Published December 14, 2024
| Version v1
Dataset
Open
SynthMap+ (English) Synthetic Train Data for ICDAR'25 MapText Competition
Authors/Creators
-
1.
University of Minnesota
Description
Dataset of synthetic map images in English 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 provide grouping labels for location phrases.
| Train | |
| Annotations | en25synth_train.json |
| Images | train.zip |
| Files | en25synth/train/*.jpg |
| Tiles | 35,000 |
| Map Sheets | - |
| Words | 348,494 |
| Label Groups | 157,483 |
| Label Groups (Group Size > 1) | 133,955 |
| Illegible Words | 0 |
| Truncated Words | 0 |
| Valid Words | 348,494 |
[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).
Files
en25synth_train.json
Files
(38.8 GB)
| Name | Size | Download all |
|---|---|---|
|
md5:93f6f07f139eca0ad71fd1f45498e4de
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247.8 MB | Preview Download |
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md5:cfe6a8a5197fca41e7f158a41a48289c
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38.6 GB | Preview Download |
Additional details
Related works
- Cites
- Publication: 10.1145/3637528.3671589 (DOI)
- Is described by
- Publication: https://rrc.cvc.uab.es/?ch=32&com=tasks (URL)