Yes, lstmeval is manual but easy to automate. I use a script like this:
./train.sh $NAME 100
./train.sh $NAME 300
./train.sh $NAME 400
./train.sh $NAME 500
./train.sh $NAME 750
./train.sh $NAME 1000
./train.sh $NAME 1200
...
It does short trainings, save the models into a folder and run lstmeval.
Thank you. I see.
Lorenzo Bolzani 于2019年4月18日周四 下午3:00写道:
> Yes, lstmeval is manual but easy to automate. I use a script like this:
>
> ./train.sh $NAME 100
> ./train.sh $NAME 300
> ./train.sh $NAME 400
> ./train.sh $NAME 500
> ./train.sh $NAME 750
> ./train.sh $NAME 1000
> ./train.sh $NAME 1200
Hello,everyone:
I have used tesseract 4.0 to train a chi_sim model,but the result is
not so good as I expected,So I think out one way for fine tuning.
1.src/training/tesstrain.sh --fonts_dir /usr/share/fonts --training_text
../training_data/chi_sim_layer_training_text \
--langdata_dir ../
Yes.. I have followed the same steps. Thats not pretty clear, atleast to my
knowledge. i have finished the windows setup in cygwin. i didnt follow the
steps that mentioned for compiling leptonica and tesseract. Make command is
giving error.
$ make tesseract
make: *** No rule to make target 'tes
Dear reader,
I want to improve devanagari recognition.
I have images and manually corrected Text with line coordinates.
>From those, I've generated .box files;
see attached file which produces the error above.
Complete error Message from lstmtrain:
»Encoding of string failed! Failure bytes: 9 32
> I have images and manually corrected Text with line coordinates. From
those, I've generated .box files;
What method did you use for generating the .box files?
Please provide the image for the box file for test.
On Thu, Apr 18, 2019 at 6:09 PM wrote:
> Dear reader,
> I want to improve devanag
Also see https://github.com/OCR-D/ocrd-train/pull/66
https://github.com/tesseract-ocr/tesseract/issues/2357#issuecomment-477239316
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Is anybody here,can some one help me,thanks a lot.
于2019年4月18日周四 下午5:19写道:
> Hello,everyone:
> I have used tesseract 4.0 to train a chi_sim model,but the result is
> not so good as I expected,So I think out one way for fine tuning.
>
> 1.src/training/tesstrain.sh --fonts_dir /usr/share/font
Hello everyone,
I am looking for some datasets to test OCR engines for languages Italian,
Portuguese, Arabic, Japanese, Korean, and Chinese. Datasets need to have
raw OCR documents and the groud truth text. If you know any such dataset,
please post here. Maybe it is helpful to have a catal
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