class Face_Detector in Image Focus Crop 6
Same name and namespace in other branches
- 7 php-facedetection/FaceDetector.php \Face_Detector
Hierarchy
- class \Face_Detector
Expanded class hierarchy of Face_Detector
File
- php-facedetection/
FaceDetector.php, line 22
View source
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");
}
}
public function face_detect($file) {
if (is_resource($file)) {
$this->canvas = $file;
}
elseif (is_file($file)) {
$this->canvas = imagecreatefromjpeg($file);
}
else {
throw new Exception("Can not load {$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'], $stats['height']);
if ($this->face['w'] > 0) {
$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 json_encode($this->face);
}
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_h - 1; $i++) {
$ii[$i * $ii_w] = 0;
$ii2[$i * $ii_w] = 0;
$rowsum = 0;
$rowsum2 = 0;
for ($j = 1; $j < $ii_w - 1; $j++) {
$rgb = ImageColorAt($canvas, $j, $i);
$red = $rgb >> 16 & 0xff;
$green = $rgb >> 8 & 0xff;
$blue = $rgb & 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;
}
}
Members
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