而输出文本只需要设置字体，文本输出位置，文本的颜色，文本字符串，显示文本的图像这几个参数.下面说一下输出文本的函数：void cvPutText{CvArr * img,const char* text,CvPoint...All Rights Reserved.";/* 文本字符串2 *//* 定义要显示文字的位置、颜色和字体 */CvPoint point1 = cvPoint(50, 50);CvPoint point2...= cvPoint(80, 80);/* 设置字体在图片中出现的位置 */CvPoint point3 = cvPoint(110, 110);CvPoint point4 = cvPoint(10,
imgA,//初始图像 const CvArr* imgB,//最终图像 CvArr* pyrA, CvArr* pyrB,//pyrA,B申请存放两幅图像金字塔的缓存 CvPoint2D32f...* featuresA,//存放的是用于寻找运动的点 CvPoint2D32f* featuresB,//存放featuresA中点的新位置 int count,//featuresA中点的数目...*cornersA = new CvPoint2D32f[MAX_CORNERS]; cvGoodFeaturesToTrack( imgA, eig_image...*cornersB = new CvPoint2D32f[MAX_CORNERS]; cvCalcOpticalFlowPyrLK( imgA, imgB,...p0 = cvPoint(cvRound(cornersA[i].x), cvRound(cornersA[i].y)); CvPoint p1 = cvPoint(cvRound(cornersB
struct CvPoint { int x; int y; } CvPoint; color：边的颜色 CvScalar结构 typedef struct CvScalar {...(3, 3), cvPoint(3, 300), CV_RGB(255, 255, 255), 1, 8); cvRectangle(src, cvPoint(10, 10), cvPoint(100...[3]=cvPoint(800,300); PointArray1[4]=cvPoint(900,550); PointArray1[5]=cvPoint(100,400);...** pt=new CvPoint*[1]; pt[0]=new CvPoint[6]; pt[0][0]=cvPoint(100, 100); pt[0][1]=cvPoint(400, 50...); pt[0][2]=cvPoint(500, 400); pt[0][3]=cvPoint(300, 500); pt[0][4]=cvPoint(200, 300); pt[0][5]=cvPoint
IplImage* marker_mask = 0; IplImage* markers = 0; IplImage* img0 = 0, *img = 0, *img_gray = 0, *wshed = 0; CvPoint...(flags & CV_EVENT_FLAG_LBUTTON) ) prev_pt = cvPoint(-1,-1); else if( event == CV_EVENT_LBUTTONDOWN...) prev_pt = cvPoint(x,y); else if( event == CV_EVENT_MOUSEMOVE && (flags & CV_EVENT_FLAG_LBUTTON...) ) { CvPoint pt = cvPoint(x,y); if( prev_pt.x < 0 ) prev_pt = pt;...contours, cvScalarAll(comp_count+1), cvScalarAll(comp_count+1), -1, -1, 8, cvPoint
Gaussian distribution */ for( k = 0; k < cluster_count; k++ ) { CvPoint...* pt1 = (CvPoint2D32f*)points->data.fl + cvRandInt(&rng)%sample_count...; CvPoint2D32f* pt2 = (CvPoint2D32f*)points->data.fl +...cvRandInt(&rng)%sample_count; CvPoint2D32f temp; CV_SWAP( *pt1, *pt2, temp );...pt = ((CvPoint2D32f*)points->data.fl)[i]; int cluster_idx = clusters->data.i[i];
cxcore.h> #include class Finger { public: Finger() { area = 0.0f; w=h=0; }; public: CvPoint...(0,0) ); if(mt_contour) { CvSeqReader reader; int i; CvPoint left_top_pt=cvPoint(img->width,img...->height); CvPoint right_bottom_pt=cvPoint(0,0); CvPoint pt; CvSeq *contour2 = mt_contour;...pt = FingerTrackList[i].track[j].center; CvPoint pt_next = FingerTrackList[i].track[j+1].center;...,cvPoint(0,image2->height/2),cvPoint(image2->width ,image2->height/2),CV_RGB(255,255,0),2,8,0);
OpenCV 中的cvCircle和cvRectangle函数 void cvCircle(CvArr* img, CvPoint center, int radius, CvScalar...Rectangle void cvRectangle(CvArr* img, CvPoint pt1, CvPoint pt2, CvScalar color, int
> forePts; vector backPts; IplImage* image; // average color of foreground points...> points); bool isPtInVector(CvPoint pt, vector points); void getE1(unsigned char* color...pt, vector points) { for(int i =0 ; i < points.size(); i++) { if(pt.x == points...pt = cvPoint(x,y); if(currentMode == 0) {//foreground forePts.push_back(cvPoint...(x/SCALE,y/SCALE)); } else {//background backPts.push_back(cvPoint(x/SCALE,y/
I(x,y)red ~ ((uchar*)(img->imageData + img->widthStep*y))[x*3+2] 如果增加点 (100,100) 的亮度 30 ，那么可以: CvPoint...pt.y))[pt.x*3+1] += 30; ((uchar*)(img->imageData + img->widthStep*pt.y))[pt.x*3+2] += 30; 或者更有效的 CvPoint...(IplImage* src, IplImage* dst, float thresh, float maxvalue,CvThreshType type); void cvProject3D ( CvPoint3D32f...* points3D, int count, CvPoint2D32f* points2D,int xindx, int yindx); void cvFindFundamentalMatrix (int...CV_BLUR CV_GAUSSIAN CV_MEDIAN CV_BILATERAL 其他辅助函数： void cvPutText( CvArr* img, const char* text, CvPoint
int header_size=sizeof(CvContour), int mode=CV_RETR_LIST, int method=CV_CHAIN_APPROX_SIMPLE, CvPoint... offset=cvPoint(0,0) ) Python: cv....pt1=cvPoint(rect.x, rect.y), pt2=cvPoint(rect.x+rect.width, rect.y+rect.height); //定义矩形对顶点 cvRectangle...(rect.x, rect.y+rect.height), pt2=cvPoint(rect.x+rect.width, rect.y); cvLine(dst, pt1, pt2, CV_RGB...(0,255,0), 1, CV_AA,0); //矩形对角线相连 RecP tmp; CvPoint p1; p1 = cvPoint(rect.x + rect.width
lines = cvHoughLines2(canny, stor, CV_HOUGH_PROBABILISTIC, 1, CV_PI / 180, 80, 200, 30); cvZero(dst); CvPoint...maxStart, maxEnd; int maxDistance = 0; for (int i = 0; i < lines- total; i++) { CvPoint* line =...(CvPoint*)cvGetSeqElem(lines, i); if (abs(line[0].x - line[1].x) maxDistance) { maxDistance...lines = cvHoughLines2(canny, stor, CV_HOUGH_PROBABILISTIC, 1, CV_PI / 180, 80, 200, 30); cvZero(dst); CvPoint...CvPoint* line = (CvPoint*)cvGetSeqElem(lines, i); // line[0] and line[1] is respectively the line's
cv2.putText() # 输入文字 等 可以设置诸如： color，*thickness，linetype之类的参数 函数原型(C++)： void cvLine( CvArr* img, CvPoint...pt1, CvPoint pt2, CvScalar color, int thickness=1, int line_type=8, int shift=0 ) void cvRectangle(...CvArr* img, CvPoint pt1, CvPoint pt2, CvScalar color,int thickness=1, int line_type=8, int shift=0 ;
cv::putText(mat, QString("brightness: %1").arg(_brightness).toStdString(), cvPoint...cv::putText(mat, QString(" contrast: %1").arg(_contrast ).toStdString(), cvPoint...cv::putText(mat, QString("saturation: %1").arg(_saturation).toStdString(), cvPoint...cv::putText(mat, QString(" hue: %1").arg(_hue ).toStdString(), cvPoint...255)); cv::putText(mat, QString("press ESC out").toStdString(), cvPoint
> points,const vector oppositePoints, const vector score, float...overlapThreshold,int& numBoxesOut, vector& pointsOut, vector<CvPoint...return true; } int main() { Mat image=Mat::zeros(600,600,CV_8UC3); int numBoxes=4; vector points(numBoxes); vector oppositePoints(numBoxes); vector score(numBoxes);...Point(400,440);score[3]=0.5; float overlapThreshold=0.8; int numBoxesOut; vector<CvPoint
// cvShowImage("contours",img); for(int k = 0;k <c- total;++k) { CvPoint...* p = CV_GET_SEQ_ELEM(CvPoint,c,k); printf("(%d,%d)\n",p- x,p- y); }...CvRect rect; rect = cvBoundingRect(c,0); cvFloodFill(img,cvPoint(img- width/2,img- height
from the image_1 ( the object to be "detected" ) std::vector obj_corners(4); obj_corners[0] = cvPoint...(0, 0); obj_corners[1] = cvPoint(box.cols, 0); obj_corners[2] = cvPoint(box.cols, box.rows); obj_corners...[3] = cvPoint(0, box.rows); std::vector scene_corners(4); perspectiveTransform(obj_corners,
CvMemStorage* storage2 = cvCreateMemStorage(); CvSeq* contour3 = NULL; CvMoments moments; CvMat *region; CvPoint...int xc, yc; CvMemStorage* storage = cvCreateMemStorage(); CvSeq * circles=NULL; // Circle cir[6]; CvPoint...P0; CvPoint CenterPoint; // cvNamedWindow("win1"); //cvShowImage("win1",image); //cvNamedWindow("image...endl; cout<<"面积为"<<tmparea<<endl; cout<<endl; CvRect aRect = cvBoundingRect( contour, 0 ); //找重心 { CvPoint2D32f...center = cvPoint2D32f(0, 0); int countOfPoint = 0; for(int i = aRect.x; i < aRect.x + aRect.width; +
//-- Get the corners from the image_1 ( the object to be "detected" ) Point2f obj_corners[4] = { cvPoint...(0,0), cvPoint( img_1.cols, 0 ), cvPoint( img_1.cols, img_1.rows ), cvPoint( 0, img_1.rows ) }; Point...double Y = ( H.at(1,0)*x + H.at(1,1)*y + H.at(1,2) )*Z; scene_corners[i] = cvPoint
header_size=sizeof(CvContour), int mode=CV_RETR_LIST, int method=CV_CHAIN_APPROX_SIMPLE, CvPoint... offset=cvPoint(0,0) ); 函数说明： 第一个参数表示输入图像，必须为一个8位的二值图像。...external_color, CvScalar hole_color, int max_level, int thickness=1, int line_type=8, CvPoint... offset=cvPoint(0,0) ); 第一个参数表示输入图像，函数将在这张图像上绘制轮廓。
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