#include "opencv2/video/tracking.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/highgui/highgui.hpp"
#include <iostream>
#include <ctype.h>
using namespace cv;
using namespace std;
Mat image;
bool backprojMode = false;
bool selectObject = false;//用来判断是否选中，当鼠标左键按下时为true，左键松开时为false
int trackObject = 0;
bool showHist = true;
Point origin;//选中的起点
Rect selection;//选中的区域
int vmin = 10, vmax = 256, smin = 30;//图像掩膜需要的边界常数
//鼠标事件响应函数，这个函数从按下左键时开始响应直到左键释放
static void onMouse( int event, int x, int y, int, void* )
{
if( selectObject )
{
//选择区域的x坐标选起点与当前点的最小值，保证鼠标不管向右下角还是左上角拉动都正确选择
selection.x = MIN(x, origin.x);
selection.y = MIN(y, origin.y);
//获得选择区域的宽和高
selection.width = std::abs(x - origin.x);
selection.height = std::abs(y - origin.y);
//这条语句多余，注释掉不影响结果
// selection &= Rect(0, 0, image.cols, image.rows);
}
switch( event )
{
case CV_EVENT_LBUTTONDOWN://按下鼠标时，捕获点origin
origin = Point(x,y);
selection = Rect(x,y,0,0);
selectObject = true;//这时switch前面的if语句条件为true，执行该语句
break;
case CV_EVENT_LBUTTONUP://松开鼠标时，捕获width和height
selectObject = false;
if( selection.width > 0 && selection.height > 0 )
trackObject = -1;//重新计算直方图
break;
}
}
static void help()//打印控制按键说明
{
cout << "\nThis is a demo that shows mean-shift based tracking\n"
"You select a color objects such as your face and it tracks it.\n"
"This reads from video camera (0 by default, or the camera number the user enters\n"
"Usage: \n"
" ./camshiftdemo [camera number]\n";
cout << "\n\nHot 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"
"\tp - pause video\n"
"To initialize tracking, select the object with mouse\n";
}
const char* keys =
{
"{1| | 0 | camera number}"
};
int main( int argc, const char** argv )
{
help();
VideoCapture cap;
Rect trackWindow;//要跟踪的窗口
int hsize = 16;//创建直方图时要用的常量
float hranges[] = {0,180};
const float* phranges = hranges;
CommandLineParser parser(argc, argv, keys);
int camNum = parser.get<int>("1");//现在camNum = 0
cap.open(camNum);
//摄像头画面捕捉不成功则退出程序
if( !cap.isOpened() )
{
help();
cout << "***Could not initialize capturing...***\n";
cout << "Current parameter's value: \n";
parser.printParams();//打印出cmd参数信息
return -1;
}
//关于显示窗口的一些设置
namedWindow( "Histogram", 0 );
namedWindow( "CamShift Demo", 0 );
//设置鼠标事件，把鼠标响应与onMouse函数关联起来
setMouseCallback( "CamShift Demo", onMouse, 0 );
//创建三个滑块条，特定条件用滑块条选择不同参数能获得较好的跟踪效果
createTrackbar( "Vmin", "CamShift Demo", &vmin, 256, 0 );
createTrackbar( "Vmax", "CamShift Demo", &vmax, 256, 0 );
createTrackbar( "Smin", "CamShift Demo", &smin, 256, 0 );
//创建Mat变量，frame, hsv, hue, mask, hist, histimg, backproj;其中histimg初始化为200*300的零矩阵
Mat frame, hsv, hue, mask, hist, histimg = Mat::zeros(200, 320, CV_8UC3), backproj;
bool paused = false;
//主循环
for(;;)
{
if( !paused )
{
cap >> frame;//从摄像头输入frame
if( frame.empty() )//为空，跳出主循环
break;
}
frame.copyTo(image);//frame存入image
if( !paused )
{
cvtColor(image, hsv, CV_BGR2HSV);//将BGR转换成HSV格式，存入hsv中，hsv是3通道
if( trackObject )//松开鼠标左键时，trackObject为-1，执行核心部分
{
int _vmin = vmin, _vmax = vmax;
//inRange用来检查元素的取值范围是否在另两个矩阵的元素取值之间，返回验证矩阵mask（0-1矩阵）
//这里用于制作掩膜板，只处理像素值为H:0~180，S:smin~256, V:vmin~vmax之间的部分。mask是要求的，单通道
inRange(hsv, Scalar(0, smin, MIN(_vmin,_vmax)),
Scalar(180, 256, MAX(_vmin, _vmax)), mask);
int ch[] = {0, 0};
//type包含通道信息，例如CV_8UC3，而深度信息depth不包含通道信息，例如CV_8U.
hue.create(hsv.size(), hsv.depth());//hue是单通道
mixChannels(&hsv, 1, &hue, 1, ch, 1);//将H分量拷贝到hue中，其他分量不拷贝。
if( trackObject < 0 )
{
//roi为选中区域的矩阵，maskroi为0-1矩阵
Mat roi(hue, selection), maskroi(mask, selection);
//绘制色调直方图hist，仅限于用户选定的目标矩形区域
calcHist(&roi, 1, 0, maskroi, hist, 1, &hsize, &phranges);
normalize(hist, hist, 0, 255, CV_MINMAX);//必须是单通道，hist是单通道。归一化，范围为0-255
trackWindow = selection;
trackObject = 1;//trackObject置1，接下来就不需要再执行这个if块了
histimg = Scalar::all(0);//用于显示直方图
//计算每个直方的宽度
int binW = histimg.cols / hsize;//hsize为16，共显示16个
Mat buf(1, hsize, CV_8UC3);//
for( int i = 0; i < hsize; i++ )
//直方图每一项的颜色是根据项数变化的
buf.at<Vec3b>(i) = Vec3b(saturate_cast<uchar>(i*180./hsize), 255, 255);
cvtColor(buf, buf, CV_HSV2BGR);
//量化等级一共有16个等级，故循环16次，画16个直方块
for( int i = 0; i < hsize; i++ )
{
int val = saturate_cast<int>(hist.at<float>(i)*histimg.rows/255);//获取直方图每一项的高
//画直方图。opencv中左上角为坐标原点
rectangle( histimg, Point(i*binW,histimg.rows),
Point((i+1)*binW,histimg.rows - val),
Scalar(buf.at<Vec3b>(i)), -1, 8 );
}
}
//根据直方图hist计算整幅图像的反向投影图backproj,backproj与hue相同大小
calcBackProject(&hue, 1, 0, hist, backproj, &phranges);
//计算两个矩阵backproj、mask的每个元素的按位与，返回backproj
backproj &= mask;
//调用最核心的camshift函数
//TermCriteria是算法完成的条件
RotatedRect trackBox = CamShift(backproj, trackWindow,
TermCriteria( CV_TERMCRIT_EPS | CV_TERMCRIT_ITER, 10, 1 ));
if( trackWindow.area() <= 1 )
{
int cols = backproj.cols, rows = backproj.rows, r = (MIN(cols, rows) + 5)/6;
trackWindow = Rect(trackWindow.x - r, trackWindow.y - r,
trackWindow.x + r, trackWindow.y + r) &
Rect(0, 0, cols, rows);
}
if( backprojMode )//转换显示方式，将backproj显示出来
cvtColor( backproj, image, CV_GRAY2BGR );
//画出椭圆，第二个参数是一个矩形，画该矩形的内接圆
ellipse( image, trackBox, Scalar(0,0,255), 3, CV_AA );
}
}
else if( trackObject < 0 )
paused = false;
if( selectObject && selection.width > 0 && selection.height > 0 )
{
Mat roi(image, selection);
bitwise_not(roi, roi);
}
imshow( "CamShift Demo", image );
imshow( "Histogram", histimg );
//每轮都要等待用户的按键控制
char c = (char)waitKey(10);
if( c == 27 )//"Esc"键，直接退出
break;
switch(c)
{
case 'b'://转换显示方式
backprojMode = !backprojMode;
break;
case 'c'://停止追踪
trackObject = 0;
histimg = Scalar::all(0);
break;
case 'h'://隐藏或显示直方图
showHist = !showHist;
if( !showHist )
destroyWindow( "Histogram" );
else
namedWindow( "Histogram", 1 );
break;
case 'p'://暂停
paused = !paused;//frame停止从摄像头获取图像，只显示旧的图像
break;
default:
;
}
}
return 0;
}
