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SUPPORT CONVERTCRAFT KEEP THE FREE TIER ALIVE

We don’t track you and we don’t know if you’re using an adblocker. Our ads are run by Google — no pop-ups, no annoying ads, just clean placements. Ads help us keep our free tier completely free for everyone.

Why We Need Your Support

  • Google Ads Only: We run Google AdSense — no pop-ups, no video ads, no misleading banners. Just clean, non-intrusive placements.
  • No Tracking: We do not track you, sell your data, or monitor your browsing. Your privacy is absolute.
  • Free Forever: Ads fund our servers so we can keep the free tier available to everyone, everywhere, without compromise.

Whitelist Us 💜

If you use an adblocker, please consider whitelisting ConvertCraft. It takes 10 seconds and directly keeps the project alive.

Every ad view helps us maintain servers, develop new tools, and keep your data private — all at no cost to you.

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Support via Buy Me a Coffee or get the Support Plan with exclusive benefits.

Panduan

Image to Text Online — OCR Gratis di Browser Anda

Ekstrak teks dari gambar apa pun tanpa mengunggahnya. Alat OCR berbasis browser kami bekerja sepenuhnya di sisi klien — cepat, pribadi, dan sepenuhnya gratis.

Optical Character Recognition (OCR) lets you extract editable text from images — scanned documents, screenshots, photos of whiteboards, or receipts.

ConvertCraft runs OCR entirely in your browser using Tesseract.js, a WebAssembly port of the industry-standard Tesseract OCR engine. Your images stay on your device at all times.

To extract text: 1) Open the Image to Text tool. 2) Drop an image file (PNG, JPG, WebP, TIFF, BMP). 3) Select the language(s) present in the image. 4) Click Extract and copy or download the recognized text.

The tool supports over 100 languages including English, Spanish, French, German, Arabic, Chinese, Japanese, and Korean. For best results, use clear images with good contrast and standard fonts.

OCR accuracy depends on image quality. Scanned documents at 300 DPI typically achieve 95%+ accuracy. Photos of printed text with good lighting also work well. Handwritten text recognition is experimental but improving.