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Home Backend Development PHP Tutorial PHP study notes: face recognition and image processing

PHP study notes: face recognition and image processing

Oct 08, 2023 am 11:33 AM
php face recognition Image Processing

PHP study notes: face recognition and image processing

PHP Study Notes: Face Recognition and Image Processing

Foreword:
With the development of artificial intelligence technology, face recognition and image processing have become popular topic. In practical applications, face recognition and image processing are mostly used in security monitoring, face unlocking, card comparison, etc. As a commonly used server-side scripting language, PHP can also be used to implement functions related to face recognition and image processing. This article will take you through face recognition and image processing in PHP, with specific code examples.

1. Face recognition in PHP
Face recognition is a technology that uses computer systems to extract and match features of face images. In PHP, we can use the OpenCV library combined with the Dlib library to implement the face recognition function.

  1. Install OpenCV and Dlib libraries
    Before using, we first need to install OpenCV and Dlib libraries. It can be installed using the command line or by compiling source code. For specific installation methods, please refer to relevant documents and tutorials.
  2. Write PHP code
    // Load OpenCV and Dlib libraries
    $opencvPath = '/path/to/opencv/library';
    $dlibPath = ' /path/to/dlib/library';
    extension_loaded('opencv') or dl(opencvPath . '/php_opencv.so');
    extension_loaded('dlib') or dl(dlibPath . '/php_dlib. so');

//Set the face recognition model path
$shapePredictorPath = '/path/to/shape_predictor_68_face_landmarks.dat';

// Load face recognition Model
$faceDetector = new DlibFrontalFaceDetector();
$shapePredictor = new DlibShapePredictor($shapePredictorPath);

// Load image file
$imageFile = '/path/to/image. jpg';
$image = DlibImageIo::load($imageFile);

// Detect faces
$faces = $faceDetector->detect($image);

// Extract feature points for each face
foreach ($faces as $faceRect) {

$landmarks = $shapePredictor->predict($image, $faceRect);
// 在人臉上繪制特征點(diǎn)
foreach ($landmarks->points as $point) {
    DlibImageDraw::circle($image, $point, 3);
}

}

// Save the modified image
$outputFile = '/path/to/output.jpg';
DlibImageIo::save($image, $outputFile);
?>

The above code demonstrates the use of PHP for face recognition The basic process includes steps such as loading libraries, setting model paths, loading images, detecting faces, extracting feature points, and saving images. By executing the above code, we can draw the feature points of the face on the picture to facilitate further processing.

2. Image processing in PHP
Image processing is a technology that performs operations such as enhancement, filtering, and transformation on images. In PHP, we can use the GD library or ImageMagick library to implement image processing functions. The following uses the GD library as an example to introduce how to implement common image processing functions.

  1. Install the GD library
    You can install the GD library through the package management tool or directly compile the source code. For specific installation methods, please refer to relevant documents and tutorials.
  2. Write PHP code
    // Load image file
    $imageFile = '/path/to/image.jpg';
    $image = imagecreatefromjpeg($ imageFile);

//Generate thumbnail image
$thumbWidth = 200;
$thumbHeight = 200;
$thumbImage = imagecreatetruecolor($thumbWidth, $thumbHeight);
imagecopyresampled($thumbImage, $image, 0, 0, 0, 0, $thumbWidth, $thumbHeight, imagesx($image), imagesy($image));
$thumbOutputFile = '/path/to/thumb. jpg';
imagejpeg($thumbImage, $thumbOutputFile);

//Adjust brightness and contrast
imagefilter($image, IMG_FILTER_BRIGHTNESS, -50);
imagefilter($image, IMG_FILTER_CONTRAST , -50);
$outputFile = '/path/to/output.jpg';
imagejpeg($image, $outputFile);
?>

The above code demonstrates The basic process of image processing using the GD library includes operations such as loading images, generating thumbnails, and adjusting brightness and contrast. By executing the above code, we can implement simple processing and transformation of images to meet actual needs.

Conclusion:
This article introduces the relevant content of face recognition and image processing in PHP, and is accompanied by specific code examples. By learning and mastering this knowledge, we can implement face recognition and image processing functions in PHP and provide technical support for practical applications. I hope this article will be helpful to you and enable you to make progress in learning and practice!

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