GOT - OCR (from : UCAS, Beijing)
Employs Mistral OCR for transcribing historical data
Next-generation reasoning model that runs locally in-browser
Analyze documents to extract and structure text
Search for similar text in documents
Search documents and retrieve relevant chunks
Find information using text queries
Process and extract text from receipts
Using Paddleocr to extract information from billing receipt
Identify and extract key entities from text
Extract text from multilingual invoices
Find relevant text chunks from documents based on queries
Find relevant passages in documents using semantic search
Tonic's GOT OCR is a powerful tool developed by UCAS (Beijing) to extract text from images using advanced OCR (Optical Character Recognition) technology. It is specifically designed to handle various OCR tasks efficiently, making it an essential solution for users needing to convert scanned documents or images into editable text.
• Advanced OCR Technology: Built with cutting-edge OCR capabilities to accurately extract text from images.
• Multiple OCR Tasks: Supports a variety of OCR-related tasks to cater to different user needs.
• Developed by UCAS: Backed by the expertise of UCAS, Beijing, ensuring high-quality performance and reliability.
What file formats does Tonic's GOT OCR support?
Tonic's GOT OCR supports common image formats such as JPG, PNG, and BMP.
Can Tonic's GOT OCR handle handwritten text?
While it specializes in scanned documents, it may have limited support for handwritten text depending on the quality and clarity of the input.
Is Tonic's GOT OCR available in multiple languages?
Yes, it supports multiple languages, making it a versatile tool for global users.