beastonking / backend

ShaveMax Back End

Description

ShaveMax is a mobile application that utilized the machine learning technology to predict the face shape and hair type of the user based on the photo provided to the system and recomment suitable hairstyles for the users.

Meet Our Team

ID	Learning Path	University	Name	Status
M009D4KY2095	Machine Learning	Gunadarma University	Gilang Ferdiansyah	Active
M009D4KX2419	Machine Learning	Gunadarma University	Nadira Putri Bimono	Active
M009D4KY1905	Machine Learning	Gunadarma University	Josep Samuel Angelo	Active
C010D4KY1226	Cloud Computing	Universitas Indonesia	Vinsensius Ferdinando	Active
C010D4KY0957	Cloud Computing	Universitas Indonesia	Bintang Pratama	Active
A010D4KY3439	Mobile Development	Universitas Indonesia	Rama Tridigdaya	Active
A550D4NY4608	Mobile Development	UIN Syarif Hidayatullah Jakarta	Muhammad Aryodiro Sunaryo	Active

Functionality

This SpringBoot application is specific application that handles the BackEnd of the ShaveMax Application, including authentication and authorization.

In this Application, there is 3 endpoints:

Sign Up

  POST /api/auth/sign-up

Parameter	Type	Description
email	string	Required. Email of the User
password	string	Required. Password of the User's account
gender	string	Required. Gender of the User that will be used as predictio parameter
An endpoint with POST method to sign up and register to shavemax application system.

Sign In

  POST /api/auth/sign-in

Parameter	Type	Description
email	string	Required. Image of the face with hair
password	string	Required. Gender of the User in the image

an endpoint with POST method to sign in or login to use shavemax application features.

Get All Hairstyles

  GET /api/hairstyles/all

an endpoint with GET method that returns all of the available hairstyles.

This application is deployed via Google Cloud Run and connected to Google Cloud SQL. Then, all the user data will be stored in Google Cloud SQL with PostgreSQL

Replication and How to Run the Application

Follow these steps to set up and run the application:

1. Clone the Repository

First, clone the repository to your local machine using the following command:

git clone https://github.com/C241-PS208/prediction-api.git

2. Build and Load Gradle

Build and load the gradle requirements: Run this only in the initial clone

gradle wrapper

then, run this:

./gradlew build

./gradlew run

3. Setup the Database

Third, Setup the Database in your local Database manager with the credential stated in Application.Properties

4. Compose the docker container

FourthCompose the docker container with this script:

docker-compose up

5. Run the application

Run the Application and if it is clear of errors, the application is ready to use. Run the application with this script:

./gradlew clean build

then

java -jar build/libs/ShavemaxApplication.jar