This is an update to my previous post, “Inspiration strikes a chord!”, detailing my pet project to decipher the songs in some decorative piano rolls I found in a restaurant. Click the following links for post 1, post 2!, and post 3!
Time to up the ante. At this point, all my development and testing has centered about a single photograph – with ideal lighting, minimal glare, and a bird’s eye viewing angle. These niceties have translated into gross assumptions in my algorithm, which will likely stick out like a sore thumb when I use different data.
So let’s do exactly that!
Here are results from three completely different photographs. I’m quickly discovering what does and does not generalize in the current algorithm. Two examples: variations in lighting cause the threshold function to generate false positives and negatives; and my pitch-scale error minimization doesn’t always converge.
Enjoy!
…and here’s some metadata…
