opencv学习笔记（ 3 ）——face detect

opencv自带有很强大的分类器，haarcascade_frontalface_alt用于人脸分类。
电脑中的路径为：/opencv-2.4.9/data/haarcascades/haarcascade_frontalface_alt.xml

程序中我们直接调用即可。

下面这段程序实现了简单的人脸检测功能，同时将人脸部分的图像抠取出来，方便后续人脸识别等操作。

#include 
#include 
#include 
#include 
#include 

#include 
#include 

using namespace std;
using namespace cv;

/** Function Headers */
void detectAndDisplay( Mat frame );

/** Global variables */
String face_cascade_name = "/home/jeslie/Program/opencv-2.4.9/data/haarcascades/haarcascade_frontalface_alt.xml";
CascadeClassifier face_cascade;

//the point of the faces
int facx1,facx2,facy1,facy2;

//CascadeClassifier eyes_cascade;
String window_name = "Capture - Face detection";

/** @function main */
int main( void )
{
    /** declear the variable: camera and image */
    VideoCapture capture;
    Mat frame;

    //Load the cascades( loads a classifier from a file )
    if( !face_cascade.load( face_cascade_name ) ){ printf("--(!)Error loading face cascade\n"); return -1; };

    //Read the video stream
    capture.open( -1 );
    if ( ! capture.isOpened() ) { printf("--(!)Error opening video capture\n"); return -1; }

    while ( capture.read(frame) )
    {
        if( frame.empty() )
        {
            printf(" --(!) No captured frame -- Break!");
            break;
        }

        //3. Apply the classifier to the frame
        detectAndDisplay( frame );

        int c = waitKey(10);
        if( (char)c == 27 ) { break; } // escape
    }
    return 0;
}

/** @function detectAndDisplay */
void detectAndDisplay( Mat frame )
{
    std::vector faces;        //the list of rectangles returned
    Mat frame_gray;
    Mat face_get;
    Mat face_save;                  //the image saved
    //-- transfrom 3 channels image to gray-level image
    cvtColor( frame, frame_gray, COLOR_BGR2GRAY );          //function prototype: cvtColor(src, bwsrc, CV_RGB2GRAY);
    equalizeHist( frame_gray, frame_gray );                 //function prototype: void equalizeHist(InputArray src, OutputArray dst)

    //-- Detect faces ( Detects objects of different sizes in the input image.
    //                  The detected objects are returned as a list of rectangles. )
    face_cascade.detectMultiScale( frame_gray, faces, 1.1, 2, 0|CASCADE_SCALE_IMAGE, Size(30, 30) );

    //-- faces.size(): the number of the faces
    for ( size_t i = 0; i < faces.size(); i++ )
    {
        //get 4 points of the face
        facx1 = faces[i].x;
        facx2 = faces[i].x + faces[i].width;

        facy1 = faces[i].y;
        facy2 = faces[i].y + faces[i].height;

        //get the image of face
        face_get = frame( Range( facy1, facy2 ), Range( facx1, facx2 ) );
        resize( face_get, face_save, Size(150,150) );

        //find 2 points to detect the face
        Point pt1( faces[i].x, faces[i].y );
        Point pt2( faces[i].x + faces[i].width, faces[i].y + faces[i].height );
        //drawing a rectangle to mark the face
        rectangle( frame, pt1, pt2, Scalar( 255, 0, 255 ), 1, 8, 0 );
    }

    //-- Show what you got
    imshow( window_name, frame );
    if( faces.size() != 0 )
        imshow( "face_save", face_save );

    imwrite( "face.jpg", face_save );
    //bug: this demo can detect only one face.also,it is the last face.So you should think about how to improve it.
}

最后归纳几个函数的用法
1、cvtColor

void cvtColor( InputArray src, OutputArray dst, int code, int dstCn=0 );

用于改变图片的color space类型（eg. BGR2RGB, BGR2GRAY…….）
2、detectSingleScale

virtual bool detectSingleScale( const Mat& image, int stripCount, Size processingRectSize,
                                    int stripSize, int yStep, double factor, vector& candidates,
                                    vector<int>& rejectLevels, vector<double>& levelWeights, bool outputRejectLevels=false);

在代码中face_cascade.detectMultiScale( frame_gray, faces, 1.1, 2, 0|CASCADE_SCALE_IMAGE, Size(30, 30) );
可以看见这个函数的参数faces得到的是人脸的区域（矩形），可以用于后续的标记、抠图等操作。
3、face_get = frame( Range( facy1, facy2 ), Range( facx1, facx2 ) );
这也是opencv中常用的一种操作，用于获得图片中某一部分（抠图可以这么理解吧= =）。
4、resize( face_get, face_save, Size(150,150) );
resize也很常用，用于改变图片的尺寸，后续人脸识别等操作中要求图片尺寸和库中的尺寸相同。