Sphinx PHP high-performance search engine supports image search

Sphinx PHP high-performance search engine requires specific code examples to support image search

With the rapid development of the Internet, image search has become more and more important in our daily lives. more and more important. From product search on e-commerce websites to face recognition on social media platforms, image search has penetrated into various fields. To meet this need, Sphinx PHP high-performance search engine provides powerful image search capabilities. This article will focus on Sphinx PHP's image search support and provide specific code examples.

Sphinx is a high-performance open source search engine that supports full-text search, fuzzy search, distributed search and other functions. It can quickly and accurately retrieve the required results by using inverted index and Boolean search algorithm. For image search, Sphinx provides index types and query methods suitable for images to achieve efficient image search.

First, we need to create an image index. In Sphinx, image indexes are a special type of index that allow us to store and search image-related information. The following is a code example for creating an image index:

$cl = new SphinxClient();

$cl->SetServer("localhost", 9312);
$cl->SetConnectTimeout(3);
$cl->SetArrayResult(true);

$index = 'image_index';
$cl->AddIndex($index);

$cl->SetFieldWeights(array(
    'tags' => 10,
    'description' => 5,
));

$cl->SetMatchMode(SPH_MATCH_ANY);
$cl->SetSortMode(SPH_SORT_RELEVANCE);

$query = "cat";
$result = $cl->Query($query, $index);
if ($result !== false) {
    if ($cl->GetLastWarning()) {
        echo "Warning: " . $cl->GetLastWarning();
    }
    print_r($result['matches']);
} else {
    echo "Query failed: " . $cl->GetLastError();
}

In the above code, we first create a SphinxClient object and set the information to connect to the server. Then, we specified the index type we want to search as an image index, and set the field weight of the image index. Next, we set the matching mode and sorting mode. Finally, we enter the keywords we want to search for and call the Query method to perform the search. If the search is successful, we can get the search results through $result['matches'] and print them out.

In addition to the above code examples, Sphinx also provides some other useful functions, such as image filtering, image sorting, and image tags. The following is a code example that uses the image filtering function to perform image search:

$cl = new SphinxClient();

$cl->SetServer("localhost", 9312);
$cl->SetConnectTimeout(3);
$cl->SetArrayResult(true);

$index = 'image_index';
$cl->AddIndex($index);

$cl->SetFilter('size', array(500, 1000)); // 设置图片大小过滤条件

$query = "cat";
$result = $cl->Query($query, $index);
if ($result !== false) {
    if ($cl->GetLastWarning()) {
        echo "Warning: " . $cl->GetLastWarning();
    }
    print_r($result['matches']);
} else {
    echo "Query failed: " . $cl->GetLastError();
}

In the above code, we specify the filtering conditions for image size by calling the SetFilter method. This can filter out images that do not meet the requirements and only return image search results that meet the conditions.

In summary, Sphinx PHP's high-performance search engine has very powerful support for image search. We can use the rich functions it provides to easily implement image search. The above code examples only demonstrate some of the functions. You can flexibly apply them according to actual needs to meet the image search needs in different scenarios. Whether it is an e-commerce website, social media platform or other application, Sphinx PHP is a powerful tool that can help us achieve efficient and accurate image search.

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