I suggest that you open issue in tesstrain repo.

The makefile does training from scratch. Is that what you wanted? Do you
have a large enough training text - how many lines? How many iterations for
training?

 Eval Char error rate=133.33333, Word error rate=96.875

That is a very high error rate. You need to get it down to 0%.

On Thu, Oct 10, 2019 at 11:26 AM J L <[email protected]> wrote:

> My system info:
> - OS: Ubuntu Desktop 18.04 LTS (4.15.0-55-generic)
>
>
> Hi.
>
> I am beginner and am trying to train some Korean character images for
> Korean recognition.
>
> To understand how to train with Tesseract 4.0 LSTM, I followed Tesstrain.
>
> I followed lines of Makefile in the Tesstrain step by step, and most of
> steps seemed to work fine until creating traineddata.
>
>
> *In detail:*
>
> 1. I made box files and unicharset by following this lines
> <https://github.com/tesseract-ocr/tesstrain/blob/master/Makefile#L128-L138>
> .
>
> 2. I made lstmf files by following this lines
> <https://github.com/tesseract-ocr/tesstrain/blob/master/Makefile#L140-L145>
> .
>
> 3. I made two split file lists for training and evaluation by following this
> lines
> <https://github.com/tesseract-ocr/tesstrain/blob/master/Makefile#L115-L116>
> .
>
> 4. Before combining lang model, I downloaded radical-stroke.txt by
> following this line
> <https://github.com/tesseract-ocr/tesstrain/blob/master/Makefile#L191>,
> and 3 langdata files (kor.punc, kor.numbers, and kor.wordlist) from this
> link <https://github.com/tesseract-ocr/langdata_lstm/tree/master/kor>.
>
>     I didn't download kor.config file because it cause an error that
> chi_tra.traineddata is needed.
>
> 5. I combined lang model by following this lines
> <https://github.com/tesseract-ocr/tesstrain/blob/cf7854cbf2a07013fc3df2bbaddebf719534b27b/Makefile#L255-L264>
> .
>
> 6. Then I started LSTM training by following this lines
> <https://github.com/tesseract-ocr/tesstrain/blob/master/Makefile#L173-L180>
> .
>
> 7. I tested them. The results are like:
> lim@ubuntu:~/tools/tesstrain$ usr/bin/lstmeval --traineddata
> data/kor/kor.traineddata --model data/kor/checkpoints/kor_checkpoint
> --eval_listfile data/kor/list.eval
> data/kor/checkpoints/kor_checkpoint is not a recognition model, trying
> training checkpoint...
> Loaded 1/1 lines (1-1) of document
> data/ground-truth/kor.malgun.exp249.lstmf
> Loaded 1/1 lines (1-1) of document
> data/ground-truth/kor.malgun.exp228.lstmf
> Truth:먹
> OCR  :이
> Truth:독
> OCR  :이
> Loaded 1/1 lines (1-1) of document
> data/ground-truth/kor.malgun.exp197.lstmf
> Loaded 1/1 lines (1-1) of document data/ground-truth/kor.malgun.exp41.lstmf
> Truth:파
> OCR  :이
> Truth:신
> OCR  :열
> ... (skip)
> At iteration 0, stage 0, Eval Char error rate=133.33333, Word error
> rate=96.875
>
> There seems to be no problem with the results.
>
> 8. I made traineddata output file.
> lim@ubuntu:~/tools/tesstrain$ usr/bin/lstmtraining --stop_training \
> --continue_from data/kor/checkpoints/kor_checkpoint \
> --traineddata data/kor/kor.traineddata \
> --model_output usr/share/tessdata/kor.traineddata
>
> 9. Then I used tesseract with kor.malgun.exp197.tif. the TIF file was
> shown to *'이'* when I followed step 7 (testing with lstmeval). So I
> expected the same result.
> lim@ubuntu:~/tools/tesstrain$ usr/bin/tesseract
> data/ground-truth/kor.malgun.exp197.tif stdout -l kor --psm 6 > result
>
> But the real result was totally mess. It's the result:
>
> [image: res.JPG]
>
>
>
> Why the results of `lstmeval` and `tesseract` are different?
>
> Thank you...
>
>
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>


-- 

____________________________________________________________
भजन - कीर्तन - आरती @ http://bhajans.ramparivar.com

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