Traffic images captured from UAVs for use in training Machine Vision Algorithms for traffic management
- 1. Universidad Francisco de Vitoria
- 2. Universidad Europea de Madrid
Description
If you use this dataset please cite this paper: Bemposta Rosende, S.; Ghisler, S.; Fernández-Andrés, J.; Sánchez-Soriano, J. Dataset: Traffic Images Captured from UAVs for Use in Training Machine Vision Algorithms for Traffic Management. Data 2022, 7, 53. https://doi.org/10.3390/data7050053
A dataset of road traffic images taken from unmanned aerial vehicles (UAV) with the purpose of being used to train artificial vision algorithms, among which those based on convolutional neural networks stand out.
Dataset is available and accessible in order to improve the performance of road traffic vision and management systems due to the lack of resources in this specific domain. The full description of the characteristics of the dataset, as well as its components and format, can be found here: https://www.mdpi.com/2306-5729/7/5/53
The dataset format is YOLO. Relevant data about the dataset:
|
Scenes |
Frames |
Targets |
Cars |
Motorbikes |
|
Regional road |
4.500 |
24.858 |
14.577 |
10.281 |
|
Urban intersection |
2.462 |
10.759 |
10.759 |
0 |
|
Rural road |
1.292 |
746 |
746 |
0 |
|
Split roundabout |
2.297 |
3.107 |
3.107 |
0 |
|
Roundabout (Far) |
1.814 |
71.819 |
64.844 |
6.975 |
|
Roundabout (Near) |
3.997 |
4.4039 |
43.569 |
470 |
|
Total |
15.070 |
155.328 |
137.602 |
17.726 |
Notes
Files
Regional_road.zip
Files
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