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.
See the user guide for usage examples and instructions.
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.
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
condahas been known to cause issues, which can be solved by removing it from the$PATHvariable before calling cmake in the script above.
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.
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.
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.
Dockerfiles based on a variety of Linux flavours are provided, see the docker README for instructions on building docker images.
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
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