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

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

• Getting Started
• Prerequisites
• Installing
• Deployment
• Built With
• Owner and Contributors
• License
• Support
• Key Features

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

• Java 17
• Maven
• Docker

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 .

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

• Spring Boot - The web framework used
• Maven - Dependency Management
• DeepLearning4j - Used for image classification
• Docker - Used for deployment
• Github Actions - Used for CI/CD
• NextJs - Used for the frontend application
• TailwindCSS - Used for styling the frontend application

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

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

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!

• 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 📱