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In the realm of autonomous transportation, there have been many initiativesfor open-sourcing self-driving cars datasets, but much less for alternativemethods of transportation such as trains. In this paper, we aim to bridge thegap by introducing FRSign, a large-scale and accurate dataset for vision-basedrailway traffic light detection and recognition. Our recordings were made onselected running trains in France and benefited from carefully hand-labeledannotations. An illustrative dataset which corresponds to ten percent of theacquired data to date is published in open source with the paper. It containsmore than 100,000 images illustrating six types of French railway trafficlights and their possible color combinations, together with the relevantinformation regarding their acquisition such as date, time, sensor parameters,and bounding boxes. This dataset is published in open-source at the address\url{https://frsign.irt-systemx.fr}. We compare, analyze various properties ofthe dataset and provide metrics to express its variability. We also discussspecific challenges and particularities related to autonomous trains incomparison to autonomous cars.

FRSign: A Large-Scale Traffic Light Dataset for Autonomous Trains