Inspiration
We love to eat well for our bodies. We know that it is hard to make sure you are eating well every day, especially with school work and extracurriculars. We loved the idea of sharing it with friends and making a community support system to make sure you are achieving your goals. It doesn't compare you to others! It only compares you to your own goals that you set!
What it does
NutriByte is an AI-Powered Nutrition Tracker that calculates the total nutrition intake per day. You can set personal daily goals that you can try to achieve and you can connect with friends and send them positive quotes! The food input is processed by the Deep Learning module which outputs the nutritional facts which you can see in the website!
How we built it
We used React App to construct the front end User Interface. It is a locally hosted website. Then we connected the backend user input by saving input in text files using databases. Our deep learning model reads these files to output the nutritional facts of each meal which you can then see on the website. We used a scikit learn module to build our machine learning model. The deep learning model was trained on nutrition data from a dataset found on Kaggle here: https://www.kaggle.com/datasets/utsavdey1410/food-nutrition-dataset
Challenges we ran into
Backend was new and hard for us! We had a hard time connecting the local host input to the databases!
Accomplishments that we're proud of
We think our front end works really well and is beautiful and we are so proud of it. We are proud of trying backend and succeeding!
What we learned
We learned how to use Scikit learn to make a deep learning model. We taught the model from our csv training data.
What's next for NutriByte
We want to add functionality to the progress ring feature where it would show you how close you are to hitting your goal by a clockwise formation of the goal circles you can see on our UI! Also we want to fully finish the backend!
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