Carla Dataset Tools (Active Collecting Integrated)

Data collection tools with active data acquisition strategy implemented for CARLA Simulator.

Installation

Download Carla version 0.9.14 here.

Environment

pip3 install -r requirements.txt

# Write following env into your bashrc or zshrc
export CARLA_ROOT=[PATH_TO_YOUR_CARLA]
export PYTHONPATH=$PYTHONPATH:$CARLA_ROOT/PythonAPI/carla/dist/[YOUR_CARLA_EGG_NAME]:$CARLA_ROOT/PythonAPI/carla/

Usage

Data Recording

Execute the command in the root directory:

python3 data_recorder.py

Dataset Preparing

Image, lidar dataset

We support image data as YOLO format, lidar data as OpenPCDet format.

Execute the command in the root directory:

python format_helper.py -s {raw_data/record...}

Lidar Data Visualization

Execute the command in the root directory to visualize lidar cloud point:

python label_tools/kitti_lidar/lidar_label_view.py -d {local_semantic_lidar.npy}

Data

Data can be collected by just executing python3 data_recorder.py. The configuration can be changed by modifying the files in the folder config.

Dataset Name	Total Frames	Map
D1	900	Town02
D1-S	579	Town02
D2	900	Town02
V	375	Town03

Result

Dataset Name	Vehicle	Training Time	mAP
D1	996	14min40s	0.508
D1-S	996	11min32s	0.492
D2	1835	16min07s	0.647

Contributing

Thank you for your interest in contributing to this project! Contributions are highly appreciated and help improve the project for everyone. If you have any questions or need further assistance, please feel free to open an issue.

Acknowledgments

• CARLA Simulator
• CARLA Ros Bridge
• CARLA_INVS

Citation

@article{Lai2023ActiveDA,
 title={Active Data Acquisition in Autonomous Driving Simulation},
 author={Jianyu Lai and Zexuan Jia and Boao Li},
 journal={ArXiv},
 year={2023},
 volume={abs/2306.13923}
}

Future Work

To validate the correctness of the strategy, we'd better try multiple algorithms:

• YOLO
• CenterPoint