OCR recognizes text from image pixels. It does not establish that the extracted text is correct. The Image to Text tool performs recognition on your device, then lets you edit, copy or save plain text without an account.
Start with a non-sensitive sample
Choose Try printed English sample. The tool creates an image locally containing:
INVOICE 12345
Total INR 250.00
Printed text sample
Choose English, no rotation and Extract text locally. Compare every line with the sample, including the decimal point and digits. This synthetic task is a bounded check; it is not evidence of accuracy on all receipts, scripts or layouts. The engine may vary whitespace and line breaks.
Prepare the image before recognizing it
Use a clear, upright JPEG, PNG or WebP. Avoid clipped characters, glare, very small print and extreme perspective. The first release accepts one image at a time, not PDFs or HEIC. Use PDF to Image separately when you are entitled to render a PDF, then check the image before recognition.
If text is sideways, select a clockwise rotation of 90°, 180° or 270°. Rotation is applied to pixels during recognition, while the selected-image preview remains in its original orientation. Do not assume automatic rotation or page-layout reconstruction.
Choose the language actually present
English is the default. Optional Hindi + English and Malayalam + English selections download additional trained data. Selecting more languages is not a guarantee of better results. Printed text, spelling, font, resolution and layout all affect recognition; handwriting and complex tables are outside the reliable first-release target.
The first run downloads several megabytes of engine and selected-model assets from this site. Those are ordinary program downloads, not an image upload. A worker receives image pixels locally; the server can see asset requests, including the model filenames. The page may also load shared analytics as explained in the privacy policy.
Check consequential characters first
Compare names, amounts, dates, reference numbers and punctuation against the original. Common ambiguities include 0 versus O, 1 versus I, missing decimal points, and reading order in columns. Do not use a transcribed financial, medical or legal value without checking it.
The displayed engine confidence is the recognizer's score, not a measured percentage of correct characters. It is not a substitute for a reference transcript. A blank result can mean no text was found, not that the source contains no text.
In our bounded local Node-engine fixtures, the default English selection preserved INVOICE 12345, while Hindi + English returned INVOICE 2345. A Malayalam fixture recognized the language but misspelled a word despite a confidence score of 92/100. These observations used the pinned engine and synthetic fonts; they are not browser benchmarks or general error rates. They demonstrate why a plausible result and a high score still require checking.
Edit and export deliberately
The result is plain text in an editable box. Copy writes that text to the system clipboard; Download .txt saves UTF-8 text to your device. Tables, fonts and original document layout are not exported as Word or PDF. Check the saved file before using it elsewhere.
Cancel terminates the current worker, including model initialization. An outstanding browser decode may finish before its memory is released, but the cancelled job cannot replace a new result. Clear image and text stops an active job and removes the current preview and editable text. It does not delete saved files, erase the clipboard or purge the browser's cache of program/model files.
Engine reference and evidence boundary
The implementation uses the pinned Tesseract.js worker and trained data, served locally by this site. The sample above is reproducible; it is not a claim that we benchmarked every language or every browser. See each release's QA record for the environments and examples actually checked.