Extract text from images with OCR
Search... using text for relevant documents
Query deep learning documents to get answers
Next-generation reasoning model that runs locally in-browser
A demo app which retrives information from multiple PDF docu
A token classification model identifies and labels specific
Multimodal retrieval using llamaindex/vdr-2b-multi-v1
Find relevant text chunks from documents based on queries
Extract key entities from text queries
Extract text from documents or images
Gemma-3 OCR App
RAG with multiple types of loaders like text, pdf and web
Extract information from documents by asking questions
QwenOCR is a powerful Optical Character Recognition (OCR) tool designed to extract text from scanned documents and images. It leverages advanced AI technologies to accurately recognize and convert printed or handwritten text into editable digital text. Whether you're working with invoices, receipts, books, or any other type of document, QwenOCR simplifies the process of digitizing your content.
• Multi-language Support: Recognizes text in multiple languages, making it a versatile tool for global users.
• High Accuracy: Utilizes cutting-edge OCR algorithms to ensure precise text extraction, even from low-quality images.
• Support for Various Formats: Works seamlessly with JPG, PNG, PDF, and other common image formats.
• Batch Processing: Enables processing of multiple documents at once, saving time and effort.
• Integration Capabilities: Can be integrated into workflows for automated document processing.
1. What file formats does QwenOCR support?
QwenOCR supports a wide range of file formats, including JPG, PNG, PDF, BMP, and more.
2. Can QwenOCR handle handwritten text?
Yes, QwenOCR is capable of recognizing handwritten text, though accuracy may vary depending on the quality of the handwriting and image.
3. Is QwenOCR available for mobile devices?
Yes, QwenOCR is accessible on mobile devices through its web-based platform, ensuring flexibility for users on the go.