Opencv与dlib联合进行人脸关键点检测与识别【转】

来自：http://blog.csdn.net/mr_curry/article/details/51994497

前言

依赖库：OpenCV 2.4.9 /dlib 19.0/libfacedetection 
本篇不记录如何配置，重点在算法实现上。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，基本不会识别错，样本没有选择需要识别的东西哦。 
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 <opencv.hpp>#include <iostream>#include <fstream>using namespace cv;using namespace std;static void read_csv(const string& filename, cv::vector<Mat>& images, cv::vector<int>& 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()));        }    }}
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FaceRotate.h

#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/cv_image.h>#include <dlib/opencv.h>using namespace dlib;frontal_face_detector detector = get_frontal_face_detector();shape_predictor sp;//Already get
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FaceRecognition.cpp

#include <FaceDetect.h>#include <ReadCSV.h>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<FaceRecognizer>  GetTrainModel(string fn_csv)//输入CSV文件的路径名{    vector<Mat> images;     vector<int> 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<FaceRecognizer> 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<FaceRecognizer> 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." <<endl; break; }    }}
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FaceDetect.cpp

用了掩码。

#include <FaceDetect.h>#include <FaceRotate.h>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<uchar>(gray), dlibRect);//标记点        std::vector<full_object_detection> shapes;        shapes.push_back(shape);//把点保存在了shape中        dlib::array<array2d<rgb_pixel>>  face_chips;        extract_image_chips(dlib::cv_image<uchar>(gray), get_face_chip_details(shapes), face_chips);        Mat pic = toMat(face_chips[0]);        cvtColor(pic, pic, CV_BGR2GRAY);        return FaceToOne(pic);    }    return error;}
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FaceDetect.h

#include <opencv.hpp>#include "facedetect-dll.h"using namespace cv;using namespace std;Mat FaceDetect(Mat frame);void Dlib_Predefine();//dlib 预定义的函数
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FaceRotate.h

#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/cv_image.h>#include <dlib/opencv.h>using namespace dlib;frontal_face_detector detector = get_frontal_face_detector();shape_predictor sp;//Already get
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Mask图片： 

有几个说明

已经全部更正。