Don't get me wrong, in terms of deployability and flexibility for production usage, TensorFlow/TFLite is really good, specially compared to other frameworks, but Google tends to oversell the abilities of open-source TensorFlow significantly in their marketing material, and you only find out when you go and try doing it yourself.
The reality is more, TensorFlow is really the only option you have if you don’t want to build everything from scratch again. Whether that’s a good or bad thing, well at least it’s because TensorFlow is actually a good product and not because Google is preventing others from building their own / pushing others down.
Neural nets usually thrive on raw high dimensional inputs, so dramatically reducing the dimensionality of the input seems like a strange decision. I'm sure it improves speed, but I would expect higher accuracy by processing the raw input.
but how is it that we have RNN solutions for handwriting when we don't even have a standard, canned RNN for OCR?
I know tesseract and related projects exist, but when I've tried them they have been fairly brittle with lower accuracy than I was expecting. Accuracy was especially problematic for letter combinations like "-ing" that would consistently be recognized as "-mg".
Is there a good ML OCR library I'm missing?
You do not have that for ing, so the software does not know that the dot is “independent”).
Online OCR is when you input the strokes directly on the tablet/phone, so it becomes a sequence of XY coordinates with an associated timestamp. It takes into account where you start and where you end the stroke on the canvas, along with the intermediate points (information galore).
Offline OCR is when you take a photo of your handwriting in your notebook, so you just get the raw pixels of a image. In offline OCR, you'd also have to properly segment and binarize the image before the OCR step.
With that being said, tesseract (version 4) uses an LSTM.
Edited with the QWERTY keyboard:
I just tried it out for the first time, and although the keyboard space on my phone is barely large enough to cram five characters in there, the input scrolls sideways automatically if you lift your finger long enough. So longer words can be entered as well. It doesn't seem to reevaluate previously decoded segments based on what follows, though, so you can end up with weird misspellings at the beginning of words. I don't think I'm going to use it from now on, because the recognition is bad enough to require significant editing and the friction is a bit too uncomfortable without a stylus.
Handwriting recognition is way more impactful for users in, say, Chinese.
(on iPhone right now)
