ZOT N Munch

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Have you ever been a victim of gatekeeping?

So have we. It sucks, doesn't it? Luckily for you, look no further! Meet Zot n' Munch, a website where users can upload image URLs of food and find resturaunts that serve that food.

How it Works

Spoonacular API

In order to identify the food in the photo, we needed some type of machine learning to be able to identify and classify the food. So we used Spoonacular API, a food API that provided a food recognition tool using machine learning. With this, we'll be able to determine the type of food presented in the image with just the image URL! After calling the API, it will return the category that it thinks the food belongs to, along with a probability of it being right or not.

Yelp API

After receiving the results from Spoonacular, we needed to find a way to be able to search for resturaunts that served that particular food. So we decided to utilize the Yelp API by passing in the food category returned from Spoonacular and a location inputted by the user. If the user doesn't input a location, the default will be Irvine, CA. After that, our call will return a list of resturaunts that serve the food found in the image!

How it All Comes Together

Finally, after combining our two functions into one that calls both, we were ready to link it to our front-end interface. When the user inputs an image URL, a list of resturaunts within the vicinity of the location they inputted (Irvine, if they didn't input a location) will appear for the user to browse through.

Disclaimer!

Please be aware that the Spoonacular API is not 100% accurate, and may misidentify food. Hopefully in the future, we can continue to train the machine to better identify and categorize the presented food items.