Foundie is here to address the problem of low self-confidence that many people, especially women, often experience regarding their appearance. Based on data from a Watson survey, 50% of Asian women feel insecure about their appearance. While many women turn to makeup to improve their appearance, in-depth interviews conducted by our development team revealed that they still struggle to determine the makeup style that best suits their facial features

This was the early features that this applications have.

1. Authentication

   

2. Face Classification

   

3. Skin Tone

   

4. Color analysis

   

5. Product Comparison

   

6. community

   

The mobile application is made starting with UI/UX designs and a little UX research, then implementing the design results using native Kotlin Android by utilizing supporting libraries such as Retrofit to interact with APIs, ViewModel to maintain stable live data, and Firebase Google Authentication to process user authentication.

Flow Android

We’ve developed a robust backend application using a microservices architecture. Our main server is built with NestJS, complemented by additional microservices using Hapi.js and Flask. Firebase handles user authentication, while BigQuery powers data analysis. Google Cloud Storage stores files, and Cloud Monitoring ensures performance monitoring. For seamless deployment, we rely on Cloud Run, with CI/CD pipelines managed by Cloud Build. Our data is securely stored in Firestore. This cohesive setup ensures efficient, scalable cloud computing

API Documentation : https://github.com/foundie/CC

Cloud Architecture

Database Structure

List Repostory for Cloud Computing

Implemented using NestJS Framework

There is three machine learning backend used in this project. Each of them is for their own models. The backend is implemented using Hapi Js and Flask.

• Face-Classification-Service
• Skin-Tone-Service
• Color-analysis-Service
• Product-Comparison-Service
• community-Service

This repository contains the implementation of three machine learning models for predicting Cras at finibus velit. Morbi tincidunt, magna quis pellentesque posuere, neque arcu malesuada ante, ut lacinia turpis eros quis nisl. Duis malesuada risus quam. Integer et finibus diam, in volutpat tortor. Donec ullamcorper nulla sodales condimentum tempus. Curabitur congue euismod ante, ut tincidunt nulla. Donec vitae bibendum arcu. Donec ut volutpat tortor.

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Skin Tone Classification provides facial skin tone analysis using image processing technology to accurately detect and classify different types of skin tones. The program analyzes user images to identify skin tones and provide appropriate beauty product recommendations.

Color Analysis Offers color analysis to determine the color palette that best matches the user's skin, hair, and eyes. Foundie helps users find the best color combination to enhance their look.

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