Ingredible

Instead of getting stuck choosing between millions of recipes, Ingredible uses database comprehension and Google Vision to track and suggest suitable recipes using a photo of the ingredients you have.

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Inspiration

After returning home prematurely from college, our parents put us all in quarantine. Some of us haven't left our house in weeks. However, we began to strongly agree that the COVID-19 pandemic should not come in the way of maximizing the culinary experience we can make for ourselves at home.

What it does

Ingredible's primary function is a recipe search engine that receives a photo from your phone camera and returns recipes that uses the ingredients in the photo. It also allows you to view, save, and share recipes with the click of a button.

How we built it

In backend, we set up a server from Domain.com that hosted and managed the recipe database that we compiled and parsed from 250k search results for recipes on the internet, primarily from Food.com. Our frontend was built in Android Studio, from which the designs were imported from Figma.

Challenges we ran into

Originally, there were supposed to be three of us working on the Android app together, but we couldn't get Android studio running on two of the Macs, so one person did the heavy lifting on Android while the others focused on other parts of the project.

Accomplishments that we're proud of

Despite unable to physically be able to troubleshoot for each other, we managed to divvy up the work to manageable chunks.

What we learned

It's necessary to be flexible with ideas, designs, and roles.

What's next for Ingredible

Extending the application to the iOS platform, adding OAuth functionality, improving NLP comprehension of Google Vision API tags

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