Wassgood

Inspiration

Many ingredients in cosmetic products are harmful but not banned by the FDA. We want to create an app that can inform the consumers about the potential dangers of the ingredients in the products they are using, so they can make the best choice that suits their personal needs.

What it does

This app has a user-friendly interface.

• To use, as soon as you open the app, you will have options to choose one out of three categories shows on the home screen.
• After you choose your option, the app will redirect to your device camera, where you can take a photo of the ingredients locating on the back of the product.
• The app will then scan those ingredients, find information from trusted articles on the web, and use natural language process to determine whether they are good or not.
• Base on your preference, you can learn which ingredient is good, neutral, or needs some caution when using.

How we built it

We used various Python libraries for web scraping and natural language processing like Vader sentiment and newspaper. We used flutter and dart for app development, google vision API and Firebase Machine Learning kit for text recognition.

Challenges we ran into

We used vision API and ML Kit for the first time, so there were some technical difficulties in integrating that in our flutter app.

What we learned

It was our first time using natural language processing and firebase ml kit. We learned to work as a team, troubleshooting the problems together, and utilize each person's strengths and weaknesses during this hackathon.

What's next for Wassgood

We are considering adding more features to the app:

• Increase the number of options for the consumers to choose from.
• Allow user import the photo from existing photo library.

Built With

• android-studio
• dart
• firebase-ml-kit
• flutter
• google-vision-api
• python