We present MMOCR-an open-source toolbox which provides a comprehensive pipeline for text detection and recognition, as well as their downstream tasks such as named entity recognition and key information extraction. MMOCR implements 14 state-of-the-art algorithms, which is significantly more than all the existing open-source OCR projects we are aware of to date. To facilitate future research and industrial applications of text recognition-related problems, we also provide a large number of trained models and detailed benchmarks to give insights into the performance of text detection, recognition and understanding. MMOCR is publicly released at https://github.com/open-mmlab/mmocr.
@article{arxiv.2108.06543,
title = {MMOCR: A Comprehensive Toolbox for Text Detection, Recognition and Understanding},
author = {Zhanghui Kuang and Hongbin Sun and Zhizhong Li and Xiaoyu Yue and Tsui Hin Lin and Jianyong Chen and Huaqiang Wei and Yiqin Zhu and Tong Gao and Wenwei Zhang and Kai Chen and Wayne Zhang and Dahua Lin},
journal= {arXiv preprint arXiv:2108.06543},
year = {2021}
}
Comments
Accepted to ACM MM (Open Source Competition Track)