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<?php
//
// This program is free software; you can redistribute it and/or
// modify it under the terms of the GNU General Public License
// as published by the Free Software Foundation; either version 2
// of the License, or (at your option) any later version.
//
// This program is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU General Public License
// along with this program; if not, write to the Free Software
// Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.
//
// @Author Karthik Tharavaad
// karthik_tharavaad@yahoo.com
// @Contributor Maurice Svay
// maurice@svay.Com
namespace svay;
use Exception;
use svay\Exception\NoFaceException;
class FaceDetector
{
protected $detection_data;
protected $canvas;
protected $face;
private $reduced_canvas;
/**
* Creates a face-detector with the given configuration
*
* Configuration can be either passed as an array or as
* a filepath to a serialized array file-dump
*
* @param string|array $detection_data
*
* @throws Exception
*/
public function __construct($detection_data = 'detection.dat')
{
if (is_array($detection_data)) {
$this->detection_data = $detection_data;
return;
}
if (!is_file($detection_data)) {
// fallback to same file in this class's directory
$detection_data = dirname(__FILE__) . DIRECTORY_SEPARATOR . $detection_data;
if (!is_file($detection_data)) {
throw new \Exception("Couldn't load detection data");
}
}
$this->detection_data = unserialize(file_get_contents($detection_data));
}
public function faceDetect($file)
{
if (is_resource($file)) {
$this->canvas = $file;
} elseif (is_file($file)) {
$this->canvas = imagecreatefromjpeg($file);
} elseif (is_string($file)) {
$this->canvas = imagecreatefromstring($file);
} else {
throw new Exception("Can not load $file");
}
$im_width = imagesx($this->canvas);
$im_height = imagesy($this->canvas);
//Resample before detection?
$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 = $this->getImgStats($this->reduced_canvas);
$this->face = $this->doDetectGreedyBigToSmall(
$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 = $this->getImgStats($this->canvas);
$this->face = $this->doDetectGreedyBigToSmall(
$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);
}
/**
* Crops the face from the photo.
* Should be called after `faceDetect` function call
* If file is provided, the face will be stored in file, other way it will be output to standard output.
*
* @param string|null $outFileName file name to store. If null, will be printed to output
*
* @throws NoFaceException
*/
public function cropFaceToJpeg($outFileName = null)
{
if (empty($this->face)) {
throw new NoFaceException('No face detected');
}
$canvas = imagecreatetruecolor($this->face['w'], $this->face['w']);
imagecopy($canvas, $this->canvas, 0, 0, $this->face['x'], $this->face['y'], $this->face['w'], $this->face['w']);
if ($outFileName === null) {
header('Content-type: image/jpeg');
}
imagejpeg($canvas, $outFileName);
}
public function toJson()
{
return json_encode($this->face);
}
public function getFace()
{
return $this->face;
}
protected function getImgStats($canvas)
{
$image_width = imagesx($canvas);
$image_height = imagesy($canvas);
$iis = $this->computeII($canvas, $image_width, $image_height);
return array(
'width' => $image_width,
'height' => $image_height,
'ii' => $iis['ii'],
'ii2' => $iis['ii2']
);
}
protected function computeII($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' => $ii2);
}
protected function doDetectGreedyBigToSmall($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 = $this->detectOnSubImage($x, $y, $scale, $ii, $ii2, $w, $width+1, $inv_area);
if ($passed) {
return array('x'=>$x, 'y'=>$y, 'w'=>$w);
}
} // end x
} // end y
} // end scale
return null;
}
protected function detectOnSubImage($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;
$count_data = count($this->detection_data);
for ($i_stage = 0; $i_stage < $count_data; $i_stage++) {
$stage = $this->detection_data[$i_stage];
$trees = $stage[0];
$stage_thresh = $stage[1];
$stage_sum = 0;
$count_trees = count($trees);
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;
$count_rects = count($rects);
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;
}
}
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