> When it's combining language model I've spotted that it's making some
dawg files.

Yes, it takes the files from langdata repo specified in the training
command.

You could change langdata/pol/pol.wordlist to have only the LAST NAMES and
GIVEN NAMES, pol.punc to have only < and change number formats in
pol.numbers to the MRZ number patterns (i.e. any required customizations
based on your use set).

I am not sure how much the dawgs help with the LSTM engine, but you can try
after customizing to see if you get improved results.

On Thu, Sep 6, 2018 at 4:23 PM, <kaminski.robert...@gmail.com> wrote:

> Thank you for your reply Shreeshrii!
>
> Indeed finetune method is much much better solution for my problem. Thanks
> to your logs and data provided in repo I realized that I don't need to
> generate every single MRZ code separately (I'm sure it was mentioned
> somewhere <dummy>). In fact the process of making tiffs with boxes and then
> lstmf's was oddly long (also loading lines in form o pages takes much less
> time). Using merged data is now just a matter of seconds. I don't know if
> it affected accuracy but now I'm generating every code in one .txt file and
> then processing it.
>
> I've managed to make my own trainneddata based on polish language and
> results are outstanding. Thank you very much!
>
> Usually I've avoided tesstrain.sh script and was trying to use my own just
> to customize the process and control it. When it's combining language model
> I've spotted that it's making some dawg files. Is it because I'm using
> already existing language data? If so how can i generate langdata myself
> for custom language. In this case documentation isn't so clear. I know that
> it's created by combine_lang_model based on wordlist(langdata). I don't
> need it at the time but I think it's good idea to clear that out if I'll
> need to do some training from scratch although I know it's rare case.
>
> Thank you for taking your time to solve my problem! :)
>
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