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AsmaaElnagger/DiabeticRetionPathyDetection

sourceHugging Faceupdated 1y agoView on Hugging Face
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App README

Diabetic Retinopathy Detection

Project Logo

A Streamlit-based web application for detecting diabetic retinopathy from eye fundus images using a deep learning model from Hugging Face.

![Open in Streamlit](https://huggingface.co/spaces/AsmaaElnagger/DiabeticRetionPathyDetection) ![Hugging Face Model](https://huggingface.co/Asmaa111/diabetic-eye)

🔍 Overview

This application uses a pre-trained deep learning model to classify eye fundus images into different stages of diabetic retinopathy. The model is hosted on Hugging Face and integrated into a user-friendly Streamlit interface.

🚀 Getting Started

Using Docker (Recommended)

  1. 1.Build the Docker image:
bash
docker build -t diabetic-retinopathy .
  1. 1.Run the container:
bash
docker run -p 8501:8501 diabetic-retinopathy
  1. 1.Access the app at http://localhost:8501

Without Docker

  1. 1.Install dependencies:
bash
pip install -r requirements.txt
  1. 1.Download the model:
bash
python download_model.py
  1. 1.Run the Streamlit app:
bash
streamlit run src/streamlit_app.py

🧠 Model Information

  • —Model Name: diabetic-eye
  • —Repository: Asmaa111/diabetic-eye
  • —Framework: PyTorch
  • —Input: Eye fundus images (JPEG/PNG)
  • —Output: Classification into retinopathy stages

📂 Project Structure

DiabeticRetionPathyDetection/
├── .streamlit/            # Streamlit configuration
├── src/
│   └── streamlit_app.py   # Main application code
├── Dockerfile             # Docker configuration
├── download_model.py      # Model download script
├── requirements.txt       # Python dependencies
└── README.md              # Project documentation

🌐 Live Demo

Try the live version hosted on Hugging Face Spaces: DiabeticRetionPathyDetection Demo

📚 Resources