The codebase of the CVPR'20 paper, titled ``Discovering Synchronized Subsets of Sequences: A Large Scale Solution''.
If you use this code in your research papers, please cite the work as follows.
author = {Sariyanidi, Evangelos and Zampella, Casey J. and Bartley, Keith G. and Herrington, John D. and Satterthwaite, Theodore D. and Schultz, Robert T. and Tunc, Birkan},
title = {Discovering Synchronized Subsets of Sequences: A Large Scale Solution},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
The SyncRef software runs on python (python 3) and is installed as follows. (We assume that pip3 is installed on your system.) Optionally, you can install on a virtual environment by running the following two commands prior to installation:
virtualenv -p python3 syncrefenv
source syncrefenv/bin/activate
To install SyncRef, simply clone this repository and run
chmod +x INSTALL.sh
./INSTALL.sh
To run a demo of the Syncref software, you can simply excute the command
python demo.py
If you installed on a virtual environment, make sure that you activated the virtual environment prior to running the demo by executing the following command
source syncrefenv/bin/activate
If you successfully run the software, you should see a figure depicting the identified synchronized sequences and the run time of the algorithm printed on the command line.
We have tested with the following verions
cython 0.29.16
numpy 1.18.2
pandas 1.0.3
sklearn 0.22.2.post1
matplotlib 3.2.1
scipy 1.4.1