Segmenting can likely be done on a really small resolution and with a CNN, making it real short.

There are some heuristic ways of doing it but i doubt you'll be able to distinguish equations from text.

Segmenting at lower resolution and then using them at higher resolution using resolution multipliers don't work as other items bleed in. FastSAM paper has some interesting ideas on doing this with CNNs which I guess SAM2 have superseded. However, the complication in the pipeline is not worth the result as I find vision LLMs are able to do almost the same task within the same OCR prompt.

Apple APIs such as Live Text, subject identification, Vision. Run them on a server, too