Inspiration
We were inspired by the recent trend of satisfying videos, the tomato sorting video being one. We also realized that often people go to the grocery store to buy fruit but do not know how to tell if it is ripe. This problem related to the sorting of ripe and unripe tomatoes so we combined the two ideas into one. We wanted to provide useful information for the customer on picking fruit while they are shopping.
What it does
If you need help picking fruit at a grocery store, you can upload and image of it to the site, and you will get the characteristics to look for in the ripe fruit.
How we built it
We implemented Microsoft Azure Cognitive Services Computer Vision API in Javascript into a website. The data that we pulled from the API was made into a JSON object which we iterated through to determine the fruit. From there, we connected fruit ripeness research to the image's fruit.
Challenges we ran into
It was difficult going through the tags generated by the API to figure out which fruit it was .
Accomplishments that we're proud of
We are proud of the end result and the functionality. We ultimately wanted to this into a mobile app, but we are glad that we were able to get the algorithm functioning.
What we learned
We learned how to work in Javascript and to make a website.
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