Re smaller traineddata size, it could possibly be related to the word list
dictionary size.

You can unpack the original traineddata and compare the word list size with
the one you used.

On 06-Dec-2017 12:07 PM, "J Klein" <[email protected]> wrote:

>
> [this might be a repost; the first attept didn't show up]
>
> I'm using the C API of tesseract 4.0 on OS X, and I tried to add some more
> characters.   (4.0 seems much better than 3.x, I should add - thanks to
> everyone who made this possible!)
>
> I used this manual section: https://github.com/
> tesseract-ocr/tesseract/wiki/TrainingTesseract-4.00#fine-
> tuning-for--a-few-characters
>
> as a guide to construct the following script:  https://pastebin.com/
> 4n2mRSpq
>
> Before running, I modified  langdata/eng/eng.training_text with the extra
> chars, maybe 15 instances of each, as instructed.
>
> I'm using only a subset of the original training fonts, but I figure it is
> OK, since I'm adding only a few distinctive chars.
>
> The NN optimizer lstmtraining ran, and gave a bunch of checkpoints, and a
> final file $train_output_dir/eng/eng.trainedata
>
> But this eng.traineddata was 5MB when the original one was 15.4MB.    And
> when I tried to copy it over the pre-loaded 'best' eng.traineddata and run
> tesseract it failed in TessBaseAPIinit3 with error=-1.
>
>
> Does anyone know why 1) my eng.trainedata is so much smaller and 2) why it
> fails to even load in API init()?
>
> Thanks for any tips!
>
>
>
>
>
>
>
>
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