程式碼C++， opencv實現人臉識別，人臉檢測，人臉匹配，視訊中的人臉檢測，攝像頭下的人臉檢測等
阿新 • • 發佈：2019-01-08
前一段時間寫了一個人臉相關的演算法，包括視訊中的人臉檢測，相機的人臉檢測，影象中人臉檢測，還有人臉識別。
使用的是VS2013和opencv。
首先建立標頭檔案common.h
然後就是建立common.cpp檔案，這裡面有相關的實現。#ifndef _COMMON_H #define _COMMON_H #include <opencv2/opencv.hpp> #include <opencv2/highgui/highgui.hpp> #include <opencv2/imgproc/imgproc.hpp> #include <iostream> #include <sys/types.h> #include <sys/stat.h> #include <fstream> #include <string> #include <ctime> #include <io.h> #include <direct.h> //#include <cstdlib> static const char help[] = "face detection on image: needs image\n" \ "face detection on video: needs video\n" \ "face detection on camera: needs camera\n" \ "face recognition: needs images\n"; /* 功能：判斷該路徑指向的是檔案還是資料夾 函式：isFileOrFolder 檔案返回： 0 資料夾返回： 1 */ bool isFileOrFolder(const std::string fileName); #endif
#include "common.h"
bool isFileOrFolder(const std::string fileName)
{
const char* path = fileName.c_str();
struct _stat buf = { 0 };
_stat(path, &buf);
return buf.st_mode & _S_IFDIR;
}
#ifndef _FACE_DETETION_VIDEO_H_ #define _FACE_DETETION_VIDEO_H_ #include "common.h" void face_detetion_video(const std::string videoPath, const std::string cascadeName); #endif
接著建立對應的cpp檔案，face_detection_video.cpp
然後是影象中的尋找人臉，檔名face_detection_img.h#include "face_deteion_video.h" void face_detetion_video(const std::string videoPath, const std::string cascadeName) { cv::VideoCapture cap(videoPath); if (!cap.isOpened()) { std::cout << "不能開啟該視訊檔案！" << std::endl; return; } double scale = 2; cv::CascadeClassifier cascade; cascade.load(cascadeName); std::vector<cv::Rect> faces; double fps = cap.get(CV_CAP_PROP_FPS); //獲取幀率 bool isVideoRewriteFile = true; // 是否把視訊重新寫入檔案, 預設是false：不重新寫入檔案 double dWidth = 0; double dHeight = 0; cv::Size frameSize; cv::VideoWriter vdWr; if (isVideoRewriteFile) { dWidth = cap.get(CV_CAP_PROP_FRAME_WIDTH); dHeight = cap.get(CV_CAP_PROP_FRAME_HEIGHT); frameSize = cv::Size(static_cast<int>(dWidth), static_cast<int>(dHeight)); size_t pos = videoPath.find_last_of('.'); std::string videoWritePath = videoPath.substr(0, pos); videoWritePath = videoWritePath + "_Result.avi"; vdWr = cv::VideoWriter(videoWritePath, CV_FOURCC('M', 'J', 'P', 'G'), fps, frameSize, true); if (!vdWr.isOpened()) { std::cout << "不能寫入視訊！" << std::endl; isVideoRewriteFile = false; } } while (1) { cv::Mat_<uchar> frame; bool bSuccess = cap.read(frame); if (!bSuccess) { break; } cv::Mat smallImg(cvRound(frame.rows / scale), cvRound(frame.cols / scale), CV_8UC1); //cvRound對double型資料進行四捨五入 cv::resize(frame, smallImg, smallImg.size(), 0, 0, cv::INTER_LINEAR); cvtColor(smallImg, smallImg, CV_RGB2GRAY); cv::equalizeHist(smallImg, smallImg); //equalizeHist提高影象的亮度和對比度 cascade.detectMultiScale(smallImg, faces, 1.1, 2, 0 /*|CV_HAAR_FIND_BIGGEST_OBJECT |CV_HAAR_DO_ROUGH_SEARCH*/ | CV_HAAR_SCALE_IMAGE , cv::Size(30, 30)); for (std::vector<cv::Rect>::const_iterator r = faces.begin(); r != faces.end(); r++){ cv::Rect rect(0, 0, 0, 0); rect.x = int(r->x*scale); rect.y = int(r->y*scale); rect.width = int((r->width - 1)*scale); rect.height = int((r->height - 1)*scale); cv::rectangle(frame, rect, cv::Scalar(0, 0, 0), 3, 8); } //是否把檢測結果寫入檔案 if (isVideoRewriteFile) { vdWr.write(frame); } cv::imshow("Video", frame); cv::waitKey((int)(1000 / fps)); } cap.release(); vdWr.release(); }
#ifndef _FACE_DETETION_IMAGE_H_
#define _FACE_DETETION_IMAGE_H_
#include "common.h"
void face_detetion_img(const std::string imagePath, const std::string cascadeName);
#endif接著就是對應標頭檔案face_detection_img.cpp
#include "face_detetion_img.h"
void face_detetion_img(const std::string imgPath, const std::string cascadeName)
{
//bool fileOrFolder = isFileOrFolder(imgPath);
std::ifstream fin;
fin.open(imgPath);
cv::CascadeClassifier cascade;
double scale = 1.3;
std::vector<cv::Rect> faces;
cv::Mat gray;
// --Detection
cascade.load(cascadeName);
std::string name;
while (getline(fin, name)){
name.erase(0, name.find_first_not_of(" \t"));
name.erase(name.find_last_not_of(" \t") + 1);
// Read Image
cv::Mat_<uchar> image = cv::imread(name, 0);
if (image.empty())
{
continue;
}
// Read Opencv Detection Bbx
cv::Mat smallImg(cvRound(image.rows / scale), cvRound(image.cols / scale), CV_8UC1); //cvRound對double型資料進行四捨五入
cv::resize(image, smallImg, smallImg.size(), 0, 0, cv::INTER_LINEAR);
cv::equalizeHist(smallImg, smallImg); //equalizeHist提高影象的亮度和對比度
// --Detection
cascade.detectMultiScale(smallImg, faces,
1.1, 2, 0
/*|CV_HAAR_FIND_BIGGEST_OBJECT
|CV_HAAR_DO_ROUGH_SEARCH*/
| CV_HAAR_SCALE_IMAGE
,
cv::Size(30, 30));
for (std::vector<cv::Rect>::const_iterator r = faces.begin(); r != faces.end(); r++){
cv::Rect rect(0, 0, 0, 0);
rect.x = int(r->x*scale);
rect.y = int(r->y*scale);
rect.width = int((r->width - 1)*scale);
rect.height = int((r->height - 1)*scale);
cv::rectangle(image, rect, cv::Scalar(0, 255, 0), 3, 8);
}
cv::imshow("test", image);
char s = cv::waitKey(0);
if ('s' == s )
{
size_t pos = name.find_last_of('.');
std::string filename = name.substr(0, pos);
filename = filename + ".bmp";
std::cout << filename << std::endl;
cv::imwrite(filename, image);
}
}
fin.close();
}然後就是從攝像投中讀取人臉資訊。建立檔案face_detection_camera.h
#ifndef _FACE_DETETION_CAMERA_H_
#define _FACE_DETETION_CAMERA_H_
#include "common.h"
void face_detetion_camera(const std::string cascadeName);
#endif#include "face_detetion_camera.h"
void face_detetion_camera(const std::string cascadeName)
{
cv::VideoCapture cap(0);
if (!cap.isOpened())
{
std::cout << "不能開啟該視訊檔案！" << std::endl;
return;
}
double scale = 2;
cv::CascadeClassifier cascade;
cascade.load(cascadeName);
std::vector<cv::Rect> faces;
bool isVideoRewriteFile = false; // 是否把攝像頭讀取的資料寫入檔案。
double dWidth = 0;
double dHeight = 0;
cv::Size frameSize;
cv::VideoWriter vdWr;
char tmp[1024] = { 0 };
if (isVideoRewriteFile)
{
dWidth = cap.get(CV_CAP_PROP_FRAME_WIDTH);
dHeight = cap.get(CV_CAP_PROP_FRAME_HEIGHT);
frameSize = cv::Size(static_cast<int>(dWidth), static_cast<int>(dHeight));
time_t t = time(0);
memset(tmp, 0, sizeof(tmp));
strftime(tmp, sizeof(tmp), "../camera_out_video/%Y.%m.%d-%H.%M.%S", localtime(&t));
std::string videoWritePath(tmp);
videoWritePath = videoWritePath + ".avi";
vdWr = cv::VideoWriter(videoWritePath, CV_FOURCC('M', 'J', 'P', 'G'), 20, frameSize, true);
if (!vdWr.isOpened())
{
std::cout << "不能寫入視訊！" << std::endl;
isVideoRewriteFile = false;
}
}
while (1)
{
cv::Mat frame;
bool bSuccess = cap.read(frame);
if (!bSuccess)
{
break;
}
cv::Mat smallImg(cvRound(frame.rows / scale), cvRound(frame.cols / scale), CV_8UC1); //cvRound對double型資料進行四捨五入
cv::resize(frame, smallImg, smallImg.size(), 0, 0, cv::INTER_LINEAR);
cvtColor(smallImg, smallImg, CV_RGB2GRAY);
cv::equalizeHist(smallImg, smallImg); //equalizeHist提高影象的亮度和對比度
cascade.detectMultiScale(smallImg, faces,
1.1, 2, 0
/*|CV_HAAR_FIND_BIGGEST_OBJECT
|CV_HAAR_DO_ROUGH_SEARCH*/
| CV_HAAR_SCALE_IMAGE
,
cv::Size(30, 30));
for (std::vector<cv::Rect>::const_iterator r = faces.begin(); r != faces.end(); r++){
cv::Rect rect(0, 0, 0, 0);
rect.x = int(r->x*scale);
rect.y = int(r->y*scale);
rect.width = int((r->width - 1)*scale);
rect.height = int((r->height - 1)*scale);
cv::rectangle(frame, rect, cv::Scalar(0, 0, 0), 3, 8);
}
//是否把檢測結果寫入檔案
if (isVideoRewriteFile)
{
vdWr.write(frame);
}
cv::imshow("Video", frame);
if (27 == cv::waitKey(20)){ // 按下ESC鍵，結束視訊
break;
}
}
cap.release();
vdWr.release();
}#ifndef _FACE_RECOGNITION_H_
#define _FACE_RECOGNITION_H_
#include "common.h"
void preDeal_original_img(const std::string recognitionPath, const std::string cascadeName);
std::vector<std::pair<cv::Mat, std::string >> get_CropFace_And_ImgPathName(const std::string recognitionPath, const std::string cascadeName);
bool matchFace(cv::Mat detectFace, cv::Mat dbFace);
void face_recognition(std::string recognitionPath, const std::string cascadeName);
#endif以及對應的cpp檔案：face_recognition.cpp
#include "face_recognition.h"
void preDeal_original_img(const std::string recognitionPath, const std::string cascadeName)
{
std::ifstream fin;
fin.open(recognitionPath);
if (!fin)
{
std::cout << "Cannot open " + recognitionPath << std::endl;
return;
}
// --Detection
cv::CascadeClassifier cascade;
cascade.load(cascadeName);
if (cascade.empty())
{
std::cout << "Cascade path error!" << std::endl;
return;
}
double scale = 1.3;
std::vector<cv::Rect> faces;
cv::Mat gray;
std::string name;
std::string camera_face = "../camera_face/";
while (getline(fin, name)){
if (name.empty())
{
continue;
}
name.erase(0, name.find_first_not_of(" \t"));
name.erase(name.find_last_not_of(" \t") + 1);
// Read Image
cv::Mat img = cv::imread(name);
if (img.empty())
{
continue;
}
cv::Mat_<uchar> image;
if (img.channels() != 1)
{
cvtColor(img, image, CV_BGR2GRAY);
image.convertTo(image, CV_8UC1);
}
else{
image = img;
}
// 改變影象
cv::Mat smallImg(cvRound(image.rows / scale), cvRound(image.cols / scale), CV_8UC1); //cvRound對double型資料進行四捨五入
cv::resize(image, smallImg, smallImg.size(), 0, 0, cv::INTER_LINEAR);
cv::equalizeHist(smallImg, smallImg); //equalizeHist提高影象的亮度和對比度
// --Detection
cascade.detectMultiScale(smallImg, faces,
1.1, 3, 0
/*|CV_HAAR_FIND_BIGGEST_OBJECT
|CV_HAAR_DO_ROUGH_SEARCH*/
| CV_HAAR_SCALE_IMAGE
,
cv::Size(30, 30));
if (faces.size() > 0)
{
size_t pos = name.find_last_of('\\');
std::string filename = name.substr(pos + 1);
if (-1 == _access(camera_face.c_str(), 0))
{
_mkdir(camera_face.c_str());
}
filename = camera_face + filename;
std::cout << filename << std::endl;
cv::imwrite(filename, img);
}
}
fin.close();
//處理後的圖片路徑名寫入Path_Image.txt中
std::string getImgPathTxt = "cd " + camera_face + " && dir /b/s/p/w *.jpg > Path_Images.txt";
system(getImgPathTxt.c_str());
}
std::vector<std::pair<cv::Mat, std::string >> get_CropFace_And_ImgPathName(const std::string recognitionPath, const std::string cascadeName)
{
std::vector<std::pair<cv::Mat, std::string>> cropFaceAndImgPathNames;
std::pair<cv::Mat, std::string> cropFaceAndImgPathName;
cv::CascadeClassifier cascade;
cascade.load(cascadeName);
if (cascade.empty())
{
std::cout << "Cascade path error!" << std::endl;
return std::vector<std::pair<cv::Mat, std::string >>();
}
std::ifstream fdatabase;
fdatabase.open(recognitionPath);
if (!fdatabase)
{
std::cout << "Cannot open " + recognitionPath << std::endl;
return std::vector<std::pair<cv::Mat, std::string >>();
}
double scale = 1.3;
std::vector<cv::Rect> faces;
cv::Mat gray;
std::string name;
std::cout << "[";
while (getline(fdatabase, name)){
if (name.empty())
{
continue;
}
name.erase(0, name.find_first_not_of(" \t"));
name.erase(name.find_last_not_of(" \t") + 1);
// Read Image
cv::Mat img = cv::imread(name);
if (img.empty())
{
continue;
}
cv::Mat image;
if (img.channels() != 1)
{
cvtColor(img, image, CV_BGR2GRAY);
image.convertTo(image, CV_8UC1);
}
else{
image = img;
}
// Read Opencv Detection Bbx
cv::Mat smallImg(cvRound(image.rows / scale), cvRound(image.cols / scale), CV_8UC1); //cvRound對double型資料進行四捨五入
cv::resize(image, smallImg, smallImg.size(), 0, 0, cv::INTER_LINEAR);
cv::equalizeHist(smallImg, smallImg); //equalizeHist提高影象的亮度和對比度
// --Detection
cascade.detectMultiScale(smallImg, faces,
1.1, 3, 0
/*|CV_HAAR_FIND_BIGGEST_OBJECT
|CV_HAAR_DO_ROUGH_SEARCH*/
| CV_HAAR_SCALE_IMAGE
,
cv::Size(30, 30));
for (std::vector<cv::Rect>::iterator r = faces.begin(); r != faces.end(); r++)
{
cv::Rect face;
face.x = int(r->x * scale);
face.y = int(r->y * scale);
face.width = int(r->width * scale);
face.height = int(r->height * scale);
// 邊界檢查，左邊界，上邊界，右邊界，下邊界。
/*face.x = face.x < 1 ? 1 : face.x;
face.y = face.y < 1 ? 1 : face.y;
face.width = (face.x + face.width) > image.cols ? (image.cols - face.x) : face.width;
face.height = (face.y + face.height) > image.rows ? (image.rows - face.y) : face.height;*/
cv::Mat cropFace;
cropFace = img(face);
/*cv::moveWindow("cropface", 960 - cropFace.cols / 2, 540 - cropFace.rows / 2);
cv::imshow("cropface", cropFace);
cv::waitKey(100);
cv::destroyWindow("cropface");*/
cropFaceAndImgPathName = make_pair(cropFace, name); //cropFaceAndImgPathName = std::pair<cv::Mat, std::string>(cropFace, name);
cropFaceAndImgPathNames.push_back(cropFaceAndImgPathName);
std::cout << '.';
}
}
fdatabase.close();
std::cout << "]" << std::endl;
return cropFaceAndImgPathNames;
}
bool matchFace(cv::Mat detectFace, cv::Mat dbFace)
{
IplImage* srcImg = cvCloneImage(&(IplImage)detectFace);
IplImage* dstImg = cvCloneImage(&(IplImage)dbFace);
IplImage* src;
IplImage* dst;
if (srcImg->nChannels != 1)
{
src = cvCreateImage(cvSize(srcImg->width, srcImg->height), srcImg->depth, 1);
cvCvtColor(srcImg, src, CV_BGR2GRAY);
}
if (dstImg->nChannels != 1)
{
dst = cvCreateImage(cvSize(dstImg->width, dstImg->height), dstImg->depth, 1);
cvCvtColor(dstImg, dst, CV_BGR2GRAY);
}
int histogramBins = 256;
float histogramRange1[2] = { 0, 255 };
float *histogramRange[1] = { &histogramRange1[0] };
CvHistogram *Histogram1 = cvCreateHist(1, &histogramBins, CV_HIST_ARRAY, histogramRange);
CvHistogram *Histogram2 = cvCreateHist(1, &histogramBins, CV_HIST_ARRAY, histogramRange);
cvCalcHist(&src, Histogram1);
cvCalcHist(&dst, Histogram2);
cvNormalizeHist(Histogram1, 1);
cvNormalizeHist(Histogram2, 1);
// CV_COMP_CHISQR,CV_COMP_BHATTACHARYYA這兩種都可以用來做直方圖的比較，值越小，說明圖形越相似
//printf("CV_COMP_CHISQR : %.4f\n", cvCompareHist(Histogram1, Histogram2, CV_COMP_CHISQR));
//printf("CV_COMP_BHATTACHARYYA : %.4f\n", cvCompareHist(Histogram1, Histogram2, CV_COMP_BHATTACHARYYA));
// CV_COMP_CORREL, CV_COMP_INTERSECT這兩種直方圖的比較，值越大，說明圖形越相似
//printf("CV_COMP_CORREL : %.4f\n", cvCompareHist(Histogram1, Histogram2, CV_COMP_CORREL));
//printf("CV_COMP_INTERSECT : %.4f\n", cvCompareHist(Histogram1, Histogram2, CV_COMP_INTERSECT));
double simility = cvCompareHist(Histogram1, Histogram2, CV_COMP_CHISQR);
if (simility > 0.5)
{
return false;
}
return true;
}
void face_recognition(std::string recognitionPath, const std::string cascadeName)
{
bool isPreDeal = false;
if (isPreDeal) //是否進行預處理
{
preDeal_original_img(recognitionPath, cascadeName);
recognitionPath = "../camera_face/";
}
//獲取資料庫中人臉影象
std::string face_Database = "../face_database/Path_Images.txt";
std::vector<std::pair<cv::Mat, std::string>> cropFaceAndImgPathNames;
std::cout << "開始資料庫中人臉資料的讀取..." << std::endl;
cropFaceAndImgPathNames = get_CropFace_And_ImgPathName(face_Database, cascadeName);
std::cout << "結束資料庫中人臉資料的讀取。" << std::endl;
//開始人臉匹配
std::ifstream frecognition;
frecognition.open(recognitionPath);
if (!frecognition)
{
std::cout << "Images path Error!" << std::endl;
return;
}
cv::CascadeClassifier cascade;
cascade.load(cascadeName);
if (cascade.empty())
{
std::cout << "Cascade path error!" << std::endl;
return;
}
double scale = 1.3;
std::vector<cv::Rect> faces;
cv::Mat gray;
std::string name;
bool isExist = false; //資料庫中是否存在該匹配檔案
while (getline(frecognition, name)){
if (name.empty())
{
continue;
}
name.erase(0, name.find_first_not_of(" \t"));
name.erase(name.find_last_not_of(" \t") + 1);
// Read Image
cv::Mat img = cv::imread(name);
cv::Mat image;
if (img.channels() != 1)
{
cvtColor(img, image, CV_BGR2GRAY);
image.convertTo(image, CV_8UC1);
}
else{
image = img;
}
// Read Opencv Detection Bbx
cv::Mat smallImg(cvRound(image.rows / scale), cvRound(image.cols / scale), CV_8UC1); //cvRound對double型資料進行四捨五入
cv::resize(image, smallImg, smallImg.size(), 0, 0, cv::INTER_LINEAR);
cv::equalizeHist(smallImg, smallImg); //equalizeHist提高影象的亮度和對比度
// --Detection
cascade.detectMultiScale(smallImg, faces,
1.1, 3, 0
/*|CV_HAAR_FIND_BIGGEST_OBJECT
|CV_HAAR_DO_ROUGH_SEARCH*/
| CV_HAAR_SCALE_IMAGE
,
cv::Size(30, 30));
for (std::vector<cv::Rect>::iterator r = faces.begin(); r != faces.end(); r++)
{
cv::Rect face;
face.x = int(r->x * scale);
face.y = int(r->y * scale);
face.width = int(r->width * scale);
face.height = int(r->height * scale);
cv::Mat detectFace = img(face);
for (std::vector<std::pair<cv::Mat, std::string>>::iterator dbFace = cropFaceAndImgPathNames.begin(); dbFace != cropFaceAndImgPathNames.end(); dbFace++)
{
std::pair<cv::Mat, std::string> dbFaceImg = *dbFace;
bool isMatch = matchFace(detectFace, dbFaceImg.first);
if (isMatch){
std::cout << name + " Matching " + dbFaceImg.second + " successful!" << std::endl;
cv::imshow("detectFace", detectFace);
cv::imshow("databaseFace", dbFaceImg.first);
cv::waitKey(200);
cv::destroyWindow("detectFace");
cv::destroyWindow("databaseFace");
isExist = true;
}
}
}
}
if (!isExist)
{
std::cout << name + " Matching failed!" << std::endl;
}
frecognition.close();
}
還有最後的主函式：main.cpp
#include "common.h"
#include "face_detetion_img.h"
#include "face_deteion_video.h"
#include "face_detetion_camera.h"
#include "face_recognition.h"
int main(int argc, char ** argv)
{
std::string cascadeFileName = "./../haarcascade_DataBase/haarcascade_frontalface_alt.xml";
//bool fileOrDir = isFileOrFolder(filePath);
if (argc < 2)
{
printf(help);
}
else if (strcmp(argv[1], "face_detetion_img") == 0)
{
std::string imgPath = "E:/1/ImagePath.txt";
face_detetion_img(imgPath, cascadeFileName);
}
else if (strcmp(argv[1], "face_detetion_video") == 0)
{
std::string videoPath = "E:\\DeepLeaning\\codes\\FindFaceInVideo\\VGGFace\\chengshd\\IMG_3170.mp4";
face_detetion_video(videoPath, cascadeFileName);
}
else if (strcmp(argv[1], "face_detetion_camera") == 0)
{
face_detetion_camera(cascadeFileName);
}
else if (strcmp(argv[1], "face_recognition") == 0)
{
std::string recognitionPath = "E:/camera/Path_Images.txt";
face_recognition(recognitionPath, cascadeFileName);
}
else
{
printf(help);
}
return 0;
}