RecipEZ

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  Our TensorFlow model recognising multiple fruits in the React localhost

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  Our recipe generator front-end, to the users preference and grocery availability

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  This is our recipe generator taking a list of items that would be generated and displaying the list of potential recipes

Inspiration

As university students, we have limited cooking knowledge and groceries. Because of this, we wanted something that can provide us with simple recipes with anything we have in the fridge! So, we came up with RecipEZ, as we believe this can help other students and culinary novices alike!

What it does

In order to be able to get recipes just from showing the camera our ingredients available we used machine learning to identify food items and then provide recipes from 2 million curated options. It displays the food identified as well as the recipes.

How we built it

TensorFlow models. React front-end. Node.js and Python backend. Web camera.

Challenges I ran into

Learning all of the programs. Connecting the two React Apps. We tried so many different ways to connect them, including Flask.

Accomplishments that I'm proud of

We're proud that we came in with nothing and were able to learn many new skills on the spot to create an application that is sleek and very useful.

What I learned

Time management in a Hackathon environment. How to use TensorFlow, Python, MySQL, API, JavaScript

What's next for RecipEZ

For the immediate future we want to streamline it and make sure all the components are able to work together. We also want to provide a more appealing design. Also we want to provide more details for the recipes such as pictures and descriptions.

Built With

• node.js
• python
• react
• tensorflow