Healthy Eater Buddy

Inspiration

Everyone wants to know what's inside their food, but there's no easy way to do it so we made HealthyEaterBuddy.

What it does

The user is able to take a picture of their food and then they will receive nutritional facts about it.

How we built it

We used the metamind api to train a convolutional neural net on a large database of pictures of food that we amassed. We then used this classifier to identify what is contained within pictures of food. This output was fed into the wolfram api to get information on nutritional facts.

Challenges we ran into

Difficulties getting the app set up

Accomplishments that we're proud of

It actually works well

What we learned

Learned about different machine learning techniques, iOS programming, RESTful APIs

What's next for Healthy Eater Buddy

We hope to make our database bigger so we can more accurately classify different types of food. We would also like to be able to figure out how to get the amount of food that is present in a picture.

Built With

• metamind
• python
• swift
• wolfram-technologies