FitsIt

FitsIt is a smart wardrobe application that helps you organize clothing and discover outfit combinations. Upload photos of your clothes, and the app uses computer vision to isolate garments, extract dominant colors, and generate scored outfit recommendations based on color harmony theory.

Demo

Coming soon.

Features

• Clothing upload — Add items by category (top, bottom, shoes, outerwear, other) with image upload.
• Automatic segmentation — SegFormer isolates clothing from the background in uploaded photos.
• Color extraction — Dominant colors are extracted from each garment for downstream matching.
• Outfit generation — Combines items from your wardrobe into complete outfits when you have at least one top, bottom, and pair of shoes.
• Color harmony scoring — Outfits are ranked using complementary, analogous, and triadic color relationships.
• Recommendations & wardrobe — Browse top-scored outfit suggestions and save favorites to your personal wardrobe.

Tech Stack

Layer	Technologies
Frontend	React 19, Vite, Tailwind CSS, Radix UI, Framer Motion
Backend	FastAPI, Python 3.11, Uvicorn
ML / Vision	PyTorch, Transformers (SegFormer), scikit-learn, Pillow
Database & Storage	Supabase (PostgreSQL, Storage)
Tooling	Docker, Docker Compose, GitHub Actions, Ruff, pytest

Project Structure

FitsIt/
├── backend/
│   ├── app.py                  # FastAPI application and routes
│   ├── color_extraction.py     # SegFormer-based segmentation and color analysis
│   ├── services/
│   │   ├── outfit_generator.py # Outfit combination logic
│   │   └── outfit_scorer.py    # Color harmony scoring
│   ├── supabase/migrations/    # Database schema migrations
│   └── tests/                  # Backend unit tests
├── frontend/
│   └── src/
│       ├── components/         # UI components (upload, items, recommendations, wardrobe)
│       └── services/           # API client
├── docker-compose.yaml
└── .github/workflows/ci.yml

Prerequisites

• Node.js 20+
• Python 3.11+
• Docker & Docker Compose (optional, for containerized development)
• Supabase project with migrations applied and a clothing-images storage bucket

Getting Started

1. Clone the repository

git clone https://github.com/tahayarkhan/FitsIt.git
cd FitsIt

2. Configure environment variables

Create backend/.env:

SUPABASE_URL=<your-supabase-project-url>
SUPABASE_SERVICE_KEY=<your-supabase-service-role-key>
FRONTEND=http://localhost:5173

Create frontend/.env:

VITE_API_URL=http://localhost:8000

3. Set up the database

Apply Supabase migrations from backend/supabase/migrations/ to your project (via the Supabase CLI or dashboard). Ensure a public storage bucket named clothing-images exists.

4. Run locally

Backend

cd backend
python -m venv venv
source venv/bin/activate   # Windows: venv\Scripts\activate
pip install -r requirements.txt
uvicorn app:app --reload --port 8000

The backend downloads the SegFormer model on first startup. A machine with a GPU (CUDA or Apple MPS) is recommended; CPU inference is supported but slower.

Frontend

cd frontend
npm install
npm run dev

Open http://localhost:5173 in your browser.

5. Run with Docker Compose

From the project root:

docker compose up --build

This starts the backend on port 8000 and the frontend on port 5173.

API

Method	Endpoint	Description
GET	/	Health check
POST	/upload-item	Upload a clothing item (multipart: file, category)
GET	/items	List all clothing items
GET	/recommendations	Get scored outfit recommendations
PATCH	/recommendations/{id}	Like or unlike a recommendation
GET	/wardrobe	Get saved (liked) outfits

Interactive API docs are available at http://localhost:8000/docs when the backend is running.

License

This project is not currently licensed for public use.