使用PHP和coreseek实现智能化的图片搜索功能

<?php
// 载入OpenCV库
$opencv = new OpenCV();

// 读取图片
$image = $opencv->loadImage('example.jpg');

// 提取颜色直方图
$histogram = $opencv->calculateHistogram($image);

// 将直方图转换为特征向量
$featureVector = flatten($histogram);

// 存储特征向量到数据库或文件
saveFeatureVector($featureVector);
?>

<?php
// 计算余弦相似度
function cosineSimilarity($vector1, $vector2) {
    $dotProduct = dotProduct($vector1, $vector2);
    $magnitude1 = magnitude($vector1);
    $magnitude2 = magnitude($vector2);
    return $dotProduct / ($magnitude1 * $magnitude2);
}

// 计算向量的点积
function dotProduct($vector1, $vector2) {
    $result = 0;
    foreach ($vector1 as $key => $value) {
        $result += $value * $vector2[$key];
    }
    return $result;
}

// 计算向量的模长
function magnitude($vector) {
    $result = 0;
    foreach ($vector as $value) {
        $result += $value * $value;
    }
    return sqrt($result);
}

// 加载用户上传的图片
$userImage = loadImage($_FILES['image']);

// 提取用户上传图片的特征向量
$userFeatureVector = extractFeatureVector($userImage);

// 加载数据库中的图片特征向量
$databaseFeatureVectors = loadFeatureVectors();

// 计算所有图片特征向量与用户上传图片的相似度
$similarImages = array();
foreach ($databaseFeatureVectors as $featureVector) {
    $similarity = cosineSimilarity($featureVector, $userFeatureVector);
    if ($similarity > 0.8) {
        $similarImages[] = $featureVector;
    }
}
?>

<?php
// 初始化coreseek
$sphinx = new SphinxClient();
$sphinx->SetServer('localhost', 9312);

// 执行关键词搜索
$result = $sphinx->Query('keyword');

// 处理搜索结果
if ($result['total'] > 0) {
    $ids = array();
    foreach ($result['matches'] as $match) {
        $ids[] = $match['id'];
    }
    
    // 根据搜索结果的ID获取图片信息
    $images = getImagesByIds($ids);
    
    // 显示搜索结果
    foreach ($images as $image) {
        displayImage($image);
    }
} else {
    echo '未找到相关图片';
}
?>