Ros Package to access manipulate and process Raw KITTI dataset. In this Project there is sensor fusion, and some other perception is done. Once it is complete I will release project Manual. In current phase , once you execute this Project you should see something similiar to below picture.
Latest Commit;
Initial Version
Accept software from packages.ros.org.
sudo sh -c 'echo "deb http://packages.ros.org/ros/ubuntu $(lsb_release -sc) main" > /etc/apt/sources.list.d/ros-latest.list'
Set up keys
sudo apt-key adv --keyserver hkp://ha.pool.sks-keyservers.net:80 --recv-key 421C365BD9FF1F717815A3895523BAEEB01FA116
Debian up-to-date:
sudo apt-get update
Install full ROS version:
sudo apt-get install ros-kinetic-desktop-full
You will need to initialize rosdep:
sudo rosdep init
rosdep update
It's convenient if the ROS environment variables are automatically added to your bash session every time a new shell is launched:
echo "source /opt/ros/kinetic/setup.bash" >> ~/.bashrc source ~/.bashrc
cd catkin_ws/src
git clone https://github.com/jediofgever/ROS_Raw_Kitti_Player.git
cd ROS_Raw_Kitti_Player
git submodule update --init --recursive
cd .. && catkin_make
for the testing without installing maskrcnn and other dependencies;
, I provide obtained masks for scenario; 2011_09_26_drive_0052_sync Download files
for 0052 here and place it under your base directory, which should look something like this;
/home/atas/kitti_data/2011_09_26/2011_09_26_drive_0052_sync/
for a quick start using maskrcnn;
- maskrcnn that I used bases on Pytorch, and some other helper libs. A complete guide to install maskrcnn and requirements can be found here
- after you have maskrcnn on your system , download raw kitti images of the scenario that you would like to test. Maskrcnn provides a script to infer masks on rgb images under demo directory. I have modified that script to obtain masks in automated fashion, here is the modified script(the paths to kitti images should be changed to according to your system path)
- the obtained masks should be on a white background, so that when we project lidar point clouds onto this image we can differantiate objects and non-objects. to write masks on a white background ; under
demodirectory of maskrcnn,predictor.pyshould be modified as this one (very small change)
under this directory 'ROS_Raw_Kitti_Player/kitti_ros/launch', find 'kitti_ros_node.launch' file, change the data paths according to your own envoirmment. For example my base directory for KITTI data is as follow ;
/home/atas/kitti_data/2011_09_26/2011_09_26_drive_0052_sync/
basically once you need to change username with yours , it should be fine afterwards.
cd catkin_ws
source devel/setup.bash
roslaunch kitti_ros kitti_ros_node.launch
Now RVIZ should open and you should be able to see something similar to above picture
A Special Thanks to Simon for letting me to use his helper package which saved me bunch of time. Checkout his awesome ROS Perception project here
Complete Documentation