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ArtifexSoftware avatar

ArtifexSoftware/pdf2docx

0
View on GitHub↗
pdf2docx.readthedocs.io↗

Pdf2docx

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, which supports automated batch processing and scripting workflows.

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Features

  • PDF to DOCX Converters - Transforms static PDF documents into editable Word DOCX files while preserving original layout.
  • Parallel Processing - Distributes individual page conversion tasks across multiple CPU cores to accelerate processing.
  • Table Extraction Utilities - Isolates and retrieves tabular content from PDF pages as structured data.
  • Tabular Data Reconstruction - Identifies and reconstructs structural grids from unstructured PDF visuals into digital table formats.
  • Document Processing Parallelization - Uses multiple CPU cores to accelerate the conversion of large PDF files.
  • Tabular Data Extraction - Isolates and retrieves tabular content from PDF pages as structured data.
  • Decryption Utilities - Removes encryption from PDF files to enable content processing and format conversion.
  • Layered Decomposition - Decomposes PDF structures into primitive text and vector components before mapping them to Word elements.
  • PDF Layout Analysis Tools - Programmatically determines the spatial coordinates and bounding boxes of elements within a PDF for verification.
  • Encrypted PDF Unlockers - Decrypts password-protected PDF files to make them accessible for conversion or data extraction.
  • Coordinate-Based Layout Analysis - Analyzes physical page coordinates to determine document structure and group text fragments.
  • Layout Visualization Tools - Provides a visual tool to inspect and verify the accuracy of document layout during conversion.
  • Input Stream Decryption - Decrypts encrypted PDF byte streams during the read process to allow access to the document model.
3,453 stars·485 forks·Python·MIT·57 views

Star history

Star history chart for artifexsoftware/pdf2docxStar history chart for artifexsoftware/pdf2docx

How this analysis was created: This summary and feature list are AI-generated from collected project material and can contain mistakes. Stars, license and language are imported from GitHub. Inclusion does not mean that we have tested or audited this project. Check the source documentation for any feature you depend on. Learn more on our About page.

Projects sharing features with Pdf2docx

These projects share indexed features with Pdf2docx. Shared tags can include platform or build tooling; verify the primary use case before treating a result as a replacement.
  • pdfminer/pdfminer.sixpdfminer avatar

    pdfminer/pdfminer.six

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    pdfminer.six is a programmatic tool for extracting text, layout information, and metadata from PDF documents into machine-readable formats. It functions as a document parser that converts internal PDF objects and structures into accessible data objects for analysis. The project includes utilities for decrypting RC4 and AES encrypted files to enable content extraction. It also provides a layout analyzer to identify fonts, colors, and text locations to determine the organizational structure of pages. The system covers a broad range of extraction capabilities, including the retrieval of embedde

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  • tabulapdf/tabulatabulapdf avatar

    tabulapdf/tabula

    7,425View on GitHub↗

    Tabula is a PDF table extraction tool and data scraper designed to isolate tabular structures within text-based PDF files. It functions as a converter that transforms these layouts into structured CSV or spreadsheet formats for data recovery and analysis. The project provides both a visual interface for manually selecting table areas and a headless command-line interface. This dual approach allows for a choice between manual data recovery via visual-area selection and the integration of table extraction into automated data pipelines. The extraction process utilizes Java-based PDF parsing and

    CSScsvexcelpdf
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  • layout-parser/layout-parserLayout-Parser avatar

    Layout-Parser/layout-parser

    5,749View on GitHub↗

    Layout-parser is a deep learning document layout parser and image analysis framework. It provides a toolkit for extracting structural information and layout patterns from scanned documents and digital images, transforming them into programmatic data structures for automated analysis. The framework integrates layout detection with optical character recognition to convert tabular regions into machine-readable data. It utilizes neural networks to identify and classify structural elements within document images without relying on manual rule-based systems. The system covers a broad range of docu

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  • pymupdf/pymupdfpymupdf avatar

    pymupdf/PyMuPDF

    9,086View on GitHub↗

    PyMuPDF is a comprehensive PDF manipulation library and document analysis tool. It serves as a text extraction tool, OCR engine, and image converter, providing a programmatic interface to edit, merge, split, and optimize PDF and Office documents. The project distinguishes itself through high-performance capabilities, including the use of C-bindings for low-level manipulation and parallelized page processing to accelerate workloads. It provides specialized conversion paths, such as transforming PDF content into Markdown for retrieval-augmented generation and large language model pipelines. It

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Frequently asked questions

What does artifexsoftware/pdf2docx do?

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.

What are the main features of artifexsoftware/pdf2docx?

The main features of artifexsoftware/pdf2docx are: PDF to DOCX Converters, Parallel Processing, Table Extraction Utilities, Tabular Data Reconstruction, Document Processing Parallelization, Tabular Data Extraction, Decryption Utilities, Layered Decomposition.

Which projects share features with artifexsoftware/pdf2docx?

Projects with overlapping indexed features include: pdfminer/pdfminer.six — pdfminer.six is a programmatic tool for extracting text, layout information, and metadata from PDF documents into… tabulapdf/tabula — Tabula is a PDF table extraction tool and data scraper designed to isolate tabular structures within text-based PDF… layout-parser/layout-parser — Layout-parser is a deep learning document layout parser and image analysis framework. It provides a toolkit for… pymupdf/pymupdf — PyMuPDF is a comprehensive PDF manipulation library and document analysis tool. It serves as a text extraction tool,… euske/pdfminer — pdfminer is a Python library for parsing PDF files to extract text, analyze layouts, decrypt content, and convert… camelot-dev/camelot — Camelot is a Python library and processing engine designed to extract tabular data from PDF documents. It converts…