Detectar cara en una foto usando PHP

En los últimos  años hemos podido ver el surgimiento de esta tecnología para detectar automáticamente el rostro de una persona, inicialmente usado en cámaras fotográficas y en la actualidad podemos verla funcionando en webs como por ejemplo la famosa red social Facebook.

Esto lo podemos lograr usando una clase en PHP:

<?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
//         [email protected]
// @Contributor Maurice Svay
//              [email protected]

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) & 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;
 }
} ?>

Para usarla debes descargar detection.dat (mirror) y usar este sencillo código:

<?php
$detector = new Face_Detector('detection.dat');
$detector->face_detect('tu_foto.jpg');
$detector->toJpeg();?>

Descargar Ejemplo

El resultado:

Via Emanuele Feronato