Support code for the DeepArUco++ method. Work by Rafael Berral-Soler, Rafael Muñoz-Salinas, Rafael Medina-Carnicer and Manuel J. Marín-Jiménez.
NEW (07/03/2024): Shadow-ArUco dataset available at
NEW (06/11/2023): Try our method in this Google Colab notebook. Updated to DeepArUco++!
To detect markers locally use the demo.py script:
python demo.py <path to image> <output path>
Demo code along with pretrained models will be available soon. Some example predictions:
This dataset will be available soon. Some samples from the dataset:
Dataset available at
Some samples from the dataset:
If you find our work helpful for your research, please cite our publications:
@InProceedings{berral2023ibpria,
author = "Berral-Soler, Rafael
and Mu{\~{n}}oz-Salinas, Rafael
and Medina-Carnicer, Rafael
and Mar{\'i}n-Jim{\'e}nez, Manuel J.",
editor="Pertusa, Antonio
and Gallego, Antonio Javier
and S{\'a}nchez, Joan Andreu
and Domingues, In{\^e}s",
title = "DeepArUco: Marker Detection and Classification in Challenging Lighting Conditions",
booktitle = "Iberian Conference on Pattern Recognition and Image Analysis",
doi = {10.1007/978-3-031-36616-1_16},
year = "2023",
publisher = "Springer Nature Switzerland",
pages = "199--210",
isbn = "978-3-031-36616-1"
}
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