凹凸性缺陷c++ OpenCv

Convexity defects C++ OpenCv

本文关键字：OpenCv c++ 缺陷 凹凸      更新时间：2023-10-16

如果您能帮我解决这个问题，我将不胜感激:)

关于这个问题cvConvexityDefects in opencv2。X/c++ ?我也有同样的问题。OpenCV c++包装器没有函数cvConvexityDefects出现在C版本，所以我试图写我自己的版本。

部分代码是(请注意，countour和hull都是矢量<点>，单独计算:

CvSeq* contourPoints;
CvSeq* hullPoints;
CvSeq* defects;
CvMemStorage* storage;
CvMemStorage* strDefects;
CvMemStorage* contourStr;
CvMemStorage* hullStr;
CvConvexityDefect *defectArray = 0;
strDefects = cvCreateMemStorage();
defects = cvCreateSeq( CV_SEQ_KIND_GENERIC|CV_32SC2, sizeof(CvSeq),sizeof(CvPoint), strDefects );
//We start converting vector<Point> resulting from findContours
contourStr = cvCreateMemStorage();
contourPoints = cvCreateSeq(CV_SEQ_KIND_GENERIC|CV_32SC2, sizeof(CvSeq), sizeof(CvPoint), contourStr);
printf("Metiendo valoresn");
for(int i=0; i<(int)contour.size(); i++) {
    CvPoint cp = {contour[i].x,  contour[i].y};
    cvSeqPush(contourPoints, &cp);
}
//Now, the hull points obtained from convexHull c++
hullStr = cvCreateMemStorage(0);
hullPoints = cvCreateSeq(CV_SEQ_KIND_GENERIC|CV_32SC2, sizeof(CvSeq), sizeof(CvPoint), hullStr);
for(int i=0; i<(int)hull.size(); i++) {
    CvPoint cp = {hull[i].x,  hull[i].y};
    cvSeqPush(hullPoints, &cp);
}
//And we compute convexity defects
storage = cvCreateMemStorage(0);
defects = cvConvexityDefects(contourPoints, hullPoints, storage);

输出为Convex hull must represented as a sequence of indices or sequence of pointers in function cvConvexityDefects。我真的不知道如何以正确的方式进行转换，我一直在网上搜索，并试图适应/复制/理解一些代码，但它总是与C语法。

我希望我说得很清楚。提前感谢!

我提出这个问题是因为我无法找到解决方案(不仅是今天我在处理这件事，呵呵)，但毕竟我能够管理这个问题!

我必须改变我计算凸包的方式，使用索引数组形式。现在我们有一个向量代替vector<点> .

这是我使用的代码(它工作，我画点在图像上):

void HandDetection::findConvexityDefects(vector<Point>& contour, vector<int>& hull, vector<Point>& convexDefects){
    if(hull.size() > 0 && contour.size() > 0){
    CvSeq* contourPoints;
    CvSeq* defects;
    CvMemStorage* storage;
    CvMemStorage* strDefects;
    CvMemStorage* contourStr;
    CvConvexityDefect *defectArray = 0;
    strDefects = cvCreateMemStorage();
    defects = cvCreateSeq( CV_SEQ_KIND_GENERIC|CV_32SC2, sizeof(CvSeq),sizeof(CvPoint), strDefects );
    //We transform our vector<Point> into a CvSeq* object of CvPoint.
    contourStr = cvCreateMemStorage();
    contourPoints = cvCreateSeq(CV_SEQ_KIND_GENERIC|CV_32SC2, sizeof(CvSeq), sizeof(CvPoint), contourStr);
    for(int i=0; i<(int)contour.size(); i++) {
        CvPoint cp = {contour[i].x,  contour[i].y};
        cvSeqPush(contourPoints, &cp);
    }
    //Now, we do the same thing with the hull index
    int count = (int)hull.size();
    //int hullK[count];
    int* hullK = (int*)malloc(count*sizeof(int));
    for(int i=0; i<count; i++){hullK[i] = hull.at(i);}
    CvMat hullMat = cvMat(1, count, CV_32SC1, hullK);
    //We calculate convexity defects
    storage = cvCreateMemStorage(0);
    defects = cvConvexityDefects(contourPoints, &hullMat, storage);
    defectArray = (CvConvexityDefect*)malloc(sizeof(CvConvexityDefect)*defects->total);
    cvCvtSeqToArray(defects, defectArray, CV_WHOLE_SEQ);
    //printf("DefectArray %i %in",defectArray->end->x, defectArray->end->y);
    //We store defects points in the convexDefects parameter.
    for(int i = 0; i<defects->total; i++){
        CvPoint ptf;
        ptf.x = defectArray[i].depth_point->x;
        ptf.y = defectArray[i].depth_point->y;
        convexDefects.push_back(ptf);
    }
    //We release memory
    cvReleaseMemStorage(contourStr);
    cvReleaseMemStorage(strDefects);
    cvReleaseMemStorage(storage);
    }
}

这对我有用。如果你发现有什么不对的地方或者有其他的管理方法，请告诉我!

找到了一些使用cpp凹凸性缺陷的直接方法。通过convexhull函数进行类型处理。它按类型填充，int*返回索引值，Point*返回坐标。

void WorkFrame( Mat img, double minArea )
{
//assumption:
// img already preprocessed, threshold, gray, smooth, morphology whatever..
//get some contours
vector<vector<Point> > contours;
vector<Vec4i> hierarchy;
findContours( img, contours, hierarchy, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_SIMPLE );
for( int i=0; i<contours.size(); i++ ) 
{
    vector<Point>& c=contours[i];
    double area = contourArea( c );
        if( area<minArea ){ continue; } //filter remaining noise
    //convexHull works typedependent.
    //std::vector<Point> ptHull1; //uncomment and compare to ptHull2
    //convexHull( c, ptHull1 ); //convexHull is smart and fills direct coordinates
    std::vector<int> ihull; 
    convexHull( c, ihull ); //convexHull is smart and fills in contourIndices
    std::vector<Vec4i> defects;
    convexityDefects( c, ihull, defects ); //expects indexed hull (internal assertion mat.channels()==1)
    std::vector< Point > ptHull2;
    std::vector<int>::iterator ii=ihull.begin();
    while( ii!=ihull.end() )
    {
        int idx=(*ii);
        ptHull2.push_back( c[idx] );
        ii++;
    }
    cv::polylines( mat, c, true, Scalar( 0xCC,0xCC,0xCC ), 1 );
    cv::polylines( mat, ptHull2, true, Scalar( 0xFF, 0x20, 0x20 ), 1 );
    std::vector<Vec4i>::iterator d=defects.begin();
    while( d!=defects.end() )
    {
        Vec4i& v=(*d); d++;
        int startidx=v[0]; Point ptStart( c[startidx] );
        int endidx=v[1]; Point ptEnd( c[endidx] );
        int faridx=v[2]; Point ptFar( c[faridx] );
        cv::circle( img, ptStart, 4, Scalar( 0x02,0x60,0xFF ), 2 );
        cv::circle( img, ptEnd,   4, Scalar( 0xFF,0x60,0x02 ), 2 );
        cv::circle( img, ptFar,   4, Scalar( 0x60,0xFF,0x02 ), 2 );
    }
}

}

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