I was only using two different fonts and It only achieved lowest error rate 
of 11.271 after the training, does this mean I really need to increase the 
iterations?

在 2019年6月17日星期一 UTC-4下午2:16:31,shree写道:
>
> How big was your training text? How many iterations? Did the fonts you use 
> for training support the plus minus sign? 
>
> You can run training with -- debug-level of -1 so that you can see whether 
> the plus minus is being picked for training in the console messages.
>
> On Mon, 17 Jun 2019, 23:29 Jingjing Lin, <joejo...@gmail.com <javascript:>> 
> wrote:
>
>> Thanks. It works. The new character I added was there.
>>
>> Do you have any idea why after fine tuning tesseract still couldn't 
>> recognize the new character I added? When I tried to add '±' to eng it 
>> works, but when I tried to add '±' to chi_sim, it couldn't work (explained 
>> below). Is there anything we need to pay attention to when fine tuning 
>> other langs rather than eng?
>>
>> I used 
>>
>> lstmeval --model ~/tesstutorial/trainplusminus/plusminus_checkpoint \
>>   --traineddata ~/tesstutorial/trainplusminus/chi_sim/chi_sim.traineddata \
>>   --eval_listfile ~/tesstutorial/evalplusminus/chi_sim.training_files.txt 
>> 2>&1 |
>>   grep ±
>>
>> to check and ± only shows up in Truth but not in OCR
>>
>>
>> 在 2019年6月17日星期一 UTC-4上午11:31:24,shree写道:
>>>
>>> combine_tessdata -u new.traineddata new.
>>>
>>> will unpack the traineddata file. check new.lstm-unicharset in it
>>>
>>> On Monday, June 17, 2019 at 8:20:24 PM UTC+5:30, Jingjing Lin wrote:
>>>>
>>>> I tried to fine tune the model and add a new character via training, 
>>>> but it seems it still couldn't recognize this new character using the new 
>>>> traineddata generated. To debug I want to check whether this new character 
>>>> is in the .unicharset in the new traineddata generated. Is there a way to 
>>>> do this?
>>>>
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