OpenCV人脸检测并把图片写成avi视频

　　读出某一个文件夹下“jpg”后缀的全部图片后，用的OpenCV自带的人脸检测检测图片中的人脸，调整图片的大小写成一个avi视频。

　　主要是要记录一下CvVideoWriter的用法和如何从文件夹中读取某一后缀的全部文件。

代码：

#include "stdafx.h"#include <opencv2\opencv.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/imgproc/imgproc.hpp>
#include <opencv2/core/core.hpp>
#include <opencv2/objdetect/objdetect.hpp>
#include <iostream>
#include <string>#include <stdio.h> 
#include <stdlib.h> 
#include <assert.h> 
#include <math.h> 
#include <float.h> 
#include <limits.h> 
#include <time.h> 
#include <ctype.h>
#include <io.h>  using namespace cv;
using namespace std;void detectAndDraw( Mat& img, CascadeClassifier& cascade,CascadeClassifier& nestedCascade,double scale, bool tryflip );int main(int argc, char** argv)  
{  CascadeClassifier cascade, nestedCascade;bool stop = false;//训练好的文件名称，放置在可执行文件同目录下cascade.load("haarcascade_frontalface_alt.xml");nestedCascade.load("haarcascade_eye_tree_eyeglasses.xml");// 图片集  string fileFolderPath = "F:\\picture";  string fileExtension = "jpg";  string fileFolder = fileFolderPath + "\\*." + fileExtension;  int codec = 0;  double frameRate = 1;  CvSize frameSize;  struct _finddata_t fileInfo;    // 文件信息结构体// 1. 第一次查找  long findResult = _findfirst(fileFolder.c_str(), &fileInfo);            if (findResult == -1)  {  _findclose(findResult);   return -1;  }  //2.设置视频的宽度和高度为 读取到的图片的最大宽度和最大高度int width = 0 ;int height = 0 ;IplImage* img;  string file_path ;do   {string temp_name =  fileInfo.name;file_path = fileFolderPath + "\\" +  temp_name ;img = cvLoadImage(file_path.c_str());    // 读入图片 if(img->width > width){width = img->width ;}if(img->height > height){height = img->height ;}} while (!_findnext(findResult, &fileInfo));_findclose(findResult); // 3.生成视频  frameSize.width  = width ;frameSize.height = height ;int zero_H = 0 ;int zero_W = 0 ;CvVideoWriter* writer = cvCreateVideoWriter("output.avi",CV_FOURCC('X','V','I','D'),frameRate,frameSize);cvNamedWindow("Pic2avi",0);cvNamedWindow("img");  struct _finddata_t fileInfo2;    // 文件信息结构体long findResult2 = _findfirst(fileFolder.c_str(), &fileInfo2);            if (findResult2 == -1)  {  _findclose(findResult2);   return -1;  }  do   {  string t_name =  fileInfo2.name;string t_file_path = fileFolderPath + "\\" +  t_name ;IplImage* frame = cvLoadImage(t_file_path.c_str(), 1);    // 读入图片cvShowImage("img", frame); IplImage* temp_frame = cvCreateImage(frameSize, IPL_DEPTH_8U, 3) ;if(frame->width <= frameSize.width){zero_W = (frameSize.width - frame->width) / 2 ;}if(frame->height <= frameSize.height){zero_H = (frameSize.height - frame->height) / 2 ;}CvRect roi =cvRect(zero_W, zero_H, frame->width, frame->height);cvSetImageROI(temp_frame,roi) ;cvResize(frame, temp_frame);cvResetImageROI(temp_frame) ;detectAndDraw( cv::Mat(temp_frame) , cascade, nestedCascade,2,0 );cvWriteFrame(writer,temp_frame); cvShowImage("Pic2avi", temp_frame);   cvWaitKey(100);frame = NULL ;temp_frame = NULL ;} while (!_findnext(findResult2, &fileInfo2));    _findclose(findResult2);   return 0;  
}  void detectAndDraw( Mat& img, CascadeClassifier& cascade,CascadeClassifier& nestedCascade,double scale, bool tryflip )
{int i = 0;double t = 0;//建立用于存放人脸的向量容器vector<Rect> faces, faces2;//定义一些颜色，用来标示不同的人脸const static Scalar colors[] =  { CV_RGB(0,0,255),CV_RGB(0,128,255),CV_RGB(0,255,255),CV_RGB(0,255,0),CV_RGB(255,128,0),CV_RGB(255,255,0),CV_RGB(255,0,0),CV_RGB(255,0,255)} ;//建立缩小的图片，加快检测速度//nt cvRound (double value) 对一个double型的数进行四舍五入，并返回一个整型数！Mat gray, smallImg( cvRound (img.rows/scale), cvRound(img.cols/scale), CV_8UC1 );//转成灰度图像，Harr特征基于灰度图cvtColor( img, gray, CV_BGR2GRAY );//改变图像大小，使用双线性差值resize( gray, smallImg, smallImg.size(), 0, 0, INTER_LINEAR );//变换后的图像进行直方图均值化处理equalizeHist( smallImg, smallImg );//程序开始和结束插入此函数获取时间，经过计算求得算法执行时间t = (double)cvGetTickCount();//检测人脸//detectMultiScale函数中smallImg表示的是要检测的输入图像为smallImg，faces表示检测到的人脸目标序列，1.1表示//每次图像尺寸减小的比例为1.1，2表示每一个目标至少要被检测到3次才算是真的目标(因为周围的像素和不同的窗口大//小都可以检测到人脸),CV_HAAR_SCALE_IMAGE表示不是缩放分类器来检测，而是缩放图像，Size(30, 30)为目标的//最小最大尺寸cascade.detectMultiScale( smallImg, faces,1.1, 2, 0//|CV_HAAR_FIND_BIGGEST_OBJECT//|CV_HAAR_DO_ROUGH_SEARCH|CV_HAAR_SCALE_IMAGE,Size(30, 30));//如果使能，翻转图像继续检测if( tryflip ){flip(smallImg, smallImg, 1);cascade.detectMultiScale( smallImg, faces2,1.1, 2, 0//|CV_HAAR_FIND_BIGGEST_OBJECT//|CV_HAAR_DO_ROUGH_SEARCH|CV_HAAR_SCALE_IMAGE,Size(30, 30) );for( vector<Rect>::const_iterator r = faces2.begin(); r != faces2.end(); r++ ){faces.push_back(Rect(smallImg.cols - r->x - r->width, r->y, r->width, r->height));}}t = (double)cvGetTickCount() - t;//   qDebug( "detection time = %g ms\n", t/((double)cvGetTickFrequency()*1000.) );for( vector<Rect>::const_iterator r = faces.begin(); r != faces.end(); r++, i++ ){Mat smallImgROI;vector<Rect> nestedObjects;Point center;Scalar color = colors[i%8];int radius;double aspect_ratio = (double)r->width/r->height;if( 0.75 < aspect_ratio && aspect_ratio < 1.3 ){//标示人脸时在缩小之前的图像上标示，所以这里根据缩放比例换算回去center.x = cvRound((r->x + r->width*0.5)*scale);center.y = cvRound((r->y + r->height*0.5)*scale);radius = cvRound((r->width + r->height)*0.25*scale);circle( img, center, radius, color, 3, 8, 0 );}elserectangle( img, cvPoint(cvRound(r->x*scale), cvRound(r->y*scale)),cvPoint(cvRound((r->x + r->width-1)*scale), cvRound((r->y + r->height-1)*scale)),color, 3, 8, 0);if( nestedCascade.empty() )continue;smallImgROI = smallImg(*r);//同样方法检测人眼nestedCascade.detectMultiScale( smallImgROI, nestedObjects,1.1, 2, 0//|CV_HAAR_FIND_BIGGEST_OBJECT//|CV_HAAR_DO_ROUGH_SEARCH|CV_HAAR_DO_CANNY_PRUNING//|CV_HAAR_SCALE_IMAGE,Size(30, 30) );for( vector<Rect>::const_iterator nr = nestedObjects.begin(); nr != nestedObjects.end(); nr++ ){center.x = cvRound((r->x + nr->x + nr->width*0.5)*scale);center.y = cvRound((r->y + nr->y + nr->height*0.5)*scale);radius = cvRound((nr->width + nr->height)*0.25*scale);circle( img, center, radius, color, 3, 8, 0 );}}cv::imshow( "result", img );
}

代码中，

CvVideoWriter* writer = cvCreateVideoWriter("output.avi",CV_FOURCC('X','V','I','D'),frameRate,frameSize);

这部分用来设置生成的avi视频的各个参数。
　　
注释中的1和2就是从文件夹中读取某一后缀的全部文件。