doctr

checkout https://github.com/mindee/doctr or https://github.com/VikParuchuri/surya for something practical multimodal llm would of course blow it all out the water, so some llama3-like model is probably SOTA in terms of what you can run yourself. something like https://huggingface.co/blog/idefics2

https://github.com/mindee/doctr/issues/1049 https://github.com/JaidedAI/EasyOCR#whats-coming-next Happy to see OCR is advancing lately, but I really need HWR. I am looking for something this polished and reliable for handwriting, does anyone have any pointers? I want to integrate it in a workflow with my eink tablet I take notes on. A few years ago, I tried various models, but they performed poorly (around 80% accuracy) on my handwriting, which I can read almost 90% of the time.

Tesseract alone is widely known to be "meh" at this point. If you look at RAG frameworks as one example they'll typically use/support a variety of implementations. Tesseract is almost always supported but it's rarely ideal with projects like Unstructured[0] and DocTR[1] being preferred. By leveraging more-or-less SOTA vision models[2][3] they embarrass Tesseract. I haven't compared them to the Apple Vision framework but they're absolutely better than Tesseract and potentially even Apple Vision. There are also various approaches to use these in conjunction but that gets involved. [0] - https://github.com/Unstructured-IO/unstructured-inference [1] - https://github.com/mindee/doctr [2] - https://github.com/mindee/doctr#models-architectures [3] - https://github.com/Unstructured-IO/unstructured-inference#mo...