PDF-Extract-Kit

PDF-Extract-Kit is a toolkit specifically designed to extract high-quality content from PDF files. It implements in-depth analysis of PDF documents through multiple components, including layout detection, formula detection, formula recognition and optical character recognition (OCR). The toolkit uses advanced models such as LayoutLMv3, YOLOv8, UniMERNet and PaddleOCR to adapt to various types of PDF documents with high accuracy in layout and formula detection. It is also specifically optimized for scanning blurred or watermarked documents to ensure accurate extraction results even in complex situations.

Demand group:

" PDF-Extract-Kit is mainly targeted at users who need to extract information from PDF documents, such as researchers, students, data analysts and document processing professionals. It is particularly suitable for processing complex documents such as academic articles, textbooks, research reports and financial statements. Documents, capable of providing precise layout and formula detection, as well as high-quality OCR results."

Example of usage scenario:

Researchers use PDF-Extract-Kit to extract data and figures from academic papers.

Students use the toolkit to extract key formulas and concepts from textbooks to aid learning.

Data analysts use this toolkit to extract key data from financial reports for analysis.

Product features:

Use the LayoutLMv3 model for layout detection, including recognition of images, tables, titles, text and other areas.

Use YOLOv8 model for formula detection, including inline formulas and independent formulas.

Formula recognition using UniMERNet provides recognition quality comparable to commercial software.

Use PaddleOCR for text recognition, supporting Chinese and English OCR.

Detailed installation guide and running script parameter description are provided to facilitate users to get started quickly.

Supports running on Windows and macOS platforms, and provides corresponding usage guides.

Usage tutorial:

1. Visit PDF-Extract-Kit ’s GitHub page and clone or download the project.

2. Install the required dependencies and model weights according to the installation guide.

3. Set script parameters according to the operation guide, including PDF file path, output path, etc.

4. Run the extraction script to start the extraction process of PDF content.

5. Choose whether to visualize the results or render the recognition results as needed.

6. Check the output folder to get the extracted PDF content.