Method to realize content recognition and intelligent recommendation of pictures using PHP and Qiniu cloud storage interface

Method of using PHP and Qiniu cloud storage interface to realize image content recognition and intelligent recommendation

The rapid development of cloud computing and artificial intelligence provides more possibilities for image processing. Using Qiniu cloud storage interface, we can easily realize content identification and intelligent recommendation of pictures. This article will introduce how to use PHP to write code to achieve this function.

1. Introduction to Qiniu Cloud Storage

Qiniu Cloud Storage is the leading cloud storage platform in China, providing efficient and stable storage and distribution services. Its powerful functions and ease of use have become the cloud storage solution of choice for many developers.

2. Image content identification

1. Register a Qiniu developer account and obtain AK/SK

First, we need to register a Qiniu developer account, and obtain the Access Key and Secret Key, which will be used for authentication.

2. Installing related dependencies

We need to install the PHP SDK of Qiniu Cloud Storage for development. Execute the following command in the terminal to install the SDK:

composer require qiniu/php-sdk

3. Upload images and obtain recognition results

In the PHP code, we can use the API of Qiniu Cloud Storage to Upload images and perform content identification. The following is a simple example:

<?php
require 'vendor/autoload.php'; // 引入SDK

use QiniuAuth;
use QiniuStorageUploadManager;

$accessKey = 'YourAccessKey';
$secretKey = 'YourSecretKey';
$bucketName = 'YourBucketName';
$auth = new Auth($accessKey, $secretKey);
$uploadMgr = new UploadManager();

$filePath = '/path/to/your/image.png';
$key = "image.png"; // 上传到七牛云存储后的文件名

// 生成上传Token
$token = $auth->uploadToken($bucketName);

// 调用七牛云存储的API进行文件上传
list($ret, $err) = $uploadMgr->putFile($token, $key, $filePath);

if ($err !== null) {
    echo '上传失败：' . $err->message();
} else {
    $result = json_decode($ret, true);
    
    // 获取返回结果中的识别信息
    $label = $result['result'][0]['label'];
    
    // 进一步处理...
}
?>

In this code, we first introduced the Qiniu Cloud Storage SDK and set the relevant parameters, including Access Key, Secret Key, Bucket name, etc. Then, we use the UploadManager class to upload the image and obtain the returned recognition result.

3. Intelligent Recommendation

On the basis of realizing image content recognition, we can further use these recognition results to make intelligent recommendations. For example, we can recommend related products or articles based on the content of the image.

1. Data preparation

First, we need to prepare the relevant data. For example, for product recommendation, we can create a database table to store product information, including name, description, image address, etc.

2. Implementing recommendation algorithm

In PHP code, we can use the results of image content recognition to implement intelligent recommendations. The following is an example:

<?php
// ...

// 假设识别结果为标签数组
$labels = ['food', 'fruit'];

// 根据识别结果查询相关商品信息
$sql = "SELECT * FROM products WHERE label IN ('" . implode("', '", $labels) . "')";

// 执行查询

// 处理查询结果...

?>

In this example, we assume that the recognition result is a tag array, and then query related product information based on the recognition result. Finally, we can perform further processing based on the query results, such as displaying a list of recommended products, etc.

4. Summary

By using Qiniu cloud storage interface and code written in PHP, we can easily realize content recognition and intelligent recommendation of images. This gives us the opportunity to utilize image processing and artificial intelligence in our applications to improve user experience and business results. I hope this article can help everyone in their development work in image processing.

The above is the detailed content of Method to realize content recognition and intelligent recommendation of pictures using PHP and Qiniu cloud storage interface. For more information, please follow other related articles on the PHP Chinese website!