We have a not free postprocessing software with 38 filters for a optimal
OCR Its called BIQE = Batch Image Quality Enhancer which also works with
Tesseract 4 OCR
Op donderdag 24 november 2022 om 20:57:17 UTC+1 schreef zdenop:
> please read and follow the docs:
> https://github.com/tesseract-oc
We have a postprocessing software (not free) which has 38 filters to
improve the OCR of an image in batch Its called BIQE
Op maandag 7 november 2022 om 21:37:55 UTC+1 schreef Аллигатор:
> Hi. Is it possible to improve the quality of text recognition? --oem 0
> recognizes better than --oem 3, bu
I'm using Tesseract-3.0.5, and Tessdata-3.0.4
I have trained the font successfully., and Tesseract recognizes the
properties of the fonts. I have 2 fonts trained, namely: Ubuntu, and Inter.
Tesseract assigns appropriate properties to Ubuntu font but misses
sometimes when assigning font-size to I
Which Tesseract version are you using?
On Thursday, 15 December 2022 at 13:19:50 UTC+1 soumenha...@gmail.com wrote:
> *Please help me*
>
> ESSDATA_PREFIX=../tesseract/tessdata make training MODEL_NAME=foo
> START_MODEL=eng TESSDATA=../tesseract/tessdata MAX_ITERATIONS=10
> combine_lang_model \
>
Hi
Consider an image containing a mix of English and German text.
Extracting wordstr boxes from it and fixing mistakes.
When fine tuning the two languages, I get encoding errors for English as it
does not contain German chars.
What is the correct approach here?
1. Ignore encoding errors? What
I am a simple user of Tesseract, with a single purpose. I scan Proof of
Delivery slips which have a 6 digit number in the text. I successfully OCR
the number and file the scan image using the number.
But often the numbers 8 and 3 and 5 and 6 are confused.
Rather than do anything with the Tessera
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