It's usually better to segment the text on the image (and twek the perspective if necessary) to help tesseract extract the text. All the "easy" preprocessing that can be done beforehand helps a lot. I understand that Google Vision Services doesn't need these kind of adjustments (or maybe they do them automatically?), which makes for an easier time/less code, but setting up the account sure looks like a lot of work from the article!

That's a good tip about the segmenting text, will have to keep that in mind next time.

I like the local aspect, one project I have in mind is a hand writing to printed letters for note taking/tablets. Not a new concept I think one drive has it, but it would be neat to train it on your own writing.

Why not Zoidberg

If you want to train your own net for handwritten letters, you can start with EMNIST[0] and then move on from there.

[0] https://www.nist.gov/itl/products-and-services/emnist-datase...

Thanks, yeah it's an ambitious project. It's cool but has no real gain immediately. Maybe if I was a student/used a tablet everyday.