由于使用php来写图片主色调识别功能太麻烦了，所以我给大家介绍利用利用k-means聚类算法识别图片主色调方法，比php要己100倍哦。
识别图片主色调这个，网上貌似有几种方法，不过，最准确，最优雅的解决方案还是利用聚类算法来做。。。
直接上代码。。。。不过，我测试结果表示，用PHP来做，效率不佳，PHP不适合做这种大规模运算~~~，用nodejs做 效率可以高出100倍左右。。。
代码如下复制代码$start = microtime(TRUE);main();立即学习“PHP免费学习笔记（深入）”；function main($img = ‘colors_files/T1OX3eXldXXXcqfYM._111424.jpg’){list($width, $height, $mime_code) = getimagesize($img);$im = null;$point = array();switch ($mime_code){# jpgcase 2:$im =imagecreatefromjpeg($img);break;# pngcase 3:default:exit(‘擦 ，什么图像？解析不了啊’);}$new_width = 100;$new_height = 100;$pixel = imagecreatetruecolor($new_width, $new_height);imagecopyresampled($pixel, $im, 0, 0, 0, 0, $new_width, $new_height, $width, $height);run_time();$i = $new_width;while ($i–){# reset高度$k = $new_height;while ($k–){$rgb = ImageColorAt($im, $i, $k);array_push($point, array(‘r’=>($rgb >> 16) & 0xFF, ‘g’=>($rgb >> 8) & 0xFF, ‘b’=>$rgb & 0xFF));}}imagedestroy($im);imagedestroy($pixel);run_time();$color = kmeans($point);run_time();foreach ($color as $key => $value) {echo ‘’ . RGBToHex($value[0]) . ‘’;}}function run_time(){global $start;echo ‘消耗:’, microtime(TRUE) – $start;}function kmeans($point=array(), $k=3, $min_diff=1){global $ii;$point_len = count($point);$clusters = array();$cache = array();for ($i=0; $i{$cache[$i] = $i*$i;}# 随机生成k值$i = $k;$index = 0;while ($i–){$index = mt_rand(1,$point_len-100);array_push($clusters, array($point[$index], array($point[$index])));}run_time();$point_list = array();$run_num = 0;while (TRUE){foreach ($point as $value){$smallest_distance = 10000000;# 求出距离最小的点# index用于保存point最靠近的k值$index = 0;$i = $k;while ($i–){$distance = 0;foreach ($value as $key => $p1){ if ($p1 > $clusters[$i][0][$key]){$distance += $cache[$p1 - $clusters[$i][0][$key]];PHP 8.5.5PHP 8.5.5 是 PHP 8.5 分支的维护更新版本。该版本延续了“小步快跑”的迭代逻辑，通过深度错误修复、底层性能微调以及安全加固，旨在为开发者提供一个更健壮、更高效的运行环境。该版本严格遵守语义化版本规范，不包含破坏性变更。下载}else{$distance += $cache[$clusters[$i][0][$key] – $p1];}}$ii++;if ($distance{$smallest_distance = $distance;$index = $i;}}$point_list[$index][] = $value;}$diff = 0;# 1个1个迭代k值$i = $k;while ($i–){$old = $clusters[$i];# 移到到队列中心$center = calculateCenter($point_list[$i], 3);# 形成新的k值集合队列$new_cluster = array($center, $point_list[$i]);$clusters[$i] = $new_cluster;# 计算新的k值与队列所在点的位置$diff = euclidean($old[0], $center);}# 判断是否已足够聚合if ($diff{break;>}}echo ‘—>’.$ii;return $clusters;}# 计算2点距离$ii = 0;function euclidean($p1, $p2){$s = 0;foreach ($p1 as $key => $value){$temp = ($value – $p2[$key]);$s += $temp*$temp;}return sqrt($s);}# 移动k值到所有点的中心function calculateCenter($point_list, $attr_num) {$vals = array();$point_num = 0;$keys = array_keys($point_list[0]);foreach($keys as $value){$vals[$value] = 0;}foreach ($point_list as $arr){$point_num++;foreach ($arr as $key => $value){$vals[$key] += $value;}}foreach ($keys as $index){$vals[$index] = $vals[$index] / $point_num;}return $vals;}function RGBToHex($r, $g=”, $b=”){if (is_array($r)){$b = $r['b'];$g = $r['g'];$r = $r['r'];}$hex = “#”;$hex.= str_pad(dechex($r), 2, ’0′, STR_PAD_LEFT);$hex.= str_pad(dechex($g), 2, ’0′, STR_PAD_LEFT);$hex.= str_pad(dechex($b), 2, ’0′, STR_PAD_LEFT);return $hex;}?>http://www.bkjia.com/PHPjc/444594.html www.bkjia.com true http://www.bkjia.com/PHPjc/444594.html TechArticle由于使用php来写图片主色调识别功能太麻烦了，所以我给大家介绍利用利用k-means聚类算法识别图片主色调方法，比php要己100倍哦。 识别图片...