What OCR actually does
Optical character recognition (OCR) looks at pixels and guesses characters. It is not magic and it is not 100% accurate — especially on blurry phones, fancy fonts, or complex scripts. Treat every result as a draft you may need to fix. Photo2Text uses the open-source Tesseract engine inside your browser so the image itself does not get uploaded to our servers.
Step-by-step: extract text from an image
- Prepare the image. Use even lighting, reduce glare, and crop tightly around the words you care about.
- Open the converter. Go to the Image to Text tool on Photo2Text.
- Choose a language. English is fine for most screenshots; pick Urdu or Arabic when the page is in those scripts.
- Upload or drop the file. JPG, PNG, and WebP work. On phones you can also take a photo.
- Click Extract Text. The OCR model loads on demand — that keeps the first page visit fast.
- Edit, copy, or download. Fix obvious mistakes in the textarea, then copy or save a .txt file.
Quick quality checklist
- Text should be readable when you zoom the photo yourself.
- Prefer PNG for UI screenshots; high-quality JPG for camera shots.
- One language (or a deliberate combined mode) beats guessing.
- If output is gibberish, recrop and reshoot before blaming the tool.
Where to go next
Need script-specific help? See Urdu OCR tips or try Arabic image to text. For format workflows, use JPG to Text and PNG to Text. Comparing options? Read our best free OCR tools guide.
Sources & further reading
- Tesseract OCR documentation — upstream open-source OCR engine overview
- Tesseract.js on GitHub — browser / WASM port used by Photo2Text