nomnom!

find your next favorite snack :)

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Inspiration ✈️🍫

While traveling, we often discover amazing snacks that we wish we could find back home. However, finding similar snacks in different countries can be challenging. nomnom! was born to bridge this gap—helping snack lovers find their next favorite treat, no matter where they are in the world.

What it does 🍪🔍

📸 Take a picture of a snack they enjoy. 🤖 Use AI to identify and suggest similar snacks available in other regions. 🌍 Filter results by country to find local equivalents. 📚 Explore a global snack database with images, flavors, and recommendations.

How we built it 🛠️

  • Frontend: Built with FlutterFlow for a seamless cross-platform experience.
  • Backend: Uses the Gemini API to analyze snack images and recommend similar products.
  • Database: We use Firebase to store snack information, including images, categories, and region availability.

Challenges we ran into ⚠️

  • Training the AI to accurately match snacks based on appearance and flavor profiles.
  • Ensuring a diverse snack database that covers multiple countries.
  • Implementing an intuitive UI that makes filtering and searching easy.

Accomplishments that we're proud of 🎉

  • Successfully integrating image recognition with snack recommendations.
  • Creating a user-friendly and visually appealing UI in FlutterFlow.
  • Building a functional prototype within the hackathon timeframe.

What we learned 📖

  • How to leverage AI for food recognition and similarity mapping.
  • Best practices for FlutterFlow development and API integration.
  • The complexity of cross-cultural food preferences and availability.

What's next for nomnom! 🚀

  • 🌎 Expanding the snack database to include more countries and niche snacks.
  • ⭐ Adding user reviews and recommendations for better snack discovery.
  • 📲 Implementing a social sharing feature so users can share their favorite finds.
  • 🗣️ Enhancing translation capabilities to cover a more diverse set of snacks from around the world.

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