Awesome
Kitti360 Visualization
Ros package to visualize KITTI-360 data with RVIZ
Getting Started:
Data Preparation
Download the KITTI360 dataset to your computer. We support the perspective images, Raw Velodyne Scans, calibrations, vehicle poses.
Ended up as : KITTI-360/{calibration/data_2d_raw/data_3d_raw/data_poses}.
Overwrite the folder names in the launch file to your data.
Software Prerequisite
This repo runs with ROS python3 (noetic), and we expect PyQt5 correctly setup with ROS installation.
Clone the repo under the {workspace}/src/ folder. Overwrite the folder names in the launch file to point to your data.
cd catkin_ws/src
git clone https://github.com/Owen-Liuyuxuan/kitti360_visualize
cd ..
catkin_make
source devel/setup.bash # devel/setup.zsh or devel/setup.sh for your own need.
# modify and check the data path!! Also control the publishing frequency of the data stream.
nano src/kitti360_visualize/launch/visualize_launch.launch
# this will launch the data publisher / rviz / GUI controller
roslaunch kitti360_visualize visualize_launch.launch
Core Features:
- KITTI-360 raw data sequence support.
- Stereo RGB cameras.
- LiDAR, RGB point clouds.
- TF-tree (camera and LiDAR).
- GUI control & ROS topic control.
GUI
User manual:
index: integer selection notice do not overflow the index number.
Stop: stop any data loading or processing of the visualization node.
Pause: prevent pointer of the sequantial data stream from increasing, keep the current frame.
Cancel: quit. (click this before killing the entire launch process)
Raw Data & Depth Prediction Dataset
We support video-like streaming raw data. Depth Prediction dataset follows similar structure of raw data, thus can be visualized in RGB point clouds together(optionally).
ROS Topics
/kitti360/left_camera/image (sensor_msgs/Image)
/kitti360/right_camera/image (sensor_msgs/Image)
/kitti360/left_camera/camera_info (sensor_msgs/CameraInfo)
/kitti360/right_camera/camera_info (sensor_msgs/CameraInfo)
/kitti360/lidar (sensor_msgs/PointCloud2)
The tf trees are also well constructed. We have a predefined rviz file for visualizing all topics and tf trees.