Display OCRBench leaderboard for model evaluations
Florence 2 used in OCR to extract & visualize text
Recognize text from images
Convert Brahmi script images to Devanagari text
Convert images to text using OCR
Extract text from manga images
Convert scanned images to text
Extract text from images using OCR
A robust offline system for recognizing handwritten Hindi
Extract text from images
Extract Japanese text from images
OCR and Document Search Web Application
Extract text from images using OCR
Ocrbench Leaderboard is a comprehensive tool designed to track and compare the performance of various OCR (Optical Character Recognition) models. It provides a centralized platform for researchers and developers to evaluate and benchmark OCR systems, fostering transparency and innovation in the field of document image understanding.
What is the purpose of Ocrbench Leaderboard?
The purpose is to provide a standardized platform for evaluating OCR models, ensuring fairness and transparency in performance comparisons.
How often are the results updated?
Results are updated regularly as new models are submitted and evaluated.
Can I submit my own OCR model?
Yes, the leaderboard allows submissions from researchers and developers, contributing to the growth of the OCR community.