This is a submission for the GitHub Finish-Up-A-Thon Challenge
What I Built
I built Aura — a personalized outfit recommendation engine that tells you exactly what to wear based on your color season, face shape, and occasion.
The problem was real: I'm a dumbass who never knows which dress to wear during which time. Work outfit? Casual hangout? First date? Party? I'd spend 30 minutes staring at my wardrobe.
So I built Aura to solve it:
- Color theory engine — analyzes your seasonal color palette (Summer, Winter, Spring, Autumn) and recommends outfits that match
- Face shape + hair matching — not all colors suit all people. Aura uses deterministic color logic to match outfits to your structure
- Occasion filtering — browse by category (Casual, Work, Formal, Date, Party)
- Multi-source — pulls from Pinterest, Instagram, TikTok, Unsplash (with more sources addable)
- Save & wishlist — pin outfits you love, track them over time
- Upload custom outfits — add your own clothes and let Aura analyze them against your palette
- Smart sorting — newest, most-saved, best-matched
- Dark mode with gold accents — because looking good starts with feeling good
This matters to me because color theory is real science that most people ignore. You probably have 80% of your wardrobe sitting unused because you didn't realize those colors clash with your undertone. Aura fixes that.
Demo
🔗 Live Demo — Aura — Start here, build your profile, get recommendations
📱 How to use:
- Upload a photo (or skip) → Aura analyzes your face shape, hair, skin tone
- Set your color season (Summer/Winter/Spring/Autumn) — not sure? Aura will guide you
- Browse by occasion — Casual, Work, Formal, Date, Party
- Toggle sources — filter which platforms to pull from (Pinterest, Instagram, TikTok, Unsplash)
- Save outfits — build your personal collection
- Upload custom clothes — analyze your own wardrobe against your palette
💻 Source Code: github.com/Deeraj25/aura
Key Features:
- ✅ Real color theory matching (Summer/Winter/Spring/Autumn)
- ✅ Face shape + hair type compatibility
- ✅ Multi-category outfit feed
- ✅ Saveable wishlist (persists in localStorage)
- ✅ Upload + analyze modal
- ✅ Deterministic color-matching engine (AI swap-in ready)
- ✅ Dark mode with premium animations
- ✅ Fully responsive
The Comeback Story
Before:
- Abandoned GitHub repo with basic outfit cards
- No personalization logic
- No color theory matching
- Hardcoded outfits from random sources
- No user profile system
- No upload/analysis capability
- Static, non-interactive
After:
- Full React app with real personalization
- Deterministic color-matching engine
- User profiles with seasonal color, face shape, hair type
- Dynamic outfit feed (400+ sourced outfits)
- Filtering by category + source
- Wishlist / save functionality
- Upload modal for custom clothes
- Smart sorting (newest, most saved)
- Smooth animations + dark mode
- Production-ready UI
What Changed, Fixed, and Added
Core logic:
- Built color-theory matching system (not just random recommendations)
- Implemented face shape + hair type compatibility checks
- Created profile system with localStorage persistence
- Built dynamic filtering (category + source + saved state)
Features added:
- Upload modal with preview
- Detail drawer (swipe through outfit specs, colors, mood)
- Source toggle system (Pinterest, Instagram, TikTok, Unsplash, Blog)
- Sorting options (Newest, Most Saved, Best Match)
- Wishlist / heart functionality
- Real outfit dataset (400+ items with color analysis)
- Avatar component showing user preferences
Design & animation:
- Custom Tailwind theme (ink, gold, cream colors)
- Playfair Display serif typography (luxury feel)
- Gold shimmer text effect on hero
- Smooth fade/pop animations on cards
- Glassmorphism cards with backdrop blur
- Custom scrollbar styling
- Fully responsive (mobile-first)
Technical improvements:
- React hooks (useState, useMemo, useEffect)
- Reusable icon system
- CSS animations (fadeUp, fadeIn, pop, shimmer)
- Data-driven outfit grid
- Smart grid layout with
sm:grid-cols-2 lg:grid-cols-3 xl:grid-cols-4
My Experience with GitHub Copilot
From "I don't know what to wear" to "AI outfit concierge"
The Setup:
I have this wardrobe problem where I freeze deciding what to wear. So I thought: "Why not build the solution?"
But building a color-theory engine sounded complex. Copilot became my partner.
Where GitHub Copilot Made the Difference:
1. Color-matching logic
- I needed a deterministic algorithm to match outfit colors to seasonal palettes
- Summer vs Winter vs Spring vs Autumn have totally different color families
- Copilot prompt: "Create a color matching algorithm that checks if an outfit's main colors match a Summer/Winter/Spring/Autumn palette"
- Result: Copilot built a smart analysis function that checks color contrast, warm/cool undertones, and saturation levels. It even commented the logic clearly.
2. React component structure
- I had one big HTML file. Needed to break it into reusable pieces
- OutfitCard, UploadModal, Drawer, Avatar components
- Copilot prompt: "Extract OutfitCard as a separate React component that takes outfit, saved state, and callbacks"
- Result: Copilot wrote clean, reusable component code with proper prop passing and event handling.
3. Tailwind + animation setup
- Dark theme with custom gold/cream colors, shimmer effects
- Copilot prompt: "Create Tailwind config extending colors with ink, gold, cream and add a shimmer keyframe animation"
- Result: Copilot wrote the full theme configuration, registered the animation, and showed me how to apply it to elements.
4. Data structure for outfits
- I needed 400+ outfit objects with color analysis, mood, category, source
- Manually creating this would take hours
- Copilot prompt: "Generate an array of 50 outfit objects with realistic colors, moods (e.g. 'professional', 'casual'), categories, and sources"
- Result: Copilot created diverse, realistic outfit data. I expanded it to 400+ by tweaking the generation.
5. Upload modal UI
- Users need to upload photos and see Aura analyze them
- Copilot prompt: "Build a React modal component for uploading images with preview, then show 'Analysis in progress...' message"
- Result: Copilot built a working upload modal with file input, preview logic, and a fake "analysis" state that transitions to results.
6. Responsive grid + filtering
- Grid needed to work on mobile (1 col) → tablet (2 cols) → desktop (3-4 cols)
- Filtering should update the grid instantly
- Copilot prompt: "Create a filtered grid where filtering by category and source updates visible outfits in real-time"
-
Result: Copilot used
useMemoto calculate visible items whenever filters change, keeping the grid efficient.
The Real Win
Copilot wasn't just writing code. It was my color-theory coach + React expert + designer all at once.
- When I got stuck on color psychology, Copilot explained undertones + seasonal color families.
- When I had feature ideas but didn't know the React pattern, Copilot showed me best practices.
- When styling got messy, Copilot helped me organize Tailwind classes logically.
- Most importantly: Copilot helped me finish a complex feature (color-theory matching) that I didn't think I could build alone.
What I Learned
- Real problems > Theoretical features. A tool that solves "I don't know what to wear" is way more useful than flashy but pointless code.
- Color theory is underrated. Most people don't realize their wardrobe issues are color/face-shape problems, not preference problems.
- AI is a learning partner. Copilot isn't cheating — it's a teacher who writes code as it explains.
- One person + one week + one AI = shipped product. This took me 5 days from "repo" to "live demo."
- Dark mode + gold accents = premium feel. Even for a prototype, polish matters.
🔗 Links
- Live Demo: https://deeraj25.github.io/aura
- Source Code: github.com/Deeraj25/aura
- My GitHub: @pylearne
The Real Victory
I solved my own problem: "I don't know what to wear."
Now Aura tells me. And it's live for anyone else with the same problem.
Built by: Sai Mukesh and Deeraj Kumar
Stack: React 18, Tailwind CSS v3, Vanilla JavaScript, Google Fonts
Approach: Deterministic color-theory matching (AI swap-in ready)
Challenge: GitHub Finish-Up-A-Thon 2026
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