Bettering Health & Nutrition

What it does

When given a picture of an ingredient list on the local web server, the program converts the ingredient list into detailed information about each ingredient and their nutritional overviews, then displaying this data on the same web server.

How we built it

Used html5 for the front-end, making a very user-friendly interface Used Python 3.7 in the back-end Used BeautifulSoup to design a web-scraper which received data from databases online Used Microsoft Azure's Optical Character Recognition (Computer Vision) to detect text from images Used Pygame to create a user-friendly interaction system Used Django to tie front-end and back-end together

Challenges we ran into

We were new to many of the libraries we used and ran into various library-specific problems we were unaccustomed to

Accomplishments that we're proud of

We are very happy with the final product, as we feel we have accomplished our task well while still achieving a very user-friendly and intuitive system

What we learned

We developed our programming under pressure skills as well as gained much knowledge on a lot of foreign concepts including: Machine learning, web-scraping, designing UI, creating a local server which we all understand to a much better extent now.

What's next for Nutrition Clarity

We hope to expand the functionality of Nutrition Clarity to be applicable for different types of data, as well as advance the ingredient database software to give very accurate and helpful nutritional data

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