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To address the problem of scarcity and high annotation costs of rotated imagetable detection datasets, this paper proposes a method for building a rotatedimage table detection dataset. Based on the ICDAR2019MTD modern table detectiondataset, we refer to the annotation format of the DOTA dataset to create theTRR360D rotated table detection dataset. The training set contains 600 rotatedimages and 977 annotated instances, and the test set contains 240 rotatedimages and 499 annotated instances. The AP50(T<90) evaluation metric isdefined, and this dataset is available for future researchers to study rotatedtable detection algorithms and promote the development of table detectiontechnology. The TRR360D rotated table detection dataset was created byconstraining the starting point and annotation direction, and is publiclyavailable at https://github.com/vansin/TRR360D.

TRR360D: A dataset for 360 degree rotated rectangular box table detection