MATLAB: Using ANN library wrapper in Windows XP

ANN (Approximate Nearest Neighbours) is an extremely useful library when working with any type of application where the properties of data points are influenced by their neighbours. The MATLAB MEX-wrapper for the same provided by Shai Bagon, along with the patches, compiles effortlessly in Linux (have tried on F16 and F17). However, making the same work in Windows turned out to be quite an effort. First, the MATLAB inbuilt compiler for Windows (lcc) continuously kept crashing whenever I tried executing the library, and second, the lack of pre-existing solid C/C++ compiler made things difficult.

After searching on the net for free and supported compilers for MATLAB R2010a, I first tried Open Watcom, but it gave too many errors during compilation of the mex-wrappers.  Then it was the turn to check out MS Visual C++ Express Edition. Tried on a friend’s system having MS-VC++ 2010, and it too gave quite a few errors during compilation. Thought to try out MS-VC++ 2008, and guess what, it worked out of the box and the mex-wrapper compiled with quite an ease 🙂 . Wonder why MS-VC++ 2010 created issues..

Install Nvidia Driver and CUDA Toolkit on CentOS 6

( Update: have posted a MUCH simpler method of driver install. Steps for CUDA toolkit install have to be followed as given in this post, i.e. , bulleted step # 10 – 19 )

Although the topic has been addressed succinctly in a CentOS forum post, there are certain things like plymouth configuration post Nvidia driver install, etc. which I felt needed to be jotted down for reference. So, here we go describing the Nvidia CUDA toolkit installation on a CentOS system:

  • Download the appropriate toolkit, driver and SDK from Nvidia’s website.
  • RHEL, and its derivatives come with the open source Nvidia driver called nouveau. Before installing Nvidia drivers, we need to ensure nouveau drivers dont get loaded. For this, append the following in the line starting with ‘kernel’ in the file /etc/boot/grub.conf:

rdblacklist=nouveau nouveau.modeset=0

  • Install the Development Tools and Development Libraries group packages, and a few extra packages listed below:

sudo yum groupinstall ‘Development Tools’ ‘Development Libraries’

sudo yum install kernel-devel gcc-c++ freeglut freeglut-devel libX11-devel mesa-libGLU-devel libXmu-devel libXi-devel gcc* compat-gcc* compat-glibc* compat-lib*

  • Restart the system. Upon restart, you’ll see that the resolution of the display would have gone for a toss. Thats due to blacklisting the nouveau driver, and is a sign that we are on track! Open terminal and type the following to goto non-GUI mode (called, runlevel 3):

sudo init 3

  • Above command takes us to text mode. Change directory to /usr/src/kernels/ and note down the complete path of the kernel folder present. In our scenario, it shows up as:


  • Change directory to the folder containing the downloaded files from Nvidia’s website (say ~/Downloads). Mark the 3 downloaded files as executables:

cd ~/Downloads

chmod a+x NV*; chmod a+x cuda*; chmod a+x gpu*

  • Now finally, we are ready to run the installer. First is the Nvidia Driver install :

sudo sh –kernel-source-path=/usr/src/kernels/2.6.32-220.13.1.el6.x86_64/

  • NOTE : there’s a double minus sign before the word kernel above. During the above install, accept the licence agreement shown. Reboot upon completion:

sudo reboot

  • You’ll notice that the GUI resolution is back to normal, indicating successful Nvidia driver install. Now, cudatoolkit has to be installed.
  • Open terminal and change directory to ~/Downloads. Run the cudatoolkit*.run file:

sudo sh

  • During the install, you’ll be asked to supply installation path. Enter the default path itself (/usr/local/cuda).
  • Once completed, few more steps are needed, like adding /usr/local/cuda to default path environment variable, etc. :

sudo nano /etc/

  • Add the following lines to the above created file :


  • Save the above file by pressing Ctrl+x, followed by ‘y’ and pressing Enter. Now run:

sudo ldconfig

  • For adding cuda install path to enviroment path variable, edit ~/.bash_profile file using a text editor (say, nano ~/.bash_profile) :

export CUDA_INSTALL_PATH=/usr/local/cuda
export PATH=($PATH: /usr/local/cuda/bin)
export LD_LIBRARY_PATH=/usr/local/cuda/lib64
export PATH=($PATH: /usr/local/cuda/lib)

  • Finally, gpucomputingsdk needs to be installed. For that :


  • During the install , you’ll be asked for install path. Keep in mind that the sdk can take around 400-500MB. Say, we install it to ~/Documents/NVIDIA_GPU_Computing_SDK.
  • Once done, we need to compile the files in the SDK:

cd ~/Documents/NVIDIA_GPU_Computing_SDK/C/


  • To check whether everything is working fine, we’ll run the deviceQuery file, provided by the SDK just installed:

cd ~/Documents/NVIDIA_GPU_Computing_SDK/C/bin/linux/release/


  • You should see something similar to what is shown at this link .

Congrats for successfully installing the Nvidia driver and the cudatoolkit on your CentOS system. I know, things should be much simpler. I wish someday Nvidia open-sources their drivers and CUDA toolkit to make things simpler for Linux enthusiasts. All that is left now, is to fix the ugly white-blue scrolling bar that shows up instead of the beautiful Plymouth at boot.

  • Reboot system. At the grub prompt, press ‘e’ against the first item on the grub menu to edit its kernel arguments (this mode is called kernel edit mode).
  • Out the the three lines being shown (starting with : root; kernel; initrd ), scroll to kernel line and press ‘e’ again. Type in the following at the end of that line:


  • Press Enter after typing the above and press ‘b’. You’ll see a tabulated list of keywords against several screen-resolutions. Note down the number being shown against the  most appropriate screen resolution. Say, the number is 361. Now, reboot system. Again, enter the kernel edit mode described in the previous two list items. The only difference being that instead of vga=ask, enter vga=0x361. Now press ‘b’ and you’ll see the beautiful Plymouth back in its glory!
  • To make this change permanent, open terminal and open /boot/grub/grub.conf as sudo (sudo nano /boot/grub/grub.conf).
  • Find the line saying ‘kernel’ against your most recent kernel version and add vga=0x361. Save the file (Ctrl+x, y, Enter)

Plymouth theme will now show up everytime that you’ll reboot. Enjoy!

MATLAB: Running codes in mixed OS environment

Ever faced the problem of running executables in a MATLAB installation on Linux. I frequently use an executable file (.exe) provided by an eminent research lab, but the linux enthusiast that I am, shifting to Windows just for running this file is out of the question! So, how to solve this issue!

Well, you need access to either a system running Windows at your workplace, or have a virtual Windows installation in VirtualBox. Set up ssh via cygwin (refer SSH via CYGWIN) on such a system and also make sure to have a password-less SSH login enabled (refer ssh autologin) between the Linux and Windows systems.

Once this is done and given the fact that such a Windows environment is up and running, all you have to do through the MATLAB command prompt is:

system(‘ssh username@IP_of_windows command1;command2’);

where : command1 and command2 are the things you want to execute on that system. For e.g: in my scenario, i have already put the .exe (say: test.exe) in the cygwin home folder (C:/cygwin/home/<username>/) on the Windows system. Now, i just run:

system(‘ssh username@IP_of_windows ./test.exe’);

You can use few more ssh/scp via system command calls in MATLAB to copy back & forth the data. Thats it!

MATLAB: Run m-file From Linux Terminal / DOS

Yes, MATLAB m-files can very much be executed without initiating the MATLAB GUI. This can be quite handy when when running multiple codes simultaneously without creating a huge clutter for the user, or when running multiple instances of MATLAB and there is a need to prevent unnecessary eating up of the RAM through its GUI.

In Linux, it works via the re-direction operator ( < ), while in Windows, it has to be done using the -r flag. The steps are detailed below:

For MATLAB installations on Linux, ensure the MATLAB soft link is available in /usr/local/bin, so that it can be called from the terminal without specifying its full installation path, i.e.,

cd /usr/local/bin

sudo ln -s /path_to_MATLAB_installation/matlab


matlab -desktop

Once MATLAB link has been created, exit the MATLAB GUI. Now run your m-file (say: test_run.m) from the terminal as:

matlab -nodesktop -nosplash < /path_to_file_location/test_run -logfile test_run.log

Thats it! The “-nodesktop” option ensures the full GUI isnt initiated and only the MATLAB command prompt pops up, “-nosplash” prevents the MATLAB splash screen from showing up. The redirection operator will run all the commands in the m-file as they would in a normal way and “-logfile” logs all that shows up in the MATLAB command window.

In Windows, the slight modification is that we have to first cd to the location where the m-file is present

cd path_to_file_location\

matlab.exe -nodesktop -nosplash -r test_run -logfile test_run.log

And we are done!

P.S : 1) Dont forget to check out the difference in RAM usage with “-nodesktop” enabled and normal GUI way

2) DO NOT put .m with the file name when using this command, else it’ll result in an error!

“Write failed: Broken pipe?” message on a SSH connection

It so happens that at times the SSH connection was getting lost (probably due to network issues) with a message “Write failed: broken pipe”, and this resulted in a crash in cluster based codes. Thanks to this Archlinux forum post, i understood the workaround.

Broken pipe results upon communication loss between the client and the server. So, if we can somehow send control signals over the connection within a ‘n’ second of the last data transmission, this problem should be solved. This is exactly what the command ServerAliveInterval does. Smaller the time duration specified, earlier the control signal will be sent, and the connection doesnt drop.

To achieve this, just append at the end the following line to /etc/ssh/ssh_config file at the client side :

sudo nano /etc/ssh/ssh_config

ServerAliveInterval 5     (append at the end of the file)

Now, just restart the ssh daemon and its done!

sudo systemctl restart sshd.service  (Fedora / OS having systemd)

sudo service ssh restart  (Linux Mint / OS having Upstart)

This will ensure the control signal inquiring Server Alive status is sent 5sec after every time the connection loss happens, and the cluster based codes can run smoothly!

Experience Gnome3.2 in Fedora 16 via Virtualbox

Upon installing Fedora 16 (Fedora-16-Beta) as a guest OS (via VirtualBox), i was greeted with the Fallback mode, turning my excitement to see Gnome3 in its refined new avatar Gnome3.2 into disappointment. Even installing VirtualBox guest additions didnt help.

Its in such scenarios, that i have found fedora-forums to be the best place to learn the causes and rectify them. Thanks to this thread , i realised its a SELinux policy that prevents gnome-shell from auto kick-starting. Follow these steps to enjoy Gnome3.2 experience :

1) Ensure your guest OS is fully updated. Restart once to boot into new kernel.

sudo yum update

2) Install kernel-devel and gcc, if not already present.

sudo yum install kernel-devel gcc

3) In the VirtualBox Guest GUI, Click : Devices > Install Guest Additions. Provide sudo password when prompted and let the install process complete.

4) Now, Modify the SELInux policy for VirtualBox guest additions as below:

restorecon -R – v /opt

(NOTE: single minus sign is used at both places above)

5) And you are ready to use gnome shell after a reboot. To immediately start it, do:

gnome-shell –replace &

(NOTE : its two minus signs before the word replace ..)

Fedora 16 with Gnome 3.2
Fedora 16 guest OS with Gnome 3.2 running

MATLAB : Get smoothly coloured outputs when using surf / trisurf

I had been struggling since sometime to get smoothly textured outputs using surf / trisurf commands in MATLAB. The edges of the locally planar element being used by the respective commands used to always “stand out” with respect to the texture of the contained patch.  Only today i found out a simple 1 line command that solves this problem..

tri = delaunay(X,Y);


shading interp;                   % other options are shading face / shading faceted

And you are done.. you can check for yourself the extent to which this 1 line of code creates a change in visualization of 3d textured data.

Sample outputs, before and after :

surf output BEFORE

surf output AFTER

MATLAB : Generate variable name and allot vector / matrix to it

Matlab provides a nice and simple way to generate continuous set of variable names, say in the form of var1, var2,… etc. This can be accomplished using genvarname and eval commands. Here i’ll show an example where we need to store columns of a matrix A in 3 vectors var1, var2 and var3. Following is the code snippet :

n = 3;                                         % say

A = [1 2 3;4 5 6;7 8 9];            %say

for i = 1:n

val = genvarname([‘var’ num2str(i)]);

eval([val ‘=A(:,i);’]);


And you are done.. the columns of A get stored in the vectors var1, var2 and var3. Similarly, even block matrices within A can be assigned this way. This is a much more elegant and faster way than doing the same thing via for-loops.

Configure CodeBlocks to compile OpenCV codes

CodeBlocks is one of the IDE(s) that i prefer using due to its simplicity and fast interface. Plus the benefit of having MATLAB like command suggestions. The steps are outlined below:

  • Search the path where opencv is installed in your system.. you can do a :

locate cv.h

  • in my system, this returns : /usr/local/include/opencv/cv.h. Copy the path till the opencv directory, i.e : /usr/local/include/opencv/
  • Now, open CodeBlocks > New Project > (any project type of your choice.. for starters, Console Project is a good beginning) . Now goto,

Project > Build Options > Linker Settings tab

  • Under “Other Linker options” add the following, one below the other:


  • Now, in the same window, under “Search directories tab”, add the opencv directory you copied above, i.e. for my system, it’ll be :


  • Now, Project > Properties > C/C++ Parser options, again add the same directory path.

And you are done !! Enjoy compiling OpenCV codes in CodeBlocks 🙂

Install OpenCV 2.3 with video support in Fedora 15

Much has changed since OpenCV 2.0.. android support, CUDA support, etc are up and running. So is the change in the method of installing OpenCV. So, i though to quickly jot down the steps to follow for a painless install.

I must add, due to changes in gcc, removal of libv4l support from linux kernel, etc.. OpenCV 2.1 and 2.2 give loads of issues during install. I just couldnt manage installing v2.1, though v2.2 needed few hacks as mentioned in the link : . So, for people wanting to install v2.2, can follow exactly same steps mentioned below after making the above hack. Note that, even UVC-webcams dont work with v2.2. So, if you’re like me, needing lots of webcam feed for vision-based tasks, its best to avoid v2.2. Moral of the story : Go for v2.3..

1. Install the following :

sudo yum install eigen2-devel, CTL, CTL-devel, OpenEXR_CTL-libs, tbb, yasm, yasm-devel, tbb-devel, OpenEXR CTL-devel, OpenEXR CTL, perl-URI, perl-Compress-Raw-Zlib, perl-Compress-Raw-Bzip2, perl-l0-Compress, libucil-clevel, perl-HTML-Tagset, perl-HTML-Parser, perl-Iibwww-perl, perl-XML-Parser, gstreamer-plugins-base-devel, libsigc++20-devel, glibmm24-devel, libxml++-devel, gstreamermm, xine-lib, libunicapgtk-devel, xine-lib-devel, gstreamermm-devel, python-devel, sip-macros, sip, vamp-plugin-sdk, audacity, sip-devel

sudo yum install libXext-clevel, glib2-devel, libXrender-devel, libXfixes-devel, Iibunicap, freetype-devel, boost-system, fontconfig-devel, libpng-devel, boost-filesystem, boost-serialization, boost-thread, boost-date-time, boost-regex, libXt-devel, libXdamage-devel, libXcomposite-devel, libXcursor-devel, libXrandr-devel, atk-devel, libXinerama-devel, libXxf86vm-devel, libXi-devel, libxml2-devel, blas-devel, libjpeg-turbo-devel, pixman-clevel, cairo-devel, pango-devel, libdrm-devel, mesa-libGL-devel, boost-graph, boost-wave, libucil, boost-signals, boost-python, boost-iostreams, boost-program-options, boost-random, boost-test, boost, mesa-libGLU-devel, ilmbase-devel, libunicapgtk, gdk-pixbuf2-devel, libibverbs, libmlx4, librdmacm, check, check-devel, boost-jam, rarian, rarian-compat, cmake, plpa-libs, numactl, environment-modules, boost-devel, boost-build, OpenEXR-devel, jasper-devel, lapack-devel, libunicap-devel, libtifl-devel, atlas-devel, openmpi, boost-openmpi, ucview, gstreamer-devel, gtk2-devel, jasper, 0penEXR

sudo yum install xorg-x11-proto-devel, libXau-devel, Iibxcb-devel, libX11-devel, libram1394-devel, automake, libogg-devel, libtheora-devel, libvorbis-devel, libdc1394-devel, x264-devel, faac-devel, xvidcore-devel, dirac-devel, gsm-devel, zlib-devel, faad2-devel, speex-devel, lame-devel, orc-compiler, orc-devel, libvdpau, cppunit, libvdpau-devel, schroedinger-devel, dirac, x264, lame, faad2, amrwb-devel, opencore-amr-devel, amrnb, amrnb-devel

(i have tried copying the package names via OCR software and some editing as much as could be possible from the screenshot below)


Install from Add/Remove Programs (PackageKit)

List of Packages to install for OpenCV dependency resolution

2. Now, download and Install FFMPEG

  • Eventhough FFMPEG is at v0.8.. its best to go for v0.7.. thats coz of several dependency issues. Many things like VLC, etc are based on ffmpeg v0.69 code, and v0.8 MAY give lots of issues..
  • Download ffmpeg 0.7 from :
  • extract the above file (say files get extracted to /home/user/ffmpeg)
  • Open terminal and cd to above location.. i.e. : cd /home/user/ffmpeg
  • Now type the following :

./configure –enable-gpl –enable-version3 –enable-nonfree –enable-postproc –enable-libfaac –enable-libopencore-amrnb –enable-libopencore-amrwb –enable-libtheora –enable-libvorbis –enable-libxvid –enable-x11grab –enable-swscale –enable-shared


sudo make install

  • And you are done.. FFMPEG is ready to be integrated with OpenCV.

3. Download OpenCV 2.3 . Extract to a folder (say /home/user/Opencv-2.3)

  • There still are a few packages of ffmpeg like libavcodec-dev, libavutil-dev, etc which need to be present in /usr/local/ffmpeg/ . But, the above  install of ffmpeg doesnt create this. So, open Add/Remove Programs and install following or install using yum:

sudo yum -y install ffmpeg ffmpeg-devel ffmpeg-libs

  • Now, the requisite libraries are all present in the location OpenCV can find them. Open terminal and cd to the OpenCV folder.. i.e.

cd /home/user/OpenCV-2.3

  • Create a folder called Release

mkdir Release

  • cd to the Release folder and type the following to install OpenCV

cd Release/


make -j 2

sudo make install

  • Few more steps need to be done to ensure flawless build.

sudo gedit /etc/

(Type the following and save-close the file) : /usr/local/lib

sudo ldconfig

sudo gedit /etc/bashrc

(Type the following and save-close the file) :


And you are done !!! 🙂 OpenCV 2.3 with ffmpeg support is ready to be used on Fedora 15 with full webcam support.. ENJOY !!

NOTE : due to requests for Ubuntu specific steps, i’ll put the changed steps in this post itself in a few days