This repository contains the codebase for a Map Reproducibility Assessment Tool developed as part of my master's thesis project. The tool aims to facilitate the extraction, parsing, and comparison of textual elements from original and reproduced map images, enabling researchers to assess the reproducibility of geospatial maps in geoscientific publications. The project is built using Flask for the backend API and React for the frontend interface.

• Upload original and reproduced map images
• Extract textual elements using OCR
• Calculate text similarity, bounding box overlap ratio, and distance between bounding boxes
• Visualize annotated images with bounding boxes
• Interactive table for exploring assessment results
• Utilize 2D canvas drawing to highlight text elements on the map images

• Backend: Flask (Python)
• Frontend: React.js
• OCR Engine: PaddleOCR
• Additional Libraries: theFuzz, OpenCV

1. Clone this repository: git clone <repository_url>
2. Navigate to the Flask_backend directory and install dependencies: pip install -r requirements.txt
3. Run the Flask server: python app.py
4. Navigate to the React_Frontend directory and install dependencies: npm install
5. Run the React frontend: npm start

1. Upload original and reproduced map images.
2. Select preferred languages for text extraction.
3. Click the "Upload and Extract" button to initiate text extraction and comparison.
4. Explore assessment results in the interactive table.
5. Click on a row in the table to highlight corresponding text elements on the annotated images.

This project is licensed under the MIT License.

• Special thanks to PaddleOCR for providing the OCR engine.
• Built with inspiration from the field of geoscience and reproducible research.

Feedback, bug reports, and contributions are welcome! Please feel free to open an issue or submit a pull request.