Pocket Chef

Do you ever look at your fridge, and even though there is clearly food inside, you feel like it's empty? Well with Pocket Chef, an endless source of culinary inspiration, this will never happen again!

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Inspiration

We were inspired by other image recognition softwares, that spots objects individually in an object filled image.

What it does

You take a picture of your fridge , our app detects the fresh ingredients in the Fridge to then proposes some recipes utilizing the present ingredients. This is to encourage eating at home, and to reduce food waste.

How we built it

We used React for the frontend. For the backend we used Node.js ,flask and OpenAI API.

Challenges we ran into

We struggled with making the image recognition and AI perform their task well and accurately.

Accomplishments that we're proud of

We are very proud of how we were able to link the back end and front end together. It was a big challenge to figure out the request processes, but we are extremely proud of how much we learned, and the final result.

What we learned

We learned that image recognition is very hard and long to master. The difficulty is really in making something reliable and smart, with a very short period of time.

What's next for Pocket Chef

We have many ideas to expand the incredible potential of the application. There is still a lot of space to innovate and to answer the user's needs. for example, dietary restrictions, preferences guided searches (ex. for a specific cooking time), special requests (ex. choosing an aliment to center the recipe around), and much more!

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