awesome-repositories.com
Blog
MCP
awesome-repositories.com

Entdecke die besten Open-Source-Repositories mit KI-gestützter Suche.

EntdeckenKuratierte SuchenOpen-Source-AlternativenSelf-hosted SoftwareBlogSitemap
ProjektMCP-ServerÜber unsRanking-MethodikPresse
RechtlichesDatenschutzAGB
© 2026 Bringes Technology SRL·VAT RO45896025·hello@awesome-repositories.com
·

2 Repos

Awesome GitHub RepositoriesDocument Segmentation

Techniques for decomposing images into hierarchical text structures like lines and characters.

Explore 2 awesome GitHub repositories matching graphics & multimedia · Document Segmentation. Refine with filters or upvote what's useful.

Awesome Document Segmentation GitHub Repositories

Finde die besten Repos mit KI.Wir suchen mit KI nach den am besten passenden Repositories.
  • tesseract-ocr/tesseractAvatar von tesseract-ocr

    tesseract-ocr/tesseract

    74,751Auf GitHub ansehen↗

    Tesseract is a neural network-based optical character recognition engine designed to convert scanned images and digital documents into machine-readable, searchable text. It functions as both a command-line utility for automating large-scale digitization workflows and a cross-platform library that can be embedded into desktop, mobile, or server-side applications. By utilizing long short-term memory networks, the engine provides robust text extraction across more than one hundred languages and dozens of scripts. The project distinguishes itself through a sophisticated document layout analysis f

    Decomposes visual documents into hierarchical structures, including text blocks, lines, and individual characters.

    C++hacktoberfestlstmmachine-learning
    Auf GitHub ansehen↗74,751
  • datalab-to/suryaAvatar von datalab-to

    datalab-to/surya

    20,889Auf GitHub ansehen↗

    Surya is a document processing platform designed to transform unstructured files into structured, machine-readable data. It provides a comprehensive suite of tools for text recognition, layout analysis, and reading order detection, enabling the conversion of PDFs and images into formats such as JSON, HTML, or markdown. The platform is built to handle complex document workflows, offering capabilities for data extraction, document segmentation, and automated form completion. The platform distinguishes itself through a robust pipeline-based architecture that allows users to chain analysis tasks

    Identifies and isolates distinct sections within documents to improve data extraction accuracy.

    Python
    Auf GitHub ansehen↗20,889
  1. Home
  2. Graphics & Multimedia
  3. Media Processing and Analysis
  4. Media Manipulation
  5. Media Processing Workflows
  6. Computer Vision Pipelines
  7. Document Segmentation