GOT - OCR (from : UCAS, Beijing)
Find information using text queries
Extract text from images with OCR
Find relevant passages in documents using semantic search
Extract text from images using OCR
Extract text from documents or images
Extract handwritten text from images
Find relevant text chunks from documents based on queries
Find similar text segments based on your query
Extract named entities from text
A token classification model identifies and labels specific
Process documents and answer queries
Search information in uploaded PDFs
Tonic's GOT OCR is an advanced optical character recognition tool designed to extract text from scanned documents and images. Developed by UCAS (University of Chinese Academy of Sciences) in Beijing, this OCR solution is tailored for various OCR tasks, making it a versatile tool for users looking to digitize printed or handwritten content efficiently.
• Multi-language support: Extract text from documents in multiple languages.
• High accuracy: Delivers precise text recognition even from low-quality images.
• Layout preservation: Maintains the original document's formatting and structure.
• Versatile input: Supports scanned documents,photos, and PDFs.
• Advanced OCR capabilities: Handles complex layouts, tables, and fonts.
What languages does Tonic's GOT OCR support?
Tonic's GOT OCR supports a wide range of languages, including English, Chinese, and many others, making it suitable for global users.
Can I use Tonic's GOT OCR for handwritten documents?
Yes, the tool is capable of recognizing handwriting in images, though accuracy may vary depending on the quality of the input.
What file formats does Tonic's GOT OCR support?
The tool supports common formats like PDF, JPG, PNG, and BMP, ensuring compatibility with most document types.