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 detector
	CvMemStorage * pStorage = 0;        // expandable memory buffer
	CvSeq * pFaceRectSeq;               // list of detected faces
	int ii;

	// initializations
	FILE *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 properly
		if (!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 image
		pFaceRectSeq = 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 detection
		for (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 resources
		cvReleaseImage(&pInpImg);

	}

	if (pCascade) cvReleaseHaarClassifierCascade(&pCascade);
	if (pStorage) cvReleaseMemStorage(&pStorage);
	return 0;
}