PDF to Text (OCR)
Extract readable text from any PDF using on-device AI OCR.
Turn a scanned or image-based PDF into copyable, searchable text — using on-device AI OCR that never leaves your browser.
Extract readable text from any PDF using on-device AI OCR.
A scanned document or a PDF made from photographed pages doesn't contain real text — it's really just a picture of text, which means you can't select, search, or copy it the normal way. Optical character recognition (OCR) solves that by analyzing the pixels on the page and predicting which characters they represent. This tool uses Tesseract.js, an open-source OCR engine that runs entirely inside your browser using WebAssembly, so the recognition happens on your own device rather than being sent to a cloud API.
Each page of your PDF is first rendered onto an in-memory canvas using pdf.js, then handed to Tesseract for character recognition. Because there's no upload step and no server queue, extraction speed depends only on your device's processing power and the number of pages in your document — not on how many other people are using the tool at the same time. For documents with sensitive contents, like scanned contracts, ID cards, or medical forms, this local processing means the actual text of the document is never transmitted anywhere.
Select a PDF above and click Extract Text. The recognized text appears in the box below, ready to copy or edit — and for multi-page documents, each page's text is clearly labeled so you can tell where one page ends and the next begins.
No installs, no accounts, and no waiting on server queues. Everything happens locally on your device.
Choose the PDF whose text you want to extract — works best on clear, reasonably high-resolution scans.
Each page is rendered to a canvas and analyzed by Tesseract.js's on-device OCR engine.
Review the recognized text in the output box and copy it with one click.
Accuracy depends heavily on the quality of the original scan — clear, high-contrast, straight (not skewed) pages typically recognize very well, while blurry, low-resolution, or handwritten pages will produce more errors. Tesseract.js is tuned for printed text in the English language model used here.
Not reliably. Tesseract's default English model is trained for printed text; handwritten notes usually produce poor or garbled results. It works best on typed documents, forms, and printed scans.
Recognizing text is far more computationally intensive than copying pages or rotating them. The engine has to load, then analyze every page pixel by pixel, so extraction time scales with both the number of pages and your device's processing power — there's no server involved to speed this up, since that's exactly what keeps your document private.
No. The PDF is rendered and analyzed entirely inside your browser using pdf.js and Tesseract.js, both of which run locally via WebAssembly. The text never leaves your device during recognition.
Processing...