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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,

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opencv 绘图 cvLine cvRectangle cvCircle cvEllipse cvEllipseBox cvFillPoly cvConvexPoly cvPolyLine[通俗易懂

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

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OpenCV kmeans代码

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];

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L-K光流推导及OpenCV代码实现

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

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OpenCV 实现分水岭算法

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

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OpenCV 1 图像分割--分水岭算法代码

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OpenCV OpenGL手写字符识别

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);

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opencv——访问图像元素(imagedata widthstep)

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

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cvCircle and cvRectangle

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

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基于GraphCuts图割算法的图像分割----OpenCV代码与实现

> forePts; vectorCvPoint> backPts; IplImage* image; // average color of foreground points...> points); bool isPtInVector(CvPoint pt, vectorCvPoint> points); void getE1(unsigned char* color...pt, vectorCvPoint> 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/

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OpenCV 矩形轮廓检测

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

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Qt实用技巧：使用OpenCV库操作摄像头拍照、调节参数和视频录制

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

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Python-OpenCV(1)

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 ;

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OpenCV基于DLCO描述子匹配

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,

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非极大值抑制（Non-Maximum-Suppression）

> points,const vectorCvPoint> oppositePoints, const vector score, float...overlapThreshold,int& numBoxesOut, vectorCvPoint>& pointsOut, vectorCvPoint...return true; } int main() { Mat image=Mat::zeros(600,600,CV_8UC3); int numBoxes=4; vectorCvPoint...> points(numBoxes); vectorCvPoint> oppositePoints(numBoxes); vector score(numBoxes);...Point(400,440);score[3]=0.5; float overlapThreshold=0.8; int numBoxesOut; vectorCvPoint

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视频追踪之目标选择（一）------边缘检测值函数准备

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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OpenCV 学习日记（三）--- 常见数据类型

OpenCV基本数据类型： CvPoint，这些结构中最简单的一个，包含两个整型变量x和y。 CvPoint还有两个兄弟：CvPoint2D32f 和 CvPoint3D32f。...CvRect，派生于CvPoint 和 CvSize，它含有4个变量：x、y、width、height。 CvScalar，包含一组4个双精度浮点型数。...如果你想在图像中(5, 10)点和(20, 30)点之间画一个白色的矩形，你只需简单的调用：cvRectangle(myImg, cvPoint(5, 10), cvPoint(20, 30), cvScalar

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2维特征Feature2D—特征点的图像匹配

//-- 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

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OpenCV计算物体的重心坐标（2值图像）

Mx_order,y_order=SUMx,y(I(x,y)*x^x_order*y^y_order) */ static int aoiGravityCenter(IplImage *src, CvPoint...src); cvNamedWindow( "binary image", 1 ); cvShowImage( "binary image", binary_image(src) ); } CvPoint...xy; aoiGravityCenter(binary_image(src),xy); cout<<xy.x<<endl; cout<<xy.y<<endl; cvCircle(draw,cvPoint

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OpenCV 角点检测(一) Moravec

r = kSize / 2; const int nRows = SrcImage.rows; const int nCols =SrcImage.cols; int nConut = 0; CvPoint...*pPoint = new CvPoint[nRows*nCols]; // 图像遍历 for (int i = r; i < SrcImage.rows-r; i++) { for (int...wV2), min(wV3,wV4)); // 若兴趣值大于阈值，则将点的坐标存入数组中 if (value > threshold) { pPoint[nConut] = cvPoint

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OpenCV绘图之字体和文字

opencv 绘图 cvLine cvRectangle cvCircle cvEllipse cvEllipseBox cvFillPoly cvConvexPoly cvPolyLine[通俗易懂

OpenCV kmeans代码

L-K光流推导及OpenCV代码实现

OpenCV 实现分水岭算法

OpenCV 1 图像分割--分水岭算法代码

OpenCV OpenGL手写字符识别

opencv——访问图像元素(imagedata widthstep)

cvCircle and cvRectangle

基于GraphCuts图割算法的图像分割----OpenCV代码与实现

OpenCV 矩形轮廓检测

Qt实用技巧：使用OpenCV库操作摄像头拍照、调节参数和视频录制

Python-OpenCV(1)

OpenCV基于DLCO描述子匹配

非极大值抑制（Non-Maximum-Suppression）

视频追踪之目标选择（一）------边缘检测值函数准备

OpenCV 学习日记（三）--- 常见数据类型

2维特征Feature2D—特征点的图像匹配

OpenCV计算物体的重心坐标（2值图像）

OpenCV 角点检测(一) Moravec

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