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https://github.com/c42f/displaz

A hackable lidar viewer
https://github.com/c42f/displaz

geospatial lidar point-cloud

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A hackable lidar viewer

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README 

        
==============================================

displaz - A viewer for geospatial point clouds

==============================================



**displaz** is a cross platform viewer for displaying lidar point clouds and

derived artifacts such as fitted meshes.  The interface was originally

developed for viewing large airborne laser scans, but also works quite well for

point clouds acquired using terrestrial lidar and other sources such as

bathymetric sonar.



The goal is to provide a flexible and programmable technical tool for exploring

large lidar point data sets and derived geometry.



* *Open point clouds up to the size of main memory.*  Performance remains

  interactive as the number of points becomes too large to draw in a single

  frame.

* *Create custom point visualizations.*  The OpenGL shader can be

  edited interactively.  In the shader program, you automatically have access

  to any per-point attributes defined in the input file.  Shader parameters are

  connected to user-defined GUI controls.

* *Plot interactively from your favourite programming language.*

  Displaz IPC lets you script the interface from the command line.

  Experimental language bindings are available for C++, python, julia and

  Matlab.



User guide

----------



See `the user guide `_ for usage examples and instructions.



Installation

------------



Binary installer packages for windows are provided on the `releases page

`_.  For linux, it should be fairly

easy to build it yourself by following the instructions below.



Building

--------



Linux

~~~~~

Install dependencies using your package manager.  Here's a handy list of

dependencies for several distributions::



    # Ubuntu >= 22.04 (and probably other debian-based distributions)

    sudo apt install git g++ cmake qtbase5-dev python3



    # Ubuntu >= 14.04 (and probably other debian-based distributions)

    sudo apt-get install git g++ cmake qt5-default python-docutils



    # Mint

    sudo apt-get install git g++ cmake qt5-default libqt5opengl5-dev python-docutils



    # Fedora 28

    sudo yum install git gcc-c++ make patch cmake qt5-qtbase-devel mesa-libGLU-devel python-docutils



    # OpenSuse

    sudo zypper install git gcc-c++ libqt5-qtbase-devel glu-devel python-docutils



The following commands may be used to build displaz on linux::



    # Get the source code

    git clone https://github.com/c42f/displaz.git

    cd displaz



    # Build LASlib and ilmbase

    mkdir build_external

    cd build_external

    cmake ../thirdparty/external

    make -j4

    cd ..



    # Build displaz

    mkdir build

    cd build

    cmake ..

    make -j4



    # Install into CMAKE_INSTALL_PREFIX=/usr/local

    sudo make install



Troubleshooting:



* Some people have had issues with a version of qt in their path clashing with

  the qt headers installed on the system. This may give an error such as

  "undefined reference to qt_version_tag", or some other qt library-related

  link error.  For example having the qt version distributed with the python

  package system ``conda`` has been known to cause issues, which can be solved

  by removing it from the ``$PATH`` variable *before* calling cmake in the

  script above.



Windows x64

~~~~~~~~~~~

The windows releases are built using cmake and

`Visual Studio `_.

To install the dependencies on windows, manually download and install the

following tools:



* `cmake `_

* `msysgit `_

* `qt5 `_ (ensure you get the correct version for your compiler)

* `nsis `_ (only required for installable package creation)



To build, first clone the repository using the msysgit command line::



    # Get the source code

    git clone https://github.com/c42f/displaz.git



You can build displaz with various supported cmake build system generators.

For the continuous integration build (and probably future releases), the Visual

Studio generator ``"Visual Studio 14 Win64"`` is used::



    rem Build LASlib and ilmbase

    mkdir build_external

    cd build_external

    cmake -G "Visual Studio 16 2019" -D CMAKE_BUILD_TYPE=Release ..\thirdparty\external

    cmake --build . --config Release

    cd ..



    rem Build displaz.

    rem Assumes that Qt has been installed into C:\Qt\Qt5.5.1\5.5\msvc2015_64

    mkdir build

    cd build

    cmake -G "Visual Studio 16 2019" ^

        -D CMAKE_PREFIX_PATH=C:\Qt\Qt5.5.1\5.5\msvc2015_64 ^

        -D CMAKE_INSTALL_PREFIX:PATH=dist ^

        ..

    cmake --build . --config Release



    rem Optionally, create the installer package

    cmake --build . --config Release --target package



Some of the cmake generators such as ``NMake Makefiles"`` won't find visual

studio unless it's in the path.  In that case you'd need to launch the steps

above from the x64 cross tools command prompt.



OSX

~~~



TODO - for the moment see the generic build instructions below.  Also note that

displaz is regularly built on OSX via travis-CI, so the commands in the file

``.travis.yml`` in the repository should more or less work.



Generic build

~~~~~~~~~~~~~

To build displaz, install the following tools:



* cmake >= 2.8.8

* Python docutils (optional - required to build the html documentation)



Displaz also depends on several libraries.  For simplicity, the smaller

dependencies are bundled in the thirdparty directory.  There's also an

automated download/build system for some of the larger ones (LASlib and

ilmbase) available at ``thirdparty/external/CMakeLists.txt``.  However, you

will need to install the following manually:



* Qt >= 5.0

* OpenGL >= 3.2

* ilmbase >= 1.0.1 (You don't need to install this if you're using the

  automated thirdparty build)



Both the LASlib and IlmBase libraries may be built using the separate third

party build system in ``thirdparty/external/CMakeLists.txt``.



Docker

~~~~~~

Dockerfiles based on a variety of Linux flavours are provided, see

`the docker README `_ for instructions on building docker images.



Supported Systems

-----------------



displaz is regularly compiled on linux, OSX and windows.  It's known to work

well with recent NVidia and ATI graphics cards and drivers.  Some issues have

been observed with Intel integrated graphics and older ATI drivers.  If you

observe rendering artifacts there's a reasonable chance that your graphics card

or drivers are playing dirty tricks



Third party libraries used in displaz

-------------------------------------



Behind the scenes displaz uses code written by many people.  The following

third party projects are gratefully acknowledged:



* Qt - http://qt-project.org

* LASLib - https://github.com/LAStools/LAStools

* Imath - https://github.com/AcademySoftwareFoundation/Imath

* rply - http://www.impa.br/~diego/software/rply

* GLEW - http://glew.sourceforge.net/

* Small pieces from OpenImageIO - http://openimageio.org