It seems like with the current progress in ML models, doing OCR should be an easy task. After all, recognizing handwritten numbers was one of the prime benchmarks for image recognition (MNIST was released in 1994).
Yet, when I try to OCR any of my handwritten notes all I ever get is a jumbled mess of nonsense. Am I missing something, is my handwriting really that atrocious or is it the models?
Here’s a quick example, a random passage from a scientific article:
I tried EasyOCR, Tesseract, PPOCR and a few online tools. Only PPOCR was able to correctly identify the numbers and the words “J.” and “Chem.”. The rest is just a random mess of characters.
Edit: thank you all for shitting on my handwriting. That was not asked for, and also not helpful. That sample was intentionally “not nice” but is how I would write a note for myself. (You should see how my notes look like when I don’t need to read them again, lol)
chatGPT can transcribe it perfectly, and also works on a slightly larger sample. Deepseek works ok-ish but made some mistakes, and gemini is apparently not available in my country atm. I guess the context awareness is what makes those models better in transcription, and also why I can read it back without problems.
In a single (but not smooth) stroke, like how one would write a (mirrored) h, but where you would end the h normally, you connect it back to the bottom of the stem instead.
That’s even weirder that you’d do ol for d then. I’d expect you to do a single stroke o, starting at the right hand side, but upon completing the o, continue straight up to make the stem of the d.
IMO a hallmark of messy writing should be the shortcuts taken to reduce the amount of lifts of the stylus for efficiency’s sake. You need to improve the efficiency of your sloppiness, to make things worse so it gets better 😂