Download the repo and create the virtual environment by following commands
conda create --name ULT --file spec-env.txt
conda activate ULT
pip install tensorflow-gpu==2.3
pip install opencv-python
pip install pandas
pip install parse
InferenceDemo.ipynb
We do not own the copyright of the dataset used in this repo.
Below is a summary table of the datasets used in this work along with a link from which they can be downloaded:
| Dataset | URL |
|---|---|
| DIBCO 2009 | http://users.iit.demokritos.gr/~bgat/DIBCO2009/benchmark/ |
| DIBCO 2010 | http://users.iit.demokritos.gr/~bgat/H-DIBCO2010/benchmark/ |
| DIBCO 2011 | http://utopia.duth.gr/~ipratika/DIBCO2011/benchmark/ |
| DIBCO 2012 | http://utopia.duth.gr/~ipratika/HDIBCO2012/benchmark/ |
| DIBCO 2013 | http://utopia.duth.gr/~ipratika/DIBCO2013/benchmark/ |
| DIBCO 2014 | http://users.iit.demokritos.gr/~bgat/HDIBCO2014/benchmark/ |
| DIBCO 2016 | http://vc.ee.duth.gr/h-dibco2016/benchmark/ |
| DIBCO 2017 | https://vc.ee.duth.gr/dibco2017/ |
| DIBCO 2018 | https://vc.ee.duth.gr/h-dibco2018/ |
| Monk Cuper Set | https://www.ai.rug.nl/~sheng/ |
For any paper-related questions, please feel free to contact leedengsh@gmail.com.