Florence 2 used in OCR to extract & visualize text
NepaliOCR
Convert images to text
Upload an image to extract text
Generate text from images
Unofficial demo for TB-OCR (OCR for documents)
Convert images to text using OCR
Extract text and tables from French images
Qwen2-VL is a vision-language model that performs OCR
Extract text from images
Recognize text from images
Extract text from images
Extract text from single-line Kurdish images
TextSnap is an OCR (Optical Character Recognition) tool that leverages the Florence 2.0 framework to extract and visualize text from images. It is designed to help users quickly identify and extract text from visual content, making it an essential tool for document scanning, image processing, and data extraction. TextSnap is user-friendly and provides real-time visualization of extracted text along with bounding box annotations.
• Text Extraction: Accurately extract text from images or scanned documents.
• Bounding Box Visualization: View text with bounding boxes to understand spatial context.
• Multi-Language Support: Process text in multiple languages for global accessibility.
• High Accuracy: Leverage advanced OCR technology for precise text recognition.
• Simple Interface: User-friendly design for seamless navigation and processing.
• Real-Time Processing: Get instant results with minimal processing time.
What is OCR technology?
OCR (Optical Character Recognition) is a technology that converts images of text into editable or searchable text. TextSnap uses OCR to extract text from images or scanned documents.
Which file formats does TextSnap support?
TextSnap supports JPG, PNG, BMP, and PDF formats, making it versatile for various use cases.
How accurate is TextSnap?
TextSnap uses advanced OCR algorithms, ensuring high accuracy in text extraction. Accuracy may vary based on image quality and text complexity. For best results, use clear and well-lit images.