camshiftdemo C註釋

//對運動物體的跟蹤：
//如果背景固定,可用幀差法 然後在計算下連通域 將面積小的去掉即可
//如果背景單一,即你要跟蹤的物體顏色和背景色有較大區別 可用基於顏色的跟蹤 如CAMSHIFT 魯棒性都是較好的
//如果背景複雜,如背景中有和前景一樣的顏色 就需要用到一些具有預測性的算法 如卡爾曼濾波等 可以和CAMSHIFT結合

#include "cv.h"
#include "highgui.h"
#include <stdio.h>
#include <ctype.h>

IplImage *image = 0, *hsv = 0, *hue = 0, *mask = 0, *backproject = 0, *histimg = 0;
//用HSV中的Hue分量進行跟蹤
CvHistogram *hist = 0;
//直方圖類
int backproject_mode = 0;
int select_object = 0;
int track_object = 0;
int show_hist = 1;
CvPoint origin;
CvRect selection;
CvRect track_window;
//CvRect
//矩形框的偏移和大小
//typedef struct CvRect
//{
//int x; /* 方形的最左角的x-座標 */
//int y; /* 方形的最上或者最下角的y-座標 */
//int width; /* 寬 */
//int height; /* 高 */
//}
//CvRect;
/* 構造函數*/
//inline CvRect cvRect( int x, int y, int width, int height );
CvBox2D track_box;  // tracking 返回的區域 box，帶角度
//typedef struct CvBox2D
//{
//CvPoint2D32f center; /* 盒子的中心 */
//CvSize2D32f size; /* 盒子的長和寬 */
//float angle; /* 水平軸與第一個邊的夾角，用弧度表示*/
//}實際上是橢圓的外接矩形，不同於CvRect結構，此矩形可以是傾斜的。畫橢圓那個函數也用到這個結構。
CvConnectedComp track_comp;
//連接部件
//  typedef struct CvConnectedComp {
//    double area; /* 連通域的面積 */
//    float value; /* 分割域的灰度縮放值 */
//    CvRect rect; /* 分割域的 ROI */
//   } CvConnectedComp;
int hdims = 48;
//劃分直方圖bins的個數，越多越精確
float hranges_arr[] = {0,180};
//像素值的範圍
float* hranges = hranges_arr;
//用於初始化CvHistogram類
int vmin = 10, vmax = 256, smin = 30;
//用於設置滑動條

//鼠標回調函數,該函數用鼠標進行跟蹤目標的選擇
void on_mouse( int event, int x, int y, int flags,void* param ) //源程序丟失 void* param
{
    if( !image )
        return;

    if( image->origin )
        y = image->height - y;
    //如果圖像原點座標在左下,則將其改爲左上
    if( select_object )
    //select_object爲1,表示在用鼠標進行目標選擇
    //此時對矩形類selection用當前的鼠標位置進行設置
    {
        selection.x = MIN(x,origin.x);  //#define MIN(a,b)  ((a) > (b) ? (b) : (a))
        selection.y = MIN(y,origin.y);
        selection.width = selection.x + CV_IABS(x - origin.x); //#define CV_IABS(a) (((a) ^ ((a) < 0 ? -1 : 0)) - ((a) < 0 ? -1 : 0))
        selection.height = selection.y + CV_IABS(y - origin.y);

        selection.x = MAX( selection.x, 0 );
        selection.y = MAX( selection.y, 0 );
        selection.width = MIN( selection.width, image->width );
        selection.height = MIN( selection.height, image->height );
        selection.width -= selection.x;
        selection.height -= selection.y;

    }

    switch( event )
    {
    case CV_EVENT_LBUTTONDOWN:
        //鼠標按下,開始點擊選擇跟蹤物體
        origin = cvPoint(x,y);
        selection = cvRect(x,y,0,0);//CvRect cvRect(int x(左上角), int y(左上角), int width, int height);
                                    //Stores coordinates of a rectangle.
        select_object = 1;
        break;
    case CV_EVENT_LBUTTONUP:
    //鼠標鬆開,完成選擇跟蹤物體
        select_object = 0;
        if( selection.width > 0 && selection.height > 0 )
        //如果選擇物體有效，則打開跟蹤功能
            track_object = -1;
#ifdef _DEBUG
    printf("\n # 鼠標的選擇區域：");
    printf("\n   X = %d, Y = %d, Width = %d, Height = %d",
        selection.x, selection.y, selection.width, selection.height);
#endif
        break;
    }
}


CvScalar hsv2rgb( float hue )
//用於將Hue量轉換成RGB量
{
    int rgb[3], p, sector;
    static const int sector_data[][3]=
        {{0,2,1}, {1,2,0}, {1,0,2}, {2,0,1}, {2,1,0}, {0,1,2}};
    hue *= 0.033333333333333333333333333333333f;
    sector = cvFloor(hue);
    p = cvRound(255*(hue - sector));
    p ^= sector & 1 ? 255 : 0;

    rgb[sector_data[sector][0]] = 255;
    rgb[sector_data[sector][1]] = 0;
    rgb[sector_data[sector][2]] = p;

#ifdef _DEBUG
    printf("\n # Convert HSV to RGB：");
    printf("\n   HUE = %f", hue);
    printf("\n   R = %d, G = %d, B = %d", rgb[0],rgb[1],rgb[2]);
#endif

    return cvScalar(rgb[2], rgb[1], rgb[0],0);
}

int main( int argc, char** argv )
{
    CvCapture* capture = 0;
    IplImage* frame = 0;

    if( argc == 1 || (argc == 2 && strlen(argv[1]) == 1 && isdigit(argv[1][0])))
        capture = cvCaptureFromCAM( argc == 2 ? argv[1][0] - '0' : 0 );
    else if( argc == 2 )
        capture = cvCaptureFromAVI( argv[1] );

    if( !capture )
    {
        fprintf(stderr,"Could not initialize capturing...\n");
        return -1;
    }

    printf( "Hot keys: \n"
        "\tESC - quit the program\n"
        "\tc - stop the tracking\n"
        "\tb - switch to/from backprojection view\n"
        "\th - show/hide object histogram\n"
        "To initialize tracking, select the object with mouse\n" );

    cvNamedWindow( "Histogram", 1 );
    //用於顯示直方圖
    cvNamedWindow( "CamShiftDemo", 1 );
    //用於顯示視頻
    cvSetMouseCallback( "CamShiftDemo", on_mouse, NULL );
    //設置鼠標回調函數
    cvCreateTrackbar( "Vmin", "CamShiftDemo", &vmin, 256, 0 );
    cvCreateTrackbar( "Vmax", "CamShiftDemo", &vmax, 256, 0 );
    cvCreateTrackbar( "Smin", "CamShiftDemo", &smin, 256, 0 );
    //設置滑動條

    for(;;)
    //進入視頻幀處理主循環
    {
        int i, bin_w, c;

        frame = cvQueryFrame( capture );
        if( !frame )
            break;

        if( !image )
        //image爲0,表明剛開始還未對image操作過,先建立一些緩衝區
        {
            /* allocate all the buffers */
            image = cvCreateImage( cvGetSize(frame), 8, 3 );
            image->origin = frame->origin;
            hsv = cvCreateImage( cvGetSize(frame), 8, 3 );
            hue = cvCreateImage( cvGetSize(frame), 8, 1 );
            mask = cvCreateImage( cvGetSize(frame), 8, 1 );
            //分配掩膜圖像空間
            backproject = cvCreateImage( cvGetSize(frame), 8, 1 );
            //分配反向投影圖空間,大小一樣,單通道
            hist = cvCreateHist( 1, &hdims, CV_HIST_ARRAY, &hranges, 1 );
            //分配直方圖空間// 計算直方圖
            histimg = cvCreateImage( cvSize(320,200), 8, 3 );
            //分配用於直方圖顯示的空間
            cvZero( histimg );
            //置背景爲黑色
        }

        cvCopy( frame, image, 0 );
        cvCvtColor( image, hsv, CV_BGR2HSV );  // 彩色空間轉換 BGR to HSV
        //把圖像從RGB表色系轉爲HSV表色系
        if( track_object )
        //track_object非零,表示有需要跟蹤的物體
        {
            int _vmin = vmin, _vmax = vmax;

            cvInRangeS( hsv, cvScalar(0,smin,MIN(_vmin,_vmax),0),
                        cvScalar(180,256,MAX(_vmin,_vmax),0), mask );
            //CVAPI(void) cvInRangeS( const CvArr* src, CvScalar lower,CvScalar upper, CvArr* dst );
            //製作掩膜板，只處理像素值爲H：0~180，S：smin~256，V：vmin~vmax之間的部分
            //用於檢查圖像中像素的灰度是否屬於某一指定範圍。cvInRange()檢查，src的每一個像素點是否落在lower和upper範圍中。
            //如果src的值大於或者等於lower值，並且小於upper值，那麼dst中對應的對應值將被設置爲0xff；否則，dst的值將被設置爲0。
            cvSplit( hsv, hue, 0, 0, 0 );  // 只提取 HUE 分量
            //Divides a multi-channel array into several single-channel arrays.
            //void cvSplit(const CvArr* src, CvArr* dst0, CvArr* dst1, CvArr* dst2, CvArr* dst3)
            if( track_object < 0 )
            //如果需要跟蹤的物體還沒有進行屬性提取，則進行選取框類的圖像屬性提取
            {
                float max_val = 0.f;
                cvSetImageROI( hue, selection );  // 得到選擇區域 for ROI 基於給定的矩形設置圖像的ROI（感興趣區域，region of interesting）
                //設置原選擇框爲ROI  void cvSetImageROI（IplImage* image，CvRect rect）
                cvSetImageROI( mask, selection ); // 得到選擇區域 for mask
                //設置掩膜板選擇框爲ROI
                cvCalcHist( &hue, hist, 0, mask ); // 計算直方圖
                //得到選擇框內且滿足掩膜板內的直方圖
                cvGetMinMaxHistValue( hist, 0, &max_val, 0, 0 );  // 只找最大值
                /* Finds indices and values of minimum and maximum histogram bins
                CVAPI(void)  cvGetMinMaxHistValue( const CvHistogram* hist,
                                   float* min_value, float* max_value,
                                   int* min_idx CV_DEFAULT(NULL),
                                   int* max_idx CV_DEFAULT(NULL));*/
                cvConvertScale( hist->bins, hist->bins, max_val ? 255. / max_val : 0., 0 );
                // 縮放 bin 到區間 [0,255]// 對直方圖的數值轉爲0~255
                //Converts one array to another with optional linear transformation.
                //dst(I) = scalesrc(I) + (shift0; shift1; :::)
                /*CVAPI(void)  cvConvertScale( const CvArr* src, CvArr* dst,
                             double scale CV_DEFAULT(1),
                             double shift CV_DEFAULT(0) );*/
                cvResetImageROI( hue );  // remove ROI
                /* Resets image ROI and COI
                   CVAPI(void)  cvResetImageROI( IplImage* image );*/
                cvResetImageROI( mask );
                //去除ROI
                track_window = selection;
                track_object = 1;
                //置track_object爲1,表明屬性提取完成
                //CvRect track_window;

                cvZero( histimg );
                //histimg = cvCreateImage( cvSize(320,200), 8, 3 );
                //分配用於直方圖顯示的空間
                bin_w = histimg->width / hdims;  // hdims: 條的個數，則 bin_w 爲條的寬度
                //int hdims = 48;劃分直方圖bins的個數，越多越精確

                // 畫直方圖
                for( i = 0; i < hdims; i++ )
                //畫直方圖到圖像空間
                {
                    int val = cvRound( cvGetReal1D(hist->bins,i)*histimg->height/255 );
                    //int cvRound (double value//對一個double型的數進行四捨五入，並返回一個整型數！
                    //CVAPI(double) cvGetReal1D( const CvArr* arr, int idx0 );
                    //Input array. Must have a single channel.
                    //Return a specific element of single-channel 1D, 2D, 3D or nD array.
                    CvScalar color = hsv2rgb(i*180.f/hdims);
                    cvRectangle( histimg, cvPoint(i*bin_w,histimg->height),
                                 cvPoint((i+1)*bin_w,histimg->height - val),
                                 color, -1, 8, 0 );
                    //void cvRectangle(CvArr* img, CvPoint pt1, CvPoint pt2, CvScalar color, int thickness=1,
                                        //int line-Type=8, int shift=0 ) pt1,pt2爲對頂點
                }
            }

            cvCalcBackProject( &hue, backproject, hist );
            //void cvCalcBackProject(IplImage** image, CvArr* backProject, const CvHistogram* hist)
            //計算hue的反向投影圖
            cvAnd( backproject, mask, backproject, 0 );
            //void cvAnd(const CvArr* src1, const CvArr* src2, CvArr* dst, const CvArr* mask=NULL)
            //得到掩膜內的反向投影

            // calling CAMSHIFT 算法模塊
            cvCamShift( backproject, track_window,
                        cvTermCriteria( CV_TERMCRIT_EPS | CV_TERMCRIT_ITER, 10, 1 ),
                        &track_comp, &track_box );  //CvBox2D track_box;CvRect track_window;
                        ////使用MeanShift算法對backproject中的內容進行搜索,返回跟蹤結果
            track_window = track_comp.rect;//收斂後搜索窗口的位置
            //得到跟蹤結果的矩形框
           //CvConnectedComp track_comp;
           //連接部件
           //  typedef struct CvConnectedComp {
           //    double area; /* 連通域的面積 */
           //    float value; /* 分割域的灰度縮放值 */
           //    CvRect rect; /* 分割域的 ROI */
           //   } CvConnectedComp;

            if( backproject_mode )  //int backproject_mode = 0;
                cvCvtColor( backproject, image, CV_GRAY2BGR ); // 使用backproject灰度圖像
            if( image->origin )  //image->origin = frame->origin;
                track_box.angle = -track_box.angle;
            cvEllipseBox( image, track_box, CV_RGB(255,0,0), 3, CV_AA, 0 );
            //void cvEllipseBox(CvArr* img, CvBox2D box, CvScalar color, int thickness=1, int lineType=8, int shift=0 )
            //畫橢圓
            //畫出跟蹤結果的位置
        }

        if( select_object && selection.width > 0 && selection.height > 0 )
        //如果正處於物體選擇，畫出選擇框
        {
            cvSetImageROI( image, selection );
            cvXorS( image, cvScalarAll(255), image, 0 );
            //void cvXorS(const CvArr* src, CvScalar value, CvArr* dst, const CvArr* mask=NULL)
            //src或value=dst
            cvResetImageROI( image );
        }

        cvShowImage( "CamShiftDemo", image );
        cvShowImage( "Histogram", histimg );

        c = cvWaitKey(10);
        if( c == 27 )
            break;  // exit from for-loop
        switch( c )
        {
        case 'b':
            backproject_mode ^= 1;//^異或操作，0^0=0,0^1=1,1^0=1,1^1=0
            break;
        case 'c':
            track_object = 0;
            cvZero( histimg );//直方圖清除後，track_object = 0;方便重新取屬性
            break;
        case 'h':
            show_hist ^= 1;
            if( !show_hist )
                cvDestroyWindow( "Histogram" );
            else
                cvNamedWindow( "Histogram", 1 );
            break;
        default:
            ;
        }
    }

    cvReleaseCapture( &capture );
    cvDestroyWindow("CamShiftDemo");

    return 0;
}