🎓 educate

Versatile-OCR-Program

A multimodal OCR pipeline optimized for machine learning.

#machine learning
#educate
#multilingual
#OCR
#Data processing
#Chart identification
Versatile-OCR-Program

Product Details

The product is a purpose-built OCR system designed to extract structured data from complex educational materials, supporting multilingual text, mathematical formulas, tables and charts, capable of producing high-quality data sets suitable for machine learning training. The system leverages multiple technologies and APIs to provide highly accurate extraction results, making it suitable for use by academic researchers and educators.

Main Features

1
Multi-language support: Compatible with Japanese, Korean and English, other languages ​​can be easily customized as needed.
2
Structured Output: Generate AI-ready output in JSON or Markdown format, containing human-readable descriptions of mathematical expressions and tabular summaries.
3
High accuracy: Achieve 90-95% accuracy on real-world academic datasets, suitable for documents with complex layouts.
4
Complex layout support: Accurately handles exam-style PDFs with dense science content, supporting formula-dense paragraphs and rich visual elements.
5
Intelligent interpretation: Extracted elements such as charts, tables, graphs, etc. have semantic annotations and contextual explanations.
6
Image and special region processing: Use the Google Vision API's image analysis capabilities to process image regions and generate image descriptions.
7
Table processing optimization: Use DocLayout-YOLO for table area detection and preserve the table structure.
8
Educational value: Helps students intuitively understand complex scientific and mathematical concepts, suitable for use in the education field.

How to Use

1
Step 1: Run ocr_stage1.py to extract the original elements (text, tables, graphics, etc.) from the input PDF.
2
Step 2: Use ocr_stage2.py to process the intermediate data and convert it into structured human-readable output.
3
Step 3: Customize the output format (JSON or Markdown) as needed to suit your machine learning needs.
4
Step 4: Verify and adjust the extracted data to ensure its accuracy and completeness.
5
Step 5: Apply the processed data to machine learning model training or educational material development.

Target Users

The product is particularly suitable for educators, academic researchers, and users who need to process and analyze complex documents. Its high accuracy and versatility allow users to generate training data more efficiently to support a variety of educational and research purposes.

Examples

Extract the mathematical questions and their diagrams from the exam papers to generate training data.

Extract complex tables and figures from academic articles and generate descriptions for them.

Work with illustrations and data graphs in science textbooks to help students understand concepts.

Quick Access

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Categories

🎓 educate
› data analysis
› research tools

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