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OpenCV2.4版本的camshiftdemo.cpp的詳細注釋
要我怎麼感謝這位仁兄。。。
#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;//用來判斷是否選中，當鼠標左鍵按下時為true，左鍵鬆開時為false
int trackObject = 0;
bool showHist = true;
Point origin;//選中的起點
Rect selection;//選中的區域
int vmin = 10, vmax = 256, smin = 30;//圖像掩膜需要的邊界常數
//鼠標事件響應函數，這個函數從按下左鍵時開始響應直到左鍵釋放
static void onMouse( int event, int x, int y, int, void* )
{
if( selectObject )
{
//選擇區域的x坐標選起點與當前點的最小值，保證鼠標不管向右下角還是左上角拉動都正確選擇
selection.x = MIN(x, origin.x);
selection.y = MIN(y, origin.y);
//獲得選擇區域的寬和高
selection.width = std::abs(x - origin.x);
selection.height = std::abs(y - origin.y);
//這條語句多餘，注釋掉不影響結果
// selection &= Rect(0, 0, image.cols, image.rows);
}
switch( event )
{
case CV_EVENT_LBUTTONDOWN://按下鼠標時，捕獲點origin
origin = Point(x,y);
selection = Rect(x,y,0,0);
selectObject = true;//這時switch前麵的if語句條件為true，執行該語句
break;
case CV_EVENT_LBUTTONUP://鬆開鼠標時，捕獲width和height
selectObject = false;
if( selection.width > 0 && selection.height > 0 )
trackObject = -1;//重新計算直方圖
break;
}
}
static void help()//打印控製按鍵說明
{
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;//要跟蹤的窗口
int hsize = 16;//創建直方圖時要用的常量
float hranges[] = {0,180};
const float* phranges = hranges;
CommandLineParser parser(argc, argv, keys);
int camNum = parser.get<int>("1");//現在camNum = 0
cap.open(camNum);
//攝像頭畫麵捕捉不成功則退出程序
if( !cap.isOpened() )
{
help();
cout << "***Could not initialize capturing...***\n";
cout << "Current parameter's value: \n";
parser.printParams();//打印出cmd參數信息
return -1;
}
//關於顯示窗口的一些設置
namedWindow( "Histogram", 0 );
namedWindow( "CamShift Demo", 0 );
//設置鼠標事件，把鼠標響應與onMouse函數關聯起來
setMouseCallback( "CamShift Demo", onMouse, 0 );
//創建三個滑塊條，特定條件用滑塊條選擇不同參數能獲得較好的跟蹤效果
createTrackbar( "Vmin", "CamShift Demo", &vmin, 256, 0 );
createTrackbar( "Vmax", "CamShift Demo", &vmax, 256, 0 );
createTrackbar( "Smin", "CamShift Demo", &smin, 256, 0 );
//創建Mat變量，frame, hsv, hue, mask, hist, histimg, backproj;其中histimg初始化為200*300的零矩陣
Mat frame, hsv, hue, mask, hist, histimg = Mat::zeros(200, 320, CV_8UC3), backproj;
bool paused = false;
//主循環
for(;;)
{
if( !paused )
{
cap >> frame;//從攝像頭輸入frame
if( frame.empty() )//為空，跳出主循環
break;
}
frame.copyTo(image);//frame存入image
if( !paused )
{
cvtColor(image, hsv, CV_BGR2HSV);//將BGR轉換成HSV格式，存入hsv中，hsv是3通道
if( trackObject )//鬆開鼠標左鍵時，trackObject為-1，執行核心部分
{
int _vmin = vmin, _vmax = vmax;
//inRange用來檢查元素的取值範圍是否在另兩個矩陣的元素取值之間，返回驗證矩陣mask（0-1矩陣）
//這裏用於製作掩膜板，隻處理像素值為H:0~180，S:smin~256, V:vmin~vmax之間的部分。mask是要求的，單通道
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是單通道
mixChannels(&hsv, 1, &hue, 1, ch, 1);//將H分量拷貝到hue中，其他分量不拷貝。
if( trackObject < 0 )
{
//roi為選中區域的矩陣，maskroi為0-1矩陣
Mat roi(hue, selection), maskroi(mask, selection);
//繪製色調直方圖hist，僅限於用戶選定的目標矩形區域
calcHist(&roi, 1, 0, maskroi, hist, 1, &hsize, &phranges);
normalize(hist, hist, 0, 255, CV_MINMAX);//必須是單通道，hist是單通道。歸一化，範圍為0-255
trackWindow = selection;
trackObject = 1;//trackObject置1，接下來就不需要再執行這個if塊了
histimg = Scalar::all(0);//用於顯示直方圖
//計算每個直方的寬度
int binW = histimg.cols / hsize;//hsize為16，共顯示16個
Mat buf(1, hsize, CV_8UC3);//
for( int i = 0; i < hsize; i++ )
//直方圖每一項的顏色是根據項數變化的
buf.at<Vec3b>(i) = Vec3b(saturate_cast<uchar>(i*180./hsize), 255, 255);
cvtColor(buf, buf, CV_HSV2BGR);
//量化等級一共有16個等級，故循環16次，畫16個直方塊
for( int i = 0; i < hsize; i++ )
{
int val = saturate_cast<int>(hist.at<float>(i)*histimg.rows/255);//獲取直方圖每一項的高
//畫直方圖。opencv中左上角為坐標原點
rectangle( histimg, Point(i*binW,histimg.rows),
Point((i+1)*binW,histimg.rows - val),
Scalar(buf.at<Vec3b>(i)), -1, 8 );
}
}
//根據直方圖hist計算整幅圖像的反向投影圖backproj,backproj與hue相同大小
calcBackProject(&hue, 1, 0, hist, backproj, &phranges);
//計算兩個矩陣backproj、mask的每個元素的按位與，返回backproj
backproj &= mask;
//調用最核心的camshift函數
//TermCriteria是算法完成的條件
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 )//轉換顯示方式，將backproj顯示出來
cvtColor( backproj, image, CV_GRAY2BGR );
//畫出橢圓，第二個參數是一個矩形，畫該矩形的內接圓
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 );
//每輪都要等待用戶的按鍵控製
char c = (char)waitKey(10);
if( c == 27 )//"Esc"鍵，直接退出
break;
switch(c)
{
case 'b'://轉換顯示方式
backprojMode = !backprojMode;
break;
case 'c'://停止追蹤
trackObject = 0;
histimg = Scalar::all(0);
break;
case 'h'://隱藏或顯示直方圖
showHist = !showHist;
if( !showHist )
destroyWindow( "Histogram" );
else
namedWindow( "Histogram", 1 );
break;
case 'p'://暫停
paused = !paused;//frame停止從攝像頭獲取圖像，隻顯示舊的圖像
break;
default:
;
}
}
return 0;
}
OpenCV2.4版本的camshiftdemo.cpp的詳細注釋
最後更新：2017-04-03 05:39:52