批处理人脸检测区域的保存和下采样

花了一晚上时间，终于解决了检测到的人脸区域的保存和下采样，成果如下：

1.可以批处理一个文件夹下的所有图像；

2.利用opencv进行人脸的检测；

3.对检测到的人脸区域进行保存；

4.对人脸图像32*32的下采样保存。

源代码：

#include "cv.h"#include "highgui.h"#include <stdio.h>using namespace cv;#include<iostream>  #include<opencv2\opencv.hpp>  #include "opencv2/imgproc/imgproc.hpp"  #include "opencv2/highgui/highgui.hpp"  #include <math.h>   #include <stdio.h>   #include <cv.h>     #include <highgui.h>  #include<io.h>  using std::cout;using std::endl;using namespace std;#include <cmath>  #include<string.h>  #include <iostream>  #include <fstream>  using namespace std;int main(int argc, char** argv){CvHaarClassifierCascade * pCascade = 0;  // the face detectorCvMemStorage * pStorage = 0;        // expandable memory bufferCvSeq * pFaceRectSeq;               // list of detected facesint ii;// initializationsFILE *fp;char str0[200][100];char str2[200][100];char str3[200][100];int i, n = 0;system("dir /a-d /b E:\\pic\\安以轩\\ >d:\\cam5.txt");fp = fopen("d:\\cam5.txt", "r");while (1){if (fgets(str0[n], 50, fp) == NULL) break;str0[n][strlen(str0[n]) - 1] = '\0';   // 加一个字符串结束符  n++;}n--;fclose(fp);double value_psnr01 = 0;double value_ssim01 = 0;double value_psnr21 = 0;double value_ssim21 = 0;double value_psnr11 = 0;double value_ssim11 = 0;for (i = 0; i < 100; i++){char refColor[200] = "E:\\pic\\安以轩\\";strcat(refColor, str0[i]);IplImage * pInpImg = cvLoadImage(refColor, CV_LOAD_IMAGE_COLOR);pStorage = cvCreateMemStorage(0);pCascade = (CvHaarClassifierCascade *)cvLoad("D:\\opencv\\opencv\\sources\\data\\haarcascades\\haarcascade_frontalface_alt.xml", 0, 0, 0);// validate that everything initialized properlyif (!pInpImg || !pStorage || !pCascade){printf("Initialization failed: %s \n",(!pInpImg) ? "didn't load image file" :(!pCascade) ? "didn't load Haar cascade -- ""make sure path is correct" :"failed to allocate memory for data storage");exit(-1);}// detect faces in imagepFaceRectSeq = cvHaarDetectObjects(pInpImg, pCascade, pStorage,1.1,                       // increase search scale by 10% each pass   3,                         // drop groups of fewer than three detections   CV_HAAR_DO_CANNY_PRUNING,  // skip regions unlikely to contain a face   cvSize(0, 0));              // use XML default for smallest search scale// create a window to display detected faces//cvNamedWindow("Haar Window", CV_WINDOW_AUTOSIZE);//cv::Mat xMat;// draw a rectangular outline around each detectionfor (ii = 0; ii<(pFaceRectSeq ? pFaceRectSeq->total : 0); ii++){CvRect * r = (CvRect*)cvGetSeqElem(pFaceRectSeq, ii);CvPoint pt1 = { r->x, r->y };CvPoint pt2 = { r->x + r->width, r->y + r->height };CvSize size = cvSize(r->width, r->height);cvSetImageROI(pInpImg, cvRect(r->x, r->y, size.width, size.height));IplImage* pDest = cvCreateImage(size, pInpImg->depth, pInpImg->nChannels);cvCopy(pInpImg, pDest);//cvNamedWindow("ShowImage...", 1); //cvNamedWindow会创建一个显示窗口//cvShowImage("ShowImage...", pDest); //cvShowImage在窗口中显示创建的图像cvResetImageROI(pDest);cvSaveImage(refColor, pDest);cv::Mat pDest1 = imread(refColor);resize(pDest1, pDest1, Size(32, 32), 0, 0, CV_INTER_LINEAR);//imshow("wangjian",pDest1);imwrite(refColor, pDest1);cvRectangle(pInpImg, pt1, pt2, CV_RGB(0, 255, 0), 3, 4, 0);}// display face detections//cvShowImage("Haar Window", pInpImg);//cvWaitKey(0);//cvDestroyWindow("Haar Window");// clean up and release resourcescvReleaseImage(&pInpImg); }if (pCascade) cvReleaseHaarClassifierCascade(&pCascade);if (pStorage) cvReleaseMemStorage(&pStorage);return 0;}