TrueMe

TrueMe is a finalist project in the 2024 ECS Student Project Innovation Expo Competition!

Description

TrueMe aims to assist users in their skincare and beauty journey. Users will be able to easily discover new products that are recommended to them based on their skin condition. TrueMe will utilize facial recognition to achieve this. In addition, the user will have control over their automated suggestions with filters in order to further provide personalization. TrueMe will also allow users to create their own daily routines as well as receive recommended routines.

Installation

Local Installation

• TrueMe App:
  • Ensure you have Expo Go installed or a simulator
  • Clone the repository: git clone https://github.com/atakux/TrueMe.git
  • cd ~/TrueMe and run npm install
  • Run npx expo start --tunnel -c to start the local server
• TrueMe Backend Server for AI Skin Analysis:
  • cd ~/SkinAnalysis and run flask run to start the server

Backend for AI Skin Analysis

• TrueMe Server
  • Note: This TrueMe Server is only to be used as an API
• Postman Collection to test server
• GitHub Repository

Tools Used

• Node.js
• Firebase
• Render

Testing Tools

• Postman
• Expo Go

Languages/Frameworks

• React Native
• JavaScript
• Python
• Flask

API

• Amazon API

Contributors

• Angela DeLeo
• Roman Saddi
• Project Advisor: Professor Bruce McKenzie

Licensing

Flaticon: https://www.flaticon.com/

• All icons are licensed by Flaticon under CC BY 4.0 License

Kaggle: https://www.kaggle.com/

• All datasets are licensed by Kaggle under CC BY 4.0 License, Open Data Commons, and Apache License 2.0

Roboflow: https://roboflow.com/

• All datasets are licensed by RoboFlow under CC BY 4.0 License

Privacy Policy

Privacy Policy

Contact

Angela DeLeo

• Email
• LinkedIn
• GitHub

Roman Saddi

• Email
• LinkedIn
• GitHub