I am also having similar problem. I have trained KB-JT-NEW from ben 
(continue from) and found the result: 

At iteration 127102/500000/500000, Mean rms=0.437%, delta=1.593%, char train
=11.184%, word train=11.098%, skip ratio=0%,  New worst char error = 11.184 
wrote checkpoint.

Finished! Error rate = 7.737
lstmtraining \
--stop_training \
--convert_to_int \
--continue_from data/checkpoints/KB-JT-NEW_checkpoint \
--traineddata data/KB-JT-NEW/KB-JT-NEW.traineddata \
--model_output data/KB-JT-NEW.traineddata
Loaded file data/checkpoints/KB-JT-NEW_checkpoint, unpacking...

But putting the .traineddata on /usr/local/share/tessdata/ and executing  
recognition gives bizarre result and showing:
Failed to load any lstm-specific dictionaries for lang KB-JT-NEW!!




On Tuesday, March 27, 2018 at 1:45:55 PM UTC+6, [email protected] wrote:
>
> Hello,
>
> I am working on a project where I extract and the license plates and try 
> to get the plate number automatically.
>
> After applying some computer vision and image processing, I have come up 
> with the following result.
>
> <https://lh3.googleusercontent.com/-g6CxXgDj3ck/Wrl-DoT61lI/AAAAAAAAACs/hcE9t8zmQJk_almmkwFZJYXcSuB717OywCLcBGAs/s1600/topcrop1.jpg>
>
>
> As it can be very obvious, the OCR generated with tesseract is: 6JZX97L
>
> Where as, actually, it is 6JZX974.
>
> I a, very new to the tesseract and it seemed like a very easy to use 
> library for my task, however, I do not have any idea on how to tackle a 
> scenario like this. If there is anyone who has worked on solving such a 
> problem, please share thoughts.
>
> Some other error prone numbers/letters: 0-O, 1-I, 2-Z, 5-S, 8-B...
>
> Thanks!
>

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