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README
Apache-2.0

简体中文 | English

PaddleGAN

飞桨生成对抗网络开发套件--PaddleGAN,为开发者提供经典及前沿的生成对抗网络高性能实现,并支撑开发者快速构建、训练及部署生成对抗网络,以供学术、娱乐及产业应用。

GAN--生成对抗网络,被“卷积网络之父”Yann LeCun(杨立昆)誉为「过去十年计算机科学领域最有趣的想法之一」,是近年来火遍全网,AI研究者最为关注的深度学习技术方向之一。

Licensepython version

近期贡献者

快速开始

  • 请确保您按照安装文档的说明正确安装了PaddlePaddle和PaddleGAN

  • 通过ppgan.apps接口直接使用应用:

    from ppgan.apps import RealSRPredictor
    sr = RealSRPredictor()
    sr.run("docs/imgs/monarch.png")
  • 更多应用的使用请参考ppgan.apps API

  • 更多训练、评估教程:

经典模型实现

复合应用

在线教程

您可以通过人工智能学习与实训社区AI Studio 的示例工程在线体验PaddleGAN的部分能力:

在线教程 链接
老北京视频修复 点击体验
表情动作迁移-当苏大强唱起unravel 点击体验

效果展示

图片变换

老视频修复

动作迁移

超分辨率

妆容迁移

人脸动漫化

写实人像卡通化

照片动漫化

唇形同步

版本更新

  • v0.1.0 (2020.11.02)
    • 初版发布,支持Pixel2Pixel、CycleGAN、PSGAN模型,支持视频插针、超分、老照片/视频上色、视频动作生成等应用。
    • 模块化设计,接口简单易用。

近期活动更新

欢迎加入PaddleGAN技术交流群

扫描二维码加入PaddleGAN QQ群[群号:1058398620],获得更高效的问题答疑,与各行业开发者交流讨论,我们期待您的加入!

PaddleGAN 特别兴趣小组(Special Interest Group)

最早于1961年被ACM(Association for Computing Machinery)首次提出并使用,国际顶尖开源组织包括Kubernates都采用SIGs的形式,使拥有同样特定兴趣的成员可以共同分享、学习知识并进行项目开发。这些成员不需要在同一国家/地区、同一个组织,只要大家志同道合,都可以奔着相同的目标一同学习、工作、玩耍~

PaddleGAN SIG就是这样一个汇集对GAN感兴趣小伙伴们的开发者组织,在这里,有百度飞桨的一线开发人员、有来自世界500强的资深工程师、有国内外顶尖高校的学生。

我们正在持续招募有兴趣、有能力的开发者加入我们一起共同建设本项目,并一起探索更多有用、有趣的应用。欢迎大家在加入群后联系我们讨论加入SIG并参与共建事宜。

SIG贡献:

  • zhen8838: 贡献AnimeGANv2.
  • Jay9z: 贡献DCGAN的示例、修改安装文档等。
  • HighCWu: 贡献c-DCGAN和WGAN,以及对paddle.vision.datasets数据集的支持。
  • hao-qiang & minivision-ai : 贡献人像卡通化photo2cartoon项目。

贡献代码

我们非常欢迎您可以为PaddleGAN提供任何贡献和建议。大多数贡献都需要同意参与者许可协议(CLA)。当提交拉取请求时,CLA机器人会自动检查您是否需要提供CLA。 只需要按照机器人提供的说明进行操作即可。CLA只需要同意一次,就能应用到所有的代码仓库上。关于更多的流程请参考贡献指南

许可证书

本项目的发布受Apache 2.0 license许可认证。

English | [简体中文](./README_cn.md) # PaddleGAN PaddleGAN provides developers with high-performance implementation of classic and SOTA Generative Adversarial Networks, and supports developers to quickly build, train and deploy GANs for academic, entertainment and industrial usage. GAN-Generative Adversarial Network, was praised by "the Father of Convolutional Networks" **Yann LeCun (Yang Likun)** as **[One of the most interesting ideas in the field of computer science in the past decade]**. It's the one research area in deep learning that AI researchers are most concerned about. <div align='center'> <img src='./docs/imgs/ppgan.jpg'> </div> [![License](https://img.shields.io/badge/license-Apache%202-red.svg)](LICENSE)![python version](https://img.shields.io/badge/python-3.6+-orange.svg) ## Recent Contributors [![](https://sourcerer.io/fame/LaraStuStu/paddlepaddle/paddlegan/images/0)](https://sourcerer.io/fame/LaraStuStu/paddlepaddle/paddlegan/links/0)[![](https://sourcerer.io/fame/LaraStuStu/paddlepaddle/paddlegan/images/1)](https://sourcerer.io/fame/LaraStuStu/paddlepaddle/paddlegan/links/1)[![](https://sourcerer.io/fame/LaraStuStu/paddlepaddle/paddlegan/images/2)](https://sourcerer.io/fame/LaraStuStu/paddlepaddle/paddlegan/links/2)[![](https://sourcerer.io/fame/LaraStuStu/paddlepaddle/paddlegan/images/3)](https://sourcerer.io/fame/LaraStuStu/paddlepaddle/paddlegan/links/3)[![](https://sourcerer.io/fame/LaraStuStu/paddlepaddle/paddlegan/images/4)](https://sourcerer.io/fame/LaraStuStu/paddlepaddle/paddlegan/links/4)[![](https://sourcerer.io/fame/LaraStuStu/paddlepaddle/paddlegan/images/5)](https://sourcerer.io/fame/LaraStuStu/paddlepaddle/paddlegan/links/5)[![](https://sourcerer.io/fame/LaraStuStu/paddlepaddle/paddlegan/images/6)](https://sourcerer.io/fame/LaraStuStu/paddlepaddle/paddlegan/links/6)[![](https://sourcerer.io/fame/LaraStuStu/paddlepaddle/paddlegan/images/7)](https://sourcerer.io/fame/LaraStuStu/paddlepaddle/paddlegan/links/7) ## Quick Start * Please refer to the [installation document](./docs/en_US/install.md) to make sure you have installed PaddlePaddle and PaddleGAN correctly. * Get started through ppgan.app interface: ```python from ppgan.apps import RealSRPredictor sr = RealSRPredictor() sr.run("docs/imgs/monarch.png") ``` * More applications, please refer to [ppgan.apps apis](./docs/en_US/apis/apps.md) * More tutorials: - [Data preparation](./docs/en_US/data_prepare.md) - [Training/Evaluating/Testing basic usage](./docs/zh_CN/get_started.md) ## Model Tutorial * [Pixel2Pixel](./docs/en_US/tutorials/pix2pix_cyclegan.md) * [CycleGAN](./docs/en_US/tutorials/pix2pix_cyclegan.md) * [PSGAN](./docs/en_US/tutorials/psgan.md) * [First Order Motion Model](./docs/en_US/tutorials/motion_driving.md) * [FaceParsing](./docs/en_US/tutorials/face_parse.md) * [AnimeGANv2](./docs/en_US/tutorials/animegan.md) * [U-GAT-IT](./docs/en_US/tutorials/ugatit.md) * [Photo2Cartoon](./docs/en_US/tutorials/photo2cartoon.md) * [Wav2Lip](./docs/en_US/tutorials/wav2lip.md) * [Super_Resolution](./docs/en_US/tutorials/super_resolution.md) ## Composite Application * [Video restore](./docs/zh_CN/tutorials/video_restore.md) ## Examples ### Image Translation <div align='center'> <img src='./docs/imgs/horse2zebra.gif'width='700' height='200'/> </div> ### Old video restore <div align='center'> <img src='./docs/imgs/color_sr_peking.gif' width='700'/> </div> ### Motion driving <div align='center'> <img src='./docs/imgs/first_order.gif' width='700'> </div> ### Super resolution <div align='center'> <img src='./docs/imgs/sr_demo.png'width='700' height='250'/> </div> ### Makeup shifter <div align='center'> <img src='./docs/imgs/makeup_shifter.png'width='700' height='250'/> </div> ### Face cartoonization <div align='center'> <img src='./docs/imgs/ugatit.png'width='700' height='250'/> </div> ### Realistic face cartoonization <div align='center'> <img src='./docs/imgs/photo2cartoon.png'width='700' height='250'/> </div> ### Photo animation <div align='center'> <img src='./docs/imgs/animeganv2.png'width='700' height='250'/> </div> ### Lip-syncing <div align='center'> <img src='./docs/imgs/mona.gif'width='700'> </div> ## Changelog - v0.1.0 (2020.11.02) - Release first version, supported models include Pixel2Pixel, CycleGAN, PSGAN. Supported applications include video frame interpolation, super resolution, colorize images and videos, image animation. - Modular design and friendly interface. ## Community Scan OR Code below to join [PaddleGAN QQ Group:1058398620], you can get offical technical support here and communicate with other developers/friends. Look forward to your participation! <div align='center'> <img src='./docs/imgs/qq.png'width='250' height='300'/> </div> ### PaddleGAN Special Interest Group(SIG) It was first proposed and used by [ACM(Association for Computing Machinery)](https://en.wikipedia.org/wiki/Association_for_Computing_Machinery) in 1961. Top International open source organizations including [Kubernates](https://kubernetes.io/) all adopt the form of SIGs, so that members with the same specific interests can share, learn knowledge and develop projects. These members do not need to be in the same country/region or the same organization, as long as they are like-minded, they can all study, work, and play together with the same goals~ PaddleGAN SIG is such a developer organization that brings together people who interested in GAN. There are frontline developers of PaddlePaddle, senior engineers from the world's top 500, and students from top universities at home and abroad. We are continuing to recruit developers interested and capable to join us building this project and explore more useful and interesting applications together. SIG contributions: - [zhen8838](https://github.com/zhen8838): contributed to AnimeGANv2. - [Jay9z](https://github.com/Jay9z): contributed to DCGAN and updated install docs, etc. - [HighCWu](https://github.com/HighCWu): contributed to c-DCGAN and WGAN. Support to use `paddle.vision.datasets`. - [hao-qiang](https://github.com/hao-qiang) & [ minivision-ai ](https://github.com/minivision-ai): contributed to the photo2cartoon project. ## Contributing Contributions and suggestions are highly welcomed. Most contributions require you to agree to a [Contributor License Agreement (CLA)](https://cla-assistant.io/PaddlePaddle/PaddleGAN) declaring. When you submit a pull request, a CLA-bot will automatically determine whether you need to provide a CLA. Simply follow the instructions provided by the bot. You will only need to do this once across all repos using our CLA. For more, please reference [contribution guidelines](docs/en_US/contribute.md). ## License PaddleGAN is released under the [Apache 2.0 license](LICENSE).

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