At Mapado, as you may know, we want to offer the possibility to search “things to do close to you”. And by close we mean culturally, and geographically too.

About this second point, we did not find a better solution than an auto-complete search field whit a city list in a dropdown (as you can see in the featured image).

Here is the solution we implemented.

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After testing cropping images using entropy, we now try to go deeper in Image crop automation.

Those are nice feet

One of our worst case scenarios emerged from pictures like that this one :


If we only use the “entropy” crop, the render is as following :


The bottom of this picture seems to be the most informative part, which would explain why it is selected by the entropy crop. Even though this woman has nice feet, we’re not absolutely satisfied with the crop, as it remove what we believe to be the most important part of the picture: the woman’s face.

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Yesterday, and for the first time, Jerry presented Mapado to the public of StartInLyon.
The concept is simple: 5 startups given 5 minutes of pitch and 5 minutes of Q&A. At the end of the pitches, the audience vote for their favorite project with text messages. We were competing with 4 other startups: DarlingBox, DoYouArtGolfonsGroupés and VidCoin, each of them promoting a very cool project.

It was very exciting to show what Mapado is about and the premises of what it will look like!

We are very proud to announce that we came first! Many, many, thanks to everyone believing in this project. It stimulates us even more now that we know for sure that people are eager to use our service.
Many thoughts to VidCoin, it was very close 🙂


Cropping an image with a script is not a big deal as there are many libraries available in every language, but some could lead to the following case :


A few web searches about “failsafe crop” led us to a very interesting paper : A Unified Approach to Salient Object Detection via Low Rank Matrix Recovery

Unfortunately, it involves multiple steps  and a lot of computing (~ 3 to 6 seconds per image).

We developed a python module to optimize crop quality, based on the concept of maximum entropy (ie : maximum quantity of information).

cropy is in early stage and has some issue but gives some good results if the crop width or height is not far from the original image.

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I spend the last two days installing Graphite on our server at mapado.

What we have:

  • Linux server with Debian Squeeze
  • Python 2.7 installed system-wide with python headers ( sudo apt-get install python-dev)
  • virtualenv and virtualenv-wrapper installed ( sudo pip install virtualenv virtualenv_wrapper)
  • cairo installed system-wide (apparently cairo dos not work fine with pip, so :  sudo apt-get install python-cairo)
  • Apache2 server running

What we wanted:

  • A Graphite instance running in his own virtualenv and accessible via
  • A StatsD daemon
  • Monitor our Symfony2 project
  • Monitor our python projects

Here is what we have done to achieve that: Read more →