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
- Clone the repository
- Navigate to the project directory
- Run
mvn clean install
- 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 - miliariadnaneContributors
:- Ayoub Bouazza - Frontend Engineer π¨ - bouazzaayyoub
- Mohammed Daoudi - DevOps Engineer π¬ - 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 β on GitHub. Your support is greatly appreciated! Also, if you have a moment, don't forget to make a duaa π€² for us. Thank you for your support!
- Deep learning model built with DeepLearning4j π§
- REST API π
- Upload an image πΌοΈ
- Classify the image π
- Display the classification result π
- Dockerized application π³
- CI/CD pipeline - Github Actions π€
- NextJs frontend application
- Home page π
- Upload page π€
- About page βΉοΈ
- Mobile responsive π±