前言
依赖库：opencv 2.4.9 /dlib 19.0/libfacedetection
本篇不记录如何配置，重点在实现上。使用libfacedetection实现人脸区域检测，联合dlib标记人脸特征点，最后使用opencv的FaceRecognizer实现人脸识别。准备工作
1、配置好Opencv2.4.9。（Opencv3.1需要另外下载一个包才有FaceRecognizer）
2、配置好dlib 19.0(版本其实没有多大关系) 3、配置好ShiQi.Yu的人脸检测库思想
训练模块：人脸检测——>获取人脸区域的点坐标——>人脸关键点标记——>人脸对正——>归一化处理——>保存图片——>手动筛选图片——>训练样本——>得到train.xml
识别模块：读取train.xml——>循环（人脸检测——>获取人脸区域的点坐标——>人脸关键点标记——>人脸对正——>归一化处理——>送入model->predict——>预测出结果——>putText在方框上写出名字）结果
识别速度：0.15~0.25秒，Release平台。
识别精度：还可以 使用了一段中国好声音的视频做识别。
当然，这里用的是Fisherface算法，主要还是样本不多，已经可以搞定了。 代码
ReadCSV.h
#include#include #include using namespace cv;using namespace std;static void read_csv(const string& filename, cv::vector & images, cv::vector & labels, char separator = ';') { std::ifstream file(filename.c_str(), ifstream::in); if (!file) { string error_message = "No valid input file was given, please check the given filename."; CV_Error(CV_StsBadArg, error_message); } string line, path, classlabel; while (getline(file, line)) { stringstream liness(line); getline(liness, path, separator); getline(liness, classlabel); if (!path.empty() && !classlabel.empty()) { images.push_back(imread(path, 0)); labels.push_back(atoi(classlabel.c_str())); } }}
FaceRotate.h
#include#include #include #include #include #include #include using namespace dlib;frontal_face_detector detector = get_frontal_face_detector();shape_predictor sp;//Already get
FaceRecognition.cpp
#include#include const int namenumber = 4;//测试的人脸数量const string textname[namenumber] = { "Hariem", "Miss.Na", "Mr.Wang", "Jay.Chou" };//做一个储存人脸名字的数组Ptr GetTrainModel(string fn_csv)//输入CSV文件的路径名{ vector images; vector labels; try { read_csv(fn_csv, images, labels); } catch (cv::Exception& e) { cerr << "Error opening file \"" << fn_csv << "\". Reason: " << e.msg << endl; // 文件有问题，我们啥也做不了了，退出了 exit(1); } // 如果没有读取到足够图片，我们也得退出. if (images.size() <= 1) { string error_message = "This demo needs at least 2 images to work. Please add more images to your data set!"; CV_Error(CV_StsError, error_message); } Ptr model = createEigenFaceRecognizer(80);//创建人脸识别类 可修改 LBPHFace、EigenFace、FisherFace model->train(images, labels); return model;}int main(){ Dlib_Predefine();//加载dlib的文件 Ptr model = GetTrainModel("face.csv");//获得模型 VideoCapture cap("好声音.mp4"); Mat frame,gray; while (true) { cap >> frame; if (!frame.empty()) { gray = FaceDetect(frame); if (!gray.empty()) putText(frame, textname[model->predict(gray)], Point(50, 50), FONT_HERSHEY_DUPLEX, 3, Scalar(230, 255, 0), 2);//model->predict(frame) = predictLabel 名字写在 1 1 imshow("Face Recogniton", frame); waitKey(1); } else{ cout << "The Video's end." <
FaceDetect.cpp
用了掩码。
#include#include void Dlib_Predefine(){ deserialize("shape_predictor_68_face_landmarks.dat") >> sp;//读入标记点文件}cv::Mat FaceToOne(cv::Mat source)//归一化处理函数{ cv::equalizeHist(source, source);//直方图均衡 cv::resize(source, source, cv::Size(92, 112));//裁剪 cv::Mat Mask = cv::imread("mask.jpg", 0); cv::Mat changedMask; source.copyTo(changedMask, Mask); return changedMask;}Mat FaceDetect(Mat frame)//脸是否存在{ Mat gray, error; cvtColor(frame, gray, CV_BGR2GRAY); int * pResults = NULL; pResults = facedetect_frontal_tmp((unsigned char*)(gray.ptr(0)), gray.cols, gray.rows, gray.step, 1.2f, 5, 24); int peopleNUM = (pResults ? *pResults : 0); for (int i = 0; i < peopleNUM; i++)//代表有几张人脸(pResults ? *pResults : 0) { short * p = ((short*)(pResults + 1)) + 6 * i; Rect opencvRect(p[0], p[1], p[2], p[3]); //gray = gray(opencvRect); cv::rectangle(frame, opencvRect, Scalar(230, 255, 0)); dlib::rectangle dlibRect((long)opencvRect.tl().x, (long)opencvRect.tl().y, (long)opencvRect.br().x - 1, (long)opencvRect.br().y - 1); //人脸对齐技术提高了准确率 dlib::full_object_detection shape = sp(dlib::cv_image (gray), dlibRect);//标记点 std::vector shapes; shapes.push_back(shape);//把点保存在了shape中 dlib::array > face_chips; extract_image_chips(dlib::cv_image (gray), get_face_chip_details(shapes), face_chips); Mat pic = toMat(face_chips[0]); cvtColor(pic, pic, CV_BGR2GRAY); return FaceToOne(pic); } return error;}
FaceDetect.h
#include#include "facedetect-dll.h"using namespace cv;using namespace std;Mat FaceDetect(Mat frame);void Dlib_Predefine();//dlib 预定义的函数
FaceRotate.h
#include#include #include #include #include #include #include using namespace dlib;frontal_face_detector detector = get_frontal_face_detector();shape_predictor sp;//Already get
Mask图片：
