With the continuous development of artificial intelligence technology, image processing and face detection are becoming more and more widely used. PHP, as a server-side language, can also support these applications. This article will introduce you to how to implement intelligent image processing and face detection through PHP.
1. Intelligent image processing
High-definition pictures can provide a better visual experience, but they will also cause The size becomes very large, slowing down the page loading speed. PHP provides some image processing functions that can compress image size and reduce loading time.
For example, the ImageJPEG() function can output the image in jpeg format and control the output image compression ratio:
$source_image = imagecreatefromjpeg("test.jpg"); $destination_image = imagecreatetruecolor($new_width, $new_height); imagecopyresampled($destination_image, $source_image, 0, 0, 0, 0, $new_width, $new_height, $original_width, $original_height); imagejpeg($destination_image, null, $quality);
PHP also provides a series of image processing functions, such as rotation, cropping, adding watermarks, etc. These functions are more practical in web design.
For example, the ImageRotate() function can rotate an image to a certain angle:
$source_image = imagecreatefromjpeg("test.jpg"); $destination_image = imagerotate($source_image, $angle, 0); imagejpeg($destination_image, null, $quality);
Image recognition technology allows the computer to automatically rotate an image Analyze the main content of each picture and classify and identify it. In PHP, third-party APIs can be used to achieve image recognition, such as the Google Cloud Vision API, which can automatically classify, mark, describe, detect text, etc. based on the content in the image.
For example, the following code can call the Google Cloud Vision API to complete image recognition:
$client = new Google_Client(); $client->setApplicationName("AI Demo"); $client->setDeveloperKey("YOUR_DEVELOPER_KEY"); $service = new Google_Service_Vision($client); $image = file_get_contents('test.jpg', true); $request = new Google_Service_Vision_Image(); $request->setContent($image); $results = $service->images->annotate( $service->images->annotate(new Google_Service_Vision_AnnotateImageRequest( new Google_Service_Vision_Image(array('content' => base64_encode($image))), array('TEXT_DETECTION') ))->getResponses()[0] );
2. Face detection
With the popularity of smartphones and cameras, face detection Technology has also gradually been widely used. Some third-party libraries or APIs can also be used to implement face detection in PHP.
OpenCV is a cross-platform open source computer vision library. It can handle multimedia formats such as images and videos, as well as common computer vision problems such as face detection, object recognition, and image tracking. In PHP, functions such as face detection can be implemented by calling the OpenCV API.
For example, the following code can call OpenCV to implement face detection:
$face_cascade = new CascadeClassifier(); $face_cascade->load('haarcascade_frontalface_default.xml'); $src = imread('test.jpg'); $gray = cvtColor($src, COLOR_BGR2GRAY); $faces = new RectVector(); $face_cascade->detectMultiScale($gray, $faces); foreach ($faces as $face) { rectangle($src, $face->x, $face->y, $face->x + $face->width, $face->y + $face->height, Scalar::all(255)); } imwrite('result.jpg', $src);
Face is a face recognition, analysis and facial emotion Analysis API service. It can help developers quickly implement functions such as face detection, eyes, mouth, nose, and facial feature points.
For example, the following code can call the Face API to implement face detection:
$client = new GuzzleHttpClient(); $response = $client->request('POST', 'https://api-cn.faceplusplus.com/facepp/v3/detect', [ 'multipart' => [ [ 'name' => 'api_key', 'contents' => 'YOUR_API_KEY', ], [ 'name' => 'api_secret', 'contents' => 'YOUR_API_SECRET', ], [ 'name' => 'image_file', 'contents' => fopen('test.jpg', 'r'), 'filename' => 'test.jpg', ], [ 'name' => 'return_attributes', 'contents' => 'gender,age,smiling,emotion', ], ], ]); $json = json_decode($response->getBody(), true);
Conclusion
This article introduces intelligent image processing and face detection applications in PHP. We can easily implement these functions by using the functions provided by PHP, third-party APIs or open source libraries. Of course, there is still a lot of room for improvement in these applications. We can continue to try new technologies to discover more valuable application scenarios.
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