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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 ROS2 python3 (humble), 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.

Install and launch everything based on the Install Steps

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

image

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).

image

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.