Drop in a screenshot, a scanned document, or a photo of a page. The OCR engine reads the image directly inside your browser — no server involved, no account required, no file size quota on our end.
Drag a file onto the box below, or click to browse. Everything runs inside your browser — this page does not send your image to pythonware.com or anywhere else.
drop image here, or click to browse
JPG · PNG · WEBP · up to 15 MB
processed on your device — not uploadedreading your image…
running locally · 0% complete
No sign-up, no extension, no configuration. If you can drag a file, you already know how to use this.
Drop a JPG, PNG, or WEBP file onto the upload area, or click it to browse your files. Works on desktop and mobile — on mobile, you can tap to use your camera directly.
Tesseract.js starts immediately, scanning your image for text. A live percentage counter shows you where it is. Typical images finish in a few seconds; larger files may take a little longer.
The extracted text is editable. Fix any recognition mistakes, then copy it to your clipboard or download it as a plain .txt file.
Tips for better results
Use images where text is at least 12–14pt equivalent in size. Tiny text is harder to recognise.
Even lighting and a neutral background behind the text help significantly.
Avoid heavy JPEG compression — it blurs character edges and reduces accuracy.
Straight-on shots outperform angled or skewed text every time.
For scanned documents, 150 DPI is the minimum; 300 DPI is better.
The output is editable — fix the odd misread character before you copy.
A focused utility that does one job: getting the words out of your images and into a form you can actually use.
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Your image data never leaves your device. There is no upload, no server processing, and no log of what you extracted. Privacy is structural, not a policy.
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Extraction starts the moment your file lands. A live percentage readout shows you progress so you always know how much longer to wait.
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Once the page and language data have loaded, you can disconnect. The tool keeps running without an internet connection for as long as you need it.
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Tesseract supports over 100 written languages. Printed Latin-script text works out of the box; other scripts are available through the underlying library.
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Results drop into a plain text field you can edit before doing anything with them. Correct a stray character, remove unwanted whitespace, or trim to just the section you need.
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No registration, no email address, no daily quota. Open the page, convert what you need, and leave. That's the whole experience.
OCR accuracy depends heavily on image quality. Here's an honest breakdown of when Tesseract thrives and when it needs better input.
This tool uses Tesseract.js, a WebAssembly port of the open-source Tesseract OCR engine developed at HP and later maintained by Google. It runs fully in-browser, so there is no server component at all.
WebAssembly runtime
The C++ Tesseract binary is compiled to WebAssembly, giving it near-native performance inside any modern browser without plugins or installs.
LSTM neural network
Tesseract 4+ uses an LSTM model trained on large corpora of printed text across many languages, giving it significantly higher accuracy than older pattern-matching approaches.
In-memory only
Image data is passed to the worker entirely in browser memory. It is never serialised to disk, sent via network request, or accessible outside your browser tab.
// the call (simplified)
// runs in a Web Worker — off the main thread
const worker = await Tesseract.createWorker('eng', 1);
// imageFile never leaves the browser
const result = await worker.recognize(imageFile);
// extracted string — ready to edit and copy
const text = result.data.text;
await worker.terminate();
PythonWare has been working with image processing since the original Python Imaging Library (PIL). Tesseract.js is a natural fit with that heritage — robust, open-source, and designed for real workloads.