Hi all,
I'm trying to use tesseract to recognize Japanese on image.
I found that it get a poor accuracy with the half-width
Japanese(Katakana).
I'am trying to improve the accuracy by fine-tuning ,
both [ Fine Tuning for ± a few characters] and [Training Just a Few
Layers] have been tried,
it seems may improve the accuracy of half-width Japanese but do a
lot of harm to the normal Japanese recognition.
Here is the way I do the fine-turing.
1 add half-width Japanese to the lang/jpn/jpn.training_text (clone from
tesseract-ocr/langdata seems train data for v3)
2 Create train data by tesstrain.sh
3 combine_tessdata -e /usr/local/tesseract/share/tessdata/jpn.traineddata
(which is best/jpn.traineddata) trainhalfwidth/jpn.lstm
4 lstmtraining --model_output trainhalfwidth/jpnhw \
--continue_from trainhalfwidth/jpn.lstm \
--traineddata trainhalfwidth/jpn/jpn.traineddata\
--old_traineddata
/usr/local/tesseract/share/tessdata/jpn.traineddata
\
--train_listfile trainhalfwidth/jpn.training_files.txt
--max_iterations
3600 &> trainhalfwidth/basetrain.log
Any advice? Thank you
#It seems Ray is working on the train data for lstm, any news so far?
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