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Papers

MMOCR: A Comprehensive Toolbox for Text Detection, Recognition and Understanding

2021-08-14 · Zhanghui Kuang, Hongbin Sun, Zhizhong Li, Xiaoyu Yue, Tsui Hin Lin, Jianyong Chen, Huaqiang Wei, Yiqin Zhu, Tong Gao, Wenwei Zhang, Kai Chen, Wayne Zhang, Dahua Lin

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.

📄 PDF Abstract BibTeX arXiv:2108.06543

Code (1)

open-mmlab/mmocr 공식 구현 pytorch

Tasks

Key Information Extractionnamed-entity-recognitionNamed Entity RecognitionNamed Entity Recognition (NER)Optical Character Recognition (OCR)Text Detection

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