Awesome GitHub RepositoriesCommand-Line Document Processors

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

Docling is a multimodal content converter and document parser designed to transform PDFs, Office files, and HTML into structured Markdown or JSON for generative AI applications. It functions as an OCR document processor and a PDF layout analyzer that extracts tables, charts, and hierarchical structures while preserving the original page layout. The system operates as a local-first inference engine, allowing for the processing of sensitive data in air-gapped environments without external network connectivity. It can also be deployed as an API or a Model Context Protocol server to provide parsi

SumatraPDF is a lightweight, multi-format document viewer designed for rendering PDF, eBook, and comic book files within a unified interface. It functions as both a graphical reading environment and a command-line document processor, enabling users to automate file conversion, merging, and extraction tasks without requiring a graphical interface. The application distinguishes itself through a single-executable binary distribution that utilizes direct-to-GDI rendering and memory-mapped file access to maintain high performance and minimal memory overhead. Users can personalize their workspace b

A fast, helpful, and open-source document parser

DocTR is a deep learning OCR library built on PyTorch that detects and transcribes text in document images using a two-stage detection-recognition pipeline. It provides a complete framework for building and deploying OCR pipelines with pretrained models available through the Hugging Face Hub, and supports exporting trained models to ONNX format for cross-runtime deployment. The library offers end-to-end OCR pipelines that combine text detection and recognition to extract all text from document images or PDFs, with support for rotated page handling and varied text orientations. It includes cap

WriteGPT 是一个端到端的论文自动化系统，结合了视觉识别和自动化文本生成，将图像转换为完成的数字文档。它作为一个创意文本生成器和文档处理器，利用语言模型生成长篇书面内容和论文。 该系统集成了一个神经文本流畅度评估器，以对生成散文的语言质量和自然度进行评分。它还包括一个基于 Transformer 的文本摘要器，将长文档压缩为简洁的摘要。 该项目提供了一个光学字符识别（OCR）流水线，可检测图像中任何方向的文本并将其转换为机器可读字符。它进一步支持自动化文档数字化，根据统计写作模式将生成的内容排列成结构化布局，如标题和段落。

Asciidoctor 是一个基于 Ruby 的文本处理引擎和命令行工具链，旨在将 AsciiDoc 内容转换为结构化的发布格式，包括 HTML5 和 DocBook 5。它作为一个静态内容发布工具链，将原始源文件转换为格式化的文档。 该系统利用可插拔的转换器接口和模板驱动的输出，允许通过自定义转换器或模板覆盖默认的转换逻辑。这使得能够生成特定的文档结构，并将内容导出为各种发布格式以用于不同的分发渠道。 该工具链涵盖了广泛的功能，包括通过开发者接口进行程序化内容转换、通过终端接口进行批量处理，以及为 HTML 输出生成和压缩样式表。它在将原始文本翻译成最终目标格式之前，会将其解析为内部文档模型。

pdfsam 是一款 PDF 操作软件和桌面应用程序，旨在拆分、合并、旋转和提取 PDF 文档中的页面。它作为一个 PDF 编辑器、转换器和安全工具，提供修改文档结构和管理文件格式的功能。 该项目以其专门的处理能力脱颖而出，包括用于从扫描图像中提取可编辑文本的 OCR 文档处理器，以及用于交替来自多个文件的页面的 PDF 交错功能。它还提供了一个安全套件，用于加密文档、管理访问权限和应用数字签名。 该软件涵盖了广泛的文档优化和编辑任务，例如页面组织、直接内容编辑、可填写表单创建和 PDF 压缩。它还包括用于页面旋转、裁剪、灰度转换以及插入注释和超链接的工具。 该应用程序构建为基于 Java 的桌面运行时。

This project is a Python library and command-line tool designed to convert Markdown text and files into structured HTML fragments. It functions as a Markdown-to-HTML converter and parser that transforms piped text or source files into web-ready documents. The project is an extensible text processor featuring a pluggable API for defining custom inline and block syntax. This modular framework allows for the registration of specialized syntax extensions, such as tables and footnotes, and provides a system for managing runtime configuration settings. The conversion process covers multilingual te

pdf2docx is a suite of PDF utilities designed to transform static PDF documents into editable DOCX files. It functions as a multi-core processor capable of accelerating the conversion of large files by distributing page tasks across multiple CPU cores. The project includes specialized tools for decrypting password-protected PDF files and extracting tabular content as structured data. It also provides a layout analyzer to visually inspect and verify document structure during the conversion process. Conversion is accessible through both a graphical user interface and a command-line interface,

python-docx-template is a template engine for generating Microsoft Word documents by merging .docx files with data contexts using a logic-based markup syntax. It functions as a document automator that injects variables, images, and sub-documents into Word files while maintaining the original styling. The project uses a rendering system based on Jinja2 to apply template logic and filters to Office Open XML files. It allows for the creation of custom template filters to transform data during the rendering phase and includes a command line interface for producing documents by passing a template

Markdown Resume is a command-line utility designed to transform structured text files into professional, responsive web pages and portable documents. It functions as a static site generator that separates content from presentation, allowing users to maintain version-controlled resumes through a template-driven build system. The project distinguishes itself by providing a containerized execution environment that ensures consistent document output across different host systems. It supports rapid design iteration through a live preview feature that monitors source files and triggers automatic re

Commonmark.js is a library designed to parse and render text formatted according to the CommonMark specification. It functions as a document processing pipeline that converts plain text into structured HTML or an abstract syntax tree, enabling developers to programmatically inspect, modify, and transform document elements. The library distinguishes itself through its strict adherence to standardized parsing rules, ensuring consistent and predictable output across different software environments. It provides a robust framework for document tree manipulation, allowing users to traverse, insert,