CanDoYa
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Free Image to Text Converter

Runs entirely in your browser - no upload, no sign-up.

Choose an image with clear printed text to begin.

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How does an image to text converter work?

An image to text converter uses optical character recognition, or OCR, to find printed characters in a photo or scan and return editable text. This tool runs Tesseract WebAssembly inside your browser, covers the languages used across all 40 CanDoYa locales, and lets you copy or download the result without uploading the source image.

How to use

  1. 1Choose a clear image. Drop in a JPEG, PNG, WebP, BMP, or non-animated GIF up to 15 MB and 24 megapixels, or load the built-in example.
  2. 2Select the text language. Choose the language actually printed in the image. The matching Tesseract language data downloads when you start extraction.
  3. 3Extract and verify. Run OCR, compare names and numbers with the source, edit any mistakes, then copy the text or download a UTF-8 TXT file.

Who it's for

This converter uses Tesseract.js 7, a browser port of the open-source Tesseract OCR engine. The code, WebAssembly core, and selected language data load only after you start extraction. Tesseract performs recognition in its own worker, so the page remains responsive while your device processes the image.

OCR accuracy depends more on the source than on the file format. Upright printed text, even lighting, sharp focus, strong foreground contrast, and enough pixel detail all help. Small screenshots can improve after upscaling, while skewed pages, decorative fonts, columns, handwriting, glare, and blurred camera photos are more likely to need manual correction.

FAQ

Is my image uploaded to a server?

No. The selected file is decoded and recognized on your device by a Tesseract worker. The browser downloads public OCR runtime and language files from external hosts, but those requests do not contain your image. CanDoYa does not receive or store the source image or extracted text.

Is this image to text converter free?

Yes. It has no account, payment, watermark, page credits, or result download fee. Your device supplies the processing power. The initial OCR engine and language-data download still uses your internet connection, and larger language models can matter on a metered connection.

What image limits and formats are supported?

You can process one JPEG, PNG, WebP, BMP, or non-animated GIF up to 15 MB and 24 megapixels. Those limits reduce memory failures on phones and laptops. The tool handles images only; use a dedicated scanned PDF OCR tool when you need to recognize full PDF pages.

How accurate is OCR image to text conversion?

Clean printed text can be recognized well, but no OCR result is guaranteed. Sharp focus, large letters, high contrast, a straight page, and the correct language improve accuracy. Handwriting, unusual fonts, glare, blur, tables, columns, and mixed reading directions can produce substitutions or reordered lines.

Can it extract handwritten notes?

It may recover very neat block handwriting, but this Tesseract-based tool is designed primarily for printed text. Cursive writing and inconsistent letter shapes are much less reliable. Treat handwriting output as a rough draft and compare every important word, date, and number with the original image.

Which text language should I choose?

Choose the language used by the characters in the image, not the language of your browser. The list covers all 40 CanDoYa locales, including simplified and traditional Chinese separately. If a page mixes languages, select the dominant one; this version loads one recognition model per run.

Why does the first extraction take longer?

The browser must first load the Tesseract.js code, a compatible WebAssembly core, and trained data for the selected language. Browser caches can make later runs faster, but private mode, storage cleanup, a new language, or cache eviction may trigger another download.

Can I use the extracted text without checking it?

Review it first, especially names, totals, dates, punctuation, and characters that look alike, such as O and 0 or l and 1. The displayed confidence is a broad Tesseract estimate. It does not certify each word or preserve the exact visual layout of the source.