Posts Tagged ‘freeware’

Awesome collection of software on Ubuntu

March 27, 2012 Leave a comment
Categories: Reviews, Tutorials Tags: ,

Install Picasa 3 on Ubuntu

March 27, 2012 Leave a comment
I cannot see picasa in Ubuntu software repository, so here is how to install Picasa 3 from terminal:

sudo sh -c "echo 'deb testing non-free' >> /etc/apt/sources.list";
wget --quiet -O - | sudo apt-key add -
sudo apt-get update
sudo apt-get install picasa

Alternatively, you can download the file from Google download website

32-bit Ubuntu:
wget && sudo dpkg -i picasa_3.0-current_i386.deb

64-bit Ubuntu:
wget && sudo dpkg -i picasa_3.0-current_amd64.deb
Categories: iDo Tags: ,

How to Install Eclipse and Android SDK on Ubuntu 10.04 LTS

January 17, 2012 1 comment

Before walking you through the installation process in details, it’s good to know a big picture:

  1. Since Android development needs Java, so we are going to need Java installed on Ubuntu
    • If you are using 64-bit Linux machine (e.g. 64-bit Ubuntu), you may need to install ia32-libs.
  2. You will also need Java Development Tools (JDK), and Eclipse is recommended
  3. The last thing is to install Android Development Tools (ADT) on Eclipse

All the information regarding the installation can be found at the Android developer website

Here is the installation in details:

  1. Install Java
    1. If you are using 64-bit Ubuntu, you will need to install ia32-libs package:
      sudo apt-get ia32-libs
    2. Next, install Javasudo apt-get install sun-java6-jdk

      A tricky part is that when the Java installation almost done, you will need to click <Ok>, which can be done by click in the terminal and press Tab until the <Ok> is highlighted.

  2. Next, you will need to install Java Development Tools (JDK). Eclipse is recommended because there is an Android Development Tools (ADT) plugin available.
    1. Go to
    2. I download Eclipse IDE for Java Developers (both 32- and 64-bit are available)
    3. Extract the downloaded file eclipse-java-indigo-SR1-linux-gtk-x86_64.tar.gz, and you will get the folder called eclipse, containing all necessary files
    4. Since Eclipse is built to be portable, you can move the extracted eclipse folder to any location you want. It is recommended to move the file to your home directory /home/yourusername/
    5. You might want to add the launch icon on the menu, please follow the process here.
  3. Launch Eclipse, we will now install the ADT plugin
    1. go to Help>Install New Software..
    2. According to the ADT plugin page, we will put the URL
      and click Add
    3. Tick the newly added plugin, and click Next until done
  4. Next, we will install Android software development kit (Android SDK)
    1. Download the Android SDK from
      For (both 32- and 64-bit) Ubuntu, you will download android-sdk_r16-linux.tgz
    2. Extract android-sdk_r16-linux.tgz in the home folder (/home/yourusername/)
    3. The extracted folder is android-sdk-linux
    4. Now go back to Windows>Preferences
    5. On the left panel, click Android
    6. In the SDK Location, select your extracted SDK location, which is
    7. Click Apply and OK, wait a few minutes for the program to update
  5. Retrieve all necessary files for SDK
    1. Go to Window>Android SDK Manager
    2. Tick all the Android versions that apply, and click Install packages
  6. Done, So now you may proceed to build a new project!!!

Additional reading can be found from

How to remove white-border from a figure?

August 5, 2011 Leave a comment

When adding a figure to your publication, you might want to remove the undesired white-border off your figures. I believe that the best way is to create figures without the border if it is possible. In MATLAB, I think you can do so. However, if you have the figures already, you might want to have a program to remove the borders automatically, wisely and controllably. I developed a toolbox in MATLAB for this purpose. Please refer to the URL below.

The overview of white-border removal toolbox

Problems with Gmail and Thunderbird

April 21, 2011 Leave a comment

If your Gmail is full and you think you need to store all your old e-mails to your computer, you may consider using Thunderbird. But you might encounter some problems when using it. Here I collected some links regarding the problems and solutions.

Gmail: Move all emails in trash to inbox

How to Uninstall Thunderbird Completely and Then Reinstall It

“Thunderbird is already running, but is not responding. To open a new window, you must first close the existing Thunderbird process, or restart your system.”

Categories: Uncategorized Tags: , ,

How to install Greg Mori’s superpixel MATLAB code?

February 28, 2011 11 comments

This short note aims to show you how to use superpixel code from Greg Mori whose codes are observed to have very good results and used by a bunch of computer vision researchers. However, the installation process can be challenging sometimes ^_^, so I figured it’d be nice if I document the process so that it will be easier for absolute beginners to use the code, and more importantly…I can come back to read when I forget how to do it.

I have MATLAB R2010a installed on my Ubuntu 32-bit 10.04 LTS – the Lucid Lynx

I download Mori’s code, extract the zipped file to a folder called superpixels. The folder is located at

Next I download the boundary detector code from the link
I extract it to a folder called segbench, then I put it inside the superpixels
Here are the instructions of the folders

README (Mori’s)

– Run mex on *.c in yu_imncut directory
– Obtain mfm-pb boundary detector code from
– Change path names in sp_demo.m and pbWrapper.m
– Get a fast processor and lots of RAM
– Run sp_demo.m

README (segbench’s)
(1) For the image and segmentation reading routines in the Dataset
directory to work, make sure you edit Dataset/bsdsRoot.m to point to
your local copy of the BSDS dataset.

(2) Run ‘gmake install’ from this directory to build everything.  You
should then probably put the lib/matlab directory in your MATLAB path.

(3) Read the Benchmark/README file.

According to the README instruction
– Run mex on *.c in yu_imncut directory
I run mex on all the .c file in the folder
I don’t know why the command mex *.c does not work, so I have to run mex on every file one by one. Each time I run mex, I will get message
Warning: You are using gcc version “4.4.3-4ubuntu5)”.  The version
currently supported with MEX is “4.2.3”.
For a list of currently supported compilers see:
However, it seems to work fine since I can see all the .mexglx files show up in the folder. So I assume I do it correctly and go on the next step.

In this step,
– Obtain mfm-pb boundary detector code from
I got the code already, so I follow the README (segbench’s). Firstly, I do
(1) For the image and segmentation reading routines in the Dataset
directory to work, make sure you edit Dataset/bsdsRoot.m to point to
your local copy of the BSDS dataset.
So, I go to the file /home/student1/MATLABcodes/superpixels/segbench/Dataset/bsdsRoot.m and change the root to
root = ‘/home/student1/MATLABcodes/superpixels’;
which contains the image I want to segment, “img_000070.jpg”

Next, I do (2) in README (segbench’s)
(2) Run ‘gmake install’ from this directory to build everything.  You
should then probably put the lib/matlab directory in your MATLAB path.
Now at the folder, student1@student1-desktop:~/MATLABcodes/superpixels/segbench$
we need to make MATLAB seen in this folder, so we export the MATLAB path
student1@student1-desktop:~/MATLABcodes/superpixels/segbench$ PATH=$PATH:/usr/share/matlabr2010a/bin
student1@student1-desktop:~/MATLABcodes/superpixels/segbench$ export PATH
then use make install, this time I got quite a long message in the terminal
student1@student1-desktop:~/MATLABcodes/superpixels/segbench$ make install
Then you will notice some files in the folder
What you have to do here is to addpath in MATLAB by typing in the command window

Next, (3) Read the Benchmark/README file. I found that we don’t have to do anything in this step. So just skip this.

Now it’s the last step
Change path names in sp_demo.m and pbWrapper.m
so, go to the folder /home/student1/MATLABcodes/superpixels and change the path
in pbWrapper.m I make the path pointing to ‘/home/student1/MATLABcodes/superpixels/segbench/lib/matlab’
in sp_demo.m I make the path pointing to

Now run the file sp_demo.m. Unfortunately you will get some error messages because of a function spmd. This happens because MATLAB 2010a has function spmd of its own which has the number of input argument different from that of spmd from the toolbox. One way to get around this is to change the name of spmd.c in the toolbox to spmd2.c, then compile spmd2.c using mex spmd2.c. Then replace spmd(…) with spmd2(…). If you encounter more errors from this point on, don’t panic, because it’s probably from this spmd issue, so just do the same thing and it will work fine.

That’s it! Enjoy Greg Mori’s code!


For windows users, please refer to Thanapong’s blog, whose URL is given below:

Making Superpixels for An Image

February 17, 2011 Leave a comment

Nowadays it seems to me that people in computer vision community, especially who work on image segmentation, analysis, interpreting and classification, tend to adopt the idea of using superpixels rather than using raw pixels. That because superpixels can significantly reduce computational load of an algorithm, and are cheap to produce. In my work, image segmentation using graphical model, superpixels can potentially save me a lot of time running inference/learning algorithm tremendously. There are off-the-shelf  superpixel algorithms available on the internet.  I’m using QuickShift from VLFEAT toolbox and it works fine after manually tuning a couple parameters. Here are some results.

Segmentation result overlaid on the original image.

Segmentation result overlaid on the original image.

However, it is hard to find when you are in need…Therefore, I figure that it is a good idea to put those algorithms together in this post. To be honest with you, I haven’t been using them lately, so I forgot a lot. Well, I plan to add up and grow the collection on day by day basis. So, you are very welcome to suggest any algorithm you like. Let’s make this collection together!

Pablo Arbelaez’s UCM [link] — I have a problem installing it on my machine…

QuickShift in VLFEAT [link] — very convenient MATLAB toolbox

Segmentation by Minimum Code Length [link]

Greg Mori’s superpixel code [link]

Turbopixel [link]

Scale-Invariant Image Representation: the CDT Graph [link]

There are also some empirical studies on superpixel talking about how many superpixels should be in an image, advantages, disadvantages, behavior, etc., available. Here are my favorites:

Superpixel: Empirical Studies and Applications [link]

On Parameter Learning in CRF-based Approaches to Object Class Image Segmentation [link] by Nowozin and Lampert

and chapter4 of the (draft) book “Structured Learning and Prediction in Computer Vision” [link] by Nowozin and Lampert.