Where it works well
- Screenshots of applications, dialogs, error messages and terminals
- Printed documents scanned straight on
- Slides and diagrams with real text
- Tables, though the layout will not survive
Where it does not
Handwriting, stylised or decorative type, text over a busy photograph, low contrast, and anything photographed at an angle. These are limits of the approach rather than of this particular tool — the engine here is the same one most browser-based OCR uses.
Tables and bank statements are their own case: the text comes out, the rows and columns do not, and putting them back by hand takes longer than retyping. That needs a different tool — our neighbouring project OCR Snip reads bank statements and tables while keeping their rows, also in the browser. Some of what it does is paid.
Choose the language first
The language model is what turns shapes into characters, so a Cyrillic page read as English produces plausible-looking nonsense rather than an error. For a document mixing Latin and Cyrillic, pick the combined option — it is slower and substantially more accurate than either alone.
Always re-read the output
OCR does not know when it is wrong; it returns its best guess with a confidence figure attached. The recognised text is editable here for exactly that reason — fix it while the image is still in front of you rather than after it is pasted somewhere else.
Questions
Does my image get uploaded?+
No. Recognition runs on WebAssembly in this tab. The one network request is for the engine and the language model, which download once and are then cached — worth saying plainly rather than claiming everything is local.
How accurate is it?+
Good on clean screenshots and printed text, poor on handwriting, low contrast and photographs taken at an angle. Always re-read the output: OCR confuses similar glyphs, and the classic substitutions — 0 for O, 1 for l, rn for m — are the ones that survive a quick glance.
Which languages work?+
English, Russian and Kyrgyz, plus English and Russian together for mixed documents. Picking the wrong language is the most common cause of nonsense output — a Cyrillic page read as English produces confident gibberish.
How can I improve the result?+
Give it more pixels and more contrast. A screenshot at native resolution beats a photograph of a screen; a straight scan beats an angled phone shot. Cropping to just the text block before recognising also helps, because there is less for the layout analysis to get wrong.