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3 Repos

Awesome GitHub RepositoriesOCR Model Configurations

Management of model data files for varying accuracy and performance requirements.

Explore 3 awesome GitHub repositories matching artificial intelligence & ml · OCR Model Configurations. Refine with filters or upvote what's useful.

Awesome OCR Model Configurations GitHub Repositories

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  • 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

    Select between fast integer-based models and high-accuracy float-based models to meet specific performance and precision requirements.

    C++hacktoberfestlstmmachine-learning
    Auf GitHub ansehen↗74,751
  • yuliang-liu/monkeyocrAvatar von Yuliang-Liu

    Yuliang-Liu/MonkeyOCR

    6,487Auf GitHub ansehen↗

    MonkeyOCR is a GPU-accelerated document parsing server that converts PDFs and images into structured markdown while preserving the spatial layout of text, formulas, and tables. It provides both an interactive Gradio web interface for uploading files and viewing parsed output in real time, and a RESTful HTTP API endpoint that accepts document uploads and returns structured JSON results for programmatic consumption. The system routes document pages through specialized OCR sub-models for text, formula, and table recognition based on the selected extraction task, and packages the entire model sta

    Routes document pages through specialized OCR sub-models for text, formula, and table recognition.

    Python
    Auf GitHub ansehen↗6,487
  • oomol-lab/pdf-craftAvatar von oomol-lab

    oomol-lab/pdf-craft

    4,867Auf GitHub ansehen↗

    pdf-craft is an OCR-based document parser and structure extractor designed to convert PDF files into structured data, Markdown, or EPUB ebooks. It utilizes optical character recognition and statistical analysis to identify document hierarchies and extract text and structured content. The system features specialized rendering for mathematical formulas and tables, using heuristic reconstruction to convert tabular data into digital formats. It includes a document structure extractor that builds tables of contents by analyzing font sizes, linguistic patterns, and language model title detection.

    Manages local storage of OCR model weights to ensure stability and offline functionality.

    Pythondeepseek-ocrdocumentocr
    Auf GitHub ansehen↗4,867
  1. Home
  2. Artificial Intelligence & ML
  3. Machine Learning
  4. Architectures
  5. Computer Vision Segmentation Models
  6. OCR Model Configurations

Unter-Tags erkunden

  • Multi-Model PipelinesPipelines that route document pages through specialized sub-models for different content types. **Distinct from OCR Model Configurations:** Distinct from OCR Model Configurations: focuses on routing pages through multiple specialized models rather than managing model data files.