Macro

Team Photo

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.

• Main Repo

• API Repo

• Classifier Repo

• Figma Board

Initial sketches

Architecture

• Front End: React Native, Node.js
• Back End: Express, MongoDB, Mongoose
• Machine Learning: Flask, TensorFlow
• Storage: Amazon S3

Setup

Front End

• 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

Back End

NOTE: all backend processes are automatically deployed - no setup is required!

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 (see the API Repo for details on local development)
• 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

Deployment

Front End

• 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

Back End

• Heroku automatically deploys the API repo whenever main receives an update