Macro aims to make meals easy through an easy-to-use macro tracking iOS app. Simply snap a picture of your meal and let Macro determine the calorie, protein, carbohydrate, and fat content of your dish. Macro will remember the foods you eat to help you track and achieve your dietary goals.
Macro uses a custom computer vision machine learning algorithm to classify foods and quantify volumes, which combine to provide the nutritional breakdown of a variety of foods.
- Front End: React Native, Node.js
- Back End: Express, MongoDB, Mongoose
- Machine Learning: Flask, TensorFlow
- Storage: Amazon S3
- Clone the main repo to your local machine
- Navigate to the
macro-frontend
directory - Run
yarn install
to install any necessary dependencies - Run
expo start
to start up the app. You can then use Xcode to simulate an iOS device, or connect your own iOS device via LAN or tunneling via the QR code
- NOTE - to avoid having to update the connections in the main repo, just utilize the automatically deployed Heroku server which hosts our API to test our functionally!
- To host the API locally for testing, clone the API Repo and run
yarn dev
. You will then be able to make API calls to your localhost
NOTE: the flask server takes a bit of time to boot up for the first call! If you would like to ensure that the server is up and running before you start the app, just visit this URL!
- The server is automatically deployed via Heroku
- The database is hosted by MangoDB
- The flask server is automatically deployed via Heroku (see the Classifier Repo for details on local development)
- The images database is stored on Amazon S3
- Clone the main repo to your local machine
- Navigate to the
macro-frontend
directory - Run
yarn install
to install any necessary dependencies - Run
expo build:ios
to build the app - Download the build file from expo and upload to App Store Connect via the Transporter app
- Heroku automatically deploys the API repo whenever
main
receives an update