The new location of the blog is http://detexify.posterous.com. See you there.

I has been a while since my last post here. Development of Detexify had stalled because I was supposed to write a scientific paper about detexify and after that was done I needed a break so I spent my time on other projects.

Detexify seems to be having problems. Sorry for the inconvenience. I’ll look into it this evening.

Update:

The classifier server crashed. It is up again and is currently being trained up from the database. Operations should return back to normal state soon.

Yesterday I’ve prepared two databases - one for training data and one for test data. For every symbol that has at least 10 samples I’ve randomly chosen up to 100 samples and put one third into the test database and the rest into the training database. I’ve also created a benchmark script that I took for a spin yesterday night.

I have finally put the refactored architecture into production today. In short this means the app can now much more easily be updated (e.g. interface improvements, symbols be added). You won’t notice anything of that just now, because the interface has not changed at all, yet.

I have added some functionality to the symbol table today. After a lot of work in the backend, finally something that people can see :P.

The iPhone app went live on the iTunes App Store a few days ago. So now Detexify can be used in your browser, on Android powered devices and on the iPhone. Just go to http://itunes.com/coolcherrytrees and grab either the free version or buy the supporter version (which is identical to the free version but you support the development of Detexify by buying it).

new backend

Detexify now uses MongoDB as backend storage. Why? Detexify did not really need all the things that CouchDB is great for. No concurrency - only one server process that needs to load all data into memory on boot. No need for MapReduce views. Instead it needs to do the initial loading fast so that downtimes are short. This was considerably faster with MongoDB. In addition I use MongoDB’s capped collections to cache the container for the samples that permanently stay in memory. This container functions identically to MongoDB’s capped collections so they were a perfect match. If you tried to use detexify in the past few days you will have noticed the extremely slow startup times. If it needs a restart now it should be up again in less than two minutes.

Detexify will be my diploma thesis. That means almost full time work on it.