HueYou - Your Personal Color Analyst

HueYou is a web application that analyzes your skin tone, hair color, and eye color to determine your seasonal color palette (Spring, Summer, Autumn, Winter). It provides personalized recommendations for makeup, clothing, and accessories, along with a comprehensive PDF report. The frontend features a catchy lavender/pink design, and the backend uses Python 3.10.11 with Flask and MediaPipe.

Features

• Photo upload for AI-based color analysis
• Seasonal palette determination
• Detailed recommendations for makeup, clothing, and accessories
• Comprehensive PDF report download
• Overlay view for color visualization
• Catchy lavender/pink frontend design

Project Structure

HueYou/
├── backend/
│   ├── main.py              # Flask backend
│   ├── hueyou_utils.py      # Color analysis logic
│   ├── requirements.txt     # Python dependencies
│   └── Uploads/            # Image uploads (excluded)
├── frontend/
│   ├── src/
│   │   ├── App.js          # React frontend
│   │   ├── App.css         # Frontend styles
│   │   ├── components/
│   │   │   ├── ColorBox.js
│   │   │   └── ColorBox.css
│   │   └── index.js
│   ├── public/
│   │   └── index.html
│   ├── .env                # Environment variables
│   └── package.json        # Node.js dependencies
├── setup.bat               # Windows setup script
└── .gitignore

Setup Instructions

Prerequisites

• Python 3.10.11
• Node.js 16+ and npm
• Git

Backend Setup

cd backend
python -m venv venv
venv\Scripts\activate
pip install -r requirements.txt
python main.py

Frontend Setup

cd frontend
npm install
npm start

Running the App

1. Start the backend (python main.py).
2. Start the frontend (npm start).
3. Open http://localhost:3000 in a browser.
4. Upload a clear, front-facing face image (JPG/PNG, well-lit, 500x500+ pixels).
5. View your color profile, recommendations, and download the PDF report.

Dependencies

• Backend: Flask, MediaPipe, reportlab, numpy, opencv-python
• Frontend: React, axios

Notes

• Ensure exceptions for http://localhost:5000, http://localhost:3000, and project files in any security software (e.g., Norton).
• Use high-quality images for accurate analysis.