Support KITTI and ROS data
Add comprehensable annotation and add reflectance projection.
This is a Python implementation of how to project point cloud from Velodyne coordinates into the left color image with KITTI data set, or use data collected and calibrated by yourself.
matplotlib == 3.1.3
numpy == 1.18.1
Also tested with
matplotlib == 3.4.3
numpy == 1.23.5
Download KITTI dataset and place proj_velo2cam.py in the root path.
python3 proj_velo2cam.py
You are assumed knowing how to use ROS(robot operating system), and you have record a rosbag of image and point cloud, and you also got a calibration parameter files.
Use extract_img_pc_from_rosbag.py to extract image in rosbag:
python extract_img_pc_from_rosbag.py
Use pcl_ros package to extract point cloud, and use rosbag play to play the bag:
rosbag play <your_ros.bag>
rosrun pcl_ros pointcloud_to_pcd input:=/points_raw
Just clone the whole repo and run proj_velo2cam.py.
By default, run with frame 000007 with path below:
.
├── data_object_image_2
│ └── testing
│ ├── image_2
│ │ └── 000007.png
│ └── projection
│ └── 000007.png
├── data_object_velodyne
│ └── testing
│ └── velodyne
│ └── 000007.bin
├── proj_velo2cam.py
├── readme.md
└── testing
└── calib
└── 000007.txt
todo: