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Complete the conversion from the .bag file to the .png and .bin files. Includes .bag file decoding, pcd2bin and file directory extraction.

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In the current process of Intelligent Vehicle' data acquisition (LiDAR data and visual data), we usually complete the recording of data in the ROS system. Therefore, the data we directly get is saved in the .bag file format. However, the data format of most existing perception network frameworks is consistent with the data format of the KITTI dataset. In KITTI dataset, image files are saved in .png format and PointCloud files are saved as .bin files. So we need to complete the conversion from the .bag file to the .png and .bin files.

Steps

1. Decode .bag files

Data files recorded via ROS are usually saved in .bag format. We need to use the ROS system to decode the .bag file. The decoded files include image files(.png) and PointCloud files(.pcd).

  • Build the project

    cd catkin_ws; catkin_make

  • **Coordinate system transformation(Optional):**The purpose of coordinate system rotation and translation is achieved by adjusting the following parameter values in the file map_generation_node.cpp. All rotation parameters are angled and clockwise is positive.

  • Decoding: Run roscore on the first console. Then open a new console, run ./devel/lib/obstacle_detection/map_generatein the catkin_ws directory. Open a new console, run rosbag play xxx.bag -r 0.1. The result files are save into the output.

0.1 in the code means 0.1 times speed. The Speed is determined according to computer io performance. Make sure the timestamps are within +-50ms, otherwise adjust the play speed.

2. Pcb 2 Bin

The PointCloud files decoded from the .bag file are usually in .pcd format. In order to facilitate the experiment of 3D detection, the format of the KITTI data set needs to be unified, that is, converted into the .bin format. In the .bin file, each point corresponds to four data, which are xyz and intensity.

  • Build the project

    mkdir CMakeFile; cd CMakeFile; cmake ..; make

  • Preparation: Put the .pcd files into pcd. Set the file path in the code pcd2bin.cpp.

  • Convertion: The .bin files are saved into bin

    cd CMakeFile; ./pcd2bin

3. Create files_list.txt

The KITTI dataset has txt files like train.txt trainval.txt val.txt, which contains a subset of all data files. So we need to get the files_list.txt

  • Get files_list: The result will be saved into bin named list.txt.

    cd bin; ls -1 | grep ".bin$" > list.txt

  • Create the final .txt: The txt file obtained in the previous step contains a file suffix such as .bin. This requires further processing. After this step, you will get the final txt file named files_list.txt.

    python get_list.py

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Complete the conversion from the .bag file to the .png and .bin files. Includes .bag file decoding, pcd2bin and file directory extraction.

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  • C++ 49.2%
  • CMake 48.6%
  • Python 2.2%