I’ve been doing OCR of scans of old magazines (specifically extracting music reviews and charts, so turning complex layouts into structured data) and have been impressed with GPT/Codex’s performance.
My setup has a Sol orchestrator and Terra OCR agents and seems to get great results. I’ve not dug into the details too much, it also has a Tesseract stage as an deterministic input which it told me helped. Not sure how token efficient it is but I often don’t have anything to do with my personal tokens ahead of a reset so just let it burn through it in batches.
I am impressed (both in this task and other work I’ve done) not just at how well Codex can setup a structure for a complex task like this, but how it will keep going (Claude seems to find excuses to stop) and also can critique and refine its approach as it goes.
I did try out a bunch of other models and specific OCR providers but none of them hit the same accuracy for my task as Codex so I’m sticking with it.
My setup has a Sol orchestrator and Terra OCR agents and seems to get great results. I’ve not dug into the details too much, it also has a Tesseract stage as an deterministic input which it told me helped. Not sure how token efficient it is but I often don’t have anything to do with my personal tokens ahead of a reset so just let it burn through it in batches.
I am impressed (both in this task and other work I’ve done) not just at how well Codex can setup a structure for a complex task like this, but how it will keep going (Claude seems to find excuses to stop) and also can critique and refine its approach as it goes.
I did try out a bunch of other models and specific OCR providers but none of them hit the same accuracy for my task as Codex so I’m sticking with it.