Inspiration
We were inspired by an app called photo math which took mathematical equations from pictures and translated them into text. This made us think of applying object recognition software in other ways where they would benefit people's daily lifestyles. After a brainstorming period during breakfeast, SnapThat! was born.
What it does
The user takes a photo of their at latest meal which is run through the Clarifai api to return the identity of the food. Then, it is plugged into an array to find out the nutritional content, which is returned to the user.
How we built it
We built this through Android Studios with code from the Carifai api.
Challenges we ran into
At first, we had difficulty connecting a phone to Android Studios to use as a testing device. In addition, we ran into several problems finding a useful api to use as a nutritional database. Many were simply too advanced and non-user friendly.
Accomplishments that we're proud of
We managed to build a professional app GUI to back up our code We also created our own nutritional database, albeit limited in it's scope.
What we learned
The majority of our team had no knowledge of Java, the main language for our code. In fact, one member had no prior programming exposure whatsoever. However, at the end of the hackathon, each member definitely advanced their knowledge of not only Java but also computer science as a whole.
What's next for SnapThat!
Future aims include allowing the user to post their pictures directly onto Instagram and keeping track of their daily calorie intake, as well as recommending various workout plans and food choices based on prior data.
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