TrOCR LaTeX (fine tuned on math handwriting) Take your handwritten math and turn it into clean LaTeX code. This is a fine tuned version of microsoft/trocr base handwritten , a transformer based optical character recognition model, adapted to work with handwritten math images and structured math syntax. Data Fine tuned on Google's MathWriting dataset. Contains over 500,000 digital inks of handwritten mathematical expressions obtained through either manual labelling or programmatic generation. Intended use & limitations You can use this model for OCR on a single math expression. There is degraded performance on very long expressions (due to image preprocessing, 3:2 aspect ratio seems to work best). Create an expression chunking scheme to split the image into subimages and process each to bypass this limitation. In order to process multiple expressions, you need to chuck groups into single expressions. How to use (PyTorch) Training Details Mini batch size: 8 Optimizer: Adam LR Scheduler: cosine fp16 mixed precision Trained using automatic mixed precision (AMP) with torch.cuda.amp for reduced memory usage. Gradient accumulation Used to simulate a larger effective batch size while keepi…
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