SynthMap+ (Traditional Chinese) Synthetic Train Data for ICDAR'25 MapText Competition
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Dataset of synthetic map images in traditional Chinese for the ICDAR'25 Competition on Historical Map Text Detection, Recognition, and Linking. Annotations and images follow the format described at the competition website. Please refer to [1] for the generation process and usage. We extend [1] to place text labels in horizontal and vertical writing directions. Train Annotations tc25synth_train.json Images train.zip Files tc25synth/train/*.jpg Tiles 45,000 Map Sheets - Words 296,348 Label Groups - Illegible Words 0 Truncated Words 0 Valid Words 296,348 [1] Lin, Y., & Chiang, Y. -Y. (2024). Hyper-local deformable transformers for text spotting on historical maps. In Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (pp. 5387-5397).
本数据集为面向ICDAR 2025历史地图文本检测、识别与关联竞赛的繁体中文合成地图图像数据集。 数据集的标注与图像格式严格遵循竞赛官网公布的规范。 有关本数据集的生成流程与使用方法，请参阅文献[1]。本工作对文献[1]的方法进行了拓展，支持横排与竖排两种书写方向的文本标签标注。 训练集 标注文件：tc25synth_train.json 图像文件：train.zip 文件存储路径：tc25synth/train/*.jpg 瓦片数量：45,000 地图幅数：无 总文本词数：296,348 标签组：无 难以识别文本词数：0 截断文本词数：0 有效文本词数：296,348 [1] Lin Y, Chiang Y-Y. 面向历史地图文本定位的超局部可变形Transformer（Hyper-local deformable transformers）[C]//第30届ACM SIGKDD知识发现与数据挖掘大会论文集. 2024: 5387-5397.
