python，OpenCV，camShift，目标跟踪
之前一直都是用的网上c++版本的代码，最近想做一些拓展，要用python来实现。在网上找 了一下，感觉不是很好用。于是参照官方文档和c++版本的代码改写了一些。参数也没怎么调整就直接用了。
import cv2
import numpy as np
xs,ys,ws,hs = 0,0,0,0 #selection.x selection.y
xo,yo=0,0 #origin.x origin.y
selectObject = False
trackObject = 0
def onMouse(event, x, y, flags, prams):
global xs,ys,ws,hs,selectObject,xo,yo,trackObject
if selectObject == True:
xs = min(x, xo)
ys = min(y, yo)
ws = abs(x-xo)
hs = abs(y-yo)
if event == cv2.EVENT_LBUTTONDOWN:
xo,yo = x, y
xs,ys,ws,hs= x, y, 0, 0
selectObject = True
elif event == cv2.EVENT_LBUTTONUP:
selectObject = False
trackObject = -1
cap = cv2.VideoCapture(0)
ret,frame = cap.read()
cv2.namedWindow('imshow')
cv2.setMouseCallback('imshow',onMouse)
term_crit = ( cv2.TERM_CRITERIA_EPS | cv2.TERM_CRITERIA_COUNT, 10, 1 )
while(True):
ret,frame = cap.read()
if trackObject != 0:
hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
mask = cv2.inRange(hsv, np.array((0., 30.,10.)), np.array((180.,256.,255.)))
if trackObject == -1:
track_window=(xs,ys,ws,hs)
maskroi = mask[ys:ys+hs, xs:xs+ws]
hsv_roi = hsv[ys:ys+hs, xs:xs+ws]
roi_hist = cv2.calcHist([hsv_roi],[0],maskroi,[180],[0,180])
cv2.normalize(roi_hist,roi_hist,0,255,cv2.NORM_MINMAX)
trackObject = 1
dst = cv2.calcBackProject([hsv], [0], roi_hist, [0, 180], 1)
dst &= mask
ret, track_window = cv2.CamShift(dst, track_window, term_crit)
pts = cv2.boxPoints(ret)
pts = np.int0(pts)
img2 = cv2.polylines(frame,[pts],True, 255,2)
if selectObject == True and ws>0 and hs>0:
cv2.imshow('imshow1',frame[ys:ys+hs,xs:xs+ws])
cv2.bitwise_not(frame[ys:ys+hs,xs:xs+ws],frame[ys:ys+hs,xs:xs+ws])
cv2.imshow('imshow',frame)
if cv2.waitKey(10)==27:
break
cv2.destroyAllWindows()还有就是参考的c++代码
//---------------------------------【头文件、命名空间包含部分】----------------------------
// 描述：包含程序所使用的头文件和命名空间
//-------------------------------------------------------------------------------------------------
#include "opencv2/video/tracking.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/highgui/highgui.hpp"
#include
#include
#include
using namespace cv;
using namespace std;
//-----------------------------------【全局变量声明】-----------------------------------------
// 描述：声明全局变量
//-------------------------------------------------------------------------------------------------
Mat image;
bool backprojMode = false;
bool selectObject = false;
int trackObject = 0;
bool showHist = true;
Point origin;
Rect selection;
int vmin = 10, vmax = 256, smin = 30;
//--------------------------------【onMouse( )回调函数】------------------------------------
// 描述：鼠标操作回调
//-------------------------------------------------------------------------------------------------
static void onMouse( int event, int x, int y, int, void* )
{
if( selectObject )
{
selection.x = MIN(x, origin.x);
selection.y = MIN(y, origin.y);
selection.width = std::abs(x - origin.x);
selection.height = std::abs(y - origin.y);
selection &= Rect(0, 0, image.cols, image.rows);
}
switch( event )
{
//此句代码的OpenCV2版为：
//case CV_EVENT_LBUTTONDOWN:
//此句代码的OpenCV3版为：
case EVENT_LBUTTONDOWN:
origin = Point(x,y);
selection = Rect(x,y,0,0);
selectObject = true;
break;
//此句代码的OpenCV2版为：
//case CV_EVENT_LBUTTONUP:
//此句代码的OpenCV3版为：
case EVENT_LBUTTONUP:
selectObject = false;
if( selection.width > 0 && selection.height > 0 )
trackObject = -1;
break;
}
}
//--------------------------------【help( )函数】----------------------------------------------
// 描述：输出帮助信息
//-------------------------------------------------------------------------------------------------
static void ShowHelpText()
{
cout <<"\n\n\t\t\t非常感谢购买《OpenCV3编程入门》一书！\n"
<<"\n\n\t\t\t此为本书OpenCV3版的第8个配套示例程序\n"
<< "\n\n\t\t\t 当前使用的OpenCV版本为：" << CV_VERSION
<<"\n\n ----------------------------------------------------------------------------" ;
cout << "\n\n\t此Demo显示了基于均值漂移的追踪（tracking）技术\n"
"\t请用鼠标框选一个有颜色的物体，对它进行追踪操作\n";
cout << "\n\n\t操作说明： \n"
"\t\t用鼠标框选对象来初始化跟踪\n"
"\t\tESC - 退出程序\n"
"\t\tc - 停止追踪\n"
"\t\tb - 开/关-投影视图\n"
"\t\th - 显示/隐藏-对象直方图\n"
"\t\tp - 暂停视频\n";
}
const char* keys =
{
"{1| | 0 | camera number}"
};
//-----------------------------------【main( )函数】--------------------------------------------
// 描述：控制台应用程序的入口函数，我们的程序从这里开始
//-------------------------------------------------------------------------------------------------
int main( int argc, const char** argv )
{
ShowHelpText();
VideoCapture cap;
Rect trackWindow;
int hsize = 16;
float hranges[] = {0,180};
const float* phranges = hranges;
cap.open(0);
//cap.open("H:\\opencv\\ai.avi");
if( !cap.isOpened() )
{
cout << "不能初始化摄像头\n";
}
namedWindow( "Histogram", 0 );//颜色直方图窗口
namedWindow( "CamShift Demo", 0 );//跟踪图像窗口
setMouseCallback( "CamShift Demo", onMouse, 0 );//关联鼠标事件
createTrackbar( "Vmin", "CamShift Demo", &vmin, 256, 0 );//颜色空间参数设置
createTrackbar( "Vmax", "CamShift Demo", &vmax, 256, 0 );
createTrackbar( "Smin", "CamShift Demo", &smin, 256, 0 );
Mat frame, hsv, hue, mask, hist, histimg = Mat::zeros(200, 320, CV_8UC3), backproj;
bool paused = false;//暂停
LARGE_INTEGER _start, _stop;
double start, stop;
for(;;)
{
QueryPerformanceCounter(&_start);
start = (double)_start.QuadPart; //获得计数器计数初值
if( !paused )
{
cap >> frame;
if( frame.empty() )
break;
}
QueryPerformanceCounter(&_stop); //获取计数器当前值
stop = (double)_stop.QuadPart;
cout << (stop - start) * 10 / 25332 << endl;;
frame.copyTo(image);
if( !paused )//如果么有暂停。。。要是我就不会那么多事设置一个暂停在这
{
cvtColor(image, hsv, COLOR_BGR2HSV);//将图像转换为hsv颜色空间
if( trackObject )//只有等于0的时候不跟踪？
{
int _vmin = vmin, _vmax = vmax;//颜色空间参数
inRange(hsv, Scalar(0, smin, MIN(_vmin,_vmax)),
Scalar(180, 256, MAX(_vmin, _vmax)), mask);
int ch[] = {0, 0};
hue.create(hsv.size(), hsv.depth());//反向直方图
mixChannels(&hsv, 1, &hue, 1, ch, 1);
if( trackObject < 0 )//已经用鼠标选取完区域后就可以跟踪了。。
{
Mat roi(hue, selection), maskroi(mask, selection);
calcHist(&roi, 1, 0, maskroi, hist, 1, &hsize, &phranges);
//此句代码的OpenCV3版为：
normalize(hist, hist, 0, 255, NORM_MINMAX);
//此句代码的OpenCV2版为：
//normalize(hist, hist, 0, 255, CV_MINMAX);
trackWindow = selection;
trackObject = 1;
histimg = Scalar::all(0);
int binW = histimg.cols / hsize;
Mat buf(1, hsize, CV_8UC3);
for( int i = 0; i < hsize; i++ )
buf.at(i) = Vec3b(saturate_cast(i*180./hsize), 255, 255);
//此句代码的OpenCV3版为：
cvtColor(buf, buf, COLOR_HSV2BGR);
//此句代码的OpenCV2版为：
//cvtColor(buf, buf, CV_HSV2BGR);
for( int i = 0; i < hsize; i++ )
{
int val = saturate_cast(hist.at(i)*histimg.rows/255);
rectangle( histimg, Point(i*binW,histimg.rows),
Point((i+1)*binW,histimg.rows - val),
Scalar(buf.at(i)), -1, 8 );
}
}
calcBackProject(&hue, 1, 0, hist, backproj, &phranges);
cv::imshow("backproj", backproj);
backproj &= mask;
RotatedRect trackBox = CamShift(backproj, trackWindow,
//此句代码的OpenCV3版为：
TermCriteria( TermCriteria::EPS | TermCriteria::COUNT, 10, 1 ));
//此句代码的OpenCV2版为：
//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 )
cvtColor( backproj, image, COLOR_GRAY2BGR );
//此句代码的OpenCV3版为：
ellipse( image, trackBox, Scalar(0,0,255), 3, LINE_AA );
//此句代码的OpenCV2版为：
//ellipse( image, trackBox, Scalar(0,0,255), 3, CV_AA );
}
}
else if( trackObject < 0 )//也就是说鼠标选定区域后，暂停键失效
paused = false;
if( selectObject && selection.width > 0 && selection.height > 0 )
{
Mat roi(image, selection);
bitwise_not(roi, roi);
}
cv::imshow( "CamShift Demo", image );
cv::imshow( "Histogram", histimg );
char c = (char)waitKey(90);
if( c == 27 )
break;
switch(c)
{
case 'b':
backprojMode = !backprojMode;
break;
case 'c':
trackObject = 0;
histimg = Scalar::all(0);
break;
case 'h':
showHist = !showHist;
if( !showHist )
destroyWindow( "Histogram" );
else
namedWindow( "Histogram", 1 );
break;
case 'p':
paused = !paused;
break;
case 'k':
{
imwrite("pic.jpg", image);
break;
}
default:
;
}
}
return 0;
}