Tidak Ada Deskripsi

Peter Lin 8860031c3e Update comment 4 tahun lalu
dataset ee86e2636f Initialize 4 tahun lalu
doc 13cb499ece Improve ONNX compatibility 4 tahun lalu
images b14e735b43 Update teaser image 4 tahun lalu
model 13cb499ece Improve ONNX compatibility 4 tahun lalu
LICENSE d766f5b9c7 Update license 4 tahun lalu
README.md 23a968238e Update README.md 4 tahun lalu
export_onnx.py 8860031c3e Update comment 4 tahun lalu
export_torchscript.py ee86e2636f Initialize 4 tahun lalu
inference_images.py 3888ec833b Add missing import 4 tahun lalu
inference_speed_test.py 21702785a8 Add argument option for cpu support 4 tahun lalu
inference_utils.py ee86e2636f Initialize 4 tahun lalu
inference_video.py 4a2225e561 enable CPU load 4 tahun lalu
inference_webcam.py ee86e2636f Initialize 4 tahun lalu
requirements.txt ee86e2636f Initialize 4 tahun lalu

README.md

Real-Time High-Resolution Background Matting

Teaser

Official repository for the paper Real-Time High-Resolution Background Matting. Our model requires capturing an additional background image and produces state-of-the-art matting results at 4K 30fps and HD 60fps on an Nvidia RTX 2080 TI GPU.

 

Overview

 

Updates

  • [Dec 21 2020] We updated our project to MIT License, which permits commercial use!

 

Download

Model / Weights

Video / Image Examples

Datasets

  • VideoMatte240K (Coming soon)
  • PhotoMatte85 (Coming soon)

 

Demo

Scripts

We provide several scripts in this repo for you to experiment with our model. More detailed instructions are included in the files.

  • inference_images.py: Perform matting on a directory of images.
  • inference_video.py: Perform matting on a video.
  • inference_webcam.py: An interactive matting demo using your webcam.

Notebooks

Additionally, you can try our notebooks in Google Colab for performing matting on images and videos.

Virtual Camera

We provide a demo application that pipes webcam video through our model and outputs to a virtual camera. The script only works on Linux system and can be used in Zoom meetings. For more information, checkout:

Web Demo

Developers in the community has helped us build a web demo. See Community Projects section below.

 

Usage / Documentation

You can run our model using PyTorch, TorchScript, TensorFlow, and ONNX. For detail about using our model, please check out the Usage / Documentation page.

 

Training

Training code will be released upon acceptance of the paper.

 

Project members

* Equal contribution.

 

License

This work is licensed under the MIT License. If you use our work in your project, we would love you to include an acknowledgement and fill out our survey.

 

Community Projects

A list of projects built by third-party developers in the community. If you have a project to share, fill out this survey.