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DBScan-PCL-Optimized

travis version

This project is taken from: Navarro-Hinojosa, Octavio, y Moisés Alencastre-Miranda. "DBSCAN modificado con Octrees para agrupar nubes de puntos en tiempo real." Research in Computing Science, Vol. 114: Advances in Image Processing and Computer Vision, pp. 173–186, 2016. Github: https://github.com/Hagen23/DBScan_Octrees

It was modified with:

  • It was added a CMakeList.txt for cmake compilation with PCL 1.9.0 (support 1.9.1)
  • It was added an argument param option
  • It was added a pcl visualizer
  • It was deleted the Glut visualizer
  • It was added a cluster saving method
  • It was added a cluster coloring method
  • It was replaced the input file from CSV to PCD
  • It was added a cluster coloring method for original color of the point cloud

Input file extension supported

Format Description
.pcd Point Cloud Data file format
.ply Polygon file format
.txt Text file format
.xyz X Y Z Text file format

Command line

➜ ./app --help                                                                                  

*************************************
*** DBSCAN Cluster Segmentation *** 
*************************************
Usage: ./app [options] 

Optional arguments:
-h --help       	shows help message and exits [default: false]
-v --version    	prints version information and exits [default: false]
--cloudfile     	input cloud file [required]
--octree-res    	octree resolution [default: 120]
--eps           	epsilon value [default: 40]
--minPtsAux     	minimum auxiliar points [default: 5]
--minPts        	minimum points [default: 5]
-o --output-dir 	output dir to save clusters [default: "-"]
--ext           	cluster output extension [pcd, ply, txt, xyz] [default: "pcd"]
-d --display    	display clusters in the pcl visualizer [default: false]
--cal-eps       	calculate the value of epsilon with the distance to the nearest n points [default: false]

Example

Screenshot from 2022-06-23 10-21-38



Dependencies

This projects depends on the Point Cloud Library (it works with version 1.8...1.12.1) and its dependencies.

Package Version Description
VTK 9.0.0 Visualization toolkit
PCL 1.12.1 The Point Cloud Library (PCL)
Eigen 3.7.7 Eigen is a library of template headers for linear algebra
Flann 1.9.1 Fast Library for Approximate Nearest Neighbors
Boost 1.77.0 Provides support for linear algebra, pseudorandom number generation, multithreading
OpenGL 21.2.6 Programming interface for rendering 2D and 3D vector graphics.

This project has been tested with VTK 8.1...9.1 and CMake from 3.5...3.21

Compilation

You can build the project from source or download a docker image stored in docker hub, here. This image is compiled with pcl-docker-1.12.1, Alpine linux 3.15 and the DBscan project (1.32GB).

Compile from source

  1. Download source code
git clone --recursive https://github.com/danielTobon43/DBScan-PCL-Optimized.git
  1. Create a "build" folder at the top level of the DBScan-PCL-Optimized project
cd DBScan-PCL-Optimized/ && mkdir build
  1. Compile with CMake
cd build/ && cmake ../ && make

How to run project

In the build folder run the following command:

./app --cloudfile PATH/TO/YOUR/CLOUDFILE

Note ¡You can modify the parameters to obtain better results! I recommend modifying only the eps value, between 40 - 60 you can get better clusters, or 0.5 to 10.

There is a flag to calculate epsilon using 100 points with --cal-eps. Please check Command line.

Download docker image

To use it you have to install docker-engine in your host machine:

Docker multi-stage graph generated with: dockerfilegraph

docker pull ghcr.io/danieltobon43/dbscan-octrees:latest

Check downloaded image

docker images

Run a docker container Linux

You can either run a docker command or create a shell script.

1. Option 1: Docker command

docker run --rm -it \
           --volume=/tmp/.X11-unix:/tmp/.X11-unix:rw \
           --volume=/tmp/.docker.xauth:/tmp/.docker.xauth:rw \
           --env="XAUTHORITY=/tmp/.docker.xauth" \
           --env="DISPLAY" \
           --name="dbscan" \
           --volume=[PATH TO YOUR PCD FOLDER]:/tmp \
           -t ghcr.io/danieltobon43/dbscan-octrees:latest --cloudfile /tmp/[YOUR PCD FILENAME]

If you get something like this after setting --display flag it might be related to this:

No protocol specified

Try running with the following command belowe or use the provided .sh script:

sudo -sE docker run --rm -it \
           --env="DISPLAY" \
           --volume=/tmp/.X11-unix:/tmp/.X11-unix:rw \
           --volume=/tmp/.docker.xauth:/tmp/.docker.xauth:rw \
           --name="dbscan" \
           --volume=[PATH TO YOUR PCD FOLDER]:/tmp \
           -t ghcr.io/danieltobon43/dbscan-octrees:latest --cloudfile /tmp/[YOUR PCD FILENAME] --display

If this still does not work to display, run: xhost +local:docker and then run the option 1 command.

2. Option 2: shell script

  • Create a visualizer.sh file with executable permissions (check this shell script dbscan-shell-script).

Screenshot from 2022-06-03 10-16-13

  • Copy the next content into the visualizer.sh file (remember to update PATH/TO/YOUR/PCD/PLY/FOLDER accordingly):
# Allow X server connection
xhost +local:root
docker run -it --rm \
    --env="DISPLAY" \
    --env="QT_X11_NO_MITSHM=1" \
    --name="pcl-container" \
    --volume="/tmp/.X11-unix:/tmp/.X11-unix:rw" \
    --volume=PATH/TO/YOUR/PCD/PLY/FOLDER:/tmp \
    ghcr.io/danieltobon43/dbscan-octrees:latest /tmp/$1
# Disallow X server connection
xhost -local:root
  • Run the docker container
./visualizer YOUR/CLOUD/FILENAME

Run docker container Windows

  1. Install a Xserver on Windows, XLaunch

xlaunch

  1. Run the docker container: Open a PowerShell Terminal with Administrator privileges and run the following command
docker run --rm -it `
           --env DISPLAY=host.docker.internal:0.0 `
           --volume //c/Users/YOURUSERNAME/Downloads/pcds:/tmp `
           -t ghcr.io/danieltobon43/dbscan-octrees:latest `
           --cloudfile /tmp/YOURFILENAME `
           --display

windows-command

More info about running Docker GUI containers on Windows, check this video

example: I have a .pcd file called Tree2.pcd stored in:

/home/user/Downloads/pcd/Tree2.pcd

To run a docker container with the previous .pcd file I will open a terminal in "Downloads folder" and use pwd from ubuntu to get my current directory path in the terminal and then:

docker run --rm -it \
           --volume=/tmp/.X11-unix:/tmp/.X11-unix:rw \
           --volume=/tmp/.docker.xauth:/tmp/.docker.xauth:rw \
           --env="XAUTHORITY=/tmp/.docker.xauth" \
           --env="DISPLAY" \
           --name="dbscan" \
           --cap-add sys_ptrace \
           -p 127.0.0.1:2222:22 \
           --user=pcl \
           --volume=`pwd`/pcd:/tmp \
           -t ghcr.io/danieltobon43/dbscan-octrees:latest --cloudfile /tmp/Tree2.pcd

The previous command will run a docker container with the dbscan-octrees:1.1-alpine3.15 image and will share a .pcd file from the host machine ([PATH TO YOUR PCD FOLDER]) to the tmp folder in the container.

Note

Be aware that, the mounted directory in the host machine will copy all the files in the target directory in the container. That's why I recommend to create a folder to store just .pcd/.ply/etc files that will be use with the container.

More information about this docker image can be found in the docker hub repository.

Epsilon calculation (experimental)

How to choose epsilon value:


Where K-distance is the distance from each point to its closest neighbour using the K-NearestNeighbors. The point itself is included in n_neighbors. The kneighbors method returns two arrays, one which contains the distance to the closest n_neighbors points and the other which contains the index for each of those points.

The graph is built with:

X_array = [0,1,2,3,4, ...1000]
Y_array = [0.0,0.1,0.2,...1.0]
X_array.size() = Y_array.size()

Enable --cal-eps flag:

Screenshot from 2022-06-23 10-24-01

Exporting clusters

You can export the generated clusters by providing the --output-dir flag. This will save the clusters in the specified directoy. The default format is pcd, but you can choose from: ply, txt, xyz using the --ext flag.

Note: There is a bug with the PCL visualizer using VTK 9.1 which causes a segmentation default core dumped after the visualizer is closed. This might cause crash the program before exporting the clusters. I recommend enable the --output-dir flag without the -d or --display flag for visualization.

Display clusters

To display the generated clusters enable the -d or --display flag in the command line.

Troubleshoot PCL-1.9.1

if compiling the project with PCL-1.9.1 this occurs:

    -- Build files have been written to: /home/t00215031/Downloads/DBScan-PCL-Optimized-master/build
    [ 20%] Building CXX object CMakeFiles/dbscan.dir/main.cpp.o
    In file included from /opt/pcl-1.9.1/common/include/pcl/pcl_macros.h:75:0,
                     from /opt/pcl-1.9.1/octree/include/pcl/octree/octree_nodes.h:47,
                     .
                     .
                     .

    /opt/pcl-1.9.1/build/include/pcl/pcl_config.h:7:4: error: #error PCL requires C++14 or above
       #error PCL requires C++14 or above
        ^
    CMakeFiles/dbscan.dir/build.make:62: recipe for target 'CMakeFiles/dbscan.dir/main.cpp.o' failed
    make[2]: *** [CMakeFiles/dbscan.dir/main.cpp.o] Error 1
    CMakeFiles/Makefile2:67: recipe for target 'CMakeFiles/dbscan.dir/all' failed
    make[1]: *** [CMakeFiles/dbscan.dir/all] Error 2
    Makefile:83: recipe for target 'all' failed
    make: *** [all] Error 2
    
    ## Solution
    1. Update gcc and g++ to version 6:
       $    sudo add-apt-repository -y ppa:ubuntu-toolchain-r/test
       $    sudo apt-get update -y
       $    sudo apt-get install -y gcc-6 g++-6 clang-3.8
       $    sudo update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-6 70 --slave /usr/bin/g++ g++ /usr/bin/g++-6
       
       --> check gcc and g++ version:
       $    gcc --version
       $    g++ --version
       
            g++ (Ubuntu 6.5.0-2ubuntu1~16.04) 6.5.0 20181026
            Copyright (C) 2017 Free Software Foundation, Inc.
            This is free software; see the source for copying conditions.  There is NO
            warranty; not even for MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
            
     2. Compile again 
        $    cmake../ && make

if:

    ../../../bin/librtabmap_core.so.0.11.11: undefined reference to `pcl::search::Search<pcl::PointXYZRGBNormal>::getName[abi:cxx11]() const'
    ../../../bin/librtabmap_core.so.0.11.11: undefined reference to `pcl::search::Search<pcl::PointXYZRGB>::getName[abi:cxx11]() const'
    ../../../bin/librtabmap_core.so.0.11.11: undefined reference to `pcl::search::Search<pcl::PointXYZ>::getName[abi:cxx11]() const'
    collect2: error: ld returned 1 exit status
    
    Solution:

            #include <pcl/search/impl/search.hpp>

            #ifndef PCL_NO_PRECOMPILE
            #include <pcl/impl/instantiate.hpp>
            #include <pcl/point_types.h>
            PCL_INSTANTIATE(Search, PCL_POINT_TYPES)
            #endif // PCL_NO_PRECOMPILE