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 >= 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.

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 - http://www.cs.unc.edu/~isenburg/lastools
PDAL - http://www.pdal.io
ilmbase - http://www.openexr.com
rply - http://www.impa.br/~diego/software/rply
GLEW - http://glew.sourceforge.net/
Small pieces from OpenImageIO - http://openimageio.org

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