dlib人脸68特征点检测提速——毫秒级

参考文章:http://f.dataguru.cn/thread-927564-1-1.html

代码是另一个博主的,从浏览记录找不到是谁了,如有侵权请联系本人。在源代码基础上加上了嘴巴张闭检测

把原本低速的dlib人脸检测换成了高速的haar检测,提速明显,但是精度下降

#include <dlib/image_processing/frontal_face_detector.h>
#include <dlib/image_processing/render_face_detections.h>
#include <dlib/image_processing.h>
#include <dlib/gui_widgets.h>
#include <dlib/image_io.h>
#include <dlib/opencv.h>

#include <opencv2/highgui/highgui.hpp>
#include <opencv2/core/core.hpp>
#include <opencv2/opencv.hpp>
#include <opencv2/imgproc/imgproc.hpp>

#include <iostream>
#include <vector>
#include <ctime>

//using namespace dlib;
using namespace std;
//using namespace cv;
double getDistance(CvPoint pointO, CvPoint pointA);

int main(int argc, char *argv[])
{
	time_t start_t, end_t;

	
	//Mat转化为dlib的matrix
	dlib::array2d<dlib::bgr_pixel> dimg;
	

	//加载训练好的级联分类器,利用haar级联分类器快速找出人脸区域,然后交给dlib检测人脸部位
	cv::CascadeClassifier faceDetector("haarcascade_frontalface_alt2.xml");
	if (faceDetector.empty())
	{
		std::cout << "face detector is empty!" << std::endl;
		return 0;
	}

	//加载人脸形状探测器
	dlib::shape_predictor sp;
	dlib::deserialize("shape_predictor_68_face_landmarks.dat") >> sp;

	cv::VideoCapture cam("3.mp4");
	while (cam.isOpened()) {
		//haar级联分类器探测人脸区域,获取一系列人脸所在区域
		std::vector<cv::Rect> objects;
		std::vector<dlib::rectangle> dets;
		cv::Mat frame;
		cv::Mat src;
		
		cam >> frame;
		cv::pyrDown(frame, frame, frame.size() / 2);
		cv::imshow("原图", frame);
	//提取灰度图
	cv::cvtColor(frame, src, CV_BGR2GRAY);
	dlib::assign_image(dimg, dlib::cv_image<uchar>(src));
	faceDetector.detectMultiScale(src, objects);
	for (int i = 0; i < objects.size(); i++)
	{
		//cv::rectangle(frame, objects[i], CV_RGB(200, 0, 0));
		dlib::rectangle r(objects[i].x, objects[i].y, objects[i].x + objects[i].width, objects[i].y + objects[i].height);
		dets.push_back(r);
	}

	//获取人脸68个特征点部位分布
	std::vector<dlib::full_object_detection> shapes;
	for (int i = 0; i < dets.size(); i++)
	{
		dlib::full_object_detection shape = sp(dimg, dets[i]);
		shapes.push_back(shape);
	}

	if (!shapes.empty()) {
		for (int i = 0; i < 68; i++) {
			circle(frame, cvPoint(shapes[0].part(i).x(), shapes[0].part(i).y()), 1, cv::Scalar(255, 255, 255), -1);
		}
	}
	//上下嘴唇
	CvPoint p66 = cvPoint(shapes[0].part(66).x(), shapes[0].part(66).y());
	CvPoint p62 = cvPoint(shapes[0].part(62).x(), shapes[0].part(62).y());
	//左眼上下
	CvPoint p37 = cvPoint(shapes[0].part(37).x(), shapes[0].part(37).y());
	CvPoint p41 = cvPoint(shapes[0].part(41).x(), shapes[0].part(41).y());
	double  L_mouth = getDistance(p66, p62);
	double L_left_eye = getDistance(p37,p41);
	cout << L_left_eye << endl;
	if (L_mouth == 0) {
		cv::putText(frame, "close mouth", cvPoint(10, 50), 5, 1, cv::Scalar(0, 0, 255), 1, 8, 0);
	}
	
	cv::imshow("frame", frame);
	cv::waitKey(27);
	}
	return 0;
}



double getDistance(CvPoint pointO, CvPoint pointA)
{
	double distance;
	distance = powf((pointO.x - pointA.x), 2) + powf((pointO.y - pointA.y), 2);
	distance = sqrtf(distance);
	return distance;
}

dlib人脸68特征点检测提速——毫秒级

速度很快,无卡顿现象 

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