JavaCVJar包(2.4.4)

package JavaCV.Test; import com.googlecode.javacpp.Pointer; import com.googlecode.javacv.cpp.opencv_highgui.CvCapture; import static com.googlecode.javacv.cpp.opencv_core.*; import static com.googlecode.javacv.cpp.opencv_imgproc.*; import static com.googlecode.javacv.cpp.opencv_highgui.*; import static com.googlecode.javacv.cpp.opencv_video.*; public class JavaCVCamShift{ IplImage frame, image , hsv , hue , mask , backproject , histimg ; IplImage[] imageArray; //用HSV中的Hue分量进行跟踪 CvHistogram hist ; //直方图类 int x1=0,y1=0,x2=0,y2=0;//选取对象的坐标 int backproject_mode = 0; int select_object = 0; int track_object = 0; int show_hist = 1; CvPoint origin; CvPoint cp1,cp2; CvRect selection; CvRect track_window; CvBox2D track_box; float[] max_val=new float[1]; int[] hdims = {16}; //划分直方图bins的个数，越多越精确 float[][] hranges_arr = {{0,180}}; //像素值的范围 float[][] hranges = hranges_arr; //用于初始化CvHistogram类 CvConnectedComp track_comp; public JavaCVCamShift() { imageArray=new IplImage[1]; CvCapture capture= cvCreateCameraCapture(0); cvNamedWindow("imageName",CV_WINDOW_AUTOSIZE); Pointer pointer=null; cvSetMouseCallback("imageName",new mouseClike(),pointer); track_comp=new CvConnectedComp(); while(true) { frame=cvQueryFrame(capture); if(frame==null)break; if( image==null ) //image为0,表明刚开始还未对image操作过,先建立一些缓冲区 { 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); //分配掩膜图像空间 backproject = cvCreateImage( cvGetSize(frame), 8, 1 ); //分配反向投影图空间,大小一样,单通道 hist = cvCreateHist( 1, hdims, CV_HIST_ARRAY, hranges, 1 ); //分配直方图空间 } cvCopy(frame,image); cvCvtColor( image, hsv, CV_BGR2HSV ); if( track_object !=0) //track_object非零,表示有需要跟踪的物体 { double _vmin = 10.0, _vmax = 256.0,smin=30.0; cvInRangeS( hsv, cvScalar(0.0,smin,Math.min(_vmin,_vmax),0.0), cvScalar(180.0,256.0,Math.max(_vmin,_vmax),0.0), mask ); //，只处理像素值为H：0~180，S：smin~256，V：vmin~vmax之间的部分制作掩膜板 cvSplit( hsv, hue, null, null, null ); //分离H分量 imageArray[0]=hue; if( track_object < 0 ) //如果需要跟踪的物体还没有进行属性提取，则进行选取框类的图像属性提取 { cvSetImageROI( imageArray[0],selection ); //设置原选择框为ROI cvSetImageROI( mask,selection ); //设置掩膜板选择框为ROI cvCalcHist( imageArray,hist,0,mask ); //得到选择框内且满足掩膜板内的直方图 cvGetMinMaxHistValue( hist, null, max_val, null, null ); cvConvertScale( hist.bins(), hist.bins(),max_val[0]>0 ? (double)255/ max_val[0]:0.0,0 ); // 对直方图的数值转为0~255 cvResetImageROI( imageArray[0] ); //去除ROI cvResetImageROI( mask ); //去除ROI track_window = selection; track_object = 1; //置track_object为1,表明属性提取完成 } cvCalcBackProject( imageArray, backproject, hist ); //计算hue的反向投影图 cvAnd( backproject, mask, backproject, null ); //得到掩膜内的反向投影 cvCamShift(backproject, track_window, cvTermCriteria( CV_TERMCRIT_EPS | CV_TERMCRIT_ITER, 10, 1 ), track_comp,track_box); //使用MeanShift算法对backproject中的内容进行搜索,返回跟踪结果 track_window = track_comp.rect(); //得到跟踪结果的矩形框 cp1=cvPoint(track_window.x(),track_window.y()); cp2=cvPoint(track_window.x()+track_window.width(),track_window.y()+track_window.height()); if( image.origin()>0 ) track_box.angle(-track_box.angle()); cvRectangle(frame,cp1,cp2, CV_RGB(0,255,0),3,CV_AA,0); } if( select_object==1 && selection.width() > 0 && selection.height() > 0 ) //如果正处于物体选择，画出选择框 { cvSetImageROI( frame, selection ); cvXorS(frame,cvScalarAll(255),frame,null ); cvResetImageROI( frame ); } cvShowImage("imageName",frame); int c=cvWaitKey(33); if(c==27) break; } cvReleaseCapture(capture); cvDestroyWindow("imageName"); } public static void main(String[] args) { new JavaCVCamShift(); } class mouseClike extends CvMouseCallback { public void call(int event,int x, int y,int flags, Pointer param) //鼠标回调函数,该函数用鼠标进行跟踪目标的选择 { if( image==null ) return; if( image.origin()!=0 ) y = image.height() - y; //如果图像原点坐标在左下,则将其改为左上 if( select_object==1 ) //select_object为1,表示在用鼠标进行目标选择 //此时对矩形类selection用当前的鼠标位置进行设置 { selection.x(Math.min(x,origin.x())); selection.y(Math.min(y,origin.y())); selection.width(selection.x() + Math.abs(x - origin.x())); selection.height(selection.y() + Math.abs(y - origin.y())); selection.x(Math.max(selection.x(),0)); selection.y(Math.max(selection.y(),0 )); selection.width(Math.min( selection.width(), image.width() )); selection.height(Math.min( selection.height(), image.height())); selection.width(selection.width()-selection.x()); selection.height( selection.height()-selection.y()); } switch( event ) { case CV_EVENT_LBUTTONDOWN: //鼠标按下,开始点击选择跟踪物体 origin = cvPoint(x,y); selection = cvRect(0,0,0,0); select_object = 1; break; case CV_EVENT_LBUTTONUP: //鼠标松开,完成选择跟踪物体 select_object = 0; if( selection.width() > 0 && selection.height() > 0 ) //如果选择物体有效，则打开跟踪功能 track_object = -1; // System.out.println("x:"+selection.x()+"y:"+selection.y()+"width:"+selection.width()+"heigth:"+selection.height()); break; } } } }