openCV学习笔记（十） —— 人脸检测之面部特征（眼睛、鼻子、嘴巴）

布满荆棘的人生 2021-09-27 05:36 1034阅读 0赞

环境：VS2017

版本：3.4.1

人脸面部特征检测的准确性依赖于学习到的分类器。

分类器可以从以下地址下载：[https://github.com/opencv/opencv\_contrib/tree/master/modules/face/data/cascades][https_github.com_opencv_opencv_contrib_tree_master_modules_face_data_cascades]

也可以从下载contrib模块，从以下路径获得：opencv\_contrib\_3.4.1\\modules\\face\\data\\cascades

**程序**

/*
    	人脸面部检测：人脸、眼睛、鼻子、嘴
    	检测的准确度依赖于分类器
    */
    
    #include <opencv2/objdetect.hpp>
    #include <opencv2/highgui.hpp>
    #include <opencv2/imgproc.hpp>
    
    #include <iostream>
    #include <vector>
    
    using namespace std;
    using namespace cv;
    
    void detectFaces(Mat &img, vector<Rect> &faces, string cascade_path);
    void detectFacialFeatures(Mat &img, vector<Rect> faces, string eye_cascade, string nose_cascade, string mouth_cascade);
    void detectEyes(Mat &img, vector<Rect> &eyes, string cascade_path);
    void detectNose(Mat &img, vector<Rect> &nose, string cascade_path);
    void detectMouth(Mat &img, vector<Rect> &mouth, string cascade_path);
    
    int main()
    {
    	string input_image_path = "test1.jpg";
    	string face_cascade_path = ".\\cascade\\haarcascades\\haarcascade_frontalface_default.xml";
    	string eye_cascade_path = ".\\cascade\\haarcascades\\haarcascade_eye.xml";
    	string nose_cascade_path = ".\\cascade\\haarcascades\\haarcascade_mcs_nose.xml";
    	string mouth_cascade_path = ".\\cascade\\haarcascades\\haarcascade_mcs_mouth.xml";
    
    	Mat img, imgGray;
    	img = imread(input_image_path);
    	if (img.empty())
    	{
    		printf("can't open image\n");
    		return -1;
    	}
    
    	cvtColor(img, imgGray, CV_BGR2GRAY);	//转换成灰度图来加快人脸识别的速度
    	equalizeHist(imgGray, imgGray);		//直方图均衡化
    
    	//检测人脸和面部特征
    	vector<Rect> faces;
    	detectFaces(img, faces, face_cascade_path);
    	detectFacialFeatures(img, faces, eye_cascade_path, nose_cascade_path, mouth_cascade_path);
    
    	imshow("Result", img);
    
    	waitKey(0);
    	destroyAllWindows();
    
    	return 0;
    }
    
    void detectFaces(Mat &img, vector<Rect> &faces, string cascade_path)
    {
    	CascadeClassifier face_cascade;
    
    	face_cascade.load(cascade_path);
    	if (face_cascade.empty())
    	{
    		printf("can't load face cascade file\n");
    		return;
    	}
    
    	face_cascade.detectMultiScale(img, faces, 1.1, 3, 0, Size(30, 30));
    	return;
    }
    
    void detectFacialFeatures(Mat &img, vector<Rect> faces, string eye_cascade, string nose_cascade, string mouth_cascade)
    {
    	printf("face_size = %zd\n", faces.size());
    
    	for (int i = 0; i < faces.size(); i++)
    	{
    		Rect face = faces[i];
    		rectangle(img, Point(face.x, face.y), Point(face.x + face.width, face.y + face.height), Scalar(255, 0, 0), 2, 4);
    
    		//眼睛、鼻子和嘴巴将在脸部（感兴趣的区域）被检测到。
    		Mat ROI = img(Rect(face.x, face.y, face.width, face.height));
    
    		//检测眼睛、鼻子和嘴巴是否全部被检测到
    		bool is_full_detection = false;
    		if ((!eye_cascade.empty()) && (!nose_cascade.empty()) && (!mouth_cascade.empty()))
    		{
    			is_full_detection = true;
    		}
    
    		//用户提供的分类器可以检测眼睛
    		if (!eye_cascade.empty())
    		{
    			vector<Rect> eyes;
    			detectEyes(ROI, eyes, eye_cascade);
    
    			//标记点与眼睛的中心相对应
    			printf("eyes_size = %zd\n", eyes.size());
    			for (int i = 0; i < eyes.size(); i++)
    			{
    				Rect e = eyes[i];
    				circle(ROI, Point(e.x + e.width / 2, e.y + e.height / 2), 3, Scalar(0, 255, 0), -1, 8);
    				//rectangle(ROI, Point(e.x, e.y), Point(e.x + e.width, e.y + e.height), Scalar(0, 255, 0), -1, 8);
    			}
    		}
    
    		//用户提供的分类器可以检测鼻子
    		double nose_center_height = 0;
    		if (!nose_cascade.empty())
    		{
    			vector <Rect> nose;
    			detectNose(ROI, nose, nose_cascade);
    
    			//标记点与鼻子的中心相对应
    			printf("nose_size = %zd\n", nose.size());
    			for (int i = 0; i < nose.size(); i++)
    			{
    				Rect n = nose[i];
    				circle(ROI, Point(n.x + n.width / 2, n.y + n.height / 2), 3, Scalar(0, 255, 0), -1, 8);
    				nose_center_height = (n.y + n.height / 2);
    
    			}
    		}
    
    		//用户提供的分类器可以检测嘴巴
    		double mouth_center_height = 0;
    		if (!mouth_cascade.empty())
    		{
    			vector<Rect> mouth;
    			detectMouth(ROI, mouth, mouth_cascade);
    
    			printf("mouth.size = %zd\n", mouth.size());
    			for (int i = 0; i < mouth.size(); i++)
    			{
    				Rect m = mouth[i];
    				mouth_center_height = (m.y + m.height / 2);
    
    				if (is_full_detection && (mouth_center_height > nose_center_height))
    				{
    					rectangle(ROI, Point(m.x, m.y), Point(m.x + m.width, m.y + m.height), Scalar(0, 255, 0), 1, 4);
    				}
    				else if (is_full_detection && (mouth_center_height <= nose_center_height))
    				{
    					continue;
    				}
    				else
    				{
    					rectangle(ROI, Point(m.x, m.y), Point(m.x + m.width, m.y + m.height), Scalar(0, 255, 0), 1, 4);
    				}
    			}
    		}
    	}
    
    	return;
    }
    
    void detectEyes(Mat &img, vector<Rect> &eyes, string cascade_path)
    {
    	CascadeClassifier eyes_cascade;
    
    	eyes_cascade.load(cascade_path);
    	
    	eyes_cascade.detectMultiScale(img, eyes, 1.20, 5, 0, Size(30, 30));
    
    	return;
    }
    
    void detectNose(Mat &img, vector<Rect> &nose, string cascade_path)
    {
    	CascadeClassifier nose_cascade;
    
    	nose_cascade.load(cascade_path);
    
    	nose_cascade.detectMultiScale(img, nose, 1.20, 5, 0, Size(30, 30));
    
    	return;
    }
    
    void detectMouth(Mat &img, vector<Rect> &mouth, string cascade_path)
    {
    	CascadeClassifier mouth_cascade;
    
    	mouth_cascade.load(cascade_path);
    
    	mouth_cascade.detectMultiScale(img, mouth, 1.20, 5, 0, Size(30, 30));
    
    	return;
    }

运行结果

![70][]

从运行结果来看，嘴巴的检测不够准确。

[https_github.com_opencv_opencv_contrib_tree_master_modules_face_data_cascades]: https://github.com/opencv/opencv_contrib/tree/master/modules/face/data/cascades
[70]: /images/20210923/941b396e8eb4452f88ca23e309f7cd40.png