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✨ ANGELIC — AI Fashion Recommendation System

An AI-powered fashion intelligence platform that analyzes facial structure, skin tone, undertone, and seasonal palette to deliver personalized styling recommendations in real time.


🌐 Live Demo

🔗 Live Website:
https://angelic-viv.vercel.app/

📦 GitHub Repository:
https://github.com/Vivek-DK/angelic

🧠 Project Vision

ANGELIC was built to bridge the gap between:

  • Artificial Intelligence
  • Fashion Styling
  • Personal Appearance Analysis
  • Real-Time User Interaction

Instead of generic fashion suggestions, the platform provides:

✔ Personalized color recommendations
✔ Face-shape based styling guidance
✔ Seasonal fashion palette detection
✔ AI-driven fashion assistant
✔ Real-time analysis experience

This project combines:

  • Computer Vision
  • Machine Learning
  • Full Stack Engineering
  • Cloud Infrastructure
  • Real-Time Systems

into a single scalable application.

🚀 Core Features

🎨 Skin Tone Detection

Analyzes:

  • skin tone
  • undertone
  • seasonal palette

using image processing and ML models.

Detects:

  • Warm Undertone
  • Cool Undertone
  • Neutral Undertone

Seasonal Analysis:

  • Summer
  • Winter
  • Autumn
  • Spring

👤 Face Shape Analysis

Uses facial landmark detection to identify:

  • Oval
  • Round
  • Square
  • Heart
  • Diamond
  • Oblong

Provides:

  • hairstyle guidance
  • outfit recommendations
  • accessory suggestions

based on face structure.

🤖 AI Fashion Assistant

Integrated AI chatbot powered by LLM APIs.

Capabilities:

  • outfit recommendations
  • color matching advice
  • styling suggestions
  • seasonal dressing tips
  • fashion Q&A

Restrictions:

The assistant is intentionally restricted to:

  • fashion
  • styling
  • wardrobe
  • appearance guidance

to maintain domain specialization.

☁ AWS S3 Cloud Image Storage

Implemented secure cloud storage using:

  • AWS S3
  • Signed URLs
  • Secure upload pipeline

Benefits:

✔ Secure uploads
✔ Faster delivery
✔ Scalable architecture
✔ Reduced backend load

⚡ Image Optimization Pipeline

Before analysis:

  • images are compressed
  • resized
  • converted to JPEG

using browser-side optimization.

Impact:

✔ Reduced upload payload size by up to 70%
✔ Faster uploads
✔ Better user experience
✔ Reduced API processing time

🔔 Real-Time Notifications

Implemented using:

  • Socket.IO
  • WebSockets

Features:

  • live notifications
  • fashion tips
  • AI assistant alerts
  • real-time user interaction

without requiring manual refresh.

📊 Analysis History Dashboard

Users can:

  • save analysis
  • view previous reports
  • fetch personalized recommendations
  • revisit color palettes

with cloud-stored image retrieval.

🏗 System Architecture

Frontend (React.js)
        │
        ▼
Node.js + Express API
        │
        ├── Authentication
        ├── History Management
        ├── AWS S3 Upload Service
        ├── Socket.IO Notifications
        │
        ▼
FastAPI ML Service
        │
        ├── Skin Tone Detection
        ├── Face Shape Analysis
        ├── Fashion AI Assistant
        │
        ▼
MongoDB Database

🧰 TECH STACK

FRONTEND

  • React.js
  • Framer Motion
  • Tailwind CSS
  • Axios
  • React Router
  • React Toastify

BACKEND

  • Node.js
  • Express.js
  • FastAPI
  • Socket.IO
  • JWT Authentication
  • Joi Validation

AI / ML

  • Python
  • OpenCV
  • Facial Landmark Detection
  • Image Processing
  • LLM APIs

DATABASE & CLOUD

  • MongoDB
  • AWS S3
  • Signed URL Uploads

DEPLOYMENT

  • Vercel
  • Render

BACKEND

  • Node.js
  • Express.js
  • FastAPI
  • Socket.IO
  • JWT Authentication
  • Joi Validation

AI / ML

  • Python
  • OpenCV
  • Facial Landmark Detection
  • Image Processing
  • LLM APIs

DATABASE & CLOUD

  • MongoDB
  • AWS S3
  • Signed URL Uploads

DEPLOYMENT

  • Vercel
  • Render

📁 Folder Structure

ANGELIC/
│
├── frontend/
│   ├── components/
│   ├── pages/
│   ├── services/
│   ├── context/
│   └── utils/
│
├── backend/
│   │
│   ├── node/
│   │   ├── routes/
│   │   ├── middleware/
│   │   ├── validators/
│   │   └── utils/
│   │
│   └── python/
│       ├── routes/
│       ├── ML/
│       └── services/
│
└── README.md

🔐 SECURITY & BACKEND ENGINEERING

Implemented production-style backend security practices:

  • JWT Authentication
  • Protected Routes
  • Request Validation
  • Rate Limiting
  • Secure AWS S3 Signed URLs
  • Input Sanitization
  • Error Handling Middleware
  • Secure API Architecture

⚙ INSTALLATION & SETUP

1️⃣ Clone Repository

git clone https://github.com/Vivek-DK/angelic.git

2️⃣ Install Frontend

cd frontend

npm install

npm run dev

3️⃣ Install Node Backend

cd backend/node

npm install

npm run dev

4️⃣ Install Python Backend

cd backend/python

python -m venv venv

venv\Scripts\activate

pip install -r requirements.txt

uvicorn main:app --reload

🔑 ENVIRONMENT VARIABLES

FRONTEND (.env)

VITE_NODE_API_URL=

VITE_PYTHON_API_URL=

NODE BACKEND (.env)

PORT=

MONGO_URI=

JWT_SECRET=

AWS_ACCESS_KEY_ID=

AWS_SECRET_ACCESS_KEY=

AWS_REGION=

AWS_BUCKET_NAME=

PYTHON BACKEND (.env)

OPENROUTER_API_KEY=

📈 ENGINEERING HIGHLIGHTS

FULL STACK ENGINEERING

  • React + Node.js + FastAPI Integration
  • REST API Architecture
  • Microservice-Based Backend Design
  • Secure Authentication System
  • Cloud-Based Image Storage

PERFORMANCE OPTIMIZATION

  • Browser-Side Image Compression
  • Reduced Upload Payload Size
  • Optimized API Processing Flow
  • Faster Upload & Analysis Experience

REAL-TIME SYSTEMS

  • WebSocket Integration
  • Live Notifications
  • Interactive UI Updates
  • Real-Time User Communication

AI INTEGRATION

  • Fashion-Focused AI Chatbot
  • Facial Analysis Pipeline
  • Personalized Recommendation Engine
  • Skin Tone & Face Shape Detection

🧪 FUTURE IMPROVEMENTS

  • Virtual Outfit Try-On
  • AI Hairstyle Preview
  • Fashion Recommendation Feed
  • Multi-Image Comparison
  • Personalized Wardrobe Planner
  • Recommendation Analytics
  • Mobile Application Support

👨‍💻 DEVELOPER

Vivek D K

Full Stack Developer focused on:

  • Scalable Backend Systems
  • AI-Integrated Applications
  • Cloud-Based Architectures
  • Modern Frontend Engineering
  • Real-Time Web Applications

CONNECT

LinkedIn

https://linkedin.com/in/vivekdk1310

GitHub

https://github.com/Vivek-DK

⭐ FINAL NOTE

ANGELIC is not just a UI-based fashion website.

It is a complete AI-integrated engineering project combining:

  • Machine Learning
  • Cloud Infrastructure
  • Real-Time Systems
  • Full Stack Development
  • Scalable Architecture
  • AI-Based Recommendation Systems

into a production-style application experience.

About

Full-stack AI styling assistant that analyzes facial landmarks and skin tone from user images to deliver personalized fashion, color palette, and grooming recommendations.

angelic-viv.vercel.app/

Topics

nodejs machine-learning ai computer-vision mongodb reactjs facial-recognition fullstack fastapi skin-tone-detection face-shape-detection

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