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🌟 Inspiration

One of life's challenges is making wise choices, such as finding the best deals on products. This has become even more important as the impact of rising tariffs has been felt—not just in the news but also in the cost of groceries. We realized there’s no quick way to know if the products we buy are affected by U.S.-Canada trade tariffs. We wanted to build something simple, smart, and empowering — a tool that supports local businesses and helps people make better choices at the shelf.

📱 What it does

MapleLens lets users:

Take a picture of a product using their phone camera or upload a picture
(Beta) Suggest Canadian or tariff-free alternatives
Process everything through a custom backend using image recognition

🛠 How we built it

Frontend: Built in Flutter, we created a responsive mobile UI with a camera-powered homepage. Users can capture and upload images directly from the app.
Backend: Hosted on Vercel, it processes image uploads and runs classification logic to detect U.S. products.
Camera Integration: Used Flutter’s image_picker package to access live camera preview and capture functionality.
Networking: Used the http package to handle photo uploads and receive results from the backend API.
Text Recognition (OCR): Integrated Google Vision API to extract product names and details directly from images.
Product Matching: Used RapidFuzz for fuzzy string matching, allowing better identification of Canadian alternatives.

🚧 Challenges we ran into (and how we overcame them)

1️⃣ Deciding the logic behind matching products to Canadian alternatives

How we overcame it: The Google Cloud Vision API returns a string of product features. Since a category of products (chips, drinks, etc.) has certain features (potatoes, bottle), we matched each product to a category so all we have to display are the alternatives associated with a category.

2️⃣ Getting the camera plugin to work on emulators (it kept showing a placeholder animation)

How we overcame it: We had to update the pubspec.yaml 🤦‍♂️

3️⃣ Handling a range of image sizes

How we overcame it: We kept receiving error 413 when testing. The issue was that some images were too big. We resolved this through the Flutter package flutter_image_compress.

🏆 Accomplishments that we're proud of

Successfully built a working end-to-end photo → backend → result pipeline
Delivered a polished and intuitive user interface in Flutter
Collaborated quickly under pressure and kept things clean, simple, and usable
Tackled a real-world, timely issue that could genuinely help people make informed buying decisions

🧠 What we learned

How to capture and upload images using Flutter's image_picker + http stack
How to integrate a Dart frontend with a Python backend
Best practices in structuring a multi-developer Flutter project
The importance of debugging emulator quirks and adapting fast
Sleep is important 😴