cvKMeans2接受Seq数据

最近，开始学习openCV，准备用openCV来加强自己对图像处理和算法的理解与应用。

下面是自己最近学习cvKMeans2时的一点经验——

在《opencv基础》与《学习opencv》中介绍cvKMeans2时，都只说samples输入样例的浮点矩阵，每个样例一行。而在实际运用时，很多情况都是在运行时才知道样本的大小，并且会随时改变，那只有求助于CvSeq。研究cvKMeans的源码，如下：

CV_IMPL int
cvKMeans2( const CvArr* _samples, int cluster_count, CvArr* _labels,
           CvTermCriteria termcrit, int attempts, CvRNG*,
           int flags, CvArr* _centers, double* _compactness )
{
    cv::Mat data = cv::cvarrToMat(_samples), labels = cv::cvarrToMat(_labels), centers;
    if( _centers )
        centers = cv::cvarrToMat(_centers);
    CV_Assert( labels.isContinuous() && labels.type() == CV_32S &&
        (labels.cols == 1 || labels.rows == 1) &&
        labels.cols + labels.rows - 1 == data.rows );
    double compactness = cv::kmeans(data, cluster_count, labels, termcrit, attempts,
                                    flags, _centers ? &centers : 0 );
    if( _compactness )
        *_compactness = compactness;
    return 1;
}

第6行中，用cv::cvarrToMat将_sample和_labels都转化成Mat,而cvarrToMat的源码如下：

static inline Mat cvarrToMat(const CvArr* arr, bool copyData=false,
                             bool allowND=true, int coiMode=0)
{
    if( CV_IS_MAT(arr) )
        return Mat((const CvMat*)arr, copyData );
    else if( CV_IS_IMAGE(arr) )
    {
        const IplImage* iplimg = (const IplImage*)arr;
        if( coiMode == 0 && iplimg->roi && iplimg->roi->coi > 0 )
            CV_Error(CV_BadCOI, "COI is not supported by the function");
        return Mat(iplimg, copyData);
    }
    else if( CV_IS_SEQ(arr) )
    {
        CvSeq* seq = (CvSeq*)arr;
        CV_Assert(seq->total > 0 && CV_ELEM_SIZE(seq->flags) == seq->elem_size);
        if(!copyData && seq->first->next == seq->first)
            return Mat(seq->total, 1, CV_MAT_TYPE(seq->flags), seq->first->data);
        Mat buf(seq->total, 1, CV_MAT_TYPE(seq->flags));
        cvCvtSeqToArray(seq, buf.data, CV_WHOLE_SEQ);
        return buf;
    }
    else
    {
        CvMat hdr, *cvmat = cvGetMat( arr, &hdr, 0, allowND ? 1 : 0 );
        if( cvmat )
            return Mat(cvmat, copyData);
    }
    return Mat();
}

其中，有对arr进行判断的，判断其是否为Mat,Image或者是Seq。我们先不管其是如何判断的，有这个判断在这，就说明cvKMeans2可以支持Seq数据，于是自己开始尝试写代码。

以下是自己的代码：

void test2() //有缺陷，运行到23行会出错。因为clusters中没有元素，故没有位置存放结果
{
    int width=500,height=500;
    int sample_count=3;
    int cluster_count=2;

    CvScalar color_tab[2];
    color_tab[0] = CV_RGB(255,0,0);
    color_tab[1] = CV_RGB(0,255,0);
    
    CvMemStorage *memPoints=cvCreateMemStorage(0);
    CvMemStorage *memClu=cvCreateMemStorage(0);

    CvSeq *points=cvCreateSeq(CV_32SC2,sizeof(CvSeq),sizeof(CvPoint),memPoints);
    CvSeq *clusters=cvCreateSeq(CV_32SC1,sizeof(CvSeq),sizeof(int),memClu);
    CvSeqWriter writer; 
    cvStartAppendToSeq(points,&writer);
    CV_WRITE_SEQ_ELEM(cvPoint(10,20),writer);
    CV_WRITE_SEQ_ELEM(cvPoint(50,100),writer);
    CV_WRITE_SEQ_ELEM(cvPoint(100,50),writer);
    cvEndWriteSeq(&writer);

    cvKMeans2( points, cluster_count, clusters,
        cvTermCriteria( CV_TERMCRIT_EPS+CV_TERMCRIT_ITER, 
        10, 0.1));
    IplImage *img=cvCreateImage(cvSize(width,height),8,3);
    cvZero( img );
    CvSeqReader readerPoints;
    CvSeqReader readerClu;
    cvStartReadSeq(points,&readerPoints,0);
    cvStartReadSeq(clusters,&readerClu,0);

    for (int i=0;i<sample_count;++i)
    {
        CvPoint2D32f point;
        int cl;
        CV_READ_SEQ_ELEM(point,readerPoints);
        CV_READ_SEQ_ELEM(cl,readerClu);
        cvCircle(img,cvPointFrom32f(point),2,color_tab[cl],CV_FILLED);
    }
 
    cvShowImage( "clusters", img );
    cvWaitKey(0);
}

运行，发现提示如下的错误：

OpenCV Error: Assertion failed (seq->total > 0 && CV_ELEM_SIZE(seq->flags) == se
q->elem_size) in unknown function, file c:\user\vp\ocv\opencv\include\opencv\cxm
at.hpp, line 225

打开源码，发现是cvarrToMat执行转化时，检测参数出错了。于是先检查了points，确定其没有问题；再看clusters，于是明白了，cvKMeans2不会为我们分配内存，clusters应该在函数调用前就用值进行填充，使其与points有一样的大小。于是有一如下的代码

void test2()//有缺陷，points应该为浮点型的坐标
{
    int width=500,height=500;
    int sample_count=3;
    int cluster_count=2;

    CvScalar color_tab[2];
    color_tab[0] = CV_RGB(255,0,0);
    color_tab[1] = CV_RGB(0,255,0);
    
    CvMemStorage *memPoints=cvCreateMemStorage(0);
    CvMemStorage *memClu=cvCreateMemStorage(0);

    CvSeq *points=cvCreateSeq(CV_32SC2,sizeof(CvSeq),sizeof(CvPoint),memPoints);
    CvSeq *clusters=cvCreateSeq(CV_32SC1,sizeof(CvSeq),sizeof(int),memClu);
    CvSeqWriter writer; 
    cvStartAppendToSeq(points,&writer);
    CV_WRITE_SEQ_ELEM(cvPoint(10,20),writer);
    CV_WRITE_SEQ_ELEM(cvPoint(50,100),writer);
    CV_WRITE_SEQ_ELEM(cvPoint(100,50),writer);
    cvEndWriteSeq(&writer);

    int i=0;
    cvStartAppendToSeq(clusters,&writer); //这里是新添加的，这里的i可以是随意值，只要添加一个占位即可
    CV_WRITE_SEQ_ELEM(i,writer);
    CV_WRITE_SEQ_ELEM(i,writer);
    CV_WRITE_SEQ_ELEM(i,writer);
    cvEndWriteSeq(&writer);
 
    cvKMeans2( points, cluster_count, clusters,
        cvTermCriteria( CV_TERMCRIT_EPS+CV_TERMCRIT_ITER, 
        10, 0.1));
    IplImage *img=cvCreateImage(cvSize(width,height),8,3);
    cvZero( img );
    CvSeqReader readerPoints;
    CvSeqReader readerClu;
    cvStartReadSeq(points,&readerPoints,0);
    cvStartReadSeq(clusters,&readerClu,0);

    for (int i=0;i<sample_count;++i)
    {
        CvPoint2D32f point;
        int cl;
        CV_READ_SEQ_ELEM(point,readerPoints);
        CV_READ_SEQ_ELEM(cl,readerClu);
        cvCircle(img,cvPointFrom32f(point),2,color_tab[cl],CV_FILLED);
    }
 
    cvShowImage( "clusters", img );
    cvWaitKey(0);
}

运行，又提示如下错误

OpenCV Error: Assertion failed (type == CV_32F && K > 0) in unknown function, fi
le ..\..\..\..\ocv\opencv\src\cxcore\cxmatrix.cpp, line 860

这次是在cv::kmeans函数中，points的类型不为CV_32F?? 哦~~  cvKMenas2只指定浮点数。故将points的构建代码改成如下所示：

  CvSeq *points=cvCreateSeq(CV_32FC2,sizeof(CvSeq),sizeof(CvPoint2D32f),memPoints);

故最后的代码如下：

void test2()
{
    int width=500,height=500;
    int sample_count=3;
    int cluster_count=2;

    CvScalar color_tab[2];
    color_tab[0] = CV_RGB(255,0,0);
    color_tab[1] = CV_RGB(0,255,0);
    
    CvMemStorage *memPoints=cvCreateMemStorage(0);
    CvMemStorage *memClu=cvCreateMemStorage(0);

    CvSeq *points=cvCreateSeq(CV_32FC2,sizeof(CvSeq),sizeof(CvPoint2D32f),memPoints);
    CvSeq *clusters=cvCreateSeq(CV_32SC1,sizeof(CvSeq),sizeof(int),memClu);
    CvSeqWriter writer; 
    cvStartAppendToSeq(points,&writer);
    CV_WRITE_SEQ_ELEM(cvPoint2D32f(10,20),writer);
    CV_WRITE_SEQ_ELEM(cvPoint2D32f(50,100),writer);
    CV_WRITE_SEQ_ELEM(cvPoint2D32f(100,50),writer);
    cvEndWriteSeq(&writer);

    int i=0;
    cvStartAppendToSeq(clusters,&writer);
    CV_WRITE_SEQ_ELEM(i,writer);
    CV_WRITE_SEQ_ELEM(i,writer);
    CV_WRITE_SEQ_ELEM(i,writer);
    cvEndWriteSeq(&writer);
 
    cvKMeans2( points, cluster_count, clusters,
        cvTermCriteria( CV_TERMCRIT_EPS+CV_TERMCRIT_ITER, 
        10, 0.1));
    IplImage *img=cvCreateImage(cvSize(width,height),8,3);
    cvZero( img );
    CvSeqReader readerPoints;
    CvSeqReader readerClu;
    cvStartReadSeq(points,&readerPoints,0);
    cvStartReadSeq(clusters,&readerClu,0);

    for (int i=0;i<sample_count;++i)
    {
        CvPoint2D32f point;
        int cl;
        CV_READ_SEQ_ELEM(point,readerPoints);
        CV_READ_SEQ_ELEM(cl,readerClu);
        cvCircle(img,cvPointFrom32f(point),2,color_tab[cl],CV_FILLED);
    }
 
    cvShowImage( "clusters", img );
    cvWaitKey(0);
}

上面的代码有内存泄漏，cvCreateImage出来的图像，应该用cvReleaseImage释放
cvCreateMemStorage出来的内存，应该用ReleaseMenStorage释放。