To address the problem of scarcity and high annotation costs of rotated image table detection datasets, this chapter proposes a method for building a rotated image table detection dataset. Based on the ICDAR2019MTD modern table detection dataset, we refer to the annotation format of the DOTA dataset to create the TRR360D rotated table detection dataset, as shown in Table 4.1. The training set contains 600 rotated images and 977 annotated instances, and the test set contains 240 rotated images and 499 annotated instances. The DOTA\_360 evaluation metric is defined, and this dataset is available for future researchers to study rotated table detection algorithms and promote the development of table detection technology. The TRR360D rotated table detection dataset was created by constraining the starting point and annotation direction, and is publicly available at \url{https://github.com/vansin/TRR360D}.
翻译:为解决旋转图像表格探测数据集的稀缺性和高注解成本问题,本章提出了建立旋转图像表格检测数据集的方法。根据 ICDAR2019MTD 现代表格检测数据集,我们参考DORTA数据集的说明格式,以创建表4.1所示TRR360D 旋转的表格检测数据集。培训数据集包含600个旋转图像和977个附加说明实例,测试集包含240个旋转图像和499个附加说明实例。DOTA*360评估指标已经定义,该数据集可供未来的研究人员研究旋转的表格检测算法和促进表格检测技术的发展。TRR360D旋转的表格检测数据集是通过限制起始点和注解方向创建的,并公布在\url{https://github.com/vansin/TRR360D}。</s>