Hey there, this is a really relevant question given how OCR projects often rely on specific font data. Let’s break this down clearly:

• Start with the font’s EULA (End User License Agreement)
  This is the first and most important step. Commercial font licenses are written to cover typical use cases (like embedding in apps, printing, web display), but many don’t explicitly address OCR training. Look for clauses around "reverse engineering," "extracting font data," or "derivative uses"—if the license prohibits extracting visual or structural data from the font file itself, you’ll need authorization even for training.

• Distinguish between using font files vs. rendered images
  If you’re generating training data by rendering the font into images (e.g., typing text with the font, saving screenshots or generated image files) rather than directly accessing the font’s underlying data (like vector outlines), this might fall into a gray area. Some vendors consider this "fair use" (depending on your region’s copyright laws), but it’s still not a guarantee—always check the EULA first.

• Reach out directly to the font vendor
  Since OCR training is a niche use case that many EULAs don’t cover, getting explicit written permission from the font’s creator or publisher is the safest bet. Explain exactly what you’re doing: training an OCR model only to recognize the font, no embedding or display of the font itself. Some vendors might allow this for free, others might offer a specific training license, and a small number might decline entirely.

• Alternative paths if authorization isn’t feasible
  If the vendor says no, consider switching to open-source fonts with permissive licenses (like SIL OFL or Apache) that explicitly allow derivative uses and training. You could also adjust your OCR model to recognize general character shapes instead of tying it to one specific commercial font, though that might require more training data.

内容的提问来源于stack exchange，提问作者Tony Merritt