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ClosetAI

ClosetAI is an AI-powered wardrobe management platform that empowers users to manage their clothing, receive intelligent outfit recommendations, and embrace sustainable fashion practices.


🌟 Key Features

AI Garment Detection
Upload clothing items and let AI automatically classify their type and color with advanced computer vision.

Smart Outfit Suggestions
Get personalized outfit recommendations based on weather conditions, mood preferences, and your unique skin tone.

Sustainable Fashion Marketplace
Donate clothes through our integrated community marketplace, promoting circular fashion economy.

Color Intelligence
Receive outfit recommendations aligned with your skin tone and color harmony principles.

Usage Analytics
Track how often you wear each item to make more conscious consumption decisions.


Authentication & User Management

  • Registration & Login: Email/password authentication with Google OAuth integration
  • Security: JWT-based authentication system
  • Profile Setup: Advanced skin tone detection during onboarding
  • User Preferences: Customizable style and color preferences

Wardrobe Management System

  • Easy Upload: Intuitive drag-and-drop clothing upload interface
  • AI Classification: Automatic item categorization with manual override options
  • Advanced Filtering: Filter items by category, color, material, and usage frequency
  • Item Management: Edit, delete, and organize your wardrobe entries
  • Usage Statistics: Comprehensive tracking of item wear frequency

Smart Outfit Recommendations

  • Mood-Based Styling: Recommendations for Casual, Formal, Party, and Sporty occasions
  • Weather Integration: Weather-aware suggestions using OpenWeatherMap API
  • Compatibility Scoring: Advanced color and material compatibility analysis (0.5–1.0 scale)
  • Skin Tone Optimization: Color suggestions tailored to your unique skin tone
  • Personal Collection: Save and favorite your preferred outfit combinations

Community Exchange & Marketplace

  • Sell & Donate: List unused clothing for sale or donation
  • Smart Browsing: Search items by location, condition, size, and category
  • NGO Partnerships: Direct donation connections with local NGOs
  • Community Sharing: Claim publicly donated clothes from the community
  • Advanced Filters: Streamlined browsing experience with multiple filter options

AI & Machine Learning Architecture

Component Technology Purpose
Clothing Detection MobileNetV1 Image classification and garment recognition
Color Analysis OpenCV + KMeans Advanced color extraction and analysis
Skin Tone Matching Fitzpatrick Scale Personalized color recommendations
Recommendation Engine Content-based Filtering Intelligent outfit suggestions
Color Harmony Vastu-based Logic Traditional color matching principles
Weather Integration API Mapping Rules Weather-to-outfit recommendation logic

Project Architecture

ClosetAI/
├── backend/                    # Django + DRF backend
│   ├── accounts/              # Authentication system
│   ├── wardrobe/              # Wardrobe management
│   ├── recommendations/       # Outfit generation logic
│   ├── marketplace/           # Donation/sell features
│   └── manage.py, settings.py, etc.
│
├── frontend/                  # React frontend
│   ├── public/
│   ├── src/
│   │   ├── components/        # Reusable UI components
│   │   ├── pages/            # Page-level components
│   │   ├── utils/            # Helper utilities
│   │   ├── App.js            # Application routes
│   │   └── index.js
│   └── package.json
│
└── README.md                  # Project documentation

Getting Started

Prerequisites

Ensure you have the following installed on your system:

  • Python 3.9+
  • Node.js & npm
  • MySQL Server
  • Git

Backend Setup

1. Install Dependencies

cd backend
pip install -r requirements.txt

If requirements.txt is missing, install manually:

pip install django djangorestframework mysqlclient pillow python-dotenv django-cors-headers google-auth

2. Environment Configuration

Create a .env file in the backend/ directory:

SECRET_KEY=your-django-secret-key
DEBUG=True
ALLOWED_HOSTS=*

DB_ENGINE=django.db.backends.mysql
DB_NAME=closetai_db
DB_USER=root
DB_PASSWORD=your-db-password
DB_HOST=localhost
DB_PORT=3306

JWT_SECRET_KEY=your-jwt-secret
OPENWEATHER_API_KEY=your-weather-api-key

3. Database Setup

Create the MySQL database:

CREATE DATABASE closetai_db;

4. Apply Database Migrations

python manage.py makemigrations
python manage.py migrate

5. Start the Backend Server

python manage.py runserver

Backend will be available at: http://localhost:8000


Frontend Setup

1. Install Dependencies

cd frontend
npm install

2. Environment Configuration

Create a .env file in the frontend/ directory:

REACT_APP_GOOGLE_CLIENT_ID=your-google-client-id
REACT_APP_API_URL=http://localhost:8000/api

3. Start the Development Server

npm start

Frontend will be available at: http://localhost:3000


Application Routes

Page URL Description
Homepage / Landing page and overview
Login /login User authentication
Register /register New user registration
Upload /upload Clothing item upload
Wardrobe /wardrobe Personal wardrobe management
Recommendations /recommendations AI outfit suggestions
Community /community Marketplace and donations

API Endpoints

Method Endpoint Description
POST /api/auth/register/ User registration
POST /api/auth/login/ Login & JWT token generation
GET /api/wardrobe/ Wardrobe management
POST /api/recommendations/ Generate outfit suggestions
GET /api/marketplace/ Browse marketplace items
POST /api/user/skin-tone/upload/ Skin tone detection upload

Testing Guidelines

Garment Upload Testing

  • Upload multiple garments in different lighting conditions
  • Test AI classification accuracy across various clothing types

Recommendation System Testing

  • Test recommendation logic across different moods and weather conditions
  • Verify skin-tone based color suggestions accuracy

Marketplace Testing

  • Post items for donation and test the claiming process
  • Browse and filter marketplace items

Responsive Design Testing

  • Use developer tools to test mobile responsiveness
  • Verify UI components across different screen sizes

Technology Stack

Layer Technologies
Frontend React, Material UI, Axios
Backend Django, Django REST Framework
Database MySQL
AI/ML MobileNet, OpenCV, KMeans, Fitzpatrick Scale
Authentication JWT, Google OAuth
External APIs OpenWeatherMap, Custom ML APIs

Development Team

Name Role Key Responsibilities
Swayam Kohli Full Stack Developer Frontend & backend integration, authentication, React components, Django APIs, marketplace functionality, recommendation engine
Sneha Rawat AI/ML Lead Garment classification, color detection, skin tone matching, content-based outfit recommendation system

Future Roadmap

Enhanced Features

  • Virtual Try-On integration (Ready Player Me or ARKit)
  • Social features including chat, outfit feed, and community leaderboard
  • Collaborative filtering for improved recommendations

Expansion Plans

  • Multi-language support (Hindi, Tamil, Bengali)
  • Calendar integration for event-specific dressing
  • AR Assistant with real-time camera feed

Social & Sustainability Impact

ClosetAI contributes to sustainable fashion by promoting:

  • Circular Economy: Encouraging clothing reuse and extending garment lifecycles
  • Environmental Impact: Reducing textile waste and carbon emissions
  • Fashion Accessibility: Making quality clothing accessible through community sharing
  • Conscious Consumption: Providing insights into wearing patterns to encourage mindful purchasing

Sample Dependencies

Django==4.2.12
djangorestframework==3.15.2
mysqlclient==2.2.0
pillow==10.3.0
python-dotenv==1.0.1
django-cors-headers==4.2.0

Contributing

We welcome contributions, feedback, and bug reports from the community. Please feel free to submit pull requests or open issues.

Contact: swayamkohli11489@gmail.com


ClosetAI - Transforming wardrobes through AI, promoting sustainable fashion, and building communities around conscious clothing consumption.

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An AI-powered wardrobe management system that helps users organize clothing, get personalized outfit recommendations, and promote sustainable fashion through community sharing.

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