Published November 8, 2024
| Version v1
Dataset
Open
FlyingArUco v2 Dataset
Description
This is a synthetic dataset composed of images containing various ArUco markers overlaid on backgrounds sampled from the MS COCO 2017 training dataset, used to train the models in DeepArUco++: improved detection of square fiducial markers in challenging lighting conditions. The contents of each file are the following:
- flyingarucov2.tar.gz: Base FlyingArUco v2 images, without any augmentation applied. For each image a .json file is provided with the ground-truth positions of each marker and encoded IDs.
- det_luma.tar.gz: Detection dataset built from the base FlyingArUco v2 dataset, using only (simulated) changes in lighting in order to obtain augmented samples.
- det_luma_b.tar.gz: Detection dataset built from the base FlyingArUco v2 dataset, using (simulated) changes in lighting and blur in order to obtain augmented samples.
- det_luma_bc.tar.gz: Detection dataset built from the base FlyingArUco v2 dataset, using (simulated) changes in lighting, blur and color shift in order to obtain augmented samples.
- det_luma_bn.tar.gz: Detection dataset built from the base FlyingArUco v2 dataset, using (simulated) changes in lighting, blur and gaussian noise in order to obtain augmented samples.
- det_luma_bnc.tar.gz: Detection dataset built from the base FlyingArUco v2 dataset, using (simulated) changes in lighting, blur, gaussian noise and color shift in order to obtain augmented samples.
- reg_luma_bc.tar.gz: Corner refinement (regression)/marker decoding dataset built from the det_luma_bc detection dataset.
Files
Files
(12.2 GB)
| Name | Size | Download all |
|---|---|---|
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md5:72d283c7c8446a3befafb704c67577cc
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2.3 GB | Download |
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md5:e74878608440153c26146f359af18247
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2.2 GB | Download |
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md5:c911dd42bd8bd89ef08809fcc6b16399
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2.1 GB | Download |
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md5:5c8c24e4664ea0c35465b03f351347ca
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2.5 GB | Download |
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md5:327e8d03e40d2d6cfb9b2a2f8e703249
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2.5 GB | Download |
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md5:d8438f39385bfc989028d9c7d70ca0be
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277.7 MB | Download |
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md5:bc414a3bf416327c55cfe6181b66f7fd
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222.8 MB | Download |
Additional details
Related works
- Is described by
- Journal article: 10.1016/j.imavis.2024.105313 (DOI)
- Is part of
- Journal article: 10.1016/j.imavis.2024.105313 (DOI)