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<h2 align="center">MODNet: Trimap-Free Portrait Matting in Real Time</h2>
<div align="center"><i>MODNet: Real-Time Trimap-Free Portrait Matting via Objective Decomposition (AAAI 2022)</i></div>
<img src="doc/gif/homepage_demo.gif" width="100%">
<div align="center">MODNet is a model for <b>real-time</b> portrait matting with <b>only RGB image input</b>.</div>
<div align="center">MODNet是一个<b>仅需RGB图片输入</b>的<b>实时</b>人像抠图模型。</div>
<div align="center">MODNet is a model for <b>real-time</b> portrait matting with <b>only RGB image input</b></div>
<div align="center">MODNet是一个<b>仅需RGB图片输入</b>的<b>实时</b>人像抠图模型</div>
<br />
<p align="center">
<a href="#online-solution-在线方案">Online Solution (在线方案)</a> |
<a href="#online-application-在线应用">Online Application (在线应用)</a> |
<a href="#research-demo">Research Demo</a> |
<a href="https://arxiv.org/pdf/2011.11961.pdf">Arxiv Preprint</a> |
<a href="https://arxiv.org/pdf/2011.11961.pdf">AAAI 2022 Paper</a> |
<a href="https://youtu.be/PqJ3BRHX3Lc">Supplementary Video</a>
</p>
@ -24,43 +26,16 @@
<a href="#contact">Contact</a>
</p>
**News:** We create a repository for our new model [MODNet-V](https://github.com/ZHKKKe/MODNet-V) that focuses on faster and better portrait video matting.
**News:** The PPM-100 benchmark is released in [this repository](https://github.com/ZHKKKe/PPM).
---
## Online Solution (在线方案)
## Online Application (在线应用)
The online solution for portrait matting is coming!
人像抠图在线方案发布了！
A **Single** model! Only **7M**! Process **2K** resolution image with a **Fast** speed on common PCs or Mobiles! **Beter** performance than research demos!
Please try online portrait image matting via [this website](https://sight-x.cn/portrait_matting)!
### Portrait Image Matting Solution (图片抠像方案)
A **Single** Model! Only **7M**! Process **2K** resolution image with a **Fast** speed on common PCs or Mobiles!
**单个**模型！大小仅为**7M**！可以在普通PC或移动设备上**快速**处理具有**2K**分辨率的图像！
Now you can try our **portrait image matting** online via [this website](https://sight-x.cn/portrait_matting).
现在，您可以通过[此网站](https://sight-x.cn/portrait_matting)在线使用我们的**图片抠像**功能。
<img src="doc/gif/commercial_image_matting_website.gif" width='100%'>
<!-- You can also scan the QR code below to try the WeChat Mini-Program based on our model.
您也可以扫描下方二维码尝试基于我们模型的微信小程序。 -->
<!-- Here are two example videos processed (frame independently) via our **portrait image matting** model:
我们**图片抠像**模型逐帧单独处理的两个示例视频:
<img src="doc/gif/commercial_image_matting_model_result.gif" width='100%'> -->
<!-- ### Portrait Video Matting Solution (视频抠像方案)
Stay tuned.
敬请期待。
-->
<!-- --- -->
**单个**模型！大小仅为**7M**！可以在普通PC或移动设备上**快速**处理具有**2K**分辨率的图像！效果比研究示例**更好**！
请通过[此网站](https://sight-x.cn/portrait_matting)在线尝试图片抠像！
## Research Demo
@ -111,7 +86,7 @@ We provide the [code](src/trainer.py) of MODNet training iteration, including:
- **Supervised Training**: Train MODNet on a labeled matting dataset
- **SOC Adaptation**: Adapt a trained MODNet to an unlabeled dataset
In the code comments, we provide examples for using the functions.
In code comments, we provide examples for using the functions.
## PPM Benchmark
@ -119,13 +94,12 @@ The PPM benchmark is released in a separate repository [PPM](https://github.com/
## License
All resources in this repository (code, models, demos, *etc.*) are released under the [Creative Commons Attribution NonCommercial ShareAlike 4.0](https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode) license.
The license will be changed to allow commercial use after our paper is accepted.
The code, models, and demos in this repository (excluding GIF files under the folder `doc/gif`) are released under the [Apache License 2.0](https://www.apache.org/licenses/LICENSE-2.0) license.
## Acknowledgement
- We thank
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;[@eyaler](https://github.com/eyaler), [@manthan3C273](https://github.com/manthan3C273), [@yarkable](https://github.com/yarkable), [@jkjung-avt](https://github.com/jkjung-avt),
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;[@yzhou0919](https://github.com/yzhou0919), [@eyaler](https://github.com/eyaler), [@manthan3C273](https://github.com/manthan3C273), [@yarkable](https://github.com/yarkable), [@jkjung-avt](https://github.com/jkjung-avt), [@manzke](https://github.com/manzke),
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;[the Gradio team](https://github.com/gradio-app/gradio), [What's AI YouTube Channel](https://www.youtube.com/channel/UCUzGQrN-lyyc0BWTYoJM_Sg), [Louis Bouchard's Blog](https://www.louisbouchard.ai),
for their contributions to this repository or their cool applications/extentions/resources of MODNet.
@ -134,12 +108,11 @@ for their contributions to this repository or their cool applications/extentions
If this work helps your research, please consider to cite:
```bibtex
@article{MODNet,
author = {Zhanghan Ke and Kaican Li and Yurou Zhou and Qiuhua Wu and Xiangyu Mao and Qiong Yan and Rynson W.H. Lau},
title = {Is a Green Screen Really Necessary for Real-Time Portrait Matting?},
journal={ArXiv},
volume={abs/2011.11961},
year = {2020},
@InProceedings{MODNet,
author = {Zhanghan Ke and Jiayu Sun and Kaican Li and Qiong Yan and Rynson W.H. Lau},
title = {MODNet: Real-Time Trimap-Free Portrait Matting via Objective Decomposition},
booktitle = {AAAI},
year = {2022},
}
```
@ -147,3 +120,5 @@ If this work helps your research, please consider to cite:
## Contact
This repository is currently maintained by Zhanghan Ke ([@ZHKKKe](https://github.com/ZHKKKe)).
For questions, please contact `kezhanghan@outlook.com`.
<img src="doc/gif/commercial_image_matting_model_result.gif" width='100%'>