We're developing a web or desktop solution that helps medical students generate structured learning materials from various sources like PDFs, lectures, PowerPoints, notes, and transcripts. This tool automates organization and formatting, making studying more efficient.
git clone https://github.com/IdrissaMaiga/MedicalProjectHackathon.gitBefore installing dependencies, set up a virtual environment to manage packages efficiently.
cd PyBackend
python -m venv venv
venv\Scripts\activatecd PyBackend
python3 -m venv venv
source venv/bin/activateOnce the virtual environment is activated, install the required dependencies:
pip install -r requirements.txtCreate your .env from .env.example.
Tesseract OCR is required for text extraction from images.
- Download and install Tesseract OCR from this link.
- Add the installation path (e.g.,
C:\Program Files\Tesseract-OCR) to your system environment variables.
brew install tesseractsudo apt update
sudo apt install tesseract-ocrIf Tesseract is not automatically detected, set the path in Python:
import pytesseract
pytesseract.pytesseract.tesseract_cmd = r"C:\Program Files\Tesseract-OCR\tesseract.exe"uvicorn main:app --reloadThe backend will be available at:
http://localhost:8000
Navigate into the frontend directory and install dependencies:
cd NextJsFrontEnd
npm installRun the frontend server:
npm run devThe frontend will be available at:
http://localhost:3000
- Extracts and structures content from PDFs, images, and other sources.
- Converts handwritten notes and printed text into digital, editable formats.
- Generates well-organized study materials.
- Automates formatting for quick review and revision.
Once both the backend and frontend are running:
- Open the web application at
http://localhost:3000. - Upload your PDFs, PowerPoints, lecture transcripts, or notes.
- The AI will process and structure the content.
- Download the organized study material in a preferred format (text, PDF, etc.).
- Your uploaded files are processed locally, ensuring privacy.
- No sensitive data is stored.
This project is licensed under the MIT License. See the LICENSE file for details.
Contributions are welcome! Feel free to fork this repository, submit issues, and send pull requests.
For questions or suggestions, reach out at: maigadrisking@gmail.com.
- Advanced AI summarization for study materials.
- Integration with popular note-taking apps.
- Improved OCR accuracy for handwritten notes.
- Cloud-based synchronization for seamless access across devices.