Test it and you could see an awesome colored cube in your screen. Using an incredible 3D technology which will allow you to navigate around the cube!.
it's Epic!
In order to build Cube, you need to have:
(Earlier versions might work OK, but are not tested.)
Mac Os users should install the following components:
brew update
to update brew repositories. Then run brew install glew
and brew install glm
for install the dependencies.To compile and install GLFW libs, you can clone the official repository and follow the guide in the GLFW documentation.
git clone https://github.com/glfw/glfw.git
cd glfw
cmake . -DGLFW_BUILD_UNIVERSAL=ON
make
sudo make install
To compile and install PCL libs, you can clone the official repository and follow the guide. Make sure you have installed Boost, Eigen, FLANN and Visualization ToolKit (VTK) dependencies.
brew tap homebrew/science
brew install boost
brew install eigen
brew install flann
brew install vtk
brew install qt
git clone https://github.com/PointCloudLibrary/pcl.git
cd pcl
mkdir build
cd build
cmake ..
make
sudo make install
Ubuntu users should install the following components:
It's possible to install GLEW from Ubuntu repositories.
sudo apt-get update && sudo apt-get upgrade
sudo apt-get install libglew-dev
To compile and install GLM lib, you can clone the official repository.
git clone https://github.com/g-truc/glm.git
mkdir build
cd build
cmake ..
make
sudo make install
To compile and install GLFW libs, you can clone the official repository and follow the guide in the GLFW documentation. Make sure you have installed xorg-dev and libgl1-mesa-dev packages.
sudo apt-get install xorg-dev
sudo apt-get install libgl1-mesa-dev
git clone https://github.com/glfw/glfw.git
cd glfw
cmake . -BUILD_SHARED_LIBS = ON
make
sudo make install
NVIDIA GRAPHIC CARDS: Remember overwrote the symbolic link in '/usr/lib/x86_64-linux-gnu/libGL.so' with the nvidia openGL library before build GLFW libs. ( Delete the old symbolic link before do this ).
To compile and install PCL libs, you can clone the official repository. Make sure you have installed Boost, Eigen, FLANN and Visualization ToolKit (VTK) dependencies.
sudo apt-get install libeigen3-dev
sudo apt-get install libflann-dev
sudo apt-get install libboost-all-dev
sudo apt-get install libvtk5.8-qt4 libvtk5.8 libvtk5-dev
git clone https://github.com/PointCloudLibrary/pcl.git
mkdir build
cd build
cmake ..
make
sudo make install
For Linux/Unix/OSX/Mingw/Cygwin the build is straight forward:
git clone https://github.com/eipporko/Cube.git
cd Cube
cmake .
make
Alternatively, you can create an out-of-source build directory and run cmake from there. The advantage to this approach is that the temporary files created by CMake won't clutter the Cube source directory, and also makes it possible to have multiple independent build targets by creating multiple build directories. In adirectory alongside the Cube use:
git clone --recursive https://github.com/eipporko/Cube.git
cd Cube
mkdir build
cd build
cmake ..
make
If you have a multi-processor/core system then you can use make -j
If you want to create Xcode project files, you only have to run cmake . -G Xcode
.
This approach is highly recommended to do it from an out-of-source build directory. - explained in 'How to build' step
When cube is in debug mode, at the end of each session saves information in a log file. For analysis purposes Cube bring tools for make easier to understand the log, building graphs which compares the different rendering times achieved.
sudo apt-get install python-setuptools
sudo apt-get install python-scitools
git clone git://github.com/pudo/dataset.git
cd dataset/
sudo python setup.py install
$ python cubeGraphGen.py
CUBE GRAPH GENERATOR
USAGE: cubeGraphGen.py [options] logFile
OPTIONS:
-h Display available options
--help Display available options
-v Run in verbose mode
May the Force be with you :)