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Update face detection samples

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This commit is contained in:
Suleyman TURKMEN 2015-09-18 11:39:39 +03:00
parent 9533982729
commit fd4761ba31
3 changed files with 134 additions and 179 deletions
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117
samples/cpp/facedetect.cpp
View File

@ -1,17 +1,7 @@
#include "opencv2/objdetect.hpp" #include "opencv2/objdetect.hpp"
#include "opencv2/imgcodecs.hpp"
#include "opencv2/videoio.hpp"
#include "opencv2/highgui.hpp" #include "opencv2/highgui.hpp"
#include "opencv2/imgproc.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 <iostream>
#include <iterator>
#include <stdio.h>
using namespace std; using namespace std;
using namespace cv; using namespace cv;
@ -28,7 +18,7 @@ static void help()
" [--try-flip]\n" " [--try-flip]\n"
" [filename|camera_index]\n\n" " [filename|camera_index]\n\n"
"see facedetect.cmd for one call:\n" "see facedetect.cmd for one call:\n"
"./facedetect --cascade=\"../../data/haarcascades/haarcascade_frontalface_alt.xml\" --nested-cascade=\"../../data/haarcascades/haarcascade_eye.xml\" --scale=1.3\n\n" "./facedetect --cascade=\"../../data/haarcascades/haarcascade_frontalface_alt.xml\" --nested-cascade=\"../../data/haarcascades/haarcascade_eye_tree_eyeglasses.xml\" --scale=1.3\n\n"
"During execution:\n\tHit any key to quit.\n" "During execution:\n\tHit any key to quit.\n"
"\tUsing OpenCV version " << CV_VERSION << "\n" << endl; "\tUsing OpenCV version " << CV_VERSION << "\n" << endl;
} }
@ -42,8 +32,8 @@ string nestedCascadeName = "../../data/haarcascades/haarcascade_eye_tree_eyeglas
int main( int argc, const char** argv ) int main( int argc, const char** argv )
{ {
CvCapture* capture = 0; VideoCapture capture;
Mat frame, frameCopy, image; Mat frame, image;
const string scaleOpt = "--scale="; const string scaleOpt = "--scale=";
size_t scaleOptLen = scaleOpt.length(); size_t scaleOptLen = scaleOpt.length();
const string cascadeOpt = "--cascade="; const string cascadeOpt = "--cascade=";
@ -103,17 +93,17 @@ int main( int argc, const char** argv )
if( inputName.empty() || (isdigit(inputName.c_str()[0]) && inputName.c_str()[1] == '\0') ) 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' ; int c = inputName.empty() ? 0 : inputName.c_str()[0] - '0' ;
if(!capture) cout << "Capture from CAM " << c << " didn't work" << endl; if(!capture.open(c))
cout << "Capture from camera #" << c << " didn't work" << endl;
} }
else if( inputName.size() ) else if( inputName.size() )
{ {
image = imread( inputName, 1 ); image = imread( inputName, 1 );
if( image.empty() ) if( image.empty() )
{ {
capture = cvCaptureFromAVI( inputName.c_str() ); if(!capture.open( inputName ))
if(!capture) cout << "Capture from AVI didn't work" << endl; cout << "Could not read " << inputName << endl;
} }
} }
else else
@ -122,36 +112,27 @@ int main( int argc, const char** argv )
if(image.empty()) cout << "Couldn't read ../data/lena.jpg" << endl; if(image.empty()) cout << "Couldn't read ../data/lena.jpg" << endl;
} }
cvNamedWindow( "result", 1 ); if( capture.isOpened() )
if( capture )
{ {
cout << "In capture ..." << endl; cout << "Video capturing has been started ..." << endl;
for(;;) for(;;)
{ {
IplImage* iplImg = cvQueryFrame( capture ); capture >> frame;
frame = cv::cvarrToMat(iplImg);
if( frame.empty() ) if( frame.empty() )
break; break;
if( iplImg->origin == IPL_ORIGIN_TL )
frame.copyTo( frameCopy );
else
flip( frame, frameCopy, 0 );
detectAndDraw( frameCopy, cascade, nestedCascade, scale, tryflip ); Mat frame1 = frame.clone();
detectAndDraw( frame1, cascade, nestedCascade, scale, tryflip );
if( waitKey( 10 ) >= 0 ) int c = waitKey(10);
goto _cleanup_; if( c == 27 || c == 'q' || c == 'Q' )
break;
} }
waitKey(0);
_cleanup_:
cvReleaseCapture( &capture );
} }
else else
{ {
cout << "In image read" << endl; cout << "Detecting face(s) in " << inputName << endl;
if( !image.empty() ) if( !image.empty() )
{ {
detectAndDraw( image, cascade, nestedCascade, scale, tryflip ); detectAndDraw( image, cascade, nestedCascade, scale, tryflip );
@ -190,8 +171,6 @@ _cleanup_:
} }
} }
cvDestroyWindow("result");
return 0; return 0;
} }
@ -199,21 +178,24 @@ void detectAndDraw( Mat& img, CascadeClassifier& cascade,
CascadeClassifier& nestedCascade, CascadeClassifier& nestedCascade,
double scale, bool tryflip ) double scale, bool tryflip )
{ {
int i = 0;
double t = 0; double t = 0;
vector<Rect> faces, faces2; vector<Rect> faces, faces2;
const static Scalar colors[] = { CV_RGB(0,0,255), const static Scalar colors[] =
CV_RGB(0,128,255), {
CV_RGB(0,255,255), Scalar(255,0,0),
CV_RGB(0,255,0), Scalar(255,128,0),
CV_RGB(255,128,0), Scalar(255,255,0),
CV_RGB(255,255,0), Scalar(0,255,0),
CV_RGB(255,0,0), Scalar(0,128,255),
CV_RGB(255,0,255)} ; Scalar(0,255,255),
Mat gray, smallImg( cvRound (img.rows/scale), cvRound(img.cols/scale), CV_8UC1 ); Scalar(0,0,255),
Scalar(255,0,255)
};
Mat gray, smallImg;
cvtColor( img, gray, COLOR_BGR2GRAY ); cvtColor( img, gray, COLOR_BGR2GRAY );
resize( gray, smallImg, smallImg.size(), 0, 0, INTER_LINEAR ); double fx = 1 / scale;
resize( gray, smallImg, Size(), fx, fx, INTER_LINEAR );
equalizeHist( smallImg, smallImg ); equalizeHist( smallImg, smallImg );
t = (double)cvGetTickCount(); t = (double)cvGetTickCount();
@ -221,8 +203,7 @@ void detectAndDraw( Mat& img, CascadeClassifier& cascade,
1.1, 2, 0 1.1, 2, 0
//|CASCADE_FIND_BIGGEST_OBJECT //|CASCADE_FIND_BIGGEST_OBJECT
//|CASCADE_DO_ROUGH_SEARCH //|CASCADE_DO_ROUGH_SEARCH
|CASCADE_SCALE_IMAGE |CASCADE_SCALE_IMAGE,
,
Size(30, 30) ); Size(30, 30) );
if( tryflip ) if( tryflip )
{ {
@ -231,8 +212,7 @@ void detectAndDraw( Mat& img, CascadeClassifier& cascade,
1.1, 2, 0 1.1, 2, 0
//|CASCADE_FIND_BIGGEST_OBJECT //|CASCADE_FIND_BIGGEST_OBJECT
//|CASCADE_DO_ROUGH_SEARCH //|CASCADE_DO_ROUGH_SEARCH
|CASCADE_SCALE_IMAGE |CASCADE_SCALE_IMAGE,
,
Size(30, 30) ); Size(30, 30) );
for( vector<Rect>::const_iterator r = faces2.begin(); r != faces2.end(); r++ ) for( vector<Rect>::const_iterator r = faces2.begin(); r != faces2.end(); r++ )
{ {
@ -241,44 +221,45 @@ void detectAndDraw( Mat& img, CascadeClassifier& cascade,
} }
t = (double)cvGetTickCount() - t; t = (double)cvGetTickCount() - t;
printf( "detection time = %g ms\n", t/((double)cvGetTickFrequency()*1000.) ); printf( "detection time = %g ms\n", t/((double)cvGetTickFrequency()*1000.) );
for( vector<Rect>::const_iterator r = faces.begin(); r != faces.end(); r++, i++ ) for ( size_t i = 0; i < faces.size(); i++ )
{ {
Rect r = faces[i];
Mat smallImgROI; Mat smallImgROI;
vector<Rect> nestedObjects; vector<Rect> nestedObjects;
Point center; Point center;
Scalar color = colors[i%8]; Scalar color = colors[i%8];
int radius; int radius;
double aspect_ratio = (double)r->width/r->height; double aspect_ratio = (double)r.width/r.height;
if( 0.75 < aspect_ratio && aspect_ratio < 1.3 ) if( 0.75 < aspect_ratio && aspect_ratio < 1.3 )
{ {
center.x = cvRound((r->x + r->width*0.5)*scale); center.x = cvRound((r.x + r.width*0.5)*scale);
center.y = cvRound((r->y + r->height*0.5)*scale); center.y = cvRound((r.y + r.height*0.5)*scale);
radius = cvRound((r->width + r->height)*0.25*scale); radius = cvRound((r.width + r.height)*0.25*scale);
circle( img, center, radius, color, 3, 8, 0 ); circle( img, center, radius, color, 3, 8, 0 );
} }
else else
rectangle( img, cvPoint(cvRound(r->x*scale), cvRound(r->y*scale)), 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)), cvPoint(cvRound((r.x + r.width-1)*scale), cvRound((r.y + r.height-1)*scale)),
color, 3, 8, 0); color, 3, 8, 0);
if( nestedCascade.empty() ) if( nestedCascade.empty() )
continue; continue;
smallImgROI = smallImg(*r); smallImgROI = smallImg( r );
nestedCascade.detectMultiScale( smallImgROI, nestedObjects, nestedCascade.detectMultiScale( smallImgROI, nestedObjects,
1.1, 2, 0 1.1, 2, 0
//|CASCADE_FIND_BIGGEST_OBJECT //|CASCADE_FIND_BIGGEST_OBJECT
//|CASCADE_DO_ROUGH_SEARCH //|CASCADE_DO_ROUGH_SEARCH
//|CASCADE_DO_CANNY_PRUNING //|CASCADE_DO_CANNY_PRUNING
|CASCADE_SCALE_IMAGE |CASCADE_SCALE_IMAGE,
,
Size(30, 30) ); Size(30, 30) );
for( vector<Rect>::const_iterator nr = nestedObjects.begin(); nr != nestedObjects.end(); nr++ ) for ( size_t j = 0; j < nestedObjects.size(); j++ )
{ {
center.x = cvRound((r->x + nr->x + nr->width*0.5)*scale); Rect nr = nestedObjects[j];
center.y = cvRound((r->y + nr->y + nr->height*0.5)*scale); center.x = cvRound((r.x + nr.x + nr.width*0.5)*scale);
radius = cvRound((nr->width + nr->height)*0.25*scale); center.y = cvRound((r.y + nr.y + nr.height*0.5)*scale);
radius = cvRound((nr.width + nr.height)*0.25*scale);
circle( img, center, radius, color, 3, 8, 0 ); circle( img, center, radius, color, 3, 8, 0 );
} }
} }
cv::imshow( "result", img ); imshow( "result", img );
} }

110
samples/cpp/smiledetect.cpp
View File

@ -1,15 +1,7 @@
#include "opencv2/objdetect.hpp" #include "opencv2/objdetect.hpp"
#include "opencv2/highgui.hpp" #include "opencv2/highgui.hpp"
#include "opencv2/imgproc.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 <iostream>
#include <iterator>
#include <stdio.h>
using namespace std; using namespace std;
using namespace cv; using namespace cv;
@ -36,11 +28,10 @@ void detectAndDraw( Mat& img, CascadeClassifier& cascade,
string cascadeName = "../../data/haarcascades/haarcascade_frontalface_alt.xml"; string cascadeName = "../../data/haarcascades/haarcascade_frontalface_alt.xml";
string nestedCascadeName = "../../data/haarcascades/haarcascade_smile.xml"; string nestedCascadeName = "../../data/haarcascades/haarcascade_smile.xml";
int main( int argc, const char** argv ) int main( int argc, const char** argv )
{ {
CvCapture* capture = 0; VideoCapture capture;
Mat frame, frameCopy, image; Mat frame, image;
const string scaleOpt = "--scale="; const string scaleOpt = "--scale=";
size_t scaleOptLen = scaleOpt.length(); size_t scaleOptLen = scaleOpt.length();
const string cascadeOpt = "--cascade="; const string cascadeOpt = "--cascade=";
@ -104,44 +95,34 @@ int main( int argc, const char** argv )
if( inputName.empty() || (isdigit(inputName.c_str()[0]) && inputName.c_str()[1] == '\0') ) 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' ; int c = inputName.empty() ? 0 : inputName.c_str()[0] - '0' ;
if(!capture) cout << "Capture from CAM " << c << " didn't work" << endl; if(!capture.open(c))
cout << "Capture from camera #" << c << " didn't work" << endl;
} }
else if( inputName.size() ) else if( inputName.size() )
{ {
capture = cvCaptureFromAVI( inputName.c_str() ); if(!capture.open( inputName ))
if(!capture) cout << "Capture from AVI didn't work" << endl; cout << "Could not read " << inputName << endl;
} }
cvNamedWindow( "result", 1 ); if( capture.isOpened() )
if( capture )
{ {
cout << "In capture ..." << endl; cout << "Video capturing has been started ..." << endl;
cout << endl << "NOTE: Smile intensity will only be valid after a first smile has been detected" << endl; cout << endl << "NOTE: Smile intensity will only be valid after a first smile has been detected" << endl;
for(;;) for(;;)
{ {
IplImage* iplImg = cvQueryFrame( capture ); capture >> frame;
frame = cv::cvarrToMat(iplImg);
if( frame.empty() ) if( frame.empty() )
break; break;
if( iplImg->origin == IPL_ORIGIN_TL )
frame.copyTo( frameCopy );
else
flip( frame, frameCopy, 0 );
detectAndDraw( frameCopy, cascade, nestedCascade, scale, tryflip ); Mat frame1 = frame.clone();
detectAndDraw( frame1, cascade, nestedCascade, scale, tryflip );
if( waitKey( 10 ) >= 0 ) int c = waitKey(10);
goto _cleanup_; if( c == 27 || c == 'q' || c == 'Q' )
break;
} }
waitKey(0);
_cleanup_:
cvReleaseCapture( &capture );
} }
else else
{ {
@ -150,7 +131,6 @@ _cleanup_:
return -1; return -1;
} }
cvDestroyWindow("result");
return 0; return 0;
} }
@ -158,28 +138,31 @@ void detectAndDraw( Mat& img, CascadeClassifier& cascade,
CascadeClassifier& nestedCascade, CascadeClassifier& nestedCascade,
double scale, bool tryflip) double scale, bool tryflip)
{ {
int i = 0;
vector<Rect> faces, faces2; vector<Rect> faces, faces2;
const static Scalar colors[] = { CV_RGB(0,0,255), const static Scalar colors[] =
CV_RGB(0,128,255), {
CV_RGB(0,255,255), Scalar(255,0,0),
CV_RGB(0,255,0), Scalar(255,128,0),
CV_RGB(255,128,0), Scalar(255,255,0),
CV_RGB(255,255,0), Scalar(0,255,0),
CV_RGB(255,0,0), Scalar(0,128,255),
CV_RGB(255,0,255)} ; Scalar(0,255,255),
Mat gray, smallImg( cvRound (img.rows/scale), cvRound(img.cols/scale), CV_8UC1 ); Scalar(0,0,255),
Scalar(255,0,255)
};
Mat gray, smallImg;
cvtColor( img, gray, COLOR_BGR2GRAY ); cvtColor( img, gray, COLOR_BGR2GRAY );
resize( gray, smallImg, smallImg.size(), 0, 0, INTER_LINEAR );
double fx = 1 / scale;
resize( gray, smallImg, Size(), fx, fx, INTER_LINEAR );
equalizeHist( smallImg, smallImg ); equalizeHist( smallImg, smallImg );
cascade.detectMultiScale( smallImg, faces, cascade.detectMultiScale( smallImg, faces,
1.1, 2, 0 1.1, 2, 0
//|CASCADE_FIND_BIGGEST_OBJECT //|CASCADE_FIND_BIGGEST_OBJECT
//|CASCADE_DO_ROUGH_SEARCH //|CASCADE_DO_ROUGH_SEARCH
|CASCADE_SCALE_IMAGE |CASCADE_SCALE_IMAGE,
,
Size(30, 30) ); Size(30, 30) );
if( tryflip ) if( tryflip )
{ {
@ -188,8 +171,7 @@ void detectAndDraw( Mat& img, CascadeClassifier& cascade,
1.1, 2, 0 1.1, 2, 0
//|CASCADE_FIND_BIGGEST_OBJECT //|CASCADE_FIND_BIGGEST_OBJECT
//|CASCADE_DO_ROUGH_SEARCH //|CASCADE_DO_ROUGH_SEARCH
|CASCADE_SCALE_IMAGE |CASCADE_SCALE_IMAGE,
,
Size(30, 30) ); Size(30, 30) );
for( vector<Rect>::const_iterator r = faces2.begin(); r != faces2.end(); r++ ) for( vector<Rect>::const_iterator r = faces2.begin(); r != faces2.end(); r++ )
{ {
@ -197,38 +179,38 @@ void detectAndDraw( Mat& img, CascadeClassifier& cascade,
} }
} }
for( vector<Rect>::iterator r = faces.begin(); r != faces.end(); r++, i++ ) for ( size_t i = 0; i < faces.size(); i++ )
{ {
Rect r = faces[i];
Mat smallImgROI; Mat smallImgROI;
vector<Rect> nestedObjects; vector<Rect> nestedObjects;
Point center; Point center;
Scalar color = colors[i%8]; Scalar color = colors[i%8];
int radius; int radius;
double aspect_ratio = (double)r->width/r->height; double aspect_ratio = (double)r.width/r.height;
if( 0.75 < aspect_ratio && aspect_ratio < 1.3 ) if( 0.75 < aspect_ratio && aspect_ratio < 1.3 )
{ {
center.x = cvRound((r->x + r->width*0.5)*scale); center.x = cvRound((r.x + r.width*0.5)*scale);
center.y = cvRound((r->y + r->height*0.5)*scale); center.y = cvRound((r.y + r.height*0.5)*scale);
radius = cvRound((r->width + r->height)*0.25*scale); radius = cvRound((r.width + r.height)*0.25*scale);
circle( img, center, radius, color, 3, 8, 0 ); circle( img, center, radius, color, 3, 8, 0 );
} }
else else
rectangle( img, cvPoint(cvRound(r->x*scale), cvRound(r->y*scale)), 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)), cvPoint(cvRound((r.x + r.width-1)*scale), cvRound((r.y + r.height-1)*scale)),
color, 3, 8, 0); color, 3, 8, 0);
const int half_height=cvRound((float)r->height/2); const int half_height=cvRound((float)r.height/2);
r->y=r->y + half_height; r.y=r.y + half_height;
r->height = half_height; r.height = half_height-1;
smallImgROI = smallImg(*r); smallImgROI = smallImg( r );
nestedCascade.detectMultiScale( smallImgROI, nestedObjects, nestedCascade.detectMultiScale( smallImgROI, nestedObjects,
1.1, 0, 0 1.1, 0, 0
//|CASCADE_FIND_BIGGEST_OBJECT //|CASCADE_FIND_BIGGEST_OBJECT
//|CASCADE_DO_ROUGH_SEARCH //|CASCADE_DO_ROUGH_SEARCH
//|CASCADE_DO_CANNY_PRUNING //|CASCADE_DO_CANNY_PRUNING
|CASCADE_SCALE_IMAGE |CASCADE_SCALE_IMAGE,
,
Size(30, 30) ); Size(30, 30) );
// The number of detected neighbors depends on image size (and also illumination, etc.). The // The number of detected neighbors depends on image size (and also illumination, etc.). The
@ -243,9 +225,9 @@ void detectAndDraw( Mat& img, CascadeClassifier& cascade,
// Draw rectangle on the left side of the image reflecting smile intensity // Draw rectangle on the left side of the image reflecting smile intensity
float intensityZeroOne = ((float)smile_neighbors - min_neighbors) / (max_neighbors - min_neighbors + 1); float intensityZeroOne = ((float)smile_neighbors - min_neighbors) / (max_neighbors - min_neighbors + 1);
int rect_height = cvRound((float)img.rows * intensityZeroOne); int rect_height = cvRound((float)img.rows * intensityZeroOne);
CvScalar col = CV_RGB((float)255 * intensityZeroOne, 0, 0); Scalar col = Scalar((float)255 * intensityZeroOne, 0, 0);
rectangle(img, cvPoint(0, img.rows), cvPoint(img.cols/10, img.rows - rect_height), col, -1); rectangle(img, cvPoint(0, img.rows), cvPoint(img.cols/10, img.rows - rect_height), col, -1);
} }
cv::imshow( "result", img ); imshow( "result", img );
} }

86
samples/cpp/ufacedetect.cpp → samples/tapi/ufacedetect.cpp
View File

@ -1,15 +1,8 @@
#include "opencv2/objdetect.hpp" #include "opencv2/objdetect.hpp"
#include "opencv2/imgcodecs.hpp"
#include "opencv2/videoio.hpp"
#include "opencv2/highgui.hpp" #include "opencv2/highgui.hpp"
#include "opencv2/imgproc.hpp" #include "opencv2/imgproc.hpp"
#include "opencv2/core/utility.hpp"
#include "opencv2/core/ocl.hpp" #include "opencv2/core/ocl.hpp"
#include <cctype>
#include <iostream> #include <iostream>
#include <iterator>
#include <stdio.h>
using namespace std; using namespace std;
using namespace cv; using namespace cv;
@ -20,13 +13,13 @@ static void help()
"This classifier can recognize many kinds of rigid objects, once the appropriate classifier is trained.\n" "This classifier can recognize many kinds of rigid objects, once the appropriate classifier is trained.\n"
"It's most known use is for faces.\n" "It's most known use is for faces.\n"
"Usage:\n" "Usage:\n"
"./facedetect [--cascade=<cascade_path> this is the primary trained classifier such as frontal face]\n" "./ufacedetect [--cascade=<cascade_path> this is the primary trained classifier such as frontal face]\n"
" [--nested-cascade[=nested_cascade_path this an optional secondary classifier such as eyes]]\n" " [--nested-cascade[=nested_cascade_path this an optional secondary classifier such as eyes]]\n"
" [--scale=<image scale greater or equal to 1, try 1.3 for example>]\n" " [--scale=<image scale greater or equal to 1, try 1.3 for example>]\n"
" [--try-flip]\n" " [--try-flip]\n"
" [filename|camera_index]\n\n" " [filename|camera_index]\n\n"
"see facedetect.cmd for one call:\n" "see facedetect.cmd for one call:\n"
"./facedetect --cascade=\"../../data/haarcascades/haarcascade_frontalface_alt.xml\" --nested-cascade=\"../../data/haarcascades/haarcascade_eye.xml\" --scale=1.3\n\n" "./ufacedetect --cascade=\"../../data/haarcascades/haarcascade_frontalface_alt.xml\" --nested-cascade=\"../../data/haarcascades/haarcascade_eye_tree_eyeglasses.xml\" --scale=1.3\n\n"
"During execution:\n\tHit any key to quit.\n" "During execution:\n\tHit any key to quit.\n"
"\tUsing OpenCV version " << CV_VERSION << "\n" << endl; "\tUsing OpenCV version " << CV_VERSION << "\n" << endl;
} }
@ -76,7 +69,7 @@ int main( int argc, const char** argv )
} }
else if( scaleOpt.compare( 0, scaleOptLen, argv[i], scaleOptLen ) == 0 ) else if( scaleOpt.compare( 0, scaleOptLen, argv[i], scaleOptLen ) == 0 )
{ {
if( !sscanf( argv[i] + scaleOpt.length(), "%lf", &scale ) || scale > 1 ) if( !sscanf( argv[i] + scaleOpt.length(), "%lf", &scale ) )
scale = 1; scale = 1;
cout << " from which we read scale = " << scale << endl; cout << " from which we read scale = " << scale << endl;
} }
@ -87,7 +80,7 @@ int main( int argc, const char** argv )
} }
else if( argv[i][0] == '-' ) else if( argv[i][0] == '-' )
{ {
cerr << "WARNING: Unknown option %s" << argv[i] << endl; cerr << "WARNING: Unknown option " << argv[i] << endl;
} }
else else
inputName = argv[i]; inputName = argv[i];
@ -120,8 +113,6 @@ int main( int argc, const char** argv )
} }
} }
namedWindow( "result", 1 );
if( capture.isOpened() ) if( capture.isOpened() )
{ {
cout << "Video capturing has been started ..." << endl; cout << "Video capturing has been started ..." << endl;
@ -133,7 +124,8 @@ int main( int argc, const char** argv )
detectAndDraw( frame, canvas, cascade, nestedCascade, scale, tryflip ); detectAndDraw( frame, canvas, cascade, nestedCascade, scale, tryflip );
if( waitKey( 10 ) >= 0 ) int c = waitKey(10);
if( c == 27 || c == 'q' || c == 'Q' )
break; break;
} }
} }
@ -183,46 +175,44 @@ int main( int argc, const char** argv )
void detectAndDraw( UMat& img, Mat& canvas, CascadeClassifier& cascade, void detectAndDraw( UMat& img, Mat& canvas, CascadeClassifier& cascade,
CascadeClassifier& nestedCascade, CascadeClassifier& nestedCascade,
double scale0, bool tryflip ) double scale, bool tryflip )
{ {
int i = 0; double t = 0;
double t = 0, scale=1;
vector<Rect> faces, faces2; vector<Rect> faces, faces2;
const static Scalar colors[] = const static Scalar colors[] =
{ {
Scalar(0,0,255), Scalar(255,0,0),
Scalar(0,128,255),
Scalar(0,255,255),
Scalar(0,255,0),
Scalar(255,128,0), Scalar(255,128,0),
Scalar(255,255,0), Scalar(255,255,0),
Scalar(255,0,0), Scalar(0,255,0),
Scalar(0,128,255),
Scalar(0,255,255),
Scalar(0,0,255),
Scalar(255,0,255) Scalar(255,0,255)
}; };
static UMat gray, smallImg; static UMat gray, smallImg;
t = (double)getTickCount(); t = (double)getTickCount();
resize( img, smallImg, Size(), scale0, scale0, INTER_LINEAR ); cvtColor( img, gray, COLOR_BGR2GRAY );
cvtColor( smallImg, gray, COLOR_BGR2GRAY ); double fx = 1 / scale;
equalizeHist( gray, gray ); resize( gray, smallImg, Size(), fx, fx, INTER_LINEAR );
equalizeHist( smallImg, smallImg );
cascade.detectMultiScale( gray, faces, cascade.detectMultiScale( smallImg, faces,
1.1, 3, 0 1.1, 3, 0
//|CASCADE_FIND_BIGGEST_OBJECT //|CASCADE_FIND_BIGGEST_OBJECT
//|CASCADE_DO_ROUGH_SEARCH //|CASCADE_DO_ROUGH_SEARCH
|CASCADE_SCALE_IMAGE |CASCADE_SCALE_IMAGE,
,
Size(30, 30) ); Size(30, 30) );
if( tryflip ) if( tryflip )
{ {
flip(gray, gray, 1); flip(smallImg, smallImg, 1);
cascade.detectMultiScale( gray, faces2, cascade.detectMultiScale( smallImg, faces2,
1.1, 2, 0 1.1, 2, 0
//|CASCADE_FIND_BIGGEST_OBJECT //|CASCADE_FIND_BIGGEST_OBJECT
//|CASCADE_DO_ROUGH_SEARCH //|CASCADE_DO_ROUGH_SEARCH
|CASCADE_SCALE_IMAGE |CASCADE_SCALE_IMAGE,
,
Size(30, 30) ); Size(30, 30) );
for( vector<Rect>::const_iterator r = faces2.begin(); r != faces2.end(); r++ ) for( vector<Rect>::const_iterator r = faces2.begin(); r != faces2.end(); r++ )
{ {
@ -230,7 +220,7 @@ void detectAndDraw( UMat& img, Mat& canvas, CascadeClassifier& cascade,
} }
} }
t = (double)getTickCount() - t; t = (double)getTickCount() - t;
smallImg.copyTo(canvas); img.copyTo(canvas);
double fps = getTickFrequency()/t; double fps = getTickFrequency()/t;
static double avgfps = 0; static double avgfps = 0;
@ -242,41 +232,43 @@ void detectAndDraw( UMat& img, Mat& canvas, CascadeClassifier& cascade,
putText(canvas, format("OpenCL: %s, fps: %.1f", ocl::useOpenCL() ? "ON" : "OFF", avgfps), Point(50, 30), putText(canvas, format("OpenCL: %s, fps: %.1f", ocl::useOpenCL() ? "ON" : "OFF", avgfps), Point(50, 30),
FONT_HERSHEY_SIMPLEX, 0.8, Scalar(0,255,0), 2); FONT_HERSHEY_SIMPLEX, 0.8, Scalar(0,255,0), 2);
for( vector<Rect>::const_iterator r = faces.begin(); r != faces.end(); r++, i++ ) for ( size_t i = 0; i < faces.size(); i++ )
{ {
Rect r = faces[i];
vector<Rect> nestedObjects; vector<Rect> nestedObjects;
Point center; Point center;
Scalar color = colors[i%8]; Scalar color = colors[i%8];
int radius; int radius;
double aspect_ratio = (double)r->width/r->height; double aspect_ratio = (double)r.width/r.height;
if( 0.75 < aspect_ratio && aspect_ratio < 1.3 ) if( 0.75 < aspect_ratio && aspect_ratio < 1.3 )
{ {
center.x = cvRound((r->x + r->width*0.5)*scale); center.x = cvRound((r.x + r.width*0.5)*scale);
center.y = cvRound((r->y + r->height*0.5)*scale); center.y = cvRound((r.y + r.height*0.5)*scale);
radius = cvRound((r->width + r->height)*0.25*scale); radius = cvRound((r.width + r.height)*0.25*scale);
circle( canvas, center, radius, color, 3, 8, 0 ); circle( canvas, center, radius, color, 3, 8, 0 );
} }
else else
rectangle( canvas, Point(cvRound(r->x*scale), cvRound(r->y*scale)), rectangle( canvas, Point(cvRound(r.x*scale), cvRound(r.y*scale)),
Point(cvRound((r->x + r->width-1)*scale), cvRound((r->y + r->height-1)*scale)), Point(cvRound((r.x + r.width-1)*scale), cvRound((r.y + r.height-1)*scale)),
color, 3, 8, 0); color, 3, 8, 0);
if( nestedCascade.empty() ) if( nestedCascade.empty() )
continue; continue;
UMat smallImgROI = gray(*r); UMat smallImgROI = smallImg(r);
nestedCascade.detectMultiScale( smallImgROI, nestedObjects, nestedCascade.detectMultiScale( smallImgROI, nestedObjects,
1.1, 2, 0 1.1, 2, 0
//|CASCADE_FIND_BIGGEST_OBJECT //|CASCADE_FIND_BIGGEST_OBJECT
//|CASCADE_DO_ROUGH_SEARCH //|CASCADE_DO_ROUGH_SEARCH
//|CASCADE_DO_CANNY_PRUNING //|CASCADE_DO_CANNY_PRUNING
|CASCADE_SCALE_IMAGE |CASCADE_SCALE_IMAGE,
,
Size(30, 30) ); Size(30, 30) );
for( vector<Rect>::const_iterator nr = nestedObjects.begin(); nr != nestedObjects.end(); nr++ )
for ( size_t j = 0; j < nestedObjects.size(); j++ )
{ {
center.x = cvRound((r->x + nr->x + nr->width*0.5)*scale); Rect nr = nestedObjects[j];
center.y = cvRound((r->y + nr->y + nr->height*0.5)*scale); center.x = cvRound((r.x + nr.x + nr.width*0.5)*scale);
radius = cvRound((nr->width + nr->height)*0.25*scale); center.y = cvRound((r.y + nr.y + nr.height*0.5)*scale);
radius = cvRound((nr.width + nr.height)*0.25*scale);
circle( canvas, center, radius, color, 3, 8, 0 ); circle( canvas, center, radius, color, 3, 8, 0 );
} }
} }