Total-Text is a text detection dataset consisting of 1,555 images covering more than three different text orientations (horizontal, multi-directional, and curved), which can be used to solve problems related to arbitrary shape text recognition. The training set contains 1,255 images and the test set contains 300 images.

Citation

@article{CK2019,
author    = {Chee Kheng Ch’ng and
Chee Seng Chan and
Chenglin Liu},
title     = {Total-Text: Towards Orientation Robustness in Scene Text Detection},
journal   = {International Journal on Document Analysis and Recognition (IJDAR)},
volume    = {23},
pages     = {31-52},
year      = {2020},
doi       = {10.1007/s10032-019-00334-z},
}