PHP calls the camera for real-time image processing: simple tutorial sharing

PHP calls the camera for real-time image processing: simple tutorial sharing

Real-time image processing of the camera is widely used in many scenarios, such as video surveillance, face recognition, image analysis, etc. For PHP developers, it is also feasible to achieve real-time image processing by calling the camera. This article will share a simple tutorial to teach you how to use PHP to call the camera for real-time image processing.

1. Install the corresponding software and driver
   To use PHP to call the camera, we need to install the corresponding software and driver first. In Windows systems, you can use the open source camera driver library OpenCV and the PHP plug-in php-opencv to achieve this. The specific installation steps are as follows:

1.1 Download and install OpenCV
You can go to the official website of OpenCV (https://opencv.org/) to download the latest version of OpenCV. Select the corresponding installation package according to your system, download and complete the installation.

1.2 Install the php-opencv plug-in
php-opencv is an extension plug-in for PHP developers to operate the OpenCV library. You can find the source code of the plug-in on GitHub (https://github.com/opencv/opencv_contrib), download it, compile and install it. The specific installation steps can be carried out according to the official documentation.

2. Calling the camera and displaying real-time images
   After installing the relevant software and drivers, we can start writing PHP code to call the camera and display real-time images.

<?php
$video = new VideoCapture(0); // 打开默认摄像头

while (true) {
    $frame = $video->read(); // 读取摄像头的图像帧

    if ($frame !== null) {
        $image = cvimencode(".bmp", $frame); // 对图像帧进行编码
        echo "<img  src="/static/imghwm/default1.png"  data-src="data:image/bmp;base64,"  class="lazy" . base64_encode($image) . ""/ alt="PHP calls the camera for real-time image processing: simple tutorial sharing" >"; // 显示图像
    }

    if (waitKey(1) >= 0) { // 按下任意键退出循环
        break;
    }
}

$video->release(); // 释放摄像头资源
?>

The above code uses the php-opencv plug-in to open the default camera and read the image frame of the camera by calling the VideoCapture class. The image frame is then encoded and the image is displayed in the browser via an echo statement. When any key is pressed, exit the loop and release the camera resources.

3. Real-time image processing
   In addition to displaying real-time images, we can also perform real-time processing on images. Taking face recognition as an example, we can use OpenCV's face recognition algorithm for real-time face detection.

<?php
$video = new VideoCapture(0); // 打开默认摄像头

$cascade = new CascadeClassifier('haarcascade_frontalface_default.xml'); // 加载人脸识别模型

while (true) {
    $frame = $video->read(); // 读取摄像头的图像帧

    if ($frame !== null) {
        $gray = cvcvtColor($frame, cvCOLOR_BGR2GRAY); // 将彩色图像转换为灰度图像
        cvequalizeHist($gray, $gray); // 直方图均衡化增强对比度

        $faces = $cascade->detectMultiScale($gray); // 人脸检测

        foreach ($faces as $face) {
            cvectangle($frame, $face, new Scalar(0, 255, 0)); // 绘制人脸矩形
        }

        $image = cvimencode(".bmp", $frame); // 对图像帧进行编码
        echo "<img  src="/static/imghwm/default1.png"  data-src="data:image/bmp;base64,"  class="lazy" . base64_encode($image) . ""/ alt="PHP calls the camera for real-time image processing: simple tutorial sharing" >"; // 显示图像
    }

    if (waitKey(1) >= 0) { // 按下任意键退出循环
        break;
    }
}

$video->release(); // 释放摄像头资源
?>

After reading the image frame from the camera, the above code first converts the color image into a grayscale image and uses histogram equalization to enhance the contrast. Then use the loaded face recognition model to perform face detection and draw the detected face rectangle. Finally, the image frames are encoded and displayed.

Through the above simple tutorial, we can use PHP to call the camera for real-time image processing. Of course, more complex algorithms and processing procedures may be required in actual applications, but this article provides an entry-level example, which I hope will be helpful to your learning of real-time image processing. If you are interested, you can further learn and explore more functions and interfaces provided by OpenCV and php-opencv.

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