What is Marker
Marker is an open-source high-precision document conversion tool, focused on quickly and accurately converting multiple document formats such as PDF and Word into Markdown, JSON, and HTML formats. Through deep learning technology, it automatically removes interfering elements such as headers and footers, while supporting multilingual processing, intelligently recognizing and formatting tables and code blocks, extracting images, and converting formulas to LaTeX format, ensuring the completeness and accuracy of the content.
Marker's main features
- Multi-format conversion: Can quickly convert common document formats such as PDF and Word into Markdown, JSON, and HTML formats, meeting the usage needs of different scenarios.
- Multilingual support: Supports document conversion in multiple languages, suitable for international document processing.
- Intelligent formatting: Automatically removes interfering elements such as headers and footers, while preserving the original formatting of the document, such as tables and code blocks.
- Formula conversion: Converts formulas in documents to LaTeX format, convenient for use in academic and scientific research scenarios.
- Image extraction: Can extract and save images from documents, ensuring the completeness of the converted document content.
- Hardware acceleration: Supports GPU, CPU, and MPS hardware acceleration, improving conversion efficiency.
- Batch processing: Supports batch conversion functionality, can process multiple documents at once, improving work efficiency.
Marker's technical principles
- Text extraction: Marker first uses OCR technology (such as Tesseract) to extract text from PDFs. For digital PDFs, it directly extracts text; for scanned PDFs, it calls the OCR engine for recognition.
- Page layout detection: Uses deep learning models (such as Surya) to detect page layout, determine the reading order of text, and ensure the converted document structure is consistent with the original document.
- Text cleaning and formatting: Cleans and formats the extracted text blocks, removes interfering elements such as headers and footers, and formats tables, code blocks, etc.
- Post-processing and merging: Merges the cleaned text blocks, performs post-processing, and generates a complete Markdown file. It converts formulas to LaTeX format and extracts images.
Marker's project address
- Github repository：https://github.com/vikParuchuri/marker
Marker's application scenarios
- Academic research: Scholars and researchers can convert paper PDFs into Markdown format, making it convenient for annotation, secondary editing, and version control.
- Technical documentation writing: Development teams can quickly convert PDF-format manuals into Markdown, making it convenient for collaborative editing on platforms such as GitBook.
- Online course material processing: Educational institutions can efficiently convert textbooks into Markdown format, making it convenient for online publishing and e-book production.
- Personal knowledge management: Knowledge workers can use Marker to organize collected PDF materials, improving the systematicity and searchability of notes.
- Content creation and sharing: Creators can convert PDF documents into Markdown, making it convenient to share content on blogs or other platforms.