TrueMe is a finalist project in the 2024 ECS Student Project Innovation Expo Competition!
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.
- 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 runnpm install
- Run
npx expo start --tunnel -c
to start the local server
- TrueMe Backend Server for AI Skin Analysis:
cd ~/SkinAnalysis
and runflask run
to start the server
- TrueMe Server
- Note: This TrueMe Server is only to be used as an API
- Postman Collection to test server
- GitHub Repository
- Angela DeLeo
- Roman Saddi
- Project Advisor: Professor Bruce McKenzie
Flaticon: https://www.flaticon.com/
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/