Face Recognition with Age and Gender Detection

This project demonstrates real-time face detection, age estimation, and gender recognition using the face-api.js library. The application accesses the user's webcam and displays facial landmarks, expressions, as well as predicted age and gender directly on the video feed.

Features

• Real-time face detection using the Tiny Face Detector
• Face landmarks detection
• Facial expression recognition
• Age estimation
• Gender recognition

Installation

1. Clone the repository:

   git clone https://github.com/JSONParseError69/real-time-face-detection-app
   cd real-time-face-detection-app

2. Install the necessary dependencies:

• This project relies on face-api.js and basic HTML/CSS/JS files, so no additional dependencies are needed.

Download the models:

• Download the face-api.js models from here and place them in a /models directory in the root of your project.

Usage

1. Open the index.html file in your browser. You can do this by simply dragging and dropping the file into a browser window or by serving the file with a local server.

2. Allow camera access when prompted.

3. You should see your webcam feed with real-time age, gender, and expression detection.

Code Overview

• index.html: The main HTML file that sets up the video element and loads the necessary scripts.
• script.js: Contains the core logic for initializing the video stream and running the face-api.js detection.
• style.css: Basic styling for the webpage.

Key Code Sections

const detections = await faceapi
  .detectAllFaces(video, new faceapi.TinyFaceDetectorOptions())
  .withFaceLandmarks()
  .withFaceExpressions()
  .withAgeAndGender();

This snippet captures all face detections, landmarks, expressions, and age/gender information in real-time.

Contributing

Feel free to fork the repository and submit pull requests. Contributions are welcome!

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

• face-api.js - A powerful library for face detection and recognition.
• Inspiration and support from all the amazing developers who contribute to open source.