Balanced RAVEN dataset from the paper: 'Scale-Localized Abstract Reasoning', presented at CVPR 2021.
Tested on both linux and windows 10.
- python 2.7
- eventlet (windows)
- tqdm
- numpy=1.16.6
- scipy=1.2.3
- opencv-python=4.2.0.32
- pillow=6.2.2
To create the dataset, run:
python main.py --fair FAIR --save-dir DEST
- FAIR - bool, (0,1) generate the original RAVEN dataset or RAVEN-FAIR. default: 0.
- DEST - str, the destination of the directory to save the data. default: ./Datasets/
Original RAVEN will be created at <DEST>/RAVEN. RAVEN-FAIR will be created at <DEST>/RAVEN-F.
We thank the original creators of the RAVEN dataset: Chi Zhang, Feng Gao, Baoxiong Jia, Yixin Zhu, Song-Chun Zhu. The original code can be found at the repository: RAVEN.
We thank you for showing interest in our work. If our work was beneficial for you, please consider citing us using:
@inproceedings{benny2021scale,
title={Scale-localized abstract reasoning},
author={Benny, Yaniv and Pekar, Niv and Wolf, Lior},
booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
pages={12557--12565},
year={2021}
}
If you have any question, please feel free to contact us.