OpenCV simple face recognition program

This article shares the specific code of OpenCV face recognition program for your reference. The specific content is as follows

//Haar Feature detection, face recognition algorithm, is used xml As a trained classifier 
 
#include<opencv2\opencv.hpp>
#include<cstdio>
#include<cstdlib>
#include<Windows.h>
 
using namespace std;
int main()
{
 // loading Haar Feature detection classifier 
 // haarcascade_frontalface_alt.xml Department of OpenCV Built-in classifier 
 //
 //C++ There are still a lot of Pointers, 
 // Remember the newline usage, \ No Spaces after it 
 const char *pstrCascadeFileName = \
 "D:\\opencv2.4.9\\sources\\data\\haarcascades\\haarcascade_frontalface_alt.xml";
 CvHaarClassifierCascade *pHaarCascade = NULL; // define 1 A result of the training Hal has had 
 // Here, cascade mean 1 drops 1 Drops falling --- This is my English solution, so you can ignore it. 
 pHaarCascade = (CvHaarClassifierCascade *)cvLoad(pstrCascadeFileName); // Load existing xml file 
 
 // Load the image, and I'm going to use the pointer again 
 const char *pstrImageName = "E:\\testpictures\\meizi.jpg"; 
 IplImage *pSrcImage = cvLoadImage(pstrImageName, CV_LOAD_IMAGE_UNCHANGED); // Load the original image unchanged. 
 
 IplImage *pGrayImage = cvCreateImage(cvGetSize(pSrcImage), IPL_DEPTH_8U, 1);// create 8 So the size 1 Channel empty image 
 cvCvtColor(pSrcImage, pGrayImage, CV_BGR2GRAY);// Copy the image 
 
 // Face recognition and marking 
 if (pHaarCascade != NULL) // If you have xml File, then proceed 
 {
 
 //CvScalar : contains 4 a double Member, can be used to indicate B . G . R . alpha----alpha It's used to represent the transparency of the image 
 CvScalar FaceCircleColors[]= // This is a 1 These columns of colors can be viewed as palettes 
 {
 { {0,0,255} }, 
 { {0,128,255} },
 { {0,255,255} },
 { {0,255,0} },
 { {255,128,0} },
 { {255,255,0} },
 { {255,0,0} },
 { {255,0,255} }
 };
 // The memory memory is 1 Can be used to store such as sequences, Outlines, graphics ,  Subdivision and other dynamic growth of the underlying structure of the data structure. 
 CvMemStorage *pcvMStorage = cvCreateMemStorage(0);
 cvClearMemStorage(pcvMStorage); // Initialize memory 
 
 // identify 
 DWORD dwTimeBegin, dwTimeEnd; //DWORD  is  Double Word .   each word for 2 The length of two bytes 
 
 // in Release Version of this function from 0 Start the timer and return the number of milliseconds since the device started (excluding system pause time). 
 // in Debug In version 2, the timer is subtracted from the device when it starts 180 Seconds. This makes it easy to test the correct overflow handling of code using this function. 
 dwTimeBegin = GetTickCount(); 
 
 // Dense sequences are derived from CvSeq , they are used to represent extensible 1 Dimensional array   -   Vectors, stacks, queues, and double-ended queues. 
 // The sparse sequence derives from CvSet . CvSet Is based on CvSeq They are all made up of nodes, each 1 The nodes are either occupied, then empty, by the flag bit flag Decision. 
 // function  cvHaarDetectObjects  Using the cascade classifier trained for a target object, the rectangular regions containing the target object are found in the image, and these regions are taken as 1 Returns the rectangle of the sequence. 
 CvSeq *pcvSeqFaces = cvHaarDetectObjects(pGrayImage, pHaarCascade, pcvMStorage);// Get it here 1 Series rectangular box 
 dwTimeEnd = GetTickCount();
 
 printf(" Number of faces:  %d  Identification time:  %d ms \n", pcvSeqFaces->total, dwTimeEnd - dwTimeBegin);// Calculate the time and the number of rectangular boxes containing faces 
 
 // tag 
 for (int i = 0; i < pcvSeqFaces->total; i++)
 {
 CvRect* r = (CvRect*)cvGetSeqElem(pcvSeqFaces, i);// Extract each from the rectangular box dense sequence 1 A rectangular box 
 CvPoint center;// define 1 A midpoint 
 int radius;// define 1 A radius 
 center.x = cvRound((r->x + r->width*0.5));// Get the center point of the center of the circle x,y coordinates 
 center.y = cvRound((r->y + r->height*0.5));
 
 radius = cvRound((r->width + r->height)*0.25);// Simplify the calculation. It should be high 1 Half of the square and the width 1 Half a square. Take the square root 
 cvCircle(pSrcImage, center, radius, FaceCircleColors[i / 8], 2);// Circle the picture, color it in, 
 }
 cvReleaseMemStorage(&pcvMStorage);// Free memory 
 }
 
 
 // The new window displays the image, and the destroy window. 
 
 const char *pstrWindowTitle = " Face recognition ";
 cvNamedWindow(pstrWindowTitle, CV_WINDOW_AUTOSIZE);
 cvShowImage(pstrWindowTitle, pSrcImage);
 cvWaitKey(0);
 
 cvDestroyWindow(pstrWindowTitle);
 cvReleaseImage(&pSrcImage);
 cvReleaseImage(&pGrayImage);
 return 0;
 
 
}