EnhancedLiDAR/instruction at master · xjsong99/EnhancedLiDAR · GitHub

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
----------------------------------Enhanced_LiDAR-------------------------------------------------
【编译方法】：
1.cd EnhancedLiDAR

2.catkin_make

3.source devel/setup.bash

4.某一个场景/Test_on_frame: roslaunch EnhancedLiDAR EnhancedLiDAR.launch
  数据集生成              : roslaunch EnhancedLiDAR EnhancedLiDAR.launch my_args:="file 775"  //start_index=775

//rosbag play --clock test.bag

5.rosrun rviz rviz

6.配置Rviz的Frame为velodyne（失败尝试base_link），并且add原始点云和过滤以后的点云的display

【关于编译的方法】：
https://blog.csdn.net/AdamShan/article/details/82901295
https://blog.csdn.net/qq_40297851/article/details/84567056

【关于marker的用法】：
https://www.jianshu.com/p/6469314a9011
http://wiki.ros.org/rviz/DisplayTypes/Marker

【GitHub提交方法】：
cd EnhancedLiDAR

git add .      				//将要提交的文件暂存到本地仓库。

git commit -m "Add existing file"     	//提交暂存在本地仓库中的文件。

(proxychains) git push origin master	//推送更改（本地仓库中）到 GitHub。
-----------------------------------------------------------------------------------------------

----------------------------------DeepPruner-------------------------------------------------
生成视差图
conda activate python2
python submission_kitti.py \
--loadmodel /home/song/DeepPruner/deeppruner/DeepPruner-best-kitti.tar \
--save_dir /media/song/程序磁盘/3D_KITTI/predicted_disp/training \
--datapath /home/song/DeepPruner/deeppruner/test_directory
-------------------------------------------------------------------------------------------------

----------------------------------pseudo-LiDAR-------------------------------------------------
生成深度图（由视差图）
python ./preprocessing/generate_depth.py  \
    --calib_dir /media/song/程序磁盘/3D_KITTI/data_object_calib/training/calib/ \
    --save_dir /media/song/程序磁盘/3D_KITTI/predicted_depth/training/ \
    --disparity_dir /media/song/程序磁盘/3D_KITTI/predicted_disp/training/ \
    --start_index 0