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ROS1(melodic) + python2.7 + Pycharm

1.Install ROS and miniconda3

2.Create conda virtual environment

conda create -n ros1_py27 python=2.7

3.Create ROS work_space

mkdir ~/catkin_ws && cd catkin_ws
mkdir src && cd src
git clone https://github.com/daxiongpro/ros-kitti-project.git  # catkin_create_pkg ros-kitti-project
cd ../../   # catkin_ws
catkin_init_workspace
catkin_make

4.Make pycharm configration

5.Prepare kitti dataset

  • Download kitti raw dataset 2011_09_26_calib.zip and 2011_09_26_drive_0005_sync.zip,label_02.Download in baidu netdisk, password:k1f5
  • Generate dataset directory as follows:
kitti_raw_data
kitti
├── bag
│   ├── 2020-07-04-15-31-16.bag
│   ├── kitti_2011_09_26_drive_0005_synced.bag
│   ├── kitti2bag.py
│   └── readme.txt
├── RawData
│   └── 2011_09_26
│       ├── 2011_09_26_drive_0005_sync
│       │   ├── image_00
│       │   ├── image_01
│       │   ├── image_02
│       │   ├── image_03
│       │   ├── oxts
│       │   └── velodyne_points
│       ├── calib_cam_to_cam.txt
│       ├── calib_imu_to_velo.txt
│       └── calib_velo_to_cam.txt
└── training
    └── label_02
        ├── 0000.txt
        ├── 0001.txt
        ├── 0002.txt
        ├── 0003.txt
        ├── 0004.txt
        ├── 0005.txt
        ├── 0006.txt
        ├── 0007.txt
        ├── 0008.txt
        ├── 0009.txt
        ├── 0010.txt
        ├── 0011.txt
        ├── 0012.txt
        ├── 0013.txt
        ├── 0014.txt
        ├── 0015.txt
        ├── 0016.txt
        ├── 0017.txt
        ├── 0018.txt
        ├── 0019.txt
        └── 0020.txt

6.Run python script

  • Change the dataset path in python script
  • Run python: eg1:python kitti.py(in ros-kitti-project/src) eg2:run ros-kitti-project/src/kitti.py in Pycharm

7.RVIZ visualization

  • Run rviz
roscore
rviz
  • Add Pointcloud topic

Now, you can see the image, pointcloud, 2D BBox, 3D BBox, IMU data published!

rviz

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