Everyone takes pictures of their food before they eat it. In today's society, the phone eats first! When it comes to nutrition, many people lose motivation to keep up with tracking their nutritional intake because of the tedious work that comes from logging each meal or ingredient manually. We decided to create software that simplifies the process by taking advantage of people's habits of taking a picture before they eat and providing a beneficial method to track their nutrient intake.

What it does

Our software takes an image and using IBM-Watson visual recognition API, can identify and classify these images into distinct food items. Our program then takes each food entry, and through a database, extracts their respective nutritional information and helps log and keep track of their daily intake. Our software also provides personalized recommendations for food based on the user's age, weight, height, activity level, and eating habits.

How we built it

Using stdlib as a means to deploy our API, we used multiple API;s and a database to extract nutrition facts from a given image. Using swift as one of the many avenues,, we were able to create an application to cater to a wide audience of all ages and lifestyles.

Challenges we ran into

Some major challenges we ran into was our unfamiliarity with the languages we coded with. Through many trials and errors and Stackoverflow we were able to learn and adapt to these new languages.

Accomplishments that we're proud of

Able to create and deploy an API as well as create a fully functional app.

What we learned

We learned the values and importance of being patient through troubleshooting and debugging.

What's next for NutriVision

We wish to expand the use of our app and API through offering our service to Android users. Possible improvements to our project include suggesting healthy recipes and also providing a service to find nutritious, local grocery stores or restaurants to promote healthy eating.

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