CURRENTLY IN PROGRESS
An outfit recommendation system that actually looks at your wardrobe, not just the forecast
React, FastAPI, PostgreSQL, PyTorch, ResNet-50
WeatherFit recommends outfits from your actual wardrobe based on the weather and what you're doing that day — not just temperature, but rain, wind, and activity context too. It started as a simple frontend rule engine and grew into a full-stack app with its own ML model doing the wardrobe classification.
DESIGN PROCESS
Onboarding is split into single-question screens with a progress bar, based on the idea that people commit more easily to a short, predictable path than an open-ended form.
DESIGN PROCESS
Condition badges and verified-seller marks appear directly in the browse feed, not buried in item pages, since trust is the main thing standing between a browser and a buyer in secondhand shopping.
DESIGN PROCESS
Buy Now and Add to Cart are separated deliberately. Most items here are one-of-one, so buyers who already know they want it shouldn’t be forced through a cart step.
CONCEPT — NOT YET BUILT
Early exploration of a full checkout flow using familiar payment patterns (Apple Pay, Google Pay) to reduce hesitation at the final step. This is a design direction, not a shipped feature yet.
01 / IN THE BUILD
Three seller roles
Individual closets, vintage stores, and independent creators each have a clear path in.
Browse to purchase
The flow covers browsing, item pages, cart, checkout, and public seller profiles.
Trust up front
Condition, seller verification, and reviews arrive early—where secondhand decisions happen.
02 / NEXT MILESTONE
The next layer pairs express payment with a creator mode, then puts Minty in front of a real vintage store to learn from actual transactions.