40% of young adults in America were reported as obese in 2019, Covid and lockdown probably hasn't helped that number. Nutrition is complicated and dieting is hard. Keeping track of calories can be overwhelming and people often mess up or just give up when doing it. Nutriologists are not cheap The average person wants to lose weight and it often influences their self-esteem

What it does

Use our Machine Learning-trained AI to keep track of the nutritional facts that are in your food. Just take a picture of whatever food you're curious about and our app will provide you and record this information. It also comes with a pedometer that factors in the extra calories you walked away that day.

How we built it

For frontend, we used react-native, the javascript library for building mobile apps. With Expo, we were able to view and test the app on our smartphone. For backend, we used Flask and ngrok for the server. We used Tensrflow/Keras to build a model that can recognize different foods. We then used Nutrionix API and edamam food database API to get the nutrional facts for the foods it recognized.

Challenges we ran into

Lack of understanding and experience with the language Difficulty teaming up in a virtual environment Not the best time-management Making the ML model advanced enough to recognize the difference between foods of cheesy consistency.

Accomplishments that we're proud of

Overcoming the stress of quarantine and covid to produce something meaningful that people can enjoy Successfully building a Machine Learning Model that could detect foods pretty damn well Combined our diversity in knowledge The settings page and learning how to work with object-oriented arrays and maps along with UseStates in react-native The progress bar turning red when passing the calorie count Diversified our social media to further communicate and interact with the hacking community via LinkedIn and Devpost

What we learned

We learned the basics of React-Native Methods to better optimize our code A variety of expo and react-native graphical libraries How to use widgets such as the expo camera and the pedometer.

What's next for NutriSnap: the nutritional helper

Add more complex foods that it can recognize Integrate firebase for its login system Give it a website to see more in-depth data online Weight loss/gain graph Generate a personal meal plan Text-to-Speech for the visually impaired Emotional API for factoring in user's food cravings Social media aspects for sharing your achievements Vegetarian and Kosher alternatives An even better UI/UX (yelp, maps to healthy restaurants, and much more!)

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