未验证 提交 f7b95e70 编写于 作者: L LielinJiang 提交者: GitHub

Set en readme as default (#119)

* set en readme as default
上级 77b8bac3
简体中文 | [English](./README_en.md)
English | [简体中文](./README_cn.md)
# 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。
PaddleGAN provides developers with high-performance implementation of classic and SOTA Generative Adversarial Networks, and support developers to quickly build, train and deploy GANs for academic, entertainment and industrial usage.
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。
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 one the research area in deep learning that AI researchers are most concerned about.
<div align='center'>
<img src='./docs/imgs/ppgan.jpg'>
......@@ -13,130 +13,119 @@ GAN--生成对抗网络,被“卷积网络之父”**Yann LeCun(杨立昆)
[![License](https://img.shields.io/badge/license-Apache%202-red.svg)](LICENSE)![python version](https://img.shields.io/badge/python-3.6+-orange.svg)
## 近期贡献者
## 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)
## 快速开始
## Quick Start
* 请确保您按照[安装文档](./docs/zh_CN/install.md)的说明正确安装了PaddlePaddle和PaddleGAN
* Please refer [install](./docs/en_US/install.md) to ensure you sucessfully installed PaddlePaddle and PaddleGAN.
* 通过ppgan.apps接口直接使用应用:
* Get started through ppgan.app interface:
```python
from ppgan.apps import RealSRPredictor
sr = RealSRPredictor()
sr.run("docs/imgs/monarch.png")
```
```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)
* 更多应用的使用请参考[ppgan.apps API](./docs/zh_CN/apis/apps.md)
* 更多训练、评估教程:
* [数据准备](./docs/zh_CN/data_prepare.md)
* [训练/评估/推理教程](./docs/zh_CN/get_started.md)
## Model Tutorial
## 经典模型实现
* [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)
* [Pixel2Pixel](./docs/zh_CN/tutorials/pix2pix_cyclegan.md)
* [CycleGAN](./docs/zh_CN/tutorials/pix2pix_cyclegan.md)
* [PSGAN](./docs/zh_CN/tutorials/psgan.md)
* [First Order Motion Model](./docs/zh_CN/tutorials/motion_driving.md)
* [FaceParsing](./docs/zh_CN/tutorials/face_parse.md)
* [AnimeGANv2](./docs/zh_CN/tutorials/animegan.md)
* [U-GAT-IT](./docs/zh_CN/tutorials/ugatit.md)
## Composite Application
## 复合应用
* [Video restore](./docs/zh_CN/tutorials/video_restore.md)
* [视频修复](./docs/zh_CN/tutorials/video_restore.md)
## Examples
## 在线教程
您可以通过[人工智能学习与实训社区AI Studio](https://aistudio.baidu.com/aistudio/index) 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](https://aistudio.baidu.com/aistudio/projectdetail/1161285)|
|表情动作迁移-当苏大强唱起unravel |[点击体验](https://aistudio.baidu.com/aistudio/projectdetail/1048840)|
## 效果展示
### 图片变换
### Image Translation
<div align='center'>
<img src='./docs/imgs/horse2zebra.gif'width='700' height='200'/>
</div>
### 老视频修复
### Old video restore
<div align='center'>
<img src='./docs/imgs/color_sr_peking.gif' width='700'/>
</div>
### 动作迁移
### Motion driving
<div align='center'>
<img src='./docs/imgs/first_order.gif' width='700'/>
<img src='./docs/imgs/first_order.gif' width='700'>
</div>
### 超分辨率
### Super resolution
<div align='center'>
<img src='./docs/imgs/sr_demo.png'width='700' height='250'/>
</div>
### 妆容迁移
### Makeup shifter
<div align='center'>
<img src='./docs/imgs/makeup_shifter.png'width='700' height='250'/>
</div>
### 人脸动漫化
### Face cartoonization
<div align='center'>
<img src='./docs/imgs/ugatit.png'width='700' height='250'/>
</div>
### 照片动漫化
### Photo animation
<div align='center'>
<img src='./docs/imgs/animeganv2.png'width='700' height='250'/>
</div>
## 版本更新
## Changelog
- 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。
- 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.
## 欢迎加入PaddleGAN技术交流群
## Community
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!
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 特别兴趣小组(Special Interest Group)
最早于1961年被[ACM(Association for Computing Machinery)](https://en.wikipedia.org/wiki/Association_for_Computing_Machinery)首次提出并使用,国际顶尖开源组织包括[Kubernates](https://kubernetes.io/)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 Special Interest Group(SIG)
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。
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~
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。
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.
SIG贡献:
We are continuing to recruit developers interested and capable to join us building this project and explore more useful and interesting applications together.
- [zhen8838](https://github.com/zhen8838): 贡献AnimeGANv2.
- [Jay9z](https://github.com/Jay9z): 贡献DCGAN的示例、修改安装文档等。
- [HighCWu](https://github.com/HighCWu): 贡献c-DCGAN和WGAN,以及对`paddle.vision.datasets`数据集的支持。
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`.
## 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](docs/zh_CN/contribute.md)
## Contributing
## 许可证书
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).
本项目的发布受[Apache 2.0 license](LICENSE)许可认证。
## License
PaddleGAN is released under the [Apache 2.0 license](LICENSE).
English | [简体中文](./README.md)
简体中文 | [English](./README.md)
# PaddleGAN
PaddleGAN provides developers with high-performance implementation of classic and SOTA Generative Adversarial Networks, and support developers to quickly build, train and deploy GANs for academic, entertainment and industrial usage.
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-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 one the research area in deep learning that AI researchers are most concerned about.
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。
<div align='center'>
<img src='./docs/imgs/ppgan.jpg'>
......@@ -13,119 +13,130 @@ GAN-Generative Adversarial Network, was praised by "the Father of Convolutional
[![License](https://img.shields.io/badge/license-Apache%202-red.svg)](LICENSE)![python version](https://img.shields.io/badge/python-3.6+-orange.svg)
## 近期贡献者
## 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
## 快速开始
* Please refer [install](./docs/en_US/install.md) to ensure you sucessfully installed PaddlePaddle and PaddleGAN.
* 请确保您按照[安装文档](./docs/zh_CN/install.md)的说明正确安装了PaddlePaddle和PaddleGAN
* Get started through ppgan.app interface:
* 通过ppgan.apps接口直接使用应用:
```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)
```python
from ppgan.apps import RealSRPredictor
sr = RealSRPredictor()
sr.run("docs/imgs/monarch.png")
```
## Model Tutorial
* 更多应用的使用请参考[ppgan.apps API](./docs/zh_CN/apis/apps.md)
* 更多训练、评估教程:
* [数据准备](./docs/zh_CN/data_prepare.md)
* [训练/评估/推理教程](./docs/zh_CN/get_started.md)
* [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)
## 经典模型实现
## Composite Application
* [Pixel2Pixel](./docs/zh_CN/tutorials/pix2pix_cyclegan.md)
* [CycleGAN](./docs/zh_CN/tutorials/pix2pix_cyclegan.md)
* [PSGAN](./docs/zh_CN/tutorials/psgan.md)
* [First Order Motion Model](./docs/zh_CN/tutorials/motion_driving.md)
* [FaceParsing](./docs/zh_CN/tutorials/face_parse.md)
* [AnimeGANv2](./docs/zh_CN/tutorials/animegan.md)
* [U-GAT-IT](./docs/zh_CN/tutorials/ugatit.md)
* [Video restore](./docs/zh_CN/tutorials/video_restore.md)
## 复合应用
## Examples
* [视频修复](./docs/zh_CN/tutorials/video_restore.md)
### Image Translation
## 在线教程
您可以通过[人工智能学习与实训社区AI Studio](https://aistudio.baidu.com/aistudio/index) 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](https://aistudio.baidu.com/aistudio/projectdetail/1161285)|
|表情动作迁移-当苏大强唱起unravel |[点击体验](https://aistudio.baidu.com/aistudio/projectdetail/1048840)|
## 效果展示
### 图片变换
<div align='center'>
<img src='./docs/imgs/horse2zebra.gif'width='700' height='200'/>
</div>
### Old video restore
### 老视频修复
<div align='center'>
<img src='./docs/imgs/color_sr_peking.gif' width='700'/>
</div>
### Motion driving
### 动作迁移
<div align='center'>
<img src='./docs/imgs/first_order.gif' width='700'>
<img src='./docs/imgs/first_order.gif' width='700'/>
</div>
### Super resolution
### 超分辨率
<div align='center'>
<img src='./docs/imgs/sr_demo.png'width='700' height='250'/>
</div>
### Makeup shifter
### 妆容迁移
<div align='center'>
<img src='./docs/imgs/makeup_shifter.png'width='700' height='250'/>
</div>
### Face cartoonization
### 人脸动漫化
<div align='center'>
<img src='./docs/imgs/ugatit.png'width='700' height='250'/>
</div>
### Photo animation
### 照片动漫化
<div align='center'>
<img src='./docs/imgs/animeganv2.png'width='700' height='250'/>
</div>
## Changelog
## 版本更新
- 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.
- 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。
## Community
## 欢迎加入PaddleGAN技术交流群
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!
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!
<div align='center'>
<img src='./docs/imgs/qq.png'width='250' height='300'/>
</div>
### PaddleGAN Special Interest Group(SIG)
### PaddleGAN 特别兴趣小组(Special Interest Group)
最早于1961年被[ACM(Association for Computing Machinery)](https://en.wikipedia.org/wiki/Association_for_Computing_Machinery)首次提出并使用,国际顶尖开源组织包括[Kubernates](https://kubernetes.io/)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~
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。
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.
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。
We are continuing to recruit developers interested and capable to join us building this project and explore more useful and interesting applications together.
SIG贡献:
SIG contributions:
- [zhen8838](https://github.com/zhen8838): 贡献AnimeGANv2.
- [Jay9z](https://github.com/Jay9z): 贡献DCGAN的示例、修改安装文档等。
- [HighCWu](https://github.com/HighCWu): 贡献c-DCGAN和WGAN,以及对`paddle.vision.datasets`数据集的支持。
- [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`.
## 贡献代码
## Contributing
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](docs/zh_CN/contribute.md)
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).
## 许可证书
## License
PaddleGAN is released under the [Apache 2.0 license](LICENSE).
本项目的发布受[Apache 2.0 license](LICENSE)许可认证。
......@@ -120,7 +120,7 @@ class DAINPredictor(BasePredictor):
if not os.path.exists(os.path.join(frame_path_combined, vidname)):
os.makedirs(os.path.join(frame_path_combined, vidname))
for i in range(frame_num - 1):
for i in tqdm(range(frame_num - 1)):
first = frames[i]
second = frames[i + 1]
first_index = int(first.split('/')[-1].split('.')[-2])
......
Markdown is supported
0% .
You are about to add 0 people to the discussion. Proceed with caution.
先完成此消息的编辑!
想要评论请 注册