GiellaLT provides an infrastructure for rule-based language technology aimed at minority and indigenous languages, and streamlines building anything from keyboards to speech technology.
The Sámi languages (more general: The GiellaLT languages) are missing from tesseract.
In order to train on the document filename.pdf, do the following:
Convert to html:
pdftohtml filename.pdf
Open the resulting filename.html and find a nice page to train on. In e.g. Preview, cut lines one by one: Mark with mose, cmd C, cmd N. Save the file as filename_page_line.png.
In filename.html, find the corresponding line. Copy it to a file filename_page_line,gt.txt, correct it if needed and save.
The files filename_page_line.png and filename_page_line.gt.txt should be placed in divvungellatekno/tesstrain/training-data/sme-ground-truth/.
Then train the model, as follows:
gmake training MODEL_NAME=sme
Check in the resulting sme.traineddata
Then copy the resulting `sme.traineddate to where tesseract may find it:
On Mac Intel:
cp divvungiellatekno/tesstrain/training-data/sme.traineddata /usr/local/share/tessdata/
On other processors and machines:
cp divvungiellatekno/tesstrain/training-data/sme.traineddata /opt/homebrew/share/tessdata/sme.traineddata