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Tutorial on Implementing Facial Expression Recognition in Images Using PHP and OpenCV

M66 2025-06-19

Introduction

Facial expression recognition is an important research area in computer vision, with wide applications in human-computer interaction, emotion monitoring, and more. In this article, we will show how to implement facial expression recognition in images using PHP and the OpenCV library, along with example code.

1. Preparation

Before we start, you need to prepare the following tools and environment.

1. Install OpenCV Library

OpenCV is an open-source computer vision library that provides numerous functions and classes for image processing and computer vision. To use OpenCV, you first need to install it on your system. The following command is for installing OpenCV on Ubuntu:

sudo apt-get install libopencv-dev

2. Install PHP Extension

To use the OpenCV library in PHP, you also need to install the OpenCV PHP extension. You can install it using the following command:

sudo apt-get install php7.4-opencv

3. Prepare Test Images

To test the facial expression recognition code, you need to prepare some images containing faces with different expressions. You can download such images from the internet and save them locally.

2. Writing the Code

Now we can start writing the facial expression recognition code. Below is a simple example code that detects faces in an image and recognizes their expressions:

<?php
// Import OpenCV and PHP extensions
use OpenCVHighgui{CV_LOAD_IMAGE_COLOR, imshow, waitKey};
use OpenCV{CascadeClassifier, Mat};

// Load the face detection model
$cascade = new CascadeClassifier();
$cascade->load('haarcascade_frontalface_default.xml');

// Load the expression recognition model
$recognizer = LBPHFaceRecognizer::create();
$recognizer->read('face_recognizer.yml');

// Expression labels
$labels = ['Angry', 'Happy', 'Neutral', 'Sad'];

// Load the test image
$image = imread('test_image.jpg', CV_LOAD_IMAGE_COLOR);

// Convert image to grayscale
$gray = cvtColor($image, CV_BGR2GRAY);

// Detect faces
$faces = [];
$cascade->detectMultiScale($gray, $faces);

// Recognize expressions for each detected face
foreach ($faces as $face) {
    // Extract the face region
    $roi = $gray->submat($face);

    // Resize the image
    $resized = resize($roi, new Mat(100, 100));

    // Predict the expression
    $label = 0;
    $confidence = 0;
    $recognizer->predict($resized, $label, $confidence);

    // Display the expression result
    rectangle($image, $face->x, $face->y, $face->x + $face->width, $face->y + $face->height, Scalar::all(255));
    putText($image, $labels[$label], new Point($face->x, $face->y - 20), FONT_HERSHEY_SIMPLEX, 0.8, Scalar::all(255));
}

// Display the image
imshow('Facial Expression Recognition', $image);
waitKey(0);
?>

3. Running the Code

After writing the code, you can run it using the following command:

php facial_expression_recognition.php

After running the script, you should see the detected faces in the image with their corresponding expressions labeled on them.

Conclusion

By using PHP and the OpenCV library, you can easily implement facial expression recognition in images. The example code provided in this article demonstrates how to detect faces and recognize expressions. You can extend and optimize the code based on your actual needs.

Note that the usage of libraries and classes in this example might vary with different versions. Please adapt the code according to the version you are using.

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