- We have validated our system on Ubuntu 18.04 ubuntu release
- Installation of ROS: ROS or Melodic: ROS Install
- Requires OpenCV >= 4.4: OpenCV Linux Install
- Python 3.8
- CUDNN >= 7.0: cuDNN Archive
- Realsense libraries librealsense github
- Realsense ros-wrapper, we suggest users to build from source ros wapper
- YOLO Darknet here: Darknet
- Suggested dataset scale: 2000 images per class && corresponding 500 for validation, and 2000 background images without object in the FoV
- Labelling tool: labelimg && labelimg repo
-
2023 update
To save you some time, if you are only looking for
YOLO IN ROS
, please go directly to this repo. -
clone our repository into working space
cd ~/xx_ws/src
git clone https://github.com/PAIR-Lab/AUTO.git
- Modify
Go to here if Cuda Available
//uncomment the below if CUDA available
//this->mydnn.setPreferableBackend(cv::dnn::DNN_BACKEND_CUDA);
//this->mydnn.setPreferableTarget(cv::dnn::DNN_TARGET_CUDA);
and here
//change yolo custom weight file location, as well as the cfg file and name file
- Compile
cd ~/xx_ws
catkin_make
- Run
rosrun offb camera && rosrun offb track
#or can just write a launch file
@article{lo2021dynamic,
title={Dynamic Object Tracking on Autonomous UAV System for Surveillance Applications},
author={Lo, Li-Yu and Yiu, Chi Hao and Tang, Yu and Yang, An-Shik and Li, Boyang and Wen, Chih-Yung},
journal={Sensors},
volume={21},
number={23},
pages={7888},
year={2021},
publisher={MDPI}
}
Patrick Li-yu LO: [email protected]
Summer Chi Hao Yiu: [email protected]
Bryant Yu Tang: [email protected]