I think pytesseract is a wrapper to the command-line, so you would probably see the same results by going directly. The python-tesseract [1] project used swig to do a deeper level of integration, though I tried the same approach a few years ago and didn’t really notice much difference in throughput. It’s possible you could use a segmentation tool like Olena [2] to carve up the image into individual paragraphs and fire off multiple instances of tesseract (see discussion here [3]). Olena might also give you a way to extract illustrations and such.
As for accuracy, I tried a Gaussian blur via opencv on the image and got slightly better results, though comparing OCR can be dicey past a certain level (the blur gave a few more words but also messed up a number). There are lots of tips in the mailing list on improving accuracy by image manipulation, but I’d start with the wiki page on this topic [4]. art --- 1. https://code.google.com/archive/p/python-tesseract 2. http://olena.lrde.epita.fr 3. http://stackoverflow.com/questions/4962978/is-tesseract-3-00-multi-threaded 4. https://github.com/tesseract-ocr/tesseract/wiki/ImproveQuality . -- You received this message because you are subscribed to the Google Groups "tesseract-ocr" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. To post to this group, send email to [email protected]. Visit this group at https://groups.google.com/group/tesseract-ocr. To view this discussion on the web visit https://groups.google.com/d/msgid/tesseract-ocr/DM3PR11MB103668656B075BD08F8D1485DC760%40DM3PR11MB1036.namprd11.prod.outlook.com. For more options, visit https://groups.google.com/d/optout.
