Aromzyy / capstone_project_app

Suppler App

Overview

This application utilizes a React frontend and a Flask backend to predict skin conditions using the MobileNetV2 machine learning model. Users can upload skin images, and the app will provide instant predictions.

Structure

• frontend: Contains the React application.
• backend: Houses the Flask API and the MobileNetV2 model.
• data_science/DDI_Dataset: Dataset used for training the model.

Getting Started

Prerequisites

• Node.js (React dependencies)
• Python 3 (Flask and ML model dependencies)

Installation

Backend

cd backend
pip install -r requirements.txt
python app.py

Frontend

cd frontend
npm install
npm start

Navigate to http://localhost:3000 to access the React frontend.

Usage

Upload an image through the React app interface, and receive a skin condition prediction powered by the Flask API using the MobileNetV2 model.

Technologies

• Frontend: React
• Backend: Flask
• ML Model: MobileNetV2

Contributing

We encourage public contributions!

1. Fork the Project
2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
3. Commit your changes (git commit -m 'Add some AmazingFeature')
4. Push to the Branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

Contact

• Aroma Atieno - [e-mail]