MODNet: Trimap-Free Portrait Matting in Real Time

MODNet is a model for real-time portrait matting with only RGB image input.

MODNet是一个仅需RGB图片输入的实时人像抠图模型。

Commercial Solution (商用方案) | Research Demo | Arxiv Preprint | Supplementary Video

Commercial Solution (商用方案)

Our commercial solution for portrait matting is coming!
我们的人像抠图商用方案来了！

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 the Beta version of our portrait image matting online via this website.
(As our current server for testing is hosted in China, your access may be delayed.)
现在，您可以通过此网站在线使用我们的图片抠像测试版。

The commercial API interface for portrait image matting will be available soon.
用于图片抠像的商用API接口即将推出。

If you are interest in a portrait image matting SDK, please contact business@sight-x.com.
如果您对图片抠像SDK感兴趣，请联系business@sight-x.com。

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:

Portrait Video Matting Solution (视频抠像方案)

Stay tuned.
敬请期待。

Research Demo

All the models behind the following demos are trained on the datasets mentioned in our paper.

Portrait Image Matting

We provide an online Colab demo for portrait image matting.
It allows you to upload portrait images and predict/visualize/download the alpha mattes.

Portrait Video Matting

We provide two real-time portrait video matting demos based on WebCam. When using the demo, you can move the WebCam around at will. If you have an Ubuntu system, we recommend you to try the offline demo to get a higher fps. Otherwise, you can access the online Colab demo.
We also provide an offline demo that allows you to process custom videos.

Community

We share some cool applications/extentions of MODNet built by the community.

There are some resources about MODNet from the community.

Code

We provide the code 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.

PPM Benchmark

The PPM benchmark will be released in a separate repository PPM.

License

All resources in this repository (code, models, demos, etc.) are released under the Creative Commons Attribution NonCommercial ShareAlike 4.0 license.
The license will be changed to allow commercial use after our paper is accepted.

Acknowledgement

We thank
@eyaler, @manthan3C273, @yarkable, @jkjung-avt,
the Gradio team, What's AI YouTube Channel, Louis Bouchard's Blog,
for their contributions to this repository or their cool applications/extentions/resources of MODNet.

Citation

If this work helps your research, please consider to cite:

@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},
}

Contact

This repository is currently maintained by Zhanghan Ke (@ZHKKKe).
For commercial questions, please contact business@sight-x.com.
For research questions, please contact kezhanghan@outlook.com.

sarvex/MODNet

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