In your scenario, I would check performance of both modern lstm (v4/v5
engine) and old "classic" v3 OCR engine in tesseract. Just for completeness
sake; first tests would be in separate runs so I'ld be able to check the
output quality of both runs into HOCR format. (2 separate runs so I don't
have to bother within tesseract internal heuristic to "pick the best one"
and only dump that one: if I were you I'ld want to see both processes'
performance and decide what to do after that.

Postprocessing is akin to "fixing it in the mix": you only do that when all
other options have been depleted.


On Sun, 24 Mar 2024, 19:29 Misti Hamon, <mistiha...@gmail.com> wrote:

> I'm going to preface this with, I haven't actually done an OCR run yet (by
> the time any replies come in, I probably will have, the source image
> editing is almost done).
>
> I'm working with some photoscanned images of knitting related work (so,
> there are some non-word characters and acronyms used, most are still
> English but there are occasional symbols, some standard ascii or unicode,
> others specialty - I should be able to exclude the specialty symbols and
> keep them as an image, or at least I hope so), based on tesseract being a
> "groups of words" based recognition, it sounds like this might produce
> unexpected results?   (example of a line that might show up that could
> cause a problem would be - K2, yo, k2tog, k to last 4, ssk, yo, k2 -
> doesn't look like English words, kind of looks like a sentence *if* you
> assume a space or comma denotes a that which came before is a word)
>
> So, in order to handle/fix stuff like that, without training, I'm looking
> for tips on how to inspect my hOCR files to verify and, if necessary,
> correct the results, that work on linux without running wine. I am looking
> into the tools suggested in the "Post OCR Verification and Editing"
> conversation, but that poster is on windows, with a different toolchain,
> so, not sure all apply to me.
>
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