Innovative application that identifies shoes.


Seetha saw a girl wearing a great pair of shoes and spent an absurd amount of time scouring the internet for them but could not find them.

What it does:

Identifies shoes or not shoes.

How we built it:

Tasks were delegated to members of the team.

Challenges we ran into:

A lot of them. We never used any of the tech we needed for the app. Our app thought the shoes were handbags at first. Team member lost their voice halfway through the hack.

Accomplishments that we're proud of:

The app of course! And learning how to use Convolutional Neural Networks.

What we learned:

We learned a lot of new technologies and languages.

What's next:

We would love to go more in-depth with the classifications. After the app identifies whether the picture is a shoe, we would then want the app to tell the type of shoe (sneaker, boot, sandal, etc.). We also plan on adding color options, price points, and quite possibly listing stores that carry the shoes or similar options.

Built with:

We used Python, TensorFlow, Google Cloud Platform, Flash, Convolutional Neural Networks.

Prizes we're going for:

Arteck HB030 Portable Keyboard

HAVIT RGB Mechanical Keyboard

Intel® Movidius™ Neural Compute Stick

Google Home Mini

$100 Amazon Gift Cards

Raspberry Pis & PiHut Essential Kits

Social Entrepreneurship Award

Grand Prize

Jetbrains Pro Software

Misfit Shine 2

Team Members

Noah Huppert, Tyler Charlantini, Matthew Oslan, Seetha Chock
View on Github