前言
依賴庫：opencv 2.4.9 /dlib 19.0/libfacedetection
本篇不記錄如何配置，重點在實現上。使用libfacedetection實現人臉區域檢測，聯合dlib標記人臉特征點，最后使用opencv的FaceRecognizer實現人臉識別。
準備工作
1、配置好Opencv2.4.9。（Opencv3.1需要另外下載一個包才有FaceRecognizer）
2、配置好dlib 19.0(版本其實沒有多大關系)
3、配置好ShiQi.Yu的人臉檢測庫
思想
訓練模塊：人臉檢測——>獲取人臉區域的點坐標——>人臉關鍵點標記——>人臉對正——>歸一化處理——>保存圖片——>手動篩選圖片——>訓練樣本——>得到train.xml
識別模塊：讀取train.xml——>循環（人臉檢測——>獲取人臉區域的點坐標——>人臉關鍵點標記——>人臉對正——>歸一化處理——>送入model->predict——>預測出結果——>putText在方框上寫出名字）
結果
識別速度：0.15~0.25秒，Release平臺。
識別精度：還可以
使用了一段中國好聲音的視頻做識別。
當然，這里用的是Fisherface算法，主要還是樣本不多，已經可以搞定了。
代碼
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()));}}
}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 getFaceRecognition.cpp
#include <FaceDetect.h>
#include <ReadCSV.h>
const int namenumber = 4;//測試的人臉數量
const string textname[namenumber] = { "Hariem", "Miss.Na", "Mr.Wang", "Jay.Chou" };//做一個儲存人臉名字的數組Ptr<FaceRecognizer> GetTrainModel(string fn_csv)//輸入CSV文件的路徑名
{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;// 文件有問題，我們啥也做不了了，退出了exit(1);}// 如果沒有讀取到足夠圖片，我們也得退出.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);//創建人臉識別類 可修改 LBPHFace、EigenFace、FisherFacemodel->train(images, labels);return model;
}int main()
{Dlib_Predefine();//加載dlib的文件Ptr<FaceRecognizer> model = GetTrainModel("face.csv");//獲得模型VideoCapture cap("好聲音.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 名字寫在 1 1imshow("Face Recogniton", frame);waitKey(1);}else{ cout << "The Video's end." <<endl; break; }}}FaceDetect.cpp
用了掩碼。
#include <FaceDetect.h>
#include <FaceRotate.h>
void Dlib_Predefine()
{deserialize("shape_predictor_68_face_landmarks.dat") >> sp;//讀入標記點文件
}cv::Mat FaceToOne(cv::Mat source)//歸一化處理函數
{cv::equalizeHist(source, source);//直方圖均衡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)//臉是否存在
{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++)//代表有幾張人臉(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);//人臉對齊技術提高了準確率dlib::full_object_detection shape = sp(dlib::cv_image<uchar>(gray), dlibRect);//標記點std::vector<full_object_detection> shapes;shapes.push_back(shape);//把點保存在了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;
}FaceDetect.h
#include <opencv.hpp>
#include "facedetect-dll.h"using namespace cv;
using namespace std;Mat FaceDetect(Mat frame);
void Dlib_Predefine();//dlib 預定義的函數
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 getMask圖片：
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