Image to Text (OCR)

What is an image to text converter?

An image to text converter — better known as OCR (optical character recognition) — looks at the pixels of a picture and turns the shapes it finds into actual characters you can select, edit, copy and search. A screenshot of an error message, a photo of a book page, a scanned letter: as pixels they're dead weight, but after OCR they're just text.

This tool does it with a twist that matters: the recognition runs in your browser. Most online OCR services upload your image to a server, run the engine there and send text back. Here, the engine itself — Tesseract, the most widely used open-source OCR engine, compiled to WebAssembly — is loaded into your tab and does all the work locally. Your image never leaves your device.

How to use it

1. Add an image — drop a PNG, JPG or WebP onto the zone, click it to browse, or simply paste a screenshot from your clipboard. A small thumbnail confirms what's loaded.
2. Pick the language of the text in the image: English, German, French or Spanish. This matters — each language has its own trained model, and the wrong one produces garbled output.
3. Hit Extract text. A progress bar tracks recognition; a typical screenshot takes a few seconds.
4. The result appears in a text box with a word and character count. Use Copy to grab it all.

The first run downloads the OCR engine and language data from a CDN (a few megabytes) and caches them, so subsequent extractions start much faster. That download is the only thing fetched from the network — the image itself is processed entirely on your machine.

Getting accurate results

OCR is only as good as the picture you feed it. A few habits make the difference between clean text and alphabet soup:

• Sharp beats big. A crisp, in-focus image at moderate resolution outperforms a huge blurry one. Screenshots are ideal — they're pixel-perfect by nature.
• High contrast. Dark text on a light background recognizes best. Grey-on-grey, text over photos and low-light phone shots all cost accuracy.
• Straight and flat. Photograph documents from directly above, not at an angle. Skewed or curved lines (a book that won't lie flat) confuse line detection.
• Reasonable text size. If the text is a tiny part of a large photo, crop in so it fills more of the frame before extracting.
• Match the language. Recognizing German with the English model loses umlauts and ß; pick the right language first.

Printed type works well; handwriting generally doesn't — the engine is trained on fonts, not cursive.

What to do with the text

Once the text is out, it's ordinary text. Check its length and reading stats with the Word Counter, or pull text from PDFs directly — no OCR needed for digital PDFs — with Extract Text from PDF. And if your source image is in a format the tool doesn't accept (say HEIC or AVIF), run it through the Image Converter to get a PNG or JPG first.

Private by design

Nothing you OCR is uploaded, stored or logged. The image stays in your browser's memory, the recognition runs locally via WebAssembly, and closing the tab wipes everything. The only network traffic is the one-time, cacheable download of the engine and language data from a public CDN — never your image, never your text. That makes this safe for documents you'd hesitate to feed a cloud OCR service: contracts, IDs, invoices, medical letters. Find more browser-local utilities on the all tools page.