My Dear Closet

Inspiration

Ever looked at a closet that is completely full and still thought: “I have nothing to wear.”

That experience is surprisingly universal. The issue usually isn’t a lack of clothing — it’s a lack of inspiration. Modern fashion cycles move incredibly fast, and the industry depends on constant consumption to stay profitable. As a result, many of us buy trendy pieces without considering how well they integrate into the rest of our wardrobe.

This creates a cycle: buy → wear once → forget → buy again.

We wanted to break that cycle.

My Dear Closet encourages people to reconnect with the clothes they already own. By helping users rediscover outfit possibilities inside their existing wardrobe, we aim to reduce overconsumption while making fashion more creative, mindful, and sustainable — for both the user and the planet.

What it does

My Dear Closet is a mobile app that helps you plan outfits using the clothes you already own.

Users can build a virtual version of their wardrobe by uploading garment images and basic details. From there, the app generates outfit suggestions and insights that help users make better style and purchasing decisions.

Core Features

Compatibility Score (0–100%)

Thinking about buying a new clothing item? The app evaluates how well it fits into your wardrobe by analyzing:

color compatibility with your existing pieces
number of possible outfit combinations
care requirements
alignment with your past outfit preferences

The result is a compatibility score that helps users decide whether a new item is actually worth buying.

AI Outfit Recommendations

Users receive scrollable outfit suggestions, similar to Pinterest. As more outfits are logged and rated, recommendations gradually adapt to the user's personal style.

Users can also generate new outfits using Gemini AI, combining pieces from their closet in creative ways.

Outfit History

The app keeps a record of previously worn outfits, helping users rediscover combinations they loved.

Closet Report

Each year, users receive a shareable Closet Report showing insights such as:

cost-per-wear of clothing
percentage of thrifted items
favorite fabrics and materials
most worn pieces

This turns sustainability into something visible, measurable, and shareable.

Context-Aware Outfit Suggestions

Outfits can be recommended based on:

current weather
occasion
personal style history

How we built it

Our tech stack included:

Backend

Python

Frontend

React.js
JavaScript
HTML/CSS

APIs

Gemini API (AI outfit generation)
Weather API (context-aware recommendations)

Challenges we ran into

One of the biggest challenges was designing a system that could meaningfully evaluate clothing compatibility. Clothing isn’t just data — it’s subjective, aesthetic, and contextual.

We experimented with different approaches for measuring compatibility, such as color matching, number of outfit combinations, and ease of care. Balancing these factors into a single score required iteration.

Another challenge was building a user interface that made outfit exploration playful rather than overwhelming. We wanted the experience to feel more like browsing inspiration than managing inventory.