Automatic Feature Selection
C++ Cuda QMake CMake
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build palceholders renamed from .gitignore to .gitkeep Mar 7, 2015
cuda minor error: missing deallocation of gpu memory fixed. Feb 22, 2016
doc Project Files Mar 6, 2015
include Project Files Mar 6, 2015
logo Logo added Mar 6, 2015
misc Project Files Mar 6, 2015
src Project Files Mar 6, 2015
AFS.pro Project Files Mar 6, 2015
CMakeLists.txt Project Files Mar 6, 2015
LICENSE Initial commit Mar 2, 2015
README.md link updated. Apr 3, 2017

README.md

Image

Automatic Feature Selection is a code framework for the feature selection method introduced in

Caner Hazirbas, Julia Diebold, Daniel Cremers, Optimizing the Relevance-Redundancy Tradeoff for Efficient Semantic Segmentation, In Scale Space and Variational Methods in Computer Vision, 2015.

Framework Structure

--AFS    
    |
    -- build            ; build directories for CMake and QtCreator projects
    |
    -- cuda             ; cuda source/header files
    |
    -- doc              ; code documentation and related conference paper
        |
        -- html         ; html documentation (double-click on **index.html**)
        |
        -- latex        ; PDF documentation             
    |
    -- include          ; header files
    |
    -- misc             ; miscellaneous source files and mrmr
        |
        -- mrmr         ; folder to store mrmr executable file
    |
    -- src              ; source files
    |
    -- AFS.pro          ; QtCreator Project File
    |
    -- CMakeLists.txt   ; CMake Project File

How To Build

Required Hardware/Software

To be able to compile and run the code you need a computer with

  • Ubuntu OS (12.04/14.04)
  • NVidia GPU with CUDA support

You need to install the following libraries (I recommend you to download and compile the libraries from source):

Along with these libraries, you need to install CUDA drivers on your machine:

Once libraries are installed, you can download the source from github:

        git clone https://github.com/tum-vision/afs.git

This framework requires mrmr method to be compiled. Please download the source files inside the folder misc/mrmr/ and compile the code with make command.

Build from CMake

  1. Please export the following paths in your .bashrc if you built libraries from source.

    • OpenCV 2.4.10
    export OPENCV_DIR=<path to OpenCV>/OpenCV/2.4.10/share/OpenCV
    export PKG_CONFIG_PATH=$PKG_CONFIG_PATH:<path to OpenCV>/OpenCV/2.4.10/lib/pkgconfig
    export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:<path to OpenCV>/OpenCV/2.4.10/lib  
    
    • Boost 1.54.0
    export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:<path to Boost>/Boost/1.54/build/lib
    
  2. Change the following lines in CMakeLists.txt

    • Line 13 : Set path to the OpenCVConfig.cmake
    • Line 23 : Set CUDA Compute Capability in arch=compute_??,code=sm_??
  3. Run console in AFS/build/CMake and type:

    cmake ../../
    make 
    make install
    make clean (to clean the project)
    

Build from QtCreator(qmake)

  1. Set INCLUDEPATH and LIBS path in AFS.pro (qmake project file) for :

    • OpenCV 2.4.10: Lines 71, 73
    • Boost 1.54.0 : Lines 89, 91
    • CUDA 6.5 : Lines 104, 106
  2. Set CUDA installation directory(CUDA_DIR) and CUDA compute capability(CUDA_ARCH) in Lines 101, 102

  3. You can use build/QtCreator/Debug and build/QtCreator/Release folders to compile the project with QtCreator

Both builds will copy the executable file (AFS) into the main project folder. You can run the executable as ./AFS.