Our inspiration for PupperSupper is a passion for the developing field of computer vision as well as a need for improving the quality of life for our pets.

What it does

The core functionality of our web app revolves around determining if there are any unsuitable ingredients for your pet found in the ingredients list of a food label.

How we built it

We began with the core logic of the program written in python 3 utilizing opencv and the Google Vision API. The backend of the webapp was built with django on AWS servers. The resulting webpage was written in html, css, and JavaScript.

Challenges we ran into

We began by envisioning a comprehensive fitness product for pets which includes nutrition, fitness, and health related reminders. Our greatest obstacle in our project was aggregating the different components of core logic, front end, and web deployment into a cohesive ending product.

Accomplishments that we're proud of

PupperSupper is able to quickly read an ingredient list, and inform the user of potential health hazards for their pet dog.

What we learned

We learned a lot from this opportunity, such as how to give credentials for an API request, how to design and implement a database in Django, as well as how to move a website from production into deployment.

What's next for PupperSupper

We are planning on continuing our development through implementing other useful features such as a fitness component and pet health reminders.

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