README.md

Fast User-Guided Video Object Segmentation by Interaction-and-Propagation Networks

Seoung Wug Oh, Joon-Young Lee, Ning Xu, Seon Joo Kim

CVPR 2019

Demo code with GUI interface.
paper

Requirements

• python 3.6
• pytorch 0.3.1
• davisinteractive
• matplotlib
• PyQt5

How to Use

Environment setup

conda create --name ivs python=3.6
source activate ivs

pip install PyQt5 matplotlib opencv-contrib-python pillow Cython
pip install davisinteractive

conda install pytorch=0.3.1 cuda90 -c pytorch
conda install torchvision

Download weights

wget -O I_e290.pth "https://www.dropbox.com/s/khx9hmtnqbzg634/I_e290.pth?dl=1"
wget -O P_e290.pth "https://www.dropbox.com/s/89heglbglig0g04/P_e290.pth?dl=1"

Run!

python gui.py -seq camel 

Test your own videos

Locate videos in ./sequences/[name] Run

python gui.py -seq [name]

Quantitative Evaluation

The GUI application in this repository is only for demo. The numbers in our paper will not be reproducable with the checkpoint included here. If you are interested in quantitative evaluation using DAVIS framework Please contact me by E-mail.

Reference

If you find our paper and repo useful, please cite our paper. Thanks!

Fast User-Guided Video Object Segmentation by Interaction-and-Propagation Networks
Seoung Wug Oh, Joon-Young Lee, Ning Xu, Seon Joo Kim
CVPR 2019

Terms of Use

This software is for non-commercial use only. The source code is released under the Attribution-NonCommercial-ShareAlike (CC BY-NC-SA) Licence (see this for details)