Generating training data from the Carla driving simulator in the KITTI dataset format
- Raw (unsynced+unrectified) and processed (synced+rectified) grayscale stereo sequences (0.5 Megapixels, stored in png format)
- Raw (unsynced+unrectified) and processed (synced+rectified) color stereo sequences (0.5 Megapixels, stored in png format)
- 3D Velodyne point clouds (100k points per frame, stored as binary float matrix)
- 3D GPS/IMU data (location, speed, acceleration, meta information, stored as text file)
- Calibration (Camera, Camera-to-GPS/IMU, Camera-to-Velodyne, stored as text file)
- 3D object tracklet labels (cars, trucks, trams, pedestrians, cyclists, stored as xml file)
This project expects the carla folder to be inside this project i.e PythonClient/carla-training-data/carla
## Running the client after running the Carla Server
$ python3 datageneration.py- KITTI Vision Benchmark Suite
KITTI website - Karlsruhe Institute of Technology
Karlsruhe Institute of Technology website - Toyota Technological Institute at Chicago Toyota Technological Institute website