Old thread
https://groups.google.com/forum/#!searchin/tesseract-ocr/layer$20chi_sim%7Csort:date/tesseract-ocr/iFMg7Gjczq4/f7_XRop2BAAJ


On Wed, Jun 19, 2019 at 9:13 PM Shree Devi Kumar <shreesh...@gmail.com>
wrote:

> Update:
>
> 1. When using a smaller training_text for chi_sim for plus training, the
> unicharset gets restricted. So, merge the lstm-unicharset with it.
>
> 2. The unicharset for chi_sim using langdata is different from the one
> extracted from tessdata_best. so using training_text from langdata will add
> more characters.
>
> 3. The fonts used for LSTM training are given in langdata_lstm in
> okfonts.txt. For plus training same fonts should be used otherwise it will
> require training of new typefaces.
>
> 4. Another user was trying to fine-tune chi_sim (check old forum posts) to
> add theta sign. If I remember correctly, the plus type training did not
> work for it. Replace top layer was the better option.
>
> 5. I am training with the following fonts.
> "Adobe Heiti Std" \
> "Adobe Kaiti Std" \
> "Arial Unicode MS" \
> "Bitstream CyberCJK" \
> "Microsoft YaHei UI" \
> "Microsoft YaHei" \
> "NSimSun" \
> "Noto Sans CJK SC" \
> "Noto Sans Mono CJK SC" \
> "STXihei" \
> "SimSun" \
> "WenQuanYi Zen Hei Medium" \
> "WenQuanYi Zen Hei Mono Medium" \
> "WenQuanYi Zen Hei Sharp Medium" \
>
> At iteration 1046/1100/1100, Mean rms=0.704%, delta=1.445%, char
> train=4.888%, word train=46.842%, skip ratio=0%,  New best char error =
> 4.888 wrote best
> model:/home/ubuntu/tesstutorial/chi_sim_plus/chi_sim_plus4.888_1046.checkpoint
> wrote checkpoint.
>
>
> On Wed, Jun 19, 2019 at 12:36 AM Jingjing Lin <joejoeu...@gmail.com>
> wrote:
>
>> Can you please test on arrows (↑
>> <https://en.wikipedia.org/wiki/%E2%86%91_(disambiguation)> or ↓
>> <https://en.wikipedia.org/wiki/%E2%86%93_(disambiguation)>) instead of ±
>> if it's not inconvenient for you?
>>
>> 在 2019年6月18日星期二 UTC-4下午2:21:18,shree写道:
>>>
>>> I will test tomorrow and let you know
>>>
>>> On Tue, 18 Jun 2019, 23:47 Jingjing Lin, <joejo...@gmail.com> 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 <joejo...@gmail.com>
>>>>> 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 <joejo...@gmail.com>
>>>>>>> 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, <joejo...@gmail.com>
>>>>>>>>> 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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> ____________________________________________________________
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