Hi Zdenko,

Sure, no problem -- I've made all the files, along with instructions, at
https://github.com/ddohler/tesseract-georgian

Cheers,
Derek

On Fri, Apr 3, 2015 at 4:06 AM, zdenko podobny <[email protected]> wrote:

> Can you create a repository for your training (in sourceforge or  github)?
>
> Maybe with detailed description how you created it (so potentially other
> people can try to improve/extend it).
>
>
> Zdenko
>
> Zdenko
>
> On Fri, Apr 3, 2015 at 5:04 AM, Derek Dohler <[email protected]> wrote:
>
>> ShreeDevi,
>>
>> Thanks for this -- I tried re-training tesseract with a range of exposure
>> values passed to text2image, but didn't see improved results.
>>
>> However, I did notice in the process that the x-heights for the document
>> I was attempting to recognize were near the lower limit of what Tesseract
>> can handle (~10px), so I doubled the image size. This resulted in much
>> improved recognition; there are still errors, but fewer of them and they
>> "make sense" now. Tesseract isn't able to segment the 5-column page layout
>> very well, but otherwise I'm pretty happy with the results.
>>
>> Derek
>>
>> On Thu, Apr 2, 2015 at 10:16 AM, ShreeDevi Kumar <[email protected]>
>> wrote:
>>
>>> Please see
>>>
>>> https://code.google.com/p/tesseract-ocr/source/browse/training/degradeimage.h
>>>
>>> https://code.google.com/p/tesseract-ocr/source/browse/training/degradeimage.cpp
>>>
>>> It maybe possible to do additional training using degraded versions of
>>> 'synthetic' images which may improve recognition of older documents.
>>>
>>> ShreeDevi
>>> ____________________________________________________________
>>> भजन - कीर्तन - आरती @ http://bhajans.ramparivar.com
>>>
>>> On Thu, Apr 2, 2015 at 7:05 PM, Sven Pedersen <[email protected]>
>>> wrote:
>>>
>>>> Cool! Good work. I hope that will help the others who have been asking
>>>> about Georgian for a couple years. :-)
>>>> --Sven
>>>>
>>>> On Wed, Apr 1, 2015 at 9:28 PM, Derek <[email protected]> wrote:
>>>>
>>>>> I've recently finished training tesseract 3.03-rc1 on the Georgian
>>>>> language, using tesstrain.sh and based off the files in the langdata
>>>>> repository. I created my own word list and bigrams list using Wikipedia.
>>>>>
>>>>> Performance is very good on high-quality scans with modern fonts, but
>>>>> it doesn't do very well on older documents; I'm not sure whether this is
>>>>> because of differences in the font, or because the synthetic images
>>>>> generated by the tesstrain.sh script don't give tesseract enough training
>>>>> in handling degraded images.
>>>>>
>>>>> I've uploaded the traineddata file and all training files here:
>>>>> https://dl.dropboxusercontent.com/u/11840441/kat_train20150401.zip
>>>>>
>>>>> I'm attaching a test image (a randomly-selected scan from Georgia's
>>>>> registry of corporations) and the output of running tesseract recognition
>>>>> on the test image. No pre-processing was done on the test image except to
>>>>> upsample it to 300dpi. The test image contains some Latin characters so I
>>>>> ran tesseract with the language selector "kat+eng".
>>>>>
>>>>> The licensing for any documents to which I hold the copyright is the
>>>>> same as the tesseract source, i.e. the Apache License, Version 2.0 (
>>>>> http://www.apache.org/licenses/LICENSE-2.0).
>>>>>
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>>>>
>>>>
>>>>
>>>> --
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