Amharic OCR

About the Amharic OCR Tool

Archivists digitising printed Amharic documents, researchers working from scanned materials, and students photographing textbook pages all need a way to extract the text from an image so they can edit, search, or quote it. This tool does that using Tesseract.js, an open-source optical character recognition engine that runs entirely in your browser. Your image is never uploaded to a server. The Tesseract engine uses the dedicated Amharic language model, which is trained specifically on Ge'ez script, rather than a generic OCR model that has no knowledge of Ethiopic characters.

Getting good results from Amharic OCR requires understanding its limits. Print text from a scan at 300 DPI or higher works well, especially when the contrast between ink and paper is clear. Photographs taken at an angle or in poor lighting produce noticeably worse results. Handwritten Amharic is not reliably recognised by any current general-purpose OCR engine, including this one. After processing, the tool shows you a confidence score that gives a rough indication of how well the recognition went. A low score means you should review the output carefully before using it.

Drop an image onto the upload area or click to select one from your device. The engine shows a real-time progress indicator while it works, and the extracted text appears in an editable area when it finishes. You can download the result as a plain text file for use in other applications.

Because OCR output sometimes contains recognition errors, particularly with closely related Ethiopic characters, it is worth reading through the extracted text before relying on it. For government forms, legal documents, or archival materials, treat the OCR output as a draft that needs a human review pass rather than a final transcript.