smile detection codes in matlab

#include "opencv2/objdetect.hpp"
#include "opencv2/highgui.hpp"
#include "opencv2/imgproc.hpp"
#include "opencv2/core/utility.hpp"

#include "opencv2/videoio/videoio_c.h"
#include "opencv2/highgui/highgui_c.h"

#include <cctype>
#include <iostream>
#include <iterator>
#include <stdio.h>

using namespace std;
using namespace cv;

static void help()
{
cout << "\nThis program demonstrates the smile detector.\n"
"Usage:\n"
"./smiledetect [--cascade=<cascade_path> this is the frontal face classifier]\n"
" [--smile-cascade=[<smile_cascade_path>]]\n"
" [--scale=<image scale greater or equal to 1, try 2.0 for example. The larger the faster the processing>]\n"
" [--try-flip]\n"
" [video_filename|camera_index]\n\n"
"Example:\n"
"./smiledetect --cascade=\"../../data/haarcascades/haarcascade_frontalface_alt.xml\" --smile-cascade=\"../../data/haarcascades/haarcascade_smile.xml\" --scale=2.0\n\n"
"During execution:\n\tHit any key to quit.\n"
"\tUsing OpenCV version " << CV_VERSION << "\n" << endl;
}

void detectAndDraw( Mat& img, CascadeClassifier& cascade,
CascadeClassifier& nestedCascade,
double scale, bool tryflip );

string cascadeName = "../../data/haarcascades/haarcascade_frontalface_alt.xml";
string nestedCascadeName = "../../data/haarcascades/haarcascade_smile.xml";


int main( int argc, const char** argv )
{
CvCapture* capture = 0;
Mat frame, frameCopy, image;
const string scaleOpt = "--scale=";
size_t scaleOptLen = scaleOpt.length();
const string cascadeOpt = "--cascade=";
size_t cascadeOptLen = cascadeOpt.length();
const string nestedCascadeOpt = "--smile-cascade";
size_t nestedCascadeOptLen = nestedCascadeOpt.length();
const string tryFlipOpt = "--try-flip";
size_t tryFlipOptLen = tryFlipOpt.length();
string inputName;
bool tryflip = false;

help();

CascadeClassifier cascade, nestedCascade;
double scale = 1;

for( int i = 1; i < argc; i++ )
{
cout << "Processing " << i << " " << argv[i] << endl;
if( cascadeOpt.compare( 0, cascadeOptLen, argv[i], cascadeOptLen ) == 0 )
{
cascadeName.assign( argv[i] + cascadeOptLen );
cout << " from which we have cascadeName= " << cascadeName << endl;
}
else if( nestedCascadeOpt.compare( 0, nestedCascadeOptLen, argv[i], nestedCascadeOptLen ) == 0 )
{
if( argv[i][nestedCascadeOpt.length()] == '=' )
nestedCascadeName.assign( argv[i] + nestedCascadeOpt.length() + 1 );
}
else if( scaleOpt.compare( 0, scaleOptLen, argv[i], scaleOptLen ) == 0 )
{
if( !sscanf( argv[i] + scaleOpt.length(), "%lf", &scale ) || scale < 1 )
scale = 1;
cout << " from which we read scale = " << scale << endl;
}
else if( tryFlipOpt.compare( 0, tryFlipOptLen, argv[i], tryFlipOptLen ) == 0 )
{
tryflip = true;
cout << " will try to flip image horizontally to detect assymetric objects\n";
}
else if( argv[i][0] == '-' )
{
cerr << "WARNING: Unknown option " << argv[i] << endl;
}
else
inputName.assign( argv[i] );
}

if( !cascade.load( cascadeName ) )
{
cerr << "ERROR: Could not load face cascade" << endl;
help();
return -1;
}
if( !nestedCascade.load( nestedCascadeName ) )
{
cerr << "ERROR: Could not load smile cascade" << endl;
help();
return -1;
}

if( inputName.empty() || (isdigit(inputName.c_str()[0]) && inputName.c_str()[1] == '\0') )
{
capture = cvCaptureFromCAM( inputName.empty() ? 0 : inputName.c_str()[0] - '0' );
int c = inputName.empty() ? 0 : inputName.c_str()[0] - '0' ;
if(!capture) cout << "Capture from CAM " << c << " didn't work" << endl;
}
else if( inputName.size() )
{
capture = cvCaptureFromAVI( inputName.c_str() );
if(!capture) cout << "Capture from AVI didn't work" << endl;
}

cvNamedWindow( "result", 1 );

if( capture )
{
cout << "In capture ..." << endl;
cout << endl << "NOTE: Smile intensity will only be valid after a first smile has been detected" << endl;

for(;
{
IplImage* iplImg = cvQueryFrame( capture );
frame = cv::cvarrToMat(iplImg);
if( frame.empty() )
break;
if( iplImg->origin == IPL_ORIGIN_TL )
frame.copyTo( frameCopy );
else
flip( frame, frameCopy, 0 );

detectAndDraw( frameCopy, cascade, nestedCascade, scale, tryflip );

if( waitKey( 10 ) >= 0 )
goto _cleanup_;
}

waitKey(0);

_cleanup_:
cvReleaseCapture( &capture );
}
else
{
cerr << "ERROR: Could not initiate capture" << endl;
help();
return -1;
}

cvDestroyWindow("result");
return 0;
}

void detectAndDraw( Mat& img, CascadeClassifier& cascade,
CascadeClassifier& nestedCascade,
double scale, bool tryflip)
{
int i = 0;
vector<Rect> faces, faces2;
const static Scalar colors[] = { CV_RGB(0,0,255),
CV_RGB(0,128,255),
CV_RGB(0,255,255),
CV_RGB(0,255,0),
CV_RGB(255,128,0),
CV_RGB(255,255,0),
CV_RGB(255,0,0),
CV_RGB(255,0,255)} ;
Mat gray, smallImg( cvRound (img.rows/scale), cvRound(img.cols/scale), CV_8UC1 );

cvtColor( img, gray, COLOR_BGR2GRAY );
resize( gray, smallImg, smallImg.size(), 0, 0, INTER_LINEAR );
equalizeHist( smallImg, smallImg );

cascade.detectMultiScale( smallImg, faces,
1.1, 2, 0
//|CASCADE_FIND_BIGGEST_OBJECT
//|CASCADE_DO_ROUGH_SEARCH
|CASCADE_SCALE_IMAGE
,
Size(30, 30) );
if( tryflip )
{
flip(smallImg, smallImg, 1);
cascade.detectMultiScale( smallImg, faces2,
1.1, 2, 0
//|CASCADE_FIND_BIGGEST_OBJECT
//|CASCADE_DO_ROUGH_SEARCH
|CASCADE_SCALE_IMAGE
,
Size(30, 30) );
for( vector<Rect>::const_iterator r = faces2.begin(); r != faces2.end(); r++ )
{
faces.push_back(Rect(smallImg.cols - r->x - r->width, r->y, r->width, r->height));
}
}

for( vector<Rect>::iterator r = faces.begin(); r != faces.end(); r++, i++ )
{
Mat smallImgROI;
vector<Rect> nestedObjects;
Point center;
Scalar color = colors[i%8];
int radius;

double aspect_ratio = (double)r->width/r->height;
if( 0.75 < aspect_ratio && aspect_ratio < 1.3 )
{
center.x = cvRound((r->x + r->width*0.5)*scale);
center.y = cvRound((r->y + r->height*0.5)*scale);
radius = cvRound((r->width + r->height)*0.25*scale);
circle( img, center, radius, color, 3, 8, 0 );
}
else
rectangle( img, cvPoint(cvRound(r->x*scale), cvRound(r->y*scale)),
cvPoint(cvRound((r->x + r->width-1)*scale), cvRound((r->y + r->height-1)*scale)),
color, 3, 8, 0);

const int half_height=cvRound((float)r->height/2);
r->y=r->y + half_height;
r->height = half_height;
smallImgROI = smallImg(*r);
nestedCascade.detectMultiScale( smallImgROI, nestedObjects,
1.1, 0, 0
//|CASCADE_FIND_BIGGEST_OBJECT
//|CASCADE_DO_ROUGH_SEARCH
//|CASCADE_DO_CANNY_PRUNING
|CASCADE_SCALE_IMAGE
,
Size(30, 30) );

// The number of detected neighbors depends on image size (and also illumination, etc.). The
// following steps use a floating minimum and maximum of neighbors. Intensity thus estimated will be
//accurate only after a first smile has been displayed by the user.
const int smile_neighbors = (int)nestedObjects.size();
static int max_neighbors=-1;
static int min_neighbors=-1;
if (min_neighbors == -1) min_neighbors = smile_neighbors;
max_neighbors = MAX(max_neighbors, smile_neighbors);

// Draw rectangle on the left side of the image reflecting smile intensity
float intensityZeroOne = ((float)smile_neighbors - min_neighbors) / (max_neighbors - min_neighbors + 1);
int rect_height = cvRound((float)img.rows * intensityZeroOne);
CvScalar col = CV_RGB((float)255 * intensityZeroOne, 0, 0);
rectangle(img, cvPoint(0, img.rows), cvPoint(img.cols/10, img.rows - rect_height), col, -1);
}

cv::imshow( "result", img );
}