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🌿🌱 Herb Classifier : Coriander VS Parsley 🌿🌱

Herb Classifier is a Spring Boot application that classifies images of coriander and parsley herbs using a deep learning model built with DeepLearning4j.

🖥️ Frontend Application

  • The frontend application is built with NextJs and TailwindCSS. Check the website
  • The frontend application repository is here

📐 Diagram of the application architecture

Diagram

📚 Table of Contents

🚀 Getting Started

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes.

📋 Prerequisites

  • Java 17
  • Maven
  • Docker

🔧 Installing

  1. Clone the repository
  2. Navigate to the project directory
  3. Run mvn clean install
  4. Build docker image `docker build -t myusername/herb-classifier-api:version -f Dockerfile .

🚢 Deployment

This application is deployed using Docker. The CI/CD pipeline is configured in .github/workflows/main.yml.

🛠️ Built With

👥 Owner and Contributors

  • Owner : Adnane Miliari - Backend Engineer - miliariadnane
  • Contributors :
    • Ayoub Bouazza - Frontend Engineer 🎨 - bouazzaayyoub
    • Mohammed Daoudi - DevOps Engineer 🐬 - Iduoad

📝 License

This project is licensed under the MIT License - see the LICENSE.md file for details

🌟 Support

If you find this project useful or interesting, please consider giving it a star ⭐ on GitHub. Your support is greatly appreciated! Also, if you have a moment, don't forget to make a duaa 🤲 for us. Thank you for your support!

⚙️ Key Features

  • Deep learning model built with DeepLearning4j 🧠
  • REST API 🌐
    • Upload an image 🖼️
    • Classify the image 🔍
    • Display the classification result 📊
  • Dockerized application 🐳
  • CI/CD pipeline - Github Actions 🤖
  • NextJs frontend application
    • Home page 🏠
    • Upload page 📤
    • About page ℹ️
  • Mobile responsive 📱

About

Spring Boot application that classifies images of coriander (Qazbor) and parsley (Maadanous) herbs using a deep learning model built with DeepLearning4j.

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