This code was used for the generation of the dataset CARLASENCES, paper
Andreas Kloukiniotis, Andreas Papandreou , Christos Anagnostopoulos, Aris Lalos, Petros Kapsalas , Duongvan Nguyen, Konstantinos Moustakas,”CarlaScenes: A synthetic dataset for odometry in autonomous driving”, CVPR 2022 Workshop on Autonomous Driving
The IP of the FTP server to download the dataset is ftp://195.251.58.20:60521
- Run python multi_data_generator.py
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Install conda
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conda env create --name
$conda name$ -f carla_to_bag/env.yml -
Replace line 258 from /home/andreas/.local/lib/python2.7/site-packages/pykitti.raw.py:
- t = dt.datetime.strptime(line[:-4], '%Y-%m-%d %H:%M:%S.%f') -> t = line
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Type python carla_to_bag/carla_to_bag.py -h for the documentation
- Example : python carla_to_bag/carla_to_bag.py -d path_to_ego/../Town03_15_09_2021_14_12_09_to_keep/ego0/ -t 2021_09_15 -r 0003 -f 10
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To align poses between vloam and ground truth from carla data type:
- python carla_to_bag/align_poses.py -h for the documentation
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To evaluate results using evo, move LO1.txt, VO1.txt and MO1.txt and aligned_poses from vloam ros results to evo folder and type:
- evo_traj kitti MO1.txt VO1.txt LO1.txt --ref=aligned_poses.txt -p --plot_mode=xyz -as
To run the files for ScenarioRunner follow [https://carla-scenariorunner.readthedocs.io/en/latest/]
- Carla Simular [https://github.com/carla-simulator/carla]
- Pykitti [https://github.com/utiasSTARS/pykitti]
- Countering Adversarial Attacks on Autonomous Vehicles Using Denoising Techniques: A Review
- Deep multi-modal data analysis and fusion for robust scene understanding in CAVs