OCR PDF
OCR PDF makes the text on a scanned PDF searchable and selectable, running text recognition entirely inside the browser rather than uploading the file to a server.
The PDF stays on this device and is processed locally in your browser, including text recognition and language detection.
Each selected page is rasterized, then read by a local Tesseract.js text-recognition engine (no upload, no external service). This produces plain text only — it does not generate a searchable PDF with an embedded text layer.
Limits: one PDF up to 25 MB and 200 pages; up to 10 pages can be recognized per job, each rendered at roughly 144 DPI capped for phone-safe memory use. Encrypted or password-protected PDFs are rejected.
How to use it
- Select a scanned PDF from your device and wait for its page count.
- Choose to recognize all pages or enter specific pages such as 1,3,5-8, then pick the document language.
- Start recognition and wait for the local Tesseract.js engine to finish.
- Copy the recognized text or download it as a .txt file.
Each selected page is rasterized locally with the same PDF rendering pipeline used elsewhere in Tooliba, then read by a local Tesseract.js text-recognition engine — the worker script, WASM engine, and English/French language data are committed same-origin assets, never fetched from a CDN. Choose English, French, or both before starting, since recognition accuracy depends on matching the document's actual language(s); mismatched languages increase the rate of misread characters. This initial version outputs plain recognized text only, available to copy to the clipboard or download as a .txt file — it does not produce a new searchable PDF with an embedded, invisible text layer, and recognition accuracy still depends on scan quality and resolution. No image or text data is uploaded to Tooliba, retained after the session, or included in analytics.
FAQ
No. This version outputs plain recognized text only, available to copy or download as a .txt file — the original PDF pages are not modified.
English, French, or both together for a document mixing the two — recognition accuracy depends on matching the document's actual language(s).
No. Pages are rasterized and recognized entirely in your browser using a local, same-origin Tesseract.js engine; nothing is uploaded to Tooliba or a third-party service.