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enhance readme #1804

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13 changes: 8 additions & 5 deletions README.md
Expand Up @@ -2,14 +2,15 @@

# Paddle Lite

[![Build Status](https://travis-ci.org/PaddlePaddle/paddle-mobile.svg?branch=develop&longCache=true&style=flat-square)](https://travis-ci.org/PaddlePaddle/paddle-mobile)
[![Documentation Status](https://img.shields.io/badge/中文文档-最新-brightgreen.svg)](https://github.com/PaddlePaddle/paddle-mobile/tree/develop/doc)
<!--[![Build Status](https://travis-ci.org/PaddlePaddle/Paddle-Lite.svg?branch=develop&longCache=true&style=flat-square)](https://travis-ci.org/PaddlePaddle/Paddle-Lite)-->
[![Documentation Status](https://img.shields.io/badge/中文文档-最新-brightgreen.svg)](https://github.com/PaddlePaddle/Paddle-Lite/wiki)
[![License](https://img.shields.io/badge/license-Apache%202-blue.svg)](LICENSE)
<!-- [![Release](https://img.shields.io/github/release/PaddlePaddle/Paddle-Mobile.svg)](https://github.com/PaddlePaddle/Paddle-Mobile/releases) -->

Paddle Lite is an updated version of Paddle-Mobile, an open-open source deep learning framework designed to make it easy to perform inference on mobile and IoT devices. It is compatible with PaddlePaddle and pre-trained models from other sources.

For tutorials, please see [PaddleLite Wiki](https://github.com/PaddlePaddle/paddle-mobile/wiki).
Paddle Lite is an updated version of Paddle-Mobile, an open-open source deep learning framework designed to make it easy to perform inference on mobile, embeded, and IoT devices. It is compatible with PaddlePaddle and pre-trained models from other sources.

For tutorials, please see [PaddleLite Wiki](https://github.com/PaddlePaddle/Paddle-Lite/wiki).

## Key Features

Expand All @@ -29,6 +30,8 @@ It also supports INT8 quantizations with [PaddleSlim model compression tools](ht

On Huawei NPU and FPGA, the performance is also boosted.

The latest benchmark is located at [benchmark](https://github.com/PaddlePaddle/Paddle-Lite/wiki/benchmark)

### High Compatibility

Hardware compatibility: Paddle Lite supports a diversity of hardwares — ARM CPU, Mali GPU, Adreno GPU, Huawei NPU and FPGA. In the near future, we will also support AI microchips from Cambricon and Bitmain.
Expand All @@ -49,7 +52,7 @@ As is shown in the figure above, analysis phase includes Machine IR module, and

The earlier Paddle-Mobile was designed to be compatible with PaddlePaddle and multiple hardwares, including ARM CPU, Mali GPU, Adreno GPU, FPGA, ARM-Linux and Apple's GPU Metal. Within Baidu, inc, many product lines have been using Paddle-Mobile. For more details, please see: [mobile/README](mobile/README).

As an update of Paddle-Mobile, Paddle Lite has incorporated many older capabilities into the [new architecture](https://github.com/PaddlePaddle/paddle-mobile/tree/develop/lite). For the time being, the code of Paddle-mobile will be kept under the directory `mobile/`, before complete transfer to Paddle Lite.
As an update of Paddle-Mobile, Paddle Lite has incorporated many older capabilities into the [new architecture](https://github.com/PaddlePaddle/Paddle-Lite/tree/develop/lite). For the time being, the code of Paddle-mobile will be kept under the directory `mobile/`, before complete transfer to Paddle Lite.

For demands of Apple's GPU Metal and web front end inference, please see `./metal` and `./web` . These two modules will be further developed and maintained.

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12 changes: 7 additions & 5 deletions README_cn.md
@@ -1,13 +1,13 @@
# Paddle Lite

[![Build Status](https://travis-ci.org/PaddlePaddle/paddle-mobile.svg?branch=develop&longCache=true&style=flat-square)](https://travis-ci.org/PaddlePaddle/paddle-mobile)
[![Documentation Status](https://img.shields.io/badge/中文文档-最新-brightgreen.svg)](https://github.com/PaddlePaddle/paddle-mobile/tree/develop/doc)
<!--[![Build Status](https://travis-ci.org/PaddlePaddle/Paddle-Lite.svg?branch=develop&longCache=true&style=flat-square)](https://travis-ci.org/PaddlePaddle/Paddle-Lite)-->
[![Documentation Status](https://img.shields.io/badge/中文文档-最新-brightgreen.svg)](https://github.com/PaddlePaddle/Paddle-Lite/wiki)
[![License](https://img.shields.io/badge/license-Apache%202-blue.svg)](LICENSE)
<!-- [![Release](https://img.shields.io/github/release/PaddlePaddle/Paddle-Mobile.svg)](https://github.com/PaddlePaddle/Paddle-Mobile/releases) -->

Paddle Lite为Paddle-Mobile的升级版,定位支持包括手机移动端在内更多场景的轻量化高效预测,支持更广泛的硬件和平台,是一个高性能、轻量级的深度学习预测引擎。在保持和PaddlePaddle无缝对接外,也兼容支持其他训练框架产出的模型。

完整使用文档位于 [PaddleLite Wiki](https://github.com/PaddlePaddle/paddle-mobile/wiki) 。
完整使用文档位于 [PaddleLite Wiki](https://github.com/PaddlePaddle/Paddle-Lite/wiki) 。

## 特性

Expand All @@ -21,6 +21,8 @@ Paddle Lite为Paddle-Mobile的升级版,定位支持包括手机移动端在
支持INT8量化计算,结合 [PaddleSlim 模型压缩工具](https://github.com/PaddlePaddle/models/tree/v1.5/PaddleSlim) 中 INT8量化训练功能,可以提供高精度高性能的预测能力。
在Huawei NPU, FPGA上也具有有很好的性能表现。

最新 Benchmark 位于 [benchmark](https://github.com/PaddlePaddle/Paddle-Lite/wiki/benchmark)。

### 通用性
硬件方面,Paddle Lite 的架构设计为多硬件兼容支持做了良好设计。除了支持ARM CPU、Mali GPU、Adreno GPU,还特别支持了华为 NPU,以及 FPGA 等边缘设备广泛使用的硬件。即将支持支持包括寒武纪、比特大陆等AI芯片,未来会增加对更多硬件的支持。

Expand All @@ -38,9 +40,9 @@ PaddleLite 的架构设计着重考虑了对多硬件和平台的支持,并且


## Paddle-Mobile升级为Paddle Lite的说明
原Paddle-Mobile作为一个致力于嵌入式平台的PaddlePaddle预测引擎,已支持多种硬件平台,包括ARM CPU、 Mali GPU、Adreno GPU,以及支持苹果设备的GPU Metal实现、ZU5、ZU9等FPGA开发板、树莓派等arm-linux开发板。在百度内已经过广泛业务场景应用验证。对应设计文档可参考: [mobile/README](https://github.com/PaddlePaddle/paddle-mobile/blob/develop/mobile/README.md)
原Paddle-Mobile作为一个致力于嵌入式平台的PaddlePaddle预测引擎,已支持多种硬件平台,包括ARM CPU、 Mali GPU、Adreno GPU,以及支持苹果设备的GPU Metal实现、ZU5、ZU9等FPGA开发板、树莓派等arm-linux开发板。在百度内已经过广泛业务场景应用验证。对应设计文档可参考: [mobile/README](https://github.com/PaddlePaddle/Paddle-Lite/blob/develop/mobile/README.md)

Paddle-Mobile 整体升级重构并更名为Paddle Lite后,原paddle-mobile 的底层能力大部分已集成到[新架构 ](https://github.com/PaddlePaddle/paddle-mobile/tree/develop/lite)下。作为过渡,暂时保留原Paddle-mobile代码。 主体代码位于 `mobile/` 目录中,后续一段时间会继续维护,并完成全部迁移。新功能会统一到[新架构 ](https://github.com/PaddlePaddle/paddle-mobile/tree/develop/lite)下开发。
Paddle-Mobile 整体升级重构并更名为Paddle Lite后,原paddle-mobile 的底层能力大部分已集成到[新架构 ](https://github.com/PaddlePaddle/Paddle-Lite/tree/develop/lite)下。作为过渡,暂时保留原Paddle-mobile代码。 主体代码位于 `mobile/` 目录中,后续一段时间会继续维护,并完成全部迁移。新功能会统一到[新架构 ](https://github.com/PaddlePaddle/Paddle-Lite/tree/develop/lite)下开发。

metal, web的模块相对独立,会继续在 `./metal` 和 `./web` 目录下开发和维护。对苹果设备的GPU Metal实现的需求及web前端预测需求,可以直接进入这两个目录。

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