Re: [tesseract-ocr] Re: lstmtraining command line related

2018-03-28 Thread notoriousterran
@Shree I want to make a traineddata Could I have one more question about training from scratch ? I execute that command line lstmtraining —debug_interval -1 —traineddata /usr/share/tesseract-ocr/4.00/tessdata/kor.traineddata —model_output /home/inplat/tesstutorial/koroutput/base —learning_rate

Re: [tesseract-ocr] Re: lstmtraining command line related

2018-03-28 Thread 이경준
Okay .. ㅜㅜ Sorry I observed rule Thank You 2018-03-29 13:40 GMT+09:00 shree : > PLEASE DO NOT SHOUT - Sending messages in Large fontsize, RED color etc is > not appreciated. > > You have used a 0-zero instead of a CAPITAL O in your network spec, it > should be O1c105 > > > On Wednesday, March 28

[tesseract-ocr] Re: lstmtraining command line related

2018-03-28 Thread shree
PLEASE DO NOT SHOUT - Sending messages in Large fontsize, RED color etc is not appreciated. You have used a 0-zero instead of a CAPITAL O in your network spec, it should be O1c105 On Wednesday, March 28, 2018 at 12:24:02 PM UTC+5:30, notorio...@gmail.com wrote: > > > > *Invalid network spec:0

Re: [tesseract-ocr] Any suggestions for more accurate Text conversion?

2018-03-28 Thread Bhargav Kanakiya
Okay, thank you! On Wed, Mar 28, 2018 at 2:45 AM, shree wrote: > Yes, for 4.0 you can try finetune training. You can download license plate > specific fonts to easily make training data. > > -- > You received this message because you are subscribed to a topic in the > Google Groups "tesseract-oc

Re: [tesseract-ocr] Any suggestions for more accurate Text conversion?

2018-03-28 Thread shree
Yes, for 4.0 you can try finetune training. You can download license plate specific fonts to easily make training data. -- You received this message because you are subscribed to the Google Groups "tesseract-ocr" group. To unsubscribe from this group and stop receiving emails from it, send an

[tesseract-ocr] tesstrain.sh (train vs eval)

2018-03-28 Thread notoriousterran
안녕하세요. 렌더링을 통한 훈련과 테스트 데이터를 만드는 과정에서, 이 둘의 관계는 딥러닝의 관점에서 사용되는 증명의 관계인가요? 아니면 진짜 테스트 데이터를 만들어서 테스트 하기 위한 관계인가요? 일반적으로 훈련데이터에 사용되지 않는 테스트 데이터를 만들고, 훈련데이터와 테스트 데이터를 6:4 비율로 만드는 일반적인 딥러닝 훈련과정속에서 In the process of creating training and testing data through rendering(tesstrain.sh), is the relatio