Waymo open dataset
The Waymo Open Dataset is comprised of high resolution sensor data collected by Waymo self-driving cars in a wide variety of conditions. We are releasing this dataset publicly to aid the research community in making advancements in machine perception and self-driving technology.
Organizations using or interested in using the resource:
Contributor(s):
Tags: autonomous, data, lidar, camera
Categories: Données, Communauté
Theme: Voiture Connectée, Données ouvertes, Navettes autonomes, Logiciel Libre
Referent:
Key people to solicit:
Other related common: Lyft Dataset from Lidar camera
Wealth sought:
Required skills:
Community of interest: Communauté autour des navettes autonomes, Communauté autour des données ouvertes, Communauté Voiture Connectée
License:
Terms of Service (TOS):
Level of development:
Link to my actions board:
Link to my cloud, wiki, drive…:
Needs:
Next step:
Documentation of the experimentations: The Waymo Open Dataset currently contains lidar and camera data from 1,000 segments (20s each). We plan to continuously grow this dataset. Here is what is currently included:
- 1,000 segments of 20s each, collected at 10Hz (200,000 frames) in diverse geographies and conditions
- Sensor data
- 1 mid-range lidar
- 4 short-range lidars
- 5 cameras (front and sides)
- Synchronized lidar and camera data
- Lidar to camera projections
- Sensor calibrations and vehicle poses
- Labeled data
- Labels for 4 object classes - Vehicles, Pedestrians, Cyclists, Signs
- High-quality labels for lidar data in all 1,000 segments
- 12M 3D bounding box labels with tracking IDs on lidar data
- High-quality labels for camera data in 100 segments (more to be added soon)
- 1.2M 2D bounding box labels with tracking IDs on camera data
- Code
- Access the GitHub repo here
This data is licensed for non-commercial use. You can find the license agreement here.
While this dataset is not reflective of the full capabilities of our sensor system and is only a fraction of the data on which Waymo’s self-driving system is trained, we believe that for research purposes this large, diverse and high-quality dataset is extremely valuable.
Other informations
List of the actors using or willing of using this common: aucun pour le moment
List of the workshop reports related to this common: