Downloads
For full datasets, please see the individual dataset pages.
Sample Datasets
Sample datasets containing small amounts of data from all sensors (all starting from the same location) can be downloaded here:
Oxford RobotCar Dataset SDK
The core software needed to parse data in the Oxford Radar RobotCar Dataset, as well as example usage, has newly been included in the original Oxford RobotCar Dataset SDK. So in addition to previously available MATLAB and Python functions for loading and displaying data, including Bayer demosaicing and undistorting images, the SDK now includes MATLAB and Python functions for:
- Parsing raw Radar data -
LoadRadar
andradar.load_radar
- Parsing raw Velodyne data -
LoadVelodyneRaw
andvelodyne.load_velodyne_raw
- Parsing binary Velodyne data -
LoadVelodyneBinary
andvelodyne.load_velodyne_binary
- Converting polar radar data to Cartesian form -
RadarPolarToCartesian
andradar.radar_polar_to_cartesian
- Converting raw Velodyne sensor data into a pointcloud -
VelodyneRawToPointcloud
andvelodyne.velodyne_raw_to_pointcloud
As well as:
- Example radar data viewiers -
PlayRadar
andplay_radar.py
- Example Velodyne data viewers -
PlayVelodyne
andplay_velodyne.py
- Updated extrinisics for new sensors (
radar.txt
,velodyne_left.txt
,velodyne_right.txt
) - Updated
BuildPointcloud
andbuild_pointcloud.py
for handling newly included Velodyne HDL-32E data
The Oxford RobotCar Dataset SDK can be found here:
https://github.com/ori-mrg/robotcar-dataset-sdk
Oxford Radar RobotCar Dataset SDK
Building on top of the base SDK we provide additional specialisations for the new dataset which can be found here: https://github.com/oxford-robotics-institute/radar-robotcar-dataset-sdk
Which includes:
Download Script
A python download script for the Oxford Radar RobotCar Dataset which:
- Avoids the need for manually selecting individual files for download from the website
- Allows filtering by dataset
- Allows filtering by sensor
Optimised Deep Learning Data Loaders - coming soon…
To aid development we also plan to provide optimised example parsers, dataloaders and usage for using the radar data and ground truth odometry in Tensorflow, PyTorch and in OpenCV. If you would like access to these more urgently please get in touch and we will prioritise their release.