A very useful piece of PHP code that will highlight any pictures where a face has been detected.

Heres the first piece of PHP code you will need, it would be best to make this an include:

class Face_Detector {

protected $detection_data;
protected $canvas;
protected $face;
private $reduced_canvas;

public function __construct($detection_file = 'detection.dat') {
if (is_file($detection_file)) {
$this->detection_data = unserialize(file_get_contents($detection_file));
} else {
throw new Exception("Couldn't load detection data");
}
//$this->detection_data = json_decode(file_get_contents('data.js'));
}

public function face_detect($file) {
if (!is_file($file)) {
throw new Exception("Can not load $file");
}

$this->canvas = imagecreatefromjpeg($file);
$im_width = imagesx($this->canvas);
$im_height = imagesy($this->canvas);

//Resample before detection?
$ratio = 0;
$diff_width = 320 - $im_width;
$diff_height = 240 - $im_height;
if ($diff_width > $diff_height) {
$ratio = $im_width / 320;
} else {
$ratio = $im_height / 240;
}

if ($ratio != 0) {
$this->reduced_canvas = imagecreatetruecolor($im_width / $ratio, $im_height / $ratio);
imagecopyresampled($this->reduced_canvas, $this->canvas, 0, 0, 0, 0, $im_width / $ratio, $im_height / $ratio, $im_width, $im_height);

$stats = $this->get_img_stats($this->reduced_canvas);
$this->face = $this->do_detect_greedy_big_to_small($stats['ii'], $stats['ii2'], $stats['width'], $stats['height']);
$this->face['x'] *= $ratio;
$this->face['y'] *= $ratio;
$this->face['w'] *= $ratio;
} else {
$stats = $this->get_img_stats($this->canvas);
$this->face = $this->do_detect_greedy_big_to_small($stats['ii'], $stats['ii2'], $stats['width'], $stats['height']);
}
return ($this->face['w'] > 0);
}

public function toJpeg() {
$color = imagecolorallocate($this->canvas, 255, 0, 0); //red
imagerectangle($this->canvas, $this->face['x'], $this->face['y'], $this->face['x']+$this->face['w'], $this->face['y']+ $this->face['w'], $color);
header('Content-type: image/jpeg');
imagejpeg($this->canvas);
}

public function toJson() {
return "{'x':" . $this->face['x'] . ", 'y':" . $this->face['y'] . ", 'w':" . $this->face['w'] . "}";
}

public function getFace() {
return $this->face;
}

protected function get_img_stats($canvas){
$image_width = imagesx($canvas);
$image_height = imagesy($canvas);
$iis =  $this->compute_ii($canvas, $image_width, $image_height);
return array(
'width' => $image_width,
'height' => $image_height,
'ii' => $iis['ii'],
'ii2' => $iis['ii2']
);
}

protected function compute_ii($canvas, $image_width, $image_height ){
$ii_w = $image_width+1;
$ii_h = $image_height+1;
$ii = array();
$ii2 = array();

for($i=0; $i<$ii_w; $i++ ){
$ii[$i] = 0;
$ii2[$i] = 0;
}

for($i=1; $i<$ii_w; $i++ ){
$ii[$i*$ii_w] = 0;
$ii2[$i*$ii_w] = 0;
$rowsum = 0;
$rowsum2 = 0;
for($j=1; $j<$ii_h; $j++ ){                 $rgb = ImageColorAt($canvas, $j, $i);                 $red = ($rgb >> 16) &amp;amp; 0xFF;
$green = ($rgb >>  &amp;amp; 0xFF;
$blue = $rgb &amp;amp; 0xFF;
$grey = ( 0.2989*$red + 0.587*$green + 0.114*$blue )>>0;  // this is what matlab uses
$rowsum += $grey;
$rowsum2 += $grey*$grey;

$ii_above = ($i-1)*$ii_w + $j;
$ii_this = $i*$ii_w + $j;

$ii[$ii_this] = $ii[$ii_above] + $rowsum;
$ii2[$ii_this] = $ii2[$ii_above] + $rowsum2;
}
}
return array('ii'=>$ii, 'ii2' => $ii2);
}

protected function do_detect_greedy_big_to_small( $ii, $ii2, $width, $height ){
$s_w = $width/20.0;
$s_h = $height/20.0;
$start_scale = $s_h < $s_w ? $s_h : $s_w;         $scale_update = 1 / 1.2;         for($scale = $start_scale; $scale > 1; $scale *= $scale_update ){
$w = (20*$scale) >> 0;
$endx = $width - $w - 1;
$endy = $height - $w - 1;
$step = max( $scale, 2 ) >> 0;
$inv_area = 1 / ($w*$w);
for($y = 0; $y < $endy ; $y += $step ){
for($x = 0; $x < $endx ; $x += $step ){                     $passed = $this->detect_on_sub_image( $x, $y, $scale, $ii, $ii2, $w, $width+1, $inv_area);
if( $passed ) {
return array('x'=>$x, 'y'=>$y, 'w'=>$w);
}
} // end x
} // end y
}  // end scale
return null;
}

protected function detect_on_sub_image( $x, $y, $scale, $ii, $ii2, $w, $iiw, $inv_area){
$mean = ( $ii[($y+$w)*$iiw + $x + $w] + $ii[$y*$iiw+$x] - $ii[($y+$w)*$iiw+$x] - $ii[$y*$iiw+$x+$w]  )*$inv_area;
$vnorm =  ( $ii2[($y+$w)*$iiw + $x + $w] + $ii2[$y*$iiw+$x] - $ii2[($y+$w)*$iiw+$x] - $ii2[$y*$iiw+$x+$w]  )*$inv_area - ($mean*$mean);
$vnorm = $vnorm > 1 ? sqrt($vnorm) : 1;

$passed = true;
for($i_stage = 0; $i_stage < count($this->detection_data); $i_stage++ ){
$stage = $this->detection_data[$i_stage];
$trees = $stage[0];

$stage_thresh = $stage[1];
$stage_sum = 0;

for($i_tree = 0; $i_tree < count($trees); $i_tree++ ){
$tree = $trees[$i_tree];
$current_node = $tree[0];
$tree_sum = 0;
while( $current_node != null ){
$vals = $current_node[0];
$node_thresh = $vals[0];
$leftval = $vals[1];
$rightval = $vals[2];
$leftidx = $vals[3];
$rightidx = $vals[4];
$rects = $current_node[1];

$rect_sum = 0;
for( $i_rect = 0; $i_rect < count($rects); $i_rect++ ){                         $s = $scale;                         $rect = $rects[$i_rect];                         $rx = ($rect[0]*$s+$x)>>0;
$ry = ($rect[1]*$s+$y)>>0;
$rw = ($rect[2]*$s)>>0;
$rh = ($rect[3]*$s)>>0;
$wt = $rect[4];

$r_sum = ( $ii[($ry+$rh)*$iiw + $rx + $rw] + $ii[$ry*$iiw+$rx] - $ii[($ry+$rh)*$iiw+$rx] - $ii[$ry*$iiw+$rx+$rw] )*$wt;
$rect_sum += $r_sum;
}

$rect_sum *= $inv_area;

$current_node = null;
if( $rect_sum >= $node_thresh*$vnorm ){
if( $rightidx == -1 )
$tree_sum = $rightval;
else
$current_node = $tree[$rightidx];
} else {
if( $leftidx == -1 )
$tree_sum = $leftval;
else
$current_node = $tree[$leftidx];
}
}
$stage_sum += $tree_sum;
}
if( $stage_sum < $stage_thresh ){
return false;
}
}
return true;
}
}

To use the code you will require a specific DAT file: http://svay.com/experiences/face-detection/detection.dat , the DAT file should be in the same folder as the piece of code as above, if this is not possible you will need to set the location in the piece of PHP code to follow.

Whenever you want to highlight a face in a picture run this piece of PHP code:

$detector = new Face_Detector('detection.dat');
$detector->face_detect('myface.jpg');
$detector->toJpeg();

Change the “myface.jpg” string to the image you wish to check. The result will look something like this:

If you require a true or false response then return “$passed” instead and remove the line that outputs the jpeg image. This code is very useful and could be used for many purposes including:

• Checking ID card photos (if the code can’t find the face the picture may not be clear enough)
• Sorting images into people and places
• Check if images taken by a webcam contain a face

If you have any suggestions about the code or any other ideas of its uses, let us know!