Image Tools
Image to Text (OCR)
Pull the text out of a photo, screenshot or scan with OCR. Upload an image, pick its language, and get editable, copyable text in seconds. The recognition runs entirely in your browser — your image is never uploaded.
Drop an image here or click to choose
JPG, PNG or WebP · runs in your browser, never uploaded
How to extract text from an image
- Choose a photo, screenshot or scan that contains text.
- Select the language the text is written in — this matters more than anything else for accuracy.
- Start recognition. The first run downloads the OCR engine and the language data; later runs reuse them.
- Copy the recognised text, then check names, numbers and punctuation against the image before relying on it.
What's happening under the hood
The tool uses Tesseract, a long-established open-source OCR engine, compiled to run inside your browser. Tesseract finds the lines of text in the image and reads each one with a neural network trained for the language you pick. It returns plain text — the words and line breaks, but not fonts, colours, columns or table structure.
Language data is downloaded the first time you choose a language and then cached by the browser, so switching to a new language is slow once and fast afterwards.
Getting accurate results
| Situation | What to do |
|---|---|
| Blurry phone photo of a page | Retake it in good light, holding the phone parallel to the page |
| Small text in a screenshot | Zoom in before taking the screenshot so the letters are larger |
| Scanned document | Scan at 300 DPI or more, as Tesseract's own documentation recommends |
| Text on a busy background | Crop tightly to the text before running OCR |
| Two languages on one page | Run it once per language and combine the results |
| Handwriting | Expect poor results — the engine is built for printed text |
Common OCR mistakes to proof-read for
- Look-alike characters: 0 and O, 1 and l and I, rn and m, 5 and S.
- Numbers in tables and receipts, where one wrong digit changes the meaning.
- Multi-column layouts, where lines from neighbouring columns can be merged.
- Right-to-left scripts such as Arabic, where decorative or very small fonts reduce accuracy.
- Hyphenated words at line ends, which come out split in two.
Frequently asked questions
Is the image uploaded to a server?
No. The OCR engine runs in your browser, so your image stays on your device — safe for private documents and screenshots.
Which languages does it support?
It can read English, Arabic, Spanish, French, German, Portuguese, Italian, Russian, Chinese and Japanese — pick the language of the text before extracting for the best accuracy.
Why is the first run slower?
The recognition engine and the language data load the first time you use it. After that it's cached by your browser and runs faster.
How do I get the most accurate text?
Use a clear, high-contrast, well-lit image where the text is straight and reasonably large. Blurry or skewed photos reduce accuracy.
Can it read text in photos of signs or products?
Often, when the text is large, flat and facing the camera. Curved labels, stylised logos and text at an angle are much harder; crop close and photograph the text as straight-on as you can.
Does it keep the layout of the page?
No — the result is plain text in reading order, with line breaks. Columns, tables and formatting have to be rebuilt by hand, so for long structured documents paste the text into a document and restyle it there.
Can I extract text from a PDF?
If the PDF has selectable text, PDF to Word gets it out directly and more accurately. For a scanned PDF, convert its pages with PDF to JPG and run each image through this tool.
How long does recognition take?
A clear screenshot usually takes a few seconds once the engine has loaded. Full-page photos from a modern phone take longer because there are many more pixels to analyse; cropping to the area with text speeds things up.
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Image to Text (OCR) guides
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