The AU-AIR is a multi-modal aerial dataset captured by a UAV. Having visual data, object annotations, and flight data (time, GPS, altitude, IMU sensor data, velocities), AU-AIR meets vision and robotics for UAVs.
https://bozcani.github.io/auairdataset
- 8 raw RGB videos (more than 2 hours in total)
- 32,283 extracted and labelled frames
- Bounding box annotations for eight objects related to traffic:
- human, car, van, truck, bike, motorbike, bus, trailar
- Time, GPS, altitude, IMU sensor data and linear velocities of the drone are avaliable for each extracted frame.
Please download both the AU-AIR images and annotations to run the demo and use the API:
Images: https://drive.google.com/open?id=1pJ3xfKtHiTdysX5G3dxqKTdGESOBYCxJ (2.2 GB)
Annotations: https://drive.google.com/open?id=1boGF0L6olGe_Nu7rd1R8N7YmQErCb0xA (3.9 MB)
You will need common dependencies like numpy and opencv.
To install the package from source, simply clone or download the repository to your machine
git clone https://github.com/bozcani/auairdataset
cd auairdataset
python setup.py install
[1] I. Bozcan and E. Kayacan, "AU-AIR: A Multi-modal Unmanned Aerial Vehicle Dataset for Low Altitude Traffic Surveillance", submitted to IEEE International Conference on Robotics and Automation 2020.