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：针对旋转图像表格检测数据集匮乏及标注成本高的问题，本文提出一种构建旋转图像表格检测数据集的方法。基于ICDAR2019MTD现代表格检测数据集，我们参考DOTA数据集的标注格式，创建了TRR360D旋转表格检测数据集，如表4.1所示。训练集包含600张旋转图像及977个标注实例，测试集包含240张旋转图像及499个标注实例。定义了DOTA_360评估指标，该数据集可供未来研究者研究旋转表格检测算法，推动表格检测技术的发展。TRR360D旋转表格检测数据集通过约束起点与标注方向生成，并在\url{https://github.com/vansin/TRR360D}公开提供。