See
https://github.com/tesseract-ocr/tesseract/blob/master/doc/lstmeval.1.asc

When using checkpoint you need to also use the starter traineddata file
used for training.

Or give final traineddata file as model.

So, if after training u have converted the checkpoint to a traineddata, you
can use that as model. Similarly for the original traineddata.

On Thu, 27 Jun 2019, 21:46 Arno Loo, <arno.laf...@gmail.com> wrote:

> Hello,
>
> I just finished my first training of tesseract 4.0 and I ran a lstmeval on
> the generated model, which I named *mod01.*
> I use this command line :
> lstmeval --model data/checkpoints/mod01_checkpoint --traineddata ./usr/
> share/tessdata/mod01.traineddata --eval_listfile data/list.eval
>
> It worked fine and it gave me a character error rate and a word error
> rate. Now I would like to know if my training improved Tesseract's accuracy
> on my specific documents. So I wanted to launch the evaluation on the same
> dataset but with the model I started the training from, the english
> provided on Tesseract's github repo : eng.traineddata. I tried :
> lstmeval --traineddata ./usr/share/tessdata/eng.traineddata --eval_listfile
> data/list.eval
> But it did not work because I did not provided any --model
>
> And this showed me that my understanding of Tesseract's was not correct.
> Since downloading a new *lang.traineddata* is enough to use Tesseract
> with this lang I thought that all the model was contained in the
> traineddata files. What is this --model argument then ?
> In which my research on the web told me to put the last checkpoint of my
> training but without explaining why.
>
> Is it possible then to run lstmeval on a pretrained model like
> eng.traineddata ?
>
> Thank you !
>
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