vgg\_ssd\_net.paddle](http://cloud.dlnel.org/filepub/?uuid=1116a5f3-7762-44b5-82bb-9954159cb5d4)，添加到项目中，体验其高精度识别效果。
 
+这里，我们使用的是**合并的模型**（merged model）。如何从配置文件（例如`config.py`）和训练得到的参数文件（例如`params_pass_0.tar.gz`）得的**合并的模型**文件，请参考[如何合并模型](../../../deployment/model/merge_config_parameters/README.cn.md)。
+
 ### 准备PaddlePaddle库
 
 用户可按照[iOS平台编译指南](https://github.com/PaddlePaddle/Paddle/blob/develop/doc/mobile/cross_compiling_for_ios_cn.md)，拉取[Paddle](https://github.com/PaddlePaddle/Paddle)最新的源码，编译适用于iOS平台的PaddlePaddle库。在执行`make install`之后，PaddlePaddle库将会安装在`CMAKE_INSTALL_PREFIX`所指定的目录下。该目录包含如下子目录：

diff --git a/Demo/iOS/AICamera/README.md b/Demo/iOS/AICamera/README.md
@@ -1,89 +1,68 @@
 # PDCamera iOS Demo with SSD Model
 
+- [Overview](#overview)
+  - [Pre-trained Models](#pre-trained-models)
+  - [Demo Screenshot](#demo-screenshot)
+- [Fast Installation through QR Code](#fast-installation-through-qr-code)
+- [Build from Source Code](#build-from-source-code)
+  - [Prepare Models](#prepare-models)
+  - [Prepare PaddlePaddle Inference Library](#prepare-paddlepaddle-inference-library)
+  - [Directory Tree](#directory-tree)
+- [Integrate Paddle C Library to iOS Project](#integrate-paddle-c-library-to-ios-project)
+
+## Overview
+
 This iOS demo shows PaddlePaddle running SSD(Single Shot MultiBox Detector）Object detection on iOS devices locally and offline. It loads a pretrained model with PaddlePaddle and uses camera to capture images and call PaddlePaddle's inference ability to show detected objects to users.
 
 You can look at SSD model architecture [here](https://github.com/PaddlePaddle/models/tree/develop/ssd) and a linux demo [here](https://github.com/PaddlePaddle/Mobile/tree/develop/Demo/linux)
 
+### Pre-trained Models
 
-## Download and run the app
+`pascal_mobilenet_300_66` and `vgg_ssd_net` models can classify 20 objects.
+`face_mobilenet_160_91` can only classify human's face.
 
-To simply run the demo with iPhone/iPad, scan the QR code below, click "Install PDCamera" in the link and the app will be downloaded in the background.
-After installed, go to Settings -> General -> Device Management -> Baidu USA llc -> Trust "Baidu USA llc"
+| Model                    | Dimensions | Accuracy |  Size |
+| ------------------------ |:----------:| --------:|------:|
+| [pascal\_mobilenet\_300\_66.paddle](http://cloud.dlnel.org/filepub/?uuid=39c325d9-b468-4940-ba47-d50c8ec5fd5b) | 300 x 300 | 66% | 23.2MB |
+| [vgg\_ssd\_net.paddle](http://cloud.dlnel.org/filepub/?uuid=1116a5f3-7762-44b5-82bb-9954159cb5d4) | 300 x 300 | 71% | 104.3MB |
+| [face\_mobilenet\_160\_91.paddle](http://cloud.dlnel.org/filepub/?uuid=038c1dbf-08b3-42a9-b2dc-efccd63859fb) | 160 x 160 | 91% | 18.4MB |
 
+### Demo Screenshot
 
-### QR code link
+Simply tap on the screen to toggle settings.
 
-<img src="assets/qr_code_ios.png" width = "20%" />
-
-### Demo screenshot
+- Models: Select Pascal MobileNet 300 or Face MobileNet 160, App will exit, need to launch to restart.
+- Camera: Toggle Front/Back Camera. App will exit, need to launch to restart.
+- Accuracy Threshold: Adjust threshold to filter more/less objects based on probability.
+- Time Refresh Rate: Adjust the time to refresh bounding box more/less frequently.
 
-<img src="assets/demo_screenshot.jpg" width = "30%" />
+<p align="center">
+<img src="assets/demo_main.jpeg" width = "25%" />
+<img src="assets/demo_pascal.jpg" width = "25%" />
+<img src="assets/demo_face.jpeg" width = "25%" /><br/>
+Figure-1
+</p>
 
 Detected object will be highlighted as a bounding box with a classified object label and probability.
 
+## Fast Installation through QR Code
 
-## Classifications
-`pascal_mobilenet_300_66` and `vgg_ssd_net` models can only classify following 20 objects:
-
-- aeroplane
-- bicycle
-- background
-- boat
-- bottle
-- bus
-- car
-- cat
-- chair
-- cow
-- diningtable
-- dog
-- horse
-- motorbike
-- person
-- pottedplant
-- sheep
-- sofa
-- train
-- tvmonitor
-
-`face_mobilenet_160_91` can only classify human's face
-
-
-## Settings
-
-Simply tap on the screen to toggle settings
-
-- Models: Select Pascal MobileNet 300 or Face MobileNet 160, App will exit, need to launch to restart.
-- Camera: Toggle Front/Back Camera. App will exit, need to launch to restart.
-- Accuracy Threshold: Adjust threshold to filter more/less objects based on probability
-- Time Refresh Rate: Adjust the time to refresh bounding box more/less frequently
+To simply run the demo with iPhone/iPad, scan the QR code below, click "Install PDCamera" in the link and the app will be downloaded in the background.
+After installed, go to Settings -> General -> Device Management -> Baidu USA llc -> Trust "Baidu USA llc"
 
+<p align="center">
+<img src="assets/qr_code_ios.png" width = "30%"/>
+</p>
 
-## Development or modify
+## Build from Source Code
 
 Use latest XCode for development. This demo requires a camera for object detection, therefore you must use a device (iPhone or iPad) for development and testing. Simulators will not work as they cannot access camera.
 
 For developers, feel free to use this as a reference to start a new project. This demo fully demonstrates how to integrate Paddle C Library to iOS and called from Swift.
 
 Swift cannot directly call C API, in order to have client in Swift work, create Objective-C briding header and a Objective-C++ wrapper (.mm files) to access paddle APIs.
 
-
-## Integrate Paddle C Library to iOS
-
--Follow this guide [Build PaddlePaddle for iOS](https://github.com/PaddlePaddle/Paddle/blob/develop/doc/mobile/cross_compiling_for_ios_cn.md) to generate paddle libs(include, lib, third_party).
--Create a folder paddle-ios and add to project root. Put the 3 paddle libs folder under paddle-ios.
-- Add the `include` directory to **Header Search Paths**
-![image](https://user-images.githubusercontent.com/12538138/32491809-b215cf7a-c37d-11e7-87f8-3d45f07bc63e.png)
-
-- Add the `Accelerate.framework` or `veclib.framework` to your project, if your PaddlePaddle is built with `IOS_USE_VECLIB_FOR_BLAS=ON`
-- Add the libraries of paddle, `libpaddle_capi_layers.a` and `libpaddle_capi_engine.a`, and all the third party libraries to your project
-    <img src="https://user-images.githubusercontent.com/12538138/32492222-2ecef414-c37f-11e7-9913-b90fc88be10f.png" width = "30%" />
-
-- Set `-force_load` for `libpaddle_capi_layers.a`
-![image](https://user-images.githubusercontent.com/12538138/32492328-8504ebae-c37f-11e7-98b5-41615519fbb3.png)
-
-
-## Download Models
+### Prepare Models
 
 Our models are too large to upload to Github. Create a model folder and add to project root. Download [face_mobilenet_160_91.paddle](http://cloud.dlnel.org/filepub/?uuid=038c1dbf-08b3-42a9-b2dc-efccd63859fb) and [pascal_mobilenet_300_66.paddle](http://cloud.dlnel.org/filepub/?uuid=39c325d9-b468-4940-ba47-d50c8ec5fd5b) to the model folder.
 
@@ -92,11 +71,53 @@ Note: Only runs on iPhone6s or above (iPhone 6 or below will crash due to memory
 If you want to try it out, download [vgg_ssd_net.paddle](http://cloud.dlnel.org/filepub/?uuid=1116a5f3-7762-44b5-82bb-9954159cb5d4), then go to
 XCode target -> Bulid Phases -> Copy Bundle Resources, click '+' to add vgg_ssd_net.paddle
 
+### Prepare PaddlePaddle Inference Library
+
+Follow this guide [Build PaddlePaddle for iOS](https://github.com/PaddlePaddle/Paddle/blob/develop/doc/mobile/cross_compiling_for_ios_cn.md) to generate paddle libs(include, lib, third_party).
+Create a folder paddle-ios and add to project root. Put the 3 paddle libs folder under paddle-ios.
+
+### Directory Tree
+
+```
+$ git clone https://github.com/PaddlePaddle/Mobile.git
+$ cd Mobile/Demo/iOS/AICamera
+$ tree
+.
+├── AICamera  # sources codes
+├── PDCamera.xcodeproj
+├── README.md
+├── README_cn.md
+├── assets
+├── models  # models
+│   ├── face_mobilenet_160_91.paddle
+│   ├── pascal_mobilenet_300_66.paddle
+│   └── vgg_ssd_net.paddle
+└── paddle-ios  # PaddlePaddle inference library
+    ├── include
+    ├── lib
+    │   ├── libpaddle_capi_engine.a
+    │   ├── libpaddle_capi_layers.a
+    │   └── libpaddle_capi_whole.a
+    └── third_party
+```
+
+## Integrate Paddle C Library to iOS Project
 
-## Accuracy
+- Add the `include` directory to **Header Search Paths**
+
+<p align="center">
+<img src="https://user-images.githubusercontent.com/12538138/32491809-b215cf7a-c37d-11e7-87f8-3d45f07bc63e.png" width="90%">
+</p>
+
+- Add the `Accelerate.framework` or `veclib.framework` to your project, if your PaddlePaddle is built with `IOS_USE_VECLIB_FOR_BLAS=ON`
+- Add the libraries of paddle, `libpaddle_capi_layers.a` and `libpaddle_capi_engine.a`, and all the third party libraries to your project
+
+<p align="center">
+<img src="https://user-images.githubusercontent.com/12538138/32492222-2ecef414-c37f-11e7-9913-b90fc88be10f.png" width = "30%">
+</p>
+
+- Set `-force_load` for `libpaddle_capi_layers.a`
 
-| Model                    | Dimensions | Accuracy |
-| ------------------------ |:----------:| --------:|
-| face_mobilenet_160_91    | 160x160    | 91%      |
-| pascal_mobilenet_300_66  | 300x300    | 66%      |
-| vgg_ssd_net              | 300x300    | 71%      |
+<p align="center">
+<img src="https://user-images.githubusercontent.com/12538138/32492328-8504ebae-c37f-11e7-98b5-41615519fbb3.png" width="90%">
+</p>
diff --git a/README.cn.md b/README.cn.md
@@ -0,0 +1,47 @@
+# 移动PaddlePaddle
+
+[![Build Status](https://travis-ci.org/PaddlePaddle/Mobile.svg?branch=develop)](https://travis-ci.org/PaddlePaddle/Mobile)
+[![Documentation Status](https://img.shields.io/badge/docs-latest-brightgreen.svg?style=flat)](http://www.paddlepaddle.org/docs/develop/mobile/README.html)
+[![Download](https://img.shields.io/badge/download-latest-brightgreen.svg?style=flat)](https://github.com/PaddlePaddle/Mobile/wiki)
+[![License](https://img.shields.io/badge/license-Apache%202-blue.svg)](LICENSE)
+
+PaddlePaddle支持在移动设备上，使用训练好的模型进行离线推断。这里，我们主要介绍如何在移动设备上部署PaddlePaddle推断库，以及移动设备上可以使用到的一些优化方法。
+
+## 构建PaddlePaddle库
+PaddlePaddle可以通过原生编译、交叉编译的方式，构建多种移动平台上的推断库。
+
+- [Android平台编译指南](https://github.com/PaddlePaddle/Paddle/blob/develop/doc/mobile/cross_compiling_for_android_cn.md)
+- [iOS平台编译指南](https://github.com/PaddlePaddle/Paddle/blob/develop/doc/mobile/cross_compiling_for_ios_cn.md)
+- [Rapsberry Pi3平台编译指南](https://github.com/PaddlePaddle/Paddle/blob/develop/doc/mobile/cross_compiling_for_raspberry_cn.md)
+- NVIDIA Driver PX2平台，采用原生编译的方式，可直接依照[PaddlePaddle源码编译指南](https://github.com/PaddlePaddle/Paddle/blob/develop/doc/getstarted/build_and_install/build_from_source_cn.rst)进行编译
+
+## 使用示例
+
+- [命令行示例程序](./benchmark/tool/C/README.cn.md)
+- [iOS示例应用：PDCamera](./Demo/iOS/AICamera/README.cn.md)
+
+## 部署优化方法
+移动端对接入库的大小通常都有要求，在编译PaddlePaddle库时，用户可以通过设置一些编译选项来进行优化。
+
+- [如何构建最小的PaddlePaddle推断库](./deployment/library/build_for_minimum_size.md)
+
+训练得到的模型，可在不降低或者轻微降低模型推断精度的前提下，进行一些变换，优化移动设备上的内存使用和执行效率。
+
+- [合并网络中的BN层](./deployment/model/merge_batch_normalization/README.md)
+- [压缩模型大小的rounding方法](./deployment/model/rounding/README.md)
+- [如何合并模型](./deployment/model/merge_config_parameters/README.cn.md)
+- INT8量化方法
+
+## 模型压缩
+基于PaddlePaddle框架，可以使用模型压缩训练进一步裁剪模型的大小。
+
+- [Pruning稀疏化方法](./model_compression/pruning/README.md)
+
+## 性能数据
+我们列出一些移动设备上的性能测试数据，给用户参考和对比。
+
+- [Mobilenet模型性能数据](./benchmark/README.md)
+- ENet模型性能数据
+- [DepthwiseConvolution优化效果](https://github.com/hedaoyuan/Function/blob/master/src/conv/README.md)
+
+本教程由[PaddlePaddle](https://github.com/PaddlePaddle/Paddle)创作，采用[Apache-2.0 license](LICENSE)许可协议进行许可。
diff --git a/README.md b/README.md
@@ -1,33 +1,40 @@
 # Mobile
 
 [![Build Status](https://travis-ci.org/PaddlePaddle/Mobile.svg?branch=develop)](https://travis-ci.org/PaddlePaddle/Mobile)
+[![Documentation Status](https://img.shields.io/badge/docs-latest-brightgreen.svg?style=flat)](http://www.paddlepaddle.org/docs/develop/mobile/README.html)
+[![Download](https://img.shields.io/badge/download-latest-brightgreen.svg?style=flat)](https://github.com/PaddlePaddle/Mobile/wiki)
 [![License](https://img.shields.io/badge/license-Apache%202-blue.svg)](LICENSE)
 
 Here mainly describes how to deploy PaddlePaddle to the mobile end, as well as some deployment optimization methods and some benchmark.
 
-## How to build PaddlePaddle for mobile
-- Build PaddlePaddle for Android [[Chinese](https://github.com/PaddlePaddle/Paddle/blob/develop/doc/mobile/cross_compiling_for_android_cn.md)] [[English](https://github.com/PaddlePaddle/Paddle/blob/develop/doc/mobile/cross_compiling_for_android_en.md)]
-- Build PaddlePaddle for IOS [[Chinese](https://github.com/PaddlePaddle/Paddle/blob/develop/doc/mobile/cross_compiling_for_ios_cn.md)] [[English](https://github.com/PaddlePaddle/Paddle/blob/develop/doc/mobile/cross_compiling_for_ios_en.md)]
-- Build PaddlePaddle for Raspberry Pi3 [[Chinese](https://github.com/PaddlePaddle/Paddle/blob/develop/doc/mobile/cross_compiling_for_raspberry_cn.md)] [[English](https://github.com/PaddlePaddle/Paddle/blob/develop/doc/mobile/cross_compiling_for_raspberry_en.md)]
-- Build PaddlePaddle for PX2
-- [How to build PaddlePaddle mobile inference library with minimum size.](./deployment/library/build_for_minimum_size.md)
+## Build PaddlePaddle
+- [Build PaddlePaddle for Android](https://github.com/PaddlePaddle/Paddle/blob/develop/doc/mobile/cross_compiling_for_android_en.md)
+- [Build PaddlePaddle for IOS](https://github.com/PaddlePaddle/Paddle/blob/develop/doc/mobile/cross_compiling_for_ios_en.md)
+- [Build PaddlePaddle for Raspberry Pi3](https://github.com/PaddlePaddle/Paddle/blob/develop/doc/mobile/cross_compiling_for_raspberry_en.md)
+- Build PaddlePaddle for NVIDIA Driver PX2
 
 ## Demo
 - [A command-line inference demo.](./benchmark/tool/C/README.md)
-- [iOS demo of AICamera](./Demo/iOS/AICamera/README.md)
+- [iOS demo of PDCamera](./Demo/iOS/AICamera/README.md)
 
 ## Deployment optimization methods
-- [Merge batch normalization before deploying the model to the mobile.](./deployment/model/merge_batch_normalization/README.md)
-- [Compress the model before deploying the model to the mobile.](./deployment/model/rounding/README.md)
-- [Merge model config and parameter files into one file.](./deployment/model/merge_config_parameters/README.md)
-- How to deploy int8 model in mobile inference with PaddlePaddle.
+Optimization for the library:
+
+- [How to build PaddlePaddle mobile inference library with minimum size.](./deployment/library/build_for_minimum_size.md)
+
+Optimization for models：
+
+- [Merge batch normalization layers](./deployment/model/merge_batch_normalization/README.md)
+- [Compress the model based on rounding](./deployment/model/rounding/README.md)
+- [Merge model's config and parameters](./deployment/model/merge_config_parameters/README.md)
+- How to deploy int8 model in mobile inference with PaddlePaddle
 
 ## Model compression
-- [How to use pruning to train smaller model](./model_compression/pruning/)
+- [How to use pruning to train smaller model](./model_compression/pruning/README.md)
 
 ## PaddlePaddle mobile benchmark
 - [Benchmark of Mobilenet](./benchmark/README.md)
 - Benchmark of ENet
-- [Benchmark of DepthwiseConvolution in PaddlePaddle](https://github.com/hedaoyuan/Function/blob/master/src/conv/README.md)
+- [Benchmark of DepthwiseConvolution](https://github.com/hedaoyuan/Function/blob/master/src/conv/README.md)
 
 This tutorial is contributed by [PaddlePaddle](https://github.com/PaddlePaddle/Paddle) and licensed under the [Apache-2.0 license](LICENSE).