Face detection in PHP

Question

Does anybody know of a good way to do face detection in PHP? I came across some code here that claims to do this, but I can't seem to get it to work properly. I'd like to make this work (even though it will be slow) and any help you can give me would be really appreciated.

Here's the code from the link:

<?php
// 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;
    }
}

Usage:

$detector = new Face_Detector('detection.dat');
$detector->face_detect('maurice_svay_150.jpg');
$detector->toJpeg();

The problem I am running into, seems to be coming up in the comments on that page as well. "imagecolorat() [function.imagecolorat]: 320,1 is out of bounds." So, I added a error_reporting(0) to the top of the file (not really the solution), and it seems to work sometimes while other times it just doesn't do anything.

Any thoughts?

Answer 1

The project has been upgraded on github repository by following this link Face detection

The problem was on the loop, this code works fine :

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;
        }
    }

Good luck

Answer 2

It would probably be easier/safer to do this with OpenCV, which is written in lower-level code. PHP is interpreted, so it's likely going to be hella slow when doing the job.

Hope this helps!