Super Parsing

This is my first Computer Vision related post. Hopefully, the first of many to come.

I wanted to try out the "SuperParsing" (ECCV 2010) code to segment some of the Street View Panoramas that I have. The code is available for download from here:

http://www.cs.unc.edu/~jtighe/Papers/ECCV10/>http://www.cs.unc.edu/~jtighe/Papers/ECCV10/

However to build the code, there are several dependencies that need to be installed. The first amongst them is the "Efficient Graph-Based Image Segmentation" code. This code can be downloaded from here:

http://people.cs.uchicago.edu/~pff/segment/

In this post, I am logging the small problems I faced while executing the above code and how I overcame them.

1. Building the code is straightforward. A simple "make" does the job.

2. The code expects an input image in the PPM format. If you are new to the PPM format (like I was), here is the complete specifications:

http://netpbm.sourceforge.net/doc/ppm.html

Well, I had my input image in the PNG format. Here is the PNG image (a street view panorama):

 

To convert it to PPM format, I used ImageMagick's "convert" command. ImageMagick can be downloaded from here http://www.imagemagick.org/script/index.php.

But the problem is that the segmentation code expects an 8-bit image (0 - 255). So, this has to be specifically mentioned while using the convert command. Also, in case the input image is too big, you can resize while converting it.

$ convert input.png -depth 8 -resize 50% input.ppm

Now we are all set to run the segmentation code. The arguments below are as given in the README file:

$ ./segment 0.5 500 20 input.ppm output.ppm
loading input image.
processing
got 2468 components
done! uff...thats hard work.

Now we can convert the segmented image back to the (more) standard PNG format.

$ convert output.ppm output.png

Here is the output segmented image:

Thats nice! Ok, more to come later...