How to extract text
- 01
Choose the image
Use the original file when possible. The browser validates its type and size before OCR.
- 02
Run text extraction
The browser prepares the image, downloads the model on first use, and performs recognition locally.
- 03
Review before reuse
Compare the result with the source, then copy it or download TXT or Markdown.
Good inputs for this OCR
- PNG, JPG, WebP, or GIF images
- Printed document text and clear captures
- Plain-text and Markdown export
Accuracy limits
- OCR output is a draft. Verify names, totals, account numbers, medical terms, and legal wording against the image.
- The bundled recognition model is optimized for Korean; other scripts, handwriting, vertical text, tables, and stylized fonts can be incomplete.
- Blur, perspective, compression, low contrast, and tiny characters reduce accuracy.
A practical OCR check
Try one representative page before a batch workflow and compare names, numbers, punctuation, and reading order with the source.
- Rotate the image upright.
- Crop unrelated areas without cutting characters.
- Treat the exported text as unverified until reviewed.
Improve a weak result
- Use a sharper source or retake the photo with even lighting.
- Crop to the text region and remove large decorative backgrounds.
- If the model does not load, check content blockers and the documented runtime host, then retry once.
Questions about local OCR
Does Aiviko receive the image or extracted text?
The tool processes both in your browser and does not intentionally send them to an Aiviko processing endpoint. Runtime, model, analytics, and advertising requests remain separate and are described in the policies.
Is OCR output safe to use without review?
No. Recognition can substitute or omit characters, especially in low-quality or complex layouts. Check consequential text against the source.