На данный момент поддерживается 2 типа классификаторов (Хаара и LBP). LBP работает быстрее. Вот код для тестирования:
facedetect.h
#ifndef FACEDETECT_H
#define FACEDETECT_H
#include <cv.h>
/*\brief Providing static function for testing face detection algoritms
*/
class FaceDetect {
public:
enum
{
HAAR=0,
LBP=1
} featureTypes;
static cv::vector<cv::Rect> detectFaces(cv::Mat input, int featureType=HAAR);
};
#endif /*FACEDETECT_H */
facedetect.cpp
#include <stdio.h>
#include "FaceDetect.h"
using namespace cv;
/**
* \brief Function for detecting faces
* @param input_img - Matrix of the type CV_8U containing an image where faces are detected.
* @param feature_type=HAAR - feature type (HAAR or LBP for now).
* @return - Vector of rectangles where each rectangle contains the detected object.
*
* \note Use LBP Classifier witch is much faster than HAAR
*
*/
vector<Rect>FaceDetect::detectFaces(Mat input, int featureType)
{
CascadeClassifier cascad;
if(feature_type==LBP)
cascad.load("storage/lbpcascade_frontalface.xml");
else
cascad.load("storage/haarcascade_frontalface_alt2.xml");
vector<Rect> result;
double t = (double)getTickCount();
cascad.detectMultiScale(input,result, 1.2, 3, CV_HAAR_DO_CANNY_PRUNING|CV_HAAR_SCALE_IMAGE|
CV_HAAR_DO_ROUGH_SEARCH, Size(40,40)); //you can play with options here
t = ((double)getTickCount() - t)/getTickFrequency();
printf("Speed = %f \n Accuracy = %d", t, result.size());
return result;
}
main.cpp
#include "cv.h"
#include "highgui.h"
#include "FaceDetect.h"
using namespace cv;
int main(int, char**)
{
Mat img;
img = imread("photo_with_many_faces.jpg", 1);
vector<Rect> result1 =FaceDetect::detectFaces(img, FaceDetect::HAAR);
vector<Rect> result2 = FaceDetect::detectFaces(img, FaceDetect::LBP);
waitKey(0);
return 0;
}
