imago-ad-illud

OCR and AI-Powered Data Processing

This project demonstrates a pipeline for processing images using OCR (Optical Character Recognition) and leveraging generative AI for data interpretation.

Project Structure

1. Phase 1: OCR (Optical Character Recognition)

   • Converts images to text using the pytesseract library.
   • Saves the extracted text to an output file.

2. Phase 2: Generative AI Integration

   • Uses OpenAI's API to analyze the OCR output.
   • Employs a language model (e.g., gpt-4o-mini, gemini-flash) to interpret the extracted text.
   • Provides insights and analysis based on the content of the image.

3. Phase 3: Thematic Data Grouping (Not implemented yet)

   • (Future development: Organizing extracted data into relevant themes or categories.)

Dependencies

• pytesseract
• Pillow (PIL)
• openai
• google-generativeai

Usage

1. Install the necessary dependencies.
2. Set up your OpenAI API key using userdata.get('OPENAI_API_KEY').
3. Place the images you want to process in the same directory as the notebook.
4. Run the notebook to execute the OCR and AI processing.

Note

• This project uses a lightweight language model to manage costs.
• Larger bodies of text may require more processing power and potentially higher API costs.
• Thematic data grouping functionality is planned for future development.

Contributing

Contributions are welcome! Feel free to submit issues or pull requests. """