DeepSeek-OCR-2 is the second-generation optical character recognition system developed to improve document understanding by introducing a “visual causal flow” mechanism, enabling the encoder to reorder visual tokens in a way that better reflects semantic structure rather than strict raster scan order. It is designed to handle complex layouts and noisy documents by giving the model causal reasoning capabilities that mimic human visual scanning behavior, enhancing OCR performance on documents with rich spatial structure. The repository provides model code and inference scripts that let researchers and developers run and benchmark the system on both images and PDFs, with support for batch evaluation and optimized pipelines leveraging vLLM and transformers.

Features

  • Visual causal token ordering for improved OCR
  • Support for complex layouts and semantic structure
  • Inference scripts for images and PDF processing
  • Integration with vLLM and transformer backends
  • Batch evaluation and benchmark tools
  • Outputs suited for markdown and structured text

Project Samples

Project Activity

See All Activity >

Categories

OCR, AI Models

License

Apache License V2.0

Follow DeepSeek-OCR 2

DeepSeek-OCR 2 Web Site

Other Useful Business Software
Find Hidden Risks in Windows Task Scheduler Icon
Find Hidden Risks in Windows Task Scheduler

Free diagnostic script reveals configuration issues, error patterns, and security risks. Instant HTML report.

Windows Task Scheduler might be hiding critical failures. Download the free JAMS diagnostic tool to uncover problems before they impact production—get a color-coded risk report with clear remediation steps in minutes.
Download Free Tool
Rate This Project
Login To Rate This Project

User Reviews

Be the first to post a review of DeepSeek-OCR 2!

Additional Project Details

Programming Language

Python

Related Categories

Python OCR Software, Python AI Models

Registered

4 days ago