To find some of the more tedious bugs, I had to create 2 new debugging techniques: attached neurons and split paths, which I will explain shortly. The whole algorithm eventually became seriously elaborate to deal with some of the more complicated situations. I need to document this very soon before I forget myself (I guess the radio silence is out of the window, dev time simply took to long for 1 algorithm, I need to do at least 3 more of these which would take far to long). I’m pretty convinced there are still some caveats to work out, but, as far as I have been able to test, all the situations using a scanner flow definition seem to work. The core still shows some hick-ups at times, which can still result in bogus results, but this has also been improving considerably. Expect a new update very shortly (like in a week or so).

I am trying to get the flow recognition algorithm working so it can handle mixed content (words, numbers and signs mixed), which has been one of the more difficult algorithms I have worked on, to date. Clearly, I still haven’t got the order quite right.  This has been the main issue holding back a new release by the way.