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Neural network example built using pyBrain to classify images by histogram.
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HistoNet (beta)

An image histogram is a type of histogram that acts as a graphical representation of the tonal distribution in a digital image. It plots the number of pixels for each tonal value. By looking at the histogram for a specific image a viewer will be able to judge the entire tonal distribution at a glance.

This project aims to create a tool to classify imgaes by analyzing histograms using a neural network. I took the idea from Green Dam Youth Escort. Green Dam recognizes pornographic images by analyzing skin-coloured regions, complemented by human face recognition. However, according to a Southern Weekly article, the software is incapable of recognizing pictures of nudity featuring black or red-skinned characters but sensitive enough to images with large patches of yellow that it censors promotional images of the film Garfield: A Tail of Two Kitties. Thats why I decided to add the neural network.

This project still very beta! And needs your colaboration! Thanks!


  1. Do some refactoring (DRY principle)
  2. Add persistence
  3. Unit-Testing


  1. Fork it
  2. Create your feature branch (git checkout -b my-new-feature)
  3. Commit your changes (git commit -am 'Added some feature')
  4. Push to the branch (git push origin my-new-feature)
  5. Create new Pull Request


Copyright (C) 2012 Guillermo Colmenero

This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

You should have received a copy of the GNU General Public License along with this program. If not, see

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