How to Create a Face Recognition App with React and Face API

In this tutorial, we will learn how to create a face recognition app using React and the Face API. Face recognition is a technology that can identify and verify the identity of a person based on their unique facial features. The Face API is a powerful library that provides various convenient methods for implementing face recognition in your applications.

By the end of this tutorial, you will have a basic understanding of how face recognition works and how to implement it in a React application using the Face API.

Prerequisites

To follow this tutorial, you will need:

Basic knowledge of JavaScript and React
A code editor of your choice
Node.js and npm installed on your machine

Setting up the React Application

Let’s start by creating a new React application. Open your terminal and run the following command:

npx create-react-app face-recognition-app

This will create a new directory called face-recognition-app with all the necessary files for a basic React application.

Now, navigate to the newly created directory:

cd face-recognition-app

To start the React development server, run the following command:

npm start

You should see the default React application running at `http://localhost:3000`.

Installing Dependencies

The next step is to install the necessary dependencies for our face recognition app. We will need the face-api.js library to perform face recognition tasks. Run the following command to install it:

npm install face-api.js

This will install the face-api.js library in our application.

Loading Face API Models

Before we can start using the Face API, we need to load the necessary face detection and face recognition models. Create a new folder called models inside the public folder, and download the following models into the models folder:

To download these files, right-click on each link and select “Save link as…”. Place the downloaded files into the models folder.

Creating the FaceRecognition Component

Now, let’s create a new React component called FaceRecognition that will handle the face recognition functionality in our application.

Create a new file called FaceRecognition.js inside the src folder and add the following code:

import React, { useEffect, useRef } from 'react';
import * as faceapi from 'face-api.js';

const FaceRecognition = () => {
  const videoRef = useRef(null);

  useEffect(() => {
    const loadModels = async () => {
      await faceapi.nets.tinyFaceDetector.loadFromUri('/models');
      await faceapi.nets.faceLandmark68Net.loadFromUri('/models');
      await faceapi.nets.faceRecognitionNet.loadFromUri('/models');
    };

    loadModels();
  }, []);

  useEffect(() => {
    const startCamera = async () => {
      const video = videoRef.current;

      if (navigator.mediaDevices.getUserMedia) {
        await navigator.mediaDevices.getUserMedia({ video: true })
          .then((stream) => {
            video.srcObject = stream;
          })
          .catch((error) => console.error('Error accessing camera:', error));
      }
    };

    startCamera();
  }, []);

  return (
    <div>
      <video ref={videoRef} autoPlay muted />
    </div>
  );
};

export default FaceRecognition;

In the code above, we import the necessary dependencies and create a functional component called FaceRecognition. Inside this component, we define two useEffect hooks. The first hook is responsible for loading the face detection, face landmark, and face recognition models from the models folder. The second hook starts the camera and displays the video stream on the page.

We also create a videoRef using the useRef hook, which is used to reference the video element in the JSX code.

Finally, we render a video element with the ref attribute set to the videoRef variable.

Adding the FaceRecognition Component to App.js

Now that we have created the FaceRecognition component, let’s include it in the main App.js file.

Open the src/App.js file and replace the existing code with the following:

import React from 'react';
import FaceRecognition from './FaceRecognition';

const App = () => {
  return (
    <div className="App">
      <h1>Face Recognition App</h1>
      <FaceRecognition />
    </div>
  );
};

export default App;

In the code above, we import the FaceRecognition component and render it inside the main App component.

Now, if you go back to your browser and refresh the page, you should see the “Face Recognition App” title and a video stream from your camera.

Detecting Faces

The next step is to detect faces in the video stream and draw bounding boxes around them.

Add the following code inside the loadModels function in the FaceRecognition component:

await faceapi.nets.tinyFaceDetector.loadFromUri('/models');
await faceapi.nets.faceLandmark68Net.loadFromUri('/models');
await faceapi.nets.faceRecognitionNet.loadFromUri('/models');

This code loads the required face detection, face landmark, and face recognition models from the models folder.

Next, add the following code inside the startCamera function:

const canvas = faceapi.createCanvasFromMedia(video);
document.body.append(canvas);

const displaySize = {
  width: video.width,
  height: video.height,
};
faceapi.matchDimensions(canvas, displaySize);

setInterval(async () => {
  const detections = await faceapi.detectAllFaces(video, new faceapi.TinyFaceDetectorOptions()).withFaceLandmarks().withFaceDescriptors();
  const resizedDetections = faceapi.resizeResults(detections, displaySize);

  canvas.getContext('2d').clearRect(0, 0, canvas.width, canvas.height);
  faceapi.draw.drawDetections(canvas, resizedDetections);
  faceapi.draw.drawFaceLandmarks(canvas, resizedDetections);
}, 100);

This code creates a new canvas element dynamically and appends it to the document.body. It also sets up the display size of the canvas based on the width and height of the video stream.

Inside the setInterval function, we use the faceapi.detectAllFaces method to detect faces in the video stream using the TinyFaceDetector. We also use the withFaceLandmarks and withFaceDescriptors options to get additional information about the detected faces.

We then resize the detection results based on the display size and draw bounding boxes around the detected faces using the drawDetections and drawFaceLandmarks methods.

Finally, we clear the canvas on each iteration to remove the previously drawn bounding boxes.

Conclusion

In this tutorial, we learned how to create a face recognition app using React and the Face API. We loaded the necessary face detection, face landmark, and face recognition models, started the camera, and detected faces in the video stream.

You can further enhance the app by adding features like face recognition and displaying the names of recognized faces. The Face API provides various methods to achieve these functionalities.

Feel free to experiment with different face recognition features and explore the capabilities of the Face API.

Happy coding!