deselaers edited this page Apr 5, 2015 · 1 revision
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Step-by-step instruction to compile FIRE on Ubuntu 10.4.

To facilitate installation, I provide here a description how to compile the FIRE server on Ubuntu 10.4 from scratch.

The description applies to FIRE V 2.3 (SVN checkout of July 26, 2010).

Compiling FIRE

  • default Ubuntu 10.4 installation (in May 2010 in virtualbox)
  • upgrade to recent state (sudo apt-get update; sudo apt-get dist-upgrade) on July 26, 2010
  • sudo apt-get install subversion g++ libmagick++-dev
  • svn checkout fire-cbir
  • cd fire-cbir
  • make

After that the bin-Directory contain a total of 47 binaries and the FIRE server is ready to use.

Integration with Apache

  • sudo apt-get install apache2
  • cd ~/fire-cbir/
  • sudo cp Python/ /usr/lib/cgi-bin
  • cd WebInterface
  • sudo cp fire-template.html /usr/lib/cgi-bin
  • sudo mkdir /usr/lib/cgi-bin/images
  • sudo cp neutral.png positive.png negative.png fire-logo.png i6.png /usr/lib/cgi-bin/images

Now all the files should be in place for the FIRE webinterface to work

Setting up a dataset

  • create a directory mkdir ~/fire-img
  • put a set of medium sized images (e.g. 500x500 pixels) into this directory. For a start use about 100 images.
  • convert all images into jpg (not necessary but often avoids problems)
  • cd ~/fire-img
  • mogrify -format jpg *
  • extract color histograms
  • ~/fire-cbir/bin/extractcolorhistograms --color --images ~/fire-img/*.jpg
  • create a filelist for this dataset
  • cd ~/fire-img/
  • echo FIRE_filelist > filelist
  • echo suffix color.histo.gz >> filelist
  • echo path this >> filelist
  • ls *.jpg | sed 's/^/file /' >> filelist

Now you have a dataset where every image is represented using a color histogram. Other features can be added by extracting them and adding the corresponding suffix lines to the filelist.

Starting the FIRE server and accessing it through the webinterface

  • cd ~/fire-cbir
  • ./bin/fire -f ~/fire-img/filelist -r 10
  • Access the fire webinterface throught http://localhost/cgi-bin/
  • There you should be able to click an image and get similar images (according to color histograms)