Flower Classification with Machine Learning

This project is a web application built with React.js and Express.js, utilizing TensorFlow to classify flowers based on uploaded images. The classification model is developed using TensorFlow and stored in PostgreSQL as the main database.

✨ Features

• 🚀 Image Classification: Predicts the type of flower from an uploaded image.
• 🎨 Modern Frontend: Built with React.js, Vite, and Tailwind CSS for a fast and responsive UI.
• 🧠 Machine Learning Model: Uses TensorFlow for accurate classification.
• 🗄️ Backend API: Powered by Express.js to handle communication between the frontend and Flask to load Machine Learning models.
• 📊 PostgreSQL Database: Stores flower data.

🛠️ Tech Stack

• Frontend: React.js, Vite, Tailwind CSS
• Backend: Express.js, Flask, PostgreSQL
• Machine Learning: TensorFlow

⚙️ Requirements

• Node.js (>= 20.18.0)
• npm (>= 10.8.2)
• Python (== 3.12)
• Pip (>= 24.2)

🚀 How to Run

1. Clone this repository:

   git clone https://github.com/Ar-Syhptra/Flower-Classification-Website.git
   cd Flower-Classification-Website

2. Install dependencies with npm:

   npm install

3. Install dependencies with pip:

   pip install -r requirements.txt

4. Run this project:

   npm run dev