Fruit Quality Detector

Overview

Fruit Quality Detector is a web application that uses a machine learning model to classify fruits as either Good or Spoiled. This project demonstrates how TensorFlow and Keras can be used to build and deploy a fruit classification system on Streamlit.

Hosted App

The application is live and hosted at: https://fruit-classify.onrender.com/

Key Learning

To successfully deploy this app on Streamlit, use TensorFlow and Keras version 2.15.0.

Features

• Upload an image of a fruit to classify its quality.
• Sidebar with sample images of both good and spoiled fruits.
• Intuitive and responsive user interface built using Streamlit.

Tech Stack

• Frontend: Streamlit
• Backend: TensorFlow, Keras
• Languages: Python

Installation Guide

Follow the steps below to run the project locally:

1. Clone the repository:

   git clone https://github.com/SimpleCyber/Fruit_Classification-IEEE.git

2. Navigate to the project directory:

   cd Fruit_Classification-IEEE

3. Install the required dependencies:

   pip install -r requirements.txt

4. Run the Streamlit app:

   streamlit run app.py

Contribution

We welcome contributions! If you’re interested, please visit the GitHub repository: https://github.com/SimpleCyber/Fruit_Classification-IEEE.git

License

This project is licensed under the MIT License. See the LICENSE file for details.

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✨ Enjoy detecting fruit quality with ease!