PDF-Extract-Kit
P
PDF Extract Kit
Overview :
PDF-Extract-Kit is a specialized toolkit for extracting high-quality content from PDF files. It achieves deep parsing of PDF documents through multiple components, including layout detection, formula detection, formula recognition, and optical character recognition (OCR). The toolkit employs advanced models such as LayoutLMv3, YOLOv8, UniMERNet, and PaddleOCR to accommodate various types of PDF documents and has high accuracy in layout and formula detection. It is also optimized for scanning blurred or watermark-containing documents to ensure accurate extraction results in complex situations.
Target Users :
PDF-Extract-Kit is designed for users who need to extract information from PDF documents, such as researchers, students, data analysts, and document processing professionals. It is particularly suitable for handling complex documents such as academic articles, textbooks, research reports, and financial statements, providing accurate layout and formula detection as well as high-quality OCR results.
Total Visits: 474.6M
Top Region: US(19.34%)
Website Views : 90.5K
Use Cases
Researchers use PDF-Extract-Kit to extract data and charts from academic papers.
Students leverage this toolkit to extract key formulas and concepts from textbooks to assist in learning.
Data analysts use the toolkit to extract key data from financial reports for analysis.
Features
Utilizes the LayoutLMv3 model for layout detection, including recognition of areas such as images, tables, titles, and text.
Uses the YOLOv8 model for formula detection, including inline and standalone formulas.
Employs UniMERNet for formula recognition, offering recognition quality on par with commercial software.
Utilizes PaddleOCR for text recognition, supporting OCR in both Chinese and English.
Provides detailed installation guides and script parameter descriptions for quick user engagement.
Supports operation on Windows and macOS platforms, with corresponding usage guidelines.
How to Use
1. Visit the PDF-Extract-Kit GitHub page and clone or download the project.
2. Follow the installation guide to install the required dependencies and model weights.
3. Set script parameters according to the operation guide, including the path to the PDF file, output path, etc.
4. Run the extraction script to begin the PDF content extraction process.
5. Choose whether to visualize the results or render the recognized results as needed.
6. Check the output folder to obtain the extracted PDF content.
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