PHP operates camera for emotion recognition: analysis from expression to emotion

PHP Operates Camera for Emotion Recognition: Analysis from Expression to Emotion

Cameras have become a common presence in our lives, and the recognition of human emotions has always been a challenging task. However, with the development of artificial intelligence, emotion recognition through cameras has become possible. This article will introduce how to use PHP language to operate the camera and analyze people's emotions through expression analysis.

Before we begin, we need to ensure that the appropriate camera driver and PHP function library are installed on our server. This can be achieved by running the appropriate installation command in the terminal. In this article, we use Linux system and V4L2 camera driver.

1. Preparation

First, we need to use the PHP GD library for image processing. Enter the following command in the terminal to install the PHP GD library:

sudo apt-get install php7.4-gd

Next, we need to install the V4L2 driver. Enter the following command in the terminal to install the required libraries:

sudo apt-get install v4l-utils

2. Obtain the camera video stream

First, we need to use PHP's shell_exec function to execute the shell command to obtain the real-time video of the camera flow. This can be achieved by the following code:

<?php
function getVideoStream() {
    $cmd = "ffmpeg -i /dev/video0 -vf fps=1 -s 1280x720 -f image2 -frames 1 /path/to/image.jpg";
    shell_exec($cmd);
    return "/path/to/image.jpg";
}

$videoStream = getVideoStream();
echo "<img src='$videoStream'>";
?>

In this code, we use the FFmpeg command to capture the video stream of the camera and save it as an image file. We then use the img tag to display that image on the page.

3. Emotion recognition and expression analysis

Next, we need to use expression analysis algorithms to analyze images and infer people's emotions. In this article, we use an open source emotion recognition library and model called Fer2013.

We can integrate the Fer2013 library into our PHP script with the following code:

<?php
function getEmotion($imagePath) {
    $modelPath = "path/to/Fer2013/model.hdf5";
    $cmd = "python3 scripts/emotion_classification.py $modelPath $imagePath";
    $emotion = shell_exec($cmd);
    return $emotion;
}

$emotion = getEmotion($videoStream);
echo "当前的情绪： $emotion";
?>

In this code, we pass the path of the image as a parameter to the getEmotion function and execute python script to call the Fer2013 library for emotion recognition. The returned sentiment results will be displayed on the screen.

4. Complete example

The following is a complete example that shows how to use PHP to operate the camera for emotion recognition:

<?php
function getVideoStream() {
    $cmd = "ffmpeg -i /dev/video0 -vf fps=1 -s 1280x720 -f image2 -frames 1 /path/to/image.jpg";
    shell_exec($cmd);
    return "/path/to/image.jpg";
}

function getEmotion($imagePath) {
    $modelPath = "path/to/Fer2013/model.hdf5";
    $cmd = "python3 scripts/emotion_classification.py $modelPath $imagePath";
    $emotion = shell_exec($cmd);
    return $emotion;
}

$videoStream = getVideoStream();
$emotion = getEmotion($videoStream);

echo "<img src='$videoStream'>";
echo "当前的情绪：$emotion";
?>

By running this example, we can Real-time camera video streams are obtained on the web page, and emotion recognition is performed on the images to infer people's emotions.

Conclusion

Through this article, we learned how to use PHP to operate the camera and analyze people's emotions through expression analysis. Although this is just a simple example, it provides us with an entry-level guide to help us start applying camera emotion recognition technology in our own projects. Hope this article is helpful to everyone!

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