This is a modern dating app which leverages Face JS built on pre-build Tensorflow models and user location to create an algorithm which adjusts to match user preference.
- Data stored to PostgreSQL database, password encryption with b-crypt.
- Front and back-end synochronized using react-query.
- Developed a media and rich text live chat for matched users using action cable, and Quill JS.
- Secure rails sessions login and authentication.
- Integrated with Google Login and Google Maps.
- Fully-built with SCSS and Framer Motion for animations.
Ruby on Rails, React, Javascript, Ruby, HTML, SCSS, Framer-Motion, Git, FaceJS, react-query @react-google-maps/api, @react-google-login, bcrypt, rails active-storage, geokit-rails
- Implement adding additional pictures to profile on frontend
- Speed up load times, especially on pages with images
- Better testing process, use selenium to create new accounts and automate testing.
- Styling updates, standardize styling to be consistent across different pages and switch font
- Require user to position face in particular position to more accurately scan face.
- Move facial recognition technology to backend, intergate python AI technologies with rails
- Resize images in chats to have specific size. Can be viewed larger by clicking (similar to discord features)
- Implement tags and incorportate into backend matching algorithm so users with similar interests can find each other
- Use API to verify if images are safe with google cloud vision.
- Improve google maps so icons are cleaner and map has more functionality
- Implement more fun features into chat. Such as a "date picker" which uses google maps to find nearby date locations for both users
- Deploy application