I see the tabular image that you shared.  I don't think training is going
to help you in this. eng.traineddata should be able to recognize it quite
well. You should select the different areas of interest and just OCR those
sections.

On Fri, Feb 5, 2021 at 5:33 PM Kumar Rajwani <kumarrajwani1...@gmail.com>
wrote:

> i have tried to do same thing in tesseract 4 which stuck at following line.
> Compute CTC targets failed!
>
> On Friday, February 5, 2021 at 5:04:42 PM UTC+5:30 Kumar Rajwani wrote:
>
>> !tesseract -v
>> tesseract 5.0.0-alpha-20201231-171-g04173
>>  leptonica-1.78.0
>>   libgif 5.1.4 : libjpeg 8d (libjpeg-turbo 1.5.2) : libpng 1.6.34 :
>> libtiff 4.0.9 : zlib 1.2.11 : libwebp 0.6.1 : libopenjp2 2.3.0
>>  Found AVX2
>>  Found AVX
>>  Found FMA
>>  Found SSE
>>  Found OpenMP 201511
>>  Found libarchive 3.2.2 zlib/1.2.11 liblzma/5.2.2 bz2lib/1.0.6
>> liblz4/1.7.1
>>
>> image example
>> i have added one image from my training data.
>>
>> i am using the colab system which have ubuntu os.
>>
>> https://colab.research.google.com/drive/1_Bn4wbK6dE5zYAuFyC4Eczq_eNU2shuz?usp=sharing
>> this is my notebook you can see complete process in finetune 2 section.
>>
>>
>> On Friday, February 5, 2021 at 4:55:43 PM UTC+5:30 shree wrote:
>>
>>> On Fri, Feb 5, 2021 at 4:44 PM Kumar Rajwani <kumarraj...@gmail.com>
>>> wrote:
>>>
>>>> hi,
>>>
>>> i have tried minus 1 and got following result
>>>> Iteration 0: GROUND  TRUTH : ) @®
>>>> Iteration 0: BEST OCR TEXT : Yo
>>>> File eng.arial.exp0.lstmf line 0 :
>>>>
>>>
>>>
>>>> What's your version of tesseract? What o/s?
>>>>
>>>
>>> Without your files, it's difficult to know what's causing the issue.
>>>
>>> with -1 debug_interval you should get the info for every iteration.
>>>
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