I will test tomorrow and let you know

On Tue, 18 Jun 2019, 23:47 Jingjing Lin, <[email protected]> wrote:

> It still couldn't work after I increased the number of ± to about 100. And
> the error rate after 2000 iterations is about 11. This is a pretty high
> error rate compare to what we have for adding a few characters to eng. With
> such high error rate, I would not be surprised that it could't recognize
> some special characters like ±. Is this it for chi_sim? Or can I increase
> iterations to make the error rate smaller?
> Thanks for your help.
>
> 在 2019年6月18日星期二 UTC-4上午10:32:37,shree写道:
>>
>>  increase the number of ± to about 100
>>
>> On Tue, Jun 18, 2019 at 7:39 PM Jingjing Lin <[email protected]> wrote:
>>
>>> Sorry to bother you again and again.
>>> I reduced the training text to about 450 lines, with like 30 ± in it. I
>>> used two fonts and iteration of 1000. But it looks like ± is still not
>>> picked up by the BEST OCR TEXT at all, it always recognizes ± as something
>>> else. What is happening here? Should I increase the number of ±? Or do I
>>> need to increase the number of fonts? I'm trying increasing iterations.
>>>
>>> 在 2019年6月18日星期二 UTC-4上午12:28:25,shree写道:
>>>>
>>>> If you increase the iterations then the plus type of training will not
>>>> give good result, i.e. the other letters will lose accuracy.
>>>>
>>>> You can try to reduce the training text size while still keeping all
>>>> the characters that you need as part of the training text,
>>>>
>>>> On Tue, Jun 18, 2019 at 2:24 AM Jingjing Lin <[email protected]>
>>>> wrote:
>>>>
>>>>> 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, <[email protected]> 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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>>>>
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>>>> ____________________________________________________________
>>>> भजन - कीर्तन - आरती @ http://bhajans.ramparivar.com
>>>>
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