face-mesh-project

This project implements a real-time facial landmark detection system using OpenCV and MediaPipe in Python. It leverages MediaPipe's face mesh solution to identify and track 468 facial landmarks, providing a detailed 3D representation of the face. OpenCV is used for capturing video input and rendering the detected landmarks.

Features

• Detailed Facial Landmark Detection: Tracks 468 facial landmarks for a comprehensive 3D representation.
• Real-Time Performance: Efficient algorithms ensure smooth and real-time processing.
• Versatility: Applicable in augmented reality, facial recognition, expression analysis, and more.

Installation

1. Clone the repository:

   git clone https://github.com/CyberBoy-Mayank/face-mesh-project.git
   cd face-mesh-project

2. Install the required dependencies:

   -r requirements.txt

Usage

1. Run the face main script:

   python main.py

2. The script will start capturing video from your in-built webcam and display the detected facial landmarks in real-time.

Example Output

![Face Mesh Example]

Benefits

• High Precision: Detailed detection of 468 facial landmarks for an accurate 3D facial model.
• Real-Time Processing: Suitable for applications requiring live interaction and feedback.
• Easy Integration: Simple to incorporate into larger projects and adaptable for various use cases.
• Robust Performance: Effective under different lighting conditions and angles.

Note:

• I'm using Python Version: 3.10.2 for this project

Contributing

Contributions are welcome! Please open an issue or submit a pull request for any improvements or bug fixes.