💇 Legend Cut - Virtual Hair Salon

Legend Cut is a cutting-edge virtual hair try-on application that uses computer vision to let you experiment with different hairstyles in real-time through your camera.

Features

• Real-time Face Detection - Powered by MediaPipe for accurate facial landmark tracking
• Gender-based Style Selection - Separate collections for male and female hairstyles
• Live Camera Integration - Try on hairstyles instantly with your webcam
• Custom Uploads - Upload your own hairstyle images
• Adjustment Controls - Fine-tune position, size, and rotation of hairstyles
• Photo Capture - Save your favorite looks
• Head Pose Estimation - Hairstyles automatically adjust to head movements
• Responsive Design - Works on desktop and mobile devices

Quick Start

Prerequisites

• Python 3.8 or higher
• Webcam (for live try-on)
• Modern web browser (Chrome, Firefox, Safari, Edge)

Installation

1. Clone the repository

git clone https://github.com/yourusername/legend-cut.git
cd legend-cut   

2. Create virtual environment(optional but recommended)

python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

3. Install dependences

pip install -r requirements.txt

4. Add hairstyle images

• Place male hairstyles in app/static/haircuts/male/

• Place female hairstyles in app/static/haircuts/female/

• Use PNG format with transparent backgrounds for best results

5. Run the application

python legendrun.py

6. Open your browser

• Navigate to http://localhost:8000
• Allow camera access when prompted

Project Structure

Legend Cut/ ├── app/ │ ├── main.py # FastAPI application │ ├── templates/ # HTML templates │ ├── static/ # Static files (CSS, JS, images) │ │ ├── css/ # Stylesheets │ │ ├── js/ # JavaScript files │ │ └── haircuts/ # Hairstyle images │ │ ├── male/ # Male hairstyles │ │ ├── female/ # Female hairstyles │ │ └── custom/ # Uploaded hairstyles │ └── utils/ # Utility modules │ ├── face_utils.py # Face detection utilities │ └── hair_overlay.py # Hair overlay processing ├── requirements.txt # Python dependencies ├── run.py # Application entry point └── README.md # This file

How It Works

1. Face Detection - MediaPipe Face Mesh detects 468 facial landmarks
2. Head Pose Estimation- Calculates head rotation and position
3. Hair Region Detection - Identifies optimal area for hair placement
4. Haircut Transformation - Resizes and rotates hairstyle to match head pose
5. Alpha Blending- Seamlessly blends hairsytle with camera feed

API Endpoints

API Endpoints Endpoint || Method || Description / GET || Main ||application page /api/health || GET || Health check /api/haircuts/{gender} || GET || Get available hairstyles /api/upload-haircut || POST || Upload custom hairstyle /api/process-frame || POST || Process video frame /api/adjust-haircut || POST || Adjust hairstyle parameters /api/reset-session || POST || Reset user session

Adding Hairstyles

Image Requirements

• Format: PNG (preferred) or JPG

• Background: Transparent (PNG) or solid color

• Size: Minimum 300x300 pixels

• Style: Front-facing view recommended

Naming Convention

Use descriptive names with underscores:

• classic_pompadour.png

• modern_fade.png

• long_layered_cut.png

⚙️ Configuration

Edit in app/static/js/main.js:

javascript
video: {
    width: { ideal: 1280 },
    height: { ideal: 720 },
    facingMode: 'user'
}

Face Detection Sensitivity

Adjust in app/utils/face_utils.py:

python

self.face_mesh = self.mp_face_mesh.FaceMesh(
    min_detection_confidence=0.5,  # Lower = more sensitive
    min_tracking_confidence=0.5     # Lower = more sensitive
)

License

ACKNOWLEDGEMENT

• https://mediapipe.dev/ (MediaPipe for face detection)
• https://fastapi.tiangolo.com/ (FastAPI) for the web framework
• https://opencv.org/ (OpenCV) for image processing
• https://getbootstrap.com/ (Bootstrap for UI components)

📧 Contact

• Project Link: https://github.com/Martin-Chauke/legend-cut

• Report bugs: Issues

Happy Styling!

Transform your look with Legend Cut - Where Style Meets Technology!

Installation Instructions

1. Create the Legend Cut folder structure:

mkdir -p Legend\ Cut/app/static/haircuts/{male,female,custom}
mkdir -p Legend\ Cut/app/static/{css,js}
mkdir -p Legend\ Cut/app/templates
mkdir -p Legend\ Cut/app/utils

2. Copy all the provided files into their respective folders

3. Add some sample haircut images (PNG with transparent background) to:

• Legend Cut/app/static/haircuts/male/

• Legend Cut/app/static/haircuts/female/

4. Install dependences

cd "Legend Cut"
pip install -r requirements.txt

5. Run the application

python legendrun.py

6. OPEN YOUR BROWSER to ** http://localhost:8000 **