Smart Mirror AR Fashion Assistant Welcome to Smart Mirror AR Fashion Assistant – an advanced augmented reality (AR) application that merges computer vision, 3D rendering, and AI-driven emotion detection to create a virtual try-on experience.

🌟 Overview The Smart Mirror offers:

Real-time emotion detection through facial expression analysis. AR overlays of fashion items (crowns, glasses, shirts) on live video. Voice compliments based on mood detection. Hand-tracking for seamless interaction with virtual fashion accessories. Daily goal tracking with a modern, gamified UI. This project transforms the retail experience by providing an interactive way to try on outfits and receive personalized fashion advice.

🎯 Key Features

1. Real-time Emotion Detection Detects emotions (happy, sad, neutral, angry) through the webcam. Offers personalized voice compliments and fashion advice.
2. AR Fashion Try-On Overlay 3D models of fashion accessories on your reflection. Accurately tracks hand movements to adjust the position of accessories.
3. Interactive UI/UX Clean and responsive design using Tailwind CSS. Intuitive controls for selecting fashion items and interacting with AR elements.
4. Voice Interaction AI-powered compliments and suggestions via pyttsx3. Real-time voice feedback enhances the user experience.
5. Daily Goal Management Track daily tasks within the mirror interface. Visual progress with checklists and animations.

🛠️ Tech Stack Frontend: Next.js 15.1.2 – Core framework. React Three Fiber – 3D rendering library. Tailwind CSS – Styling and layout. Lucide React – Icon set.

Backend:

Project Setup: Emotion Detection App (FER, Flask, MoviePy, TensorFlow)

1. Prerequisites: Python 3.11 or 3.12 pyenv or Homebrew (for managing Python versions) (creating virtual environment) Git (for cloning repositories) Virtual environment (venv)
2. Setting Up the Project: Step 1: Create the Project Directory bash Copy code mkdir ReflectAI cd ReflectAI Step 2: Set Up a Virtual Environment bash Copy code python -m venv venv source venv/bin/activate # MacOS/Linux

.\venv\Scripts\activate # Windows

Step 3: Install Required Packages (Add to requirements.txt) Create a requirements.txt:

text Copy code opencv-python-headless numpy fer pyttsx3 Flask flask-cors tensorflow Install from the file:

bash Copy code pip install -r requirements.txt 3. Addressing Common Issues: MoviePy Missing or Errors:

pip install moviepy==1.0.3 #If moviepy.editor is missing:

pip uninstall moviepy pip install moviepy #TensorFlow Installation (if missing):

pip install tensorflow

pip install tensorflow-macos

pip install --upgrade numpy h5py

🚀 How It Works Webcam Activation – The app initializes facial expression tracking. Emotion Analysis – The app detects emotions and responds with voice feedback. AR Accessory Overlay – Selected fashion items are rendered in 3D. Hand Tracking – Position AR items by moving your hand in the video feed. Goal Management – Track and complete daily goals directly on the smart mirror interface.

📸 Screenshots Live AR Fashion Try-On – Real-time accessory fitting. Emotion-Based Compliments – Mood-driven visual and verbal feedback. Goal Tracker – Mark tasks as complete interactively.

🏗️ Installation Requirements: Python 3.8+ Node.js 18.3+ npm or yarn Setup: bash Copy code

Clone the project

git clone https://github.com/yourusername/smart-mirror-ar.git
cd smart-mirror-ar

Frontend Setup

cd frontend
npm install
npm run dev

Backend Setup

cd backend
pip install -r requirements.txt
python app.py

📖 Usage Start the Flask server to enable emotion detection. Launch the frontend via Next.js. Position yourself in front of the webcam to interact with virtual fashion items.

📈 Future Enhancements Expanded AR Wardrobe – More outfits and accessories. Enhanced Emotion Data – Detect more nuanced emotions. E-commerce Integration – Directly purchase tried-on items. Virtual Closet – Save previously tried outfits.

🧑‍💻 Contributing Want to improve the project? Contributions are welcome!

Report bugs or submit feature requests. Fork the project and submit pull requests. 📄 License This project is licensed under the MIT License.

🙌 Acknowledgements TensorFlow – Emotion detection models. Three.js – 3D rendering engine. Flask – Lightweight and fast backend.

📞 Contact Author: Sauhard Gupta Email: [Your Email] GitHub: https://github.com/Sauhard74