generic-library/opencv
1
0
Fork 0
Code Issues Pull Requests Releases Wiki Activity

Update face detection samples

Browse Source
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
Download Patch File Download Diff File Expand all files Collapse all files

117
samples/cpp/facedetect.cpp
View File

@@ -1,17 +1,7 @@
#include "opencv2/objdetect.hpp"
#include "opencv2/imgcodecs.hpp"
#include "opencv2/videoio.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;
@@ -28,7 +18,7 @@ static void help()
" [--try-flip]\n"
" [filename|camera_index]\n\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"
"\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 )
{
CvCapture* capture = 0;
Mat frame, frameCopy, image;
VideoCapture capture;
Mat frame, image;
const string scaleOpt = "--scale=";
size_t scaleOptLen = scaleOpt.length();
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') )
{
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;
if(!capture.open(c))
cout << "Capture from camera #" << c << " didn't work" << endl;
}
else if( inputName.size() )
{
image = imread( inputName, 1 );
if( image.empty() )
{
capture = cvCaptureFromAVI( inputName.c_str() );
if(!capture) cout << "Capture from AVI didn't work" << endl;
if(!capture.open( inputName ))
cout << "Could not read " << inputName << endl;
}
}
else
@@ -122,36 +112,27 @@ int main( int argc, const char** argv )
if(image.empty()) cout << "Couldn't read ../data/lena.jpg" << endl;
}
cvNamedWindow( "result", 1 );
if( capture )
if( capture.isOpened() )
{
cout << "In capture ..." << endl;
cout << "Video capturing has been started ..." << endl;
for(;;)
{
IplImage* iplImg = cvQueryFrame( capture );
frame = cv::cvarrToMat(iplImg);
capture >> frame;
if( frame.empty() )
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 )
goto _cleanup_;
int c = waitKey(10);
if( c == 27 || c == 'q' || c == 'Q' )
break;
}
waitKey(0);
_cleanup_:
cvReleaseCapture( &capture );
}
else
{
cout << "In image read" << endl;
cout << "Detecting face(s) in " << inputName << endl;
if( !image.empty() )
{
detectAndDraw( image, cascade, nestedCascade, scale, tryflip );
@@ -190,8 +171,6 @@ _cleanup_:
}
}
cvDestroyWindow("result");
return 0;
}
@@ -199,21 +178,24 @@ void detectAndDraw( Mat& img, CascadeClassifier& cascade,
CascadeClassifier& nestedCascade,
double scale, bool tryflip )
{
int i = 0;
double t = 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 );
const static Scalar colors[] =
{
Scalar(255,0,0),
Scalar(255,128,0),
Scalar(255,255,0),
Scalar(0,255,0),
Scalar(0,128,255),
Scalar(0,255,255),
Scalar(0,0,255),
Scalar(255,0,255)
};
Mat gray, smallImg;
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 );
t = (double)cvGetTickCount();
@@ -221,8 +203,7 @@ void detectAndDraw( Mat& img, CascadeClassifier& cascade,
1.1, 2, 0
//|CASCADE_FIND_BIGGEST_OBJECT
//|CASCADE_DO_ROUGH_SEARCH
|CASCADE_SCALE_IMAGE
,
|CASCADE_SCALE_IMAGE,
Size(30, 30) );
if( tryflip )
{
@@ -231,8 +212,7 @@ void detectAndDraw( Mat& img, CascadeClassifier& cascade,
1.1, 2, 0
//|CASCADE_FIND_BIGGEST_OBJECT
//|CASCADE_DO_ROUGH_SEARCH
|CASCADE_SCALE_IMAGE
,
|CASCADE_SCALE_IMAGE,
Size(30, 30) );
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;
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;
vector<Rect> nestedObjects;
Point center;
Scalar color = colors[i%8];
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 )
{
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);
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)),
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);
if( nestedCascade.empty() )
continue;
smallImgROI = smallImg(*r);
smallImgROI = smallImg( r );
nestedCascade.detectMultiScale( smallImgROI, nestedObjects,
1.1, 2, 0
//|CASCADE_FIND_BIGGEST_OBJECT
//|CASCADE_DO_ROUGH_SEARCH
//|CASCADE_DO_CANNY_PRUNING
|CASCADE_SCALE_IMAGE
,
|CASCADE_SCALE_IMAGE,
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);
center.y = cvRound((r->y + nr->y + nr->height*0.5)*scale);
radius = cvRound((nr->width + nr->height)*0.25*scale);
Rect nr = nestedObjects[j];
center.x = cvRound((r.x + nr.x + nr.width*0.5)*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 );
}
}
cv::imshow( "result", img );
imshow( "result", img );
}

110
samples/cpp/smiledetect.cpp
View File

@@ -1,15 +1,7 @@
#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;
@@ -36,11 +28,10 @@ void detectAndDraw( Mat& img, CascadeClassifier& cascade,
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;
VideoCapture capture;
Mat frame, image;
const string scaleOpt = "--scale=";
size_t scaleOptLen = scaleOpt.length();
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') )
{
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;
if(!capture.open(c))
cout << "Capture from camera #" << c << " didn't work" << endl;
}
else if( inputName.size() )
{
capture = cvCaptureFromAVI( inputName.c_str() );
if(!capture) cout << "Capture from AVI didn't work" << endl;
if(!capture.open( inputName ))
cout << "Could not read " << inputName << endl;
}
cvNamedWindow( "result", 1 );
if( capture )
if( capture.isOpened() )
{
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;
for(;;)
{
IplImage* iplImg = cvQueryFrame( capture );
frame = cv::cvarrToMat(iplImg);
capture >> frame;
if( frame.empty() )
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 )
goto _cleanup_;
int c = waitKey(10);
if( c == 27 || c == 'q' || c == 'Q' )
break;
}
waitKey(0);
_cleanup_:
cvReleaseCapture( &capture );
}
else
{
@@ -150,7 +131,6 @@ _cleanup_:
return -1;
}
cvDestroyWindow("result");
return 0;
}
@@ -158,28 +138,31 @@ 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 );
const static Scalar colors[] =
{
Scalar(255,0,0),
Scalar(255,128,0),
Scalar(255,255,0),
Scalar(0,255,0),
Scalar(0,128,255),
Scalar(0,255,255),
Scalar(0,0,255),
Scalar(255,0,255)
};
Mat gray, smallImg;
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 );
cascade.detectMultiScale( smallImg, faces,
1.1, 2, 0
//|CASCADE_FIND_BIGGEST_OBJECT
//|CASCADE_DO_ROUGH_SEARCH
|CASCADE_SCALE_IMAGE
,
|CASCADE_SCALE_IMAGE,
Size(30, 30) );
if( tryflip )
{
@@ -188,8 +171,7 @@ void detectAndDraw( Mat& img, CascadeClassifier& cascade,
1.1, 2, 0
//|CASCADE_FIND_BIGGEST_OBJECT
//|CASCADE_DO_ROUGH_SEARCH
|CASCADE_SCALE_IMAGE
,
|CASCADE_SCALE_IMAGE,
Size(30, 30) );
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;
vector<Rect> nestedObjects;
Point center;
Scalar color = colors[i%8];
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 )
{
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);
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)),
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);
const int half_height=cvRound((float)r.height/2);
r.y=r.y + half_height;
r.height = half_height-1;
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
,
|CASCADE_SCALE_IMAGE,
Size(30, 30) );
// 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
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);
Scalar col = Scalar((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 );
imshow( "result", img );
}

284
samples/cpp/ufacedetect.cpp
View File

@@ -1,284 +0,0 @@
#include "opencv2/objdetect.hpp"
#include "opencv2/imgcodecs.hpp"
#include "opencv2/videoio.hpp"
#include "opencv2/highgui.hpp"
#include "opencv2/imgproc.hpp"
#include "opencv2/core/utility.hpp"
#include "opencv2/core/ocl.hpp"
#include <cctype>
#include <iostream>
#include <iterator>
#include <stdio.h>
using namespace std;
using namespace cv;
static void help()
{
cout << "\nThis program demonstrates the cascade recognizer. Now you can use Haar or LBP features.\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"
"Usage:\n"
"./facedetect [--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"
" [--scale=<image scale greater or equal to 1, try 1.3 for example>]\n"
" [--try-flip]\n"
" [filename|camera_index]\n\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"
"During execution:\n\tHit any key to quit.\n"
"\tUsing OpenCV version " << CV_VERSION << "\n" << endl;
}
void detectAndDraw( UMat& img, Mat& canvas, CascadeClassifier& cascade,
CascadeClassifier& nestedCascade,
double scale, bool tryflip );
string cascadeName = "../../data/haarcascades/haarcascade_frontalface_alt.xml";
string nestedCascadeName = "../../data/haarcascades/haarcascade_eye_tree_eyeglasses.xml";
int main( int argc, const char** argv )
{
VideoCapture capture;
UMat frame, image;
Mat canvas;
const string scaleOpt = "--scale=";
size_t scaleOptLen = scaleOpt.length();
const string cascadeOpt = "--cascade=";
size_t cascadeOptLen = cascadeOpt.length();
const string nestedCascadeOpt = "--nested-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 );
if( !nestedCascade.load( nestedCascadeName ) )
cerr << "WARNING: Could not load classifier cascade for nested objects" << endl;
}
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 %s" << argv[i] << endl;
}
else
inputName = argv[i];
}
if( !cascade.load( cascadeName ) )
{
cerr << "ERROR: Could not load classifier cascade" << endl;
help();
return -1;
}
cout << "old cascade: " << (cascade.isOldFormatCascade() ? "TRUE" : "FALSE") << endl;
if( inputName.empty() || (isdigit(inputName.c_str()[0]) && inputName.c_str()[1] == '\0') )
{
int c = inputName.empty() ? 0 : inputName.c_str()[0] - '0';
if(!capture.open(c))
cout << "Capture from camera #" << c << " didn't work" << endl;
}
else
{
if( inputName.empty() )
inputName = "../data/lena.jpg";
image = imread( inputName, 1 ).getUMat(ACCESS_READ);
if( image.empty() )
{
if(!capture.open( inputName ))
cout << "Could not read " << inputName << endl;
}
}
namedWindow( "result", 1 );
if( capture.isOpened() )
{
cout << "Video capturing has been started ..." << endl;
for(;;)
{
capture >> frame;
if( frame.empty() )
break;
detectAndDraw( frame, canvas, cascade, nestedCascade, scale, tryflip );
if( waitKey( 10 ) >= 0 )
break;
}
}
else
{
cout << "Detecting face(s) in " << inputName << endl;
if( !image.empty() )
{
detectAndDraw( image, canvas, cascade, nestedCascade, scale, tryflip );
waitKey(0);
}
else if( !inputName.empty() )
{
/* assume it is a text file containing the
list of the image filenames to be processed - one per line */
FILE* f = fopen( inputName.c_str(), "rt" );
if( f )
{
char buf[1000+1];
while( fgets( buf, 1000, f ) )
{
int len = (int)strlen(buf), c;
while( len > 0 && isspace(buf[len-1]) )
len--;
buf[len] = '\0';
cout << "file " << buf << endl;
image = imread( buf, 1 ).getUMat(ACCESS_READ);
if( !image.empty() )
{
detectAndDraw( image, canvas, cascade, nestedCascade, scale, tryflip );
c = waitKey(0);
if( c == 27 || c == 'q' || c == 'Q' )
break;
}
else
{
cerr << "Aw snap, couldn't read image " << buf << endl;
}
}
fclose(f);
}
}
}
return 0;
}
void detectAndDraw( UMat& img, Mat& canvas, CascadeClassifier& cascade,
CascadeClassifier& nestedCascade,
double scale0, bool tryflip )
{
int i = 0;
double t = 0, scale=1;
vector<Rect> faces, faces2;
const static Scalar colors[] =
{
Scalar(0,0,255),
Scalar(0,128,255),
Scalar(0,255,255),
Scalar(0,255,0),
Scalar(255,128,0),
Scalar(255,255,0),
Scalar(255,0,0),
Scalar(255,0,255)
};
static UMat gray, smallImg;
t = (double)getTickCount();
resize( img, smallImg, Size(), scale0, scale0, INTER_LINEAR );
cvtColor( smallImg, gray, COLOR_BGR2GRAY );
equalizeHist( gray, gray );
cascade.detectMultiScale( gray, faces,
1.1, 3, 0
//|CASCADE_FIND_BIGGEST_OBJECT
//|CASCADE_DO_ROUGH_SEARCH
|CASCADE_SCALE_IMAGE
,
Size(30, 30) );
if( tryflip )
{
flip(gray, gray, 1);
cascade.detectMultiScale( gray, 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));
}
}
t = (double)getTickCount() - t;
smallImg.copyTo(canvas);
double fps = getTickFrequency()/t;
static double avgfps = 0;
static int nframes = 0;
nframes++;
double alpha = nframes > 50 ? 0.01 : 1./nframes;
avgfps = avgfps*(1-alpha) + fps*alpha;
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);
for( vector<Rect>::const_iterator r = faces.begin(); r != faces.end(); r++, i++ )
{
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( canvas, center, radius, color, 3, 8, 0 );
}
else
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)),
color, 3, 8, 0);
if( nestedCascade.empty() )
continue;
UMat smallImgROI = gray(*r);
nestedCascade.detectMultiScale( smallImgROI, nestedObjects,
1.1, 2, 0
//|CASCADE_FIND_BIGGEST_OBJECT
//|CASCADE_DO_ROUGH_SEARCH
//|CASCADE_DO_CANNY_PRUNING
|CASCADE_SCALE_IMAGE
,
Size(30, 30) );
for( vector<Rect>::const_iterator nr = nestedObjects.begin(); nr != nestedObjects.end(); nr++ )
{
center.x = cvRound((r->x + nr->x + nr->width*0.5)*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 );
}
}
imshow( "result", canvas );
}