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Added sample for object detection with LBP in tutorial_code

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This commit is contained in:
Ana Huaman 2011-08-14 20:20:35 +00:00
parent fec995391f
commit e228b5c70d
2 changed files with 81 additions and 2 deletions
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5
samples/cpp/tutorial_code/objectDetection/objectDetection.cpp
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@ -69,9 +69,9 @@ void detectAndDisplay( Mat frame )
cvtColor( frame, frame_gray, CV_BGR2GRAY );
equalizeHist( frame_gray, frame_gray );
//-- Detect faces
face_cascade.detectMultiScale( frame_gray, faces, 1.1, 2, 0|CV_HAAR_SCALE_IMAGE, Size(30, 30) );
//-- Detect faces
for( int i = 0; i < faces.size(); i++ )
{
Point center( faces[i].x + faces[i].width*0.5, faces[i].y + faces[i].height*0.5 );
@ -79,9 +79,10 @@ void detectAndDisplay( Mat frame )
Mat faceROI = frame_gray( faces[i] );
std::vector<Rect> eyes;
eyes_cascade.detectMultiScale( faceROI, eyes, 1.1, 2, 0 |CV_HAAR_SCALE_IMAGE, Size(30, 30) );
//-- In each face, detect eyes
eyes_cascade.detectMultiScale( faceROI, eyes, 1.1, 2, 0 |CV_HAAR_SCALE_IMAGE, Size(30, 30) );
for( int j = 0; j < eyes.size(); j++ )
{
Point center( faces[i].x + eyes[j].x + eyes[j].width*0.5, faces[i].y + eyes[j].y + eyes[j].height*0.5 );

78
samples/cpp/tutorial_code/objectDetection/objectDetection2.cpp Normal file
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@ -0,0 +1,78 @@
/**
* @file objectDetection2.cpp
* @author A. Huaman ( based in the classic facedetect.cpp in samples/c )
* @brief A simplified version of facedetect.cpp, show how to load a cascade classifier and how to find objects (Face + eyes) in a video stream - Using LBP here
*/
#include "opencv2/objdetect/objdetect.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include <iostream>
#include <stdio.h>
using namespace std;
using namespace cv;
/** Function Headers */
void detectAndDisplay( Mat frame );
/** Global variables */
String face_cascade_name = "lbpcascade_frontalface.xml";
CascadeClassifier face_cascade;
string window_name = "Capture - Face detection";
RNG rng(12345);
/**
* @function main
*/
int main( int argc, const char** argv )
{
CvCapture* capture;
Mat frame;
//-- 1. Load the cascade
if( !face_cascade.load( face_cascade_name ) ){ printf("--(!)Error loading\n"); return -1; };
//-- 2. Read the video stream
capture = cvCaptureFromCAM( -1 );
if( capture )
{
while( true )
{
frame = cvQueryFrame( capture );
//-- 3. Apply the classifier to the frame
if( !frame.empty() )
{ detectAndDisplay( frame ); }
else
{ printf(" --(!) No captured frame -- Break!"); break; }
int c = waitKey(10);
if( (char)c == 'c' ) { break; }
}
}
return 0;
}
/**
* @function detectAndDisplay
*/
void detectAndDisplay( Mat frame )
{
std::vector<Rect> faces;
Mat frame_gray;
cvtColor( frame, frame_gray, CV_BGR2GRAY );
equalizeHist( frame_gray, frame_gray );
//-- Detect faces
face_cascade.detectMultiScale( frame_gray, faces, 1.1, 2, 0, Size(80, 80) );
for( int i = 0; i < faces.size(); i++ )
{
Point center( faces[i].x + faces[i].width*0.5, faces[i].y + faces[i].height*0.5 );
ellipse( frame, center, Size( faces[i].width*0.5, faces[i].height*0.5), 0, 0, 360, Scalar( 255, 0, 0 ), 2, 8, 0 );
}
//-- Show what you got
imshow( window_name, frame );
}