Facial Landmark Detection Application

A web-based application that detects and visualizes facial landmarks in images using dlib and OpenCV. The application provides a user-friendly interface for uploading images or capturing photos through a webcam to detect facial landmarks.

Features

• Upload images for facial landmark detection
• Real-time webcam capture and processing
• Detection of 68 facial landmarks
• Interactive user interface with dark theme
• Responsive design for various screen sizes
• Real-time processing status updates
• Support for multiple image formats

Technologies Used

• Backend:

  • FastAPI (Python web framework)
  • dlib (Facial landmark detection)
  • OpenCV (Image processing)
  • NumPy (Numerical computations)
  • Uvicorn (ASGI server)

• Frontend:

  • HTML5
  • CSS3
  • JavaScript
  • Bootstrap 5
  • Bootstrap Icons

Prerequisites

• Python 3.11 or higher
• Modern web browser with camera access (for webcam feature)

Installation

1. Clone the repository:

   git clone [repository-url]
   cd FaceLandmarkTracker

2. Install the required dependencies:

   pip install -r requirements.txt

3. The application will automatically download the required dlib facial landmark predictor model on first run.

Running the Application

1. Start the application:

   python main.py

2. Open your web browser and navigate to:

   http://localhost:5000
   

Usage

1. Upload an Image:

   • Click "Browse Files" or drag and drop an image
   • Click "Process Image" to detect facial landmarks

2. Use Webcam:

   • Click "Use Camera" to access your webcam
   • Click "Capture Photo" to take a picture
   • The captured image will be automatically processed

3. View Results:

   • The original image and processed image with facial landmarks will be displayed side by side
   • Green dots indicate detected facial landmarks
   • Click "Try Another Image" to start over

API Endpoints

• GET /: Main application interface
• POST /process-image/: Process uploaded images
• GET /health: Health check endpoint

License

[Add your license information here]

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

Acknowledgments

• dlib library for facial landmark detection
• OpenCV for image processing capabilities
• FastAPI for the web framework