What Image Classification has become in 2019
Image classification is something that reminds me of the times of college when I had many AI courses and I played with it for the first time. At that moment, it was a very experimental field and, to use it on your project, you often had to implement a lot of stuff and fight with code before you had something to test.
A few years ago, when I had the opportunity to play again with it, I found a very very different scenario. Everything that was “experimental” at college time now is “standard” and academic things are now just libraries. When I discovered OpenCV, Tensorflow, Keras, I was amazed but scared at the same time. You can put together some lines of code copied from the internet and you can have a trained network without knowing anything about AI. That’s the power of progress. That was genius, talent, research is now condensed into an industrial process.
Since I moved my first step on this field, in 2008, there were relevant changes. The first feeling as an amateur, that now all the process is “deterministic”. By using standard technologies and good documentation, it is easier to make a network work. The experience is still important, and I don’t want to compare AI with a regular database read\write operation, but finding a lot of stuff, tutorial, guides is something that allows a newbie to get something working.
The credit for this is to the big players, as usual, They make accessible AI to developers, sharing their libraries, maybe just to let us know it’s easier to consume all the stuff from them as service. ;-)
Originally published at https://www.codeproject.com on May 13, 2019.
