C++ IPPI_CALL函数代码示例

/* external contour area function */
CV_IMPL double
cvContourArea( const void *array, CvSlice slice, int oriented )
{
    double area = 0;

    CvContour contour_header;
    CvSeq* contour = 0;
    CvSeqBlock block;

    if( CV_IS_SEQ( array ))
    {
        contour = (CvSeq*)array;
        if( !CV_IS_SEQ_POLYLINE( contour ))
            CV_Error( CV_StsBadArg, "Unsupported sequence type" );
    }
    else
    {
        contour = cvPointSeqFromMat( CV_SEQ_KIND_CURVE, array, &contour_header, &block );
    }

    if( cvSliceLength( slice, contour ) == contour->total )
    {
        IPPI_CALL( icvContourArea( contour, &area ));
    }
    else
    {
        if( CV_SEQ_ELTYPE( contour ) != CV_32SC2 )
            CV_Error( CV_StsUnsupportedFormat,
            "Only curves with integer coordinates are supported in case of contour slice" );
        IPPI_CALL( icvContourSecArea( contour, slice, &area ));
    }

    return oriented ? area : fabs(area);
}

CV_IMPL void
cvImgToObs_DCT( const void* arr, float *obs, CvSize dctSize,
                CvSize obsSize, CvSize delta )
{
    CV_FUNCNAME( "cvImgToObs_DCT" );

    __BEGIN__;

    CvMat stub, *mat = (CvMat*)arr;

    CV_CALL( mat = cvGetMat( arr, &stub ));

    switch( CV_MAT_TYPE( mat->type ))
    {
    case CV_8UC1:
        IPPI_CALL( icvImgToObs_DCT_8u32f_C1R( mat->data.ptr, mat->step,
                                           cvGetMatSize(mat), obs,
                                           dctSize, obsSize, delta ));
        break;
    case CV_32FC1:
        IPPI_CALL( icvImgToObs_DCT_32f_C1R( mat->data.fl, mat->step,
                                           cvGetMatSize(mat), obs,
                                           dctSize, obsSize, delta ));
        break;
    default:
        CV_ERROR( CV_StsUnsupportedFormat, "" );
    }

    __END__;
}

CV_IMPL void
cvCornerEigenValsAndVecs( const void* srcarr, void* eigenvarr,
                          int block_size, int aperture_size )
{
    static CvFuncTable eig_tab;
    static int inittab = 0;
    void *buffer = 0;

    CV_FUNCNAME( "cvCornerEigenValsAndVecs" );

    __BEGIN__;

    CvSize src_size;
    int buf_size;
    CvEigFunc func = 0;

    CvMat stub, *src = (CvMat*)srcarr;
    CvMat eigstub, *eigenv = (CvMat*)eigenvarr;

    if( !inittab )
    {
        icvInitEigenValsVecsTable( &eig_tab );
        inittab = 1;
    }

    CV_CALL( src = cvGetMat( srcarr, &stub ));
    CV_CALL( eigenv = cvGetMat( eigenv, &eigstub ));

    if( CV_ARR_CN(src->type) != 1 )
        CV_ERROR(CV_StsBadArg, "Source image has more than 1 channel");

    if( CV_ARR_CN(eigenv->type)*eigenv->width != src->width*6 )
        CV_ERROR(CV_StsBadArg, "Eigen-vals&vecs image should be 6 times "
                 "wider than the source image");

    if( src->height != eigenv->height )
        CV_ERROR( CV_StsUnmatchedSizes, "" );

    if( CV_ARR_DEPTH(eigenv->type) != CV_32F )
        CV_ERROR( CV_BadDepth, "Eigen-vals&vecs image does not have IPL_DEPTH_32F depth" );

    func = (CvEigFunc)(eig_tab.fn_2d[CV_ARR_DEPTH(src->type)]);
    if( !func )
        CV_ERROR( CV_StsUnsupportedFormat, "" );

    src_size = icvGetMatSize( src );

    IPPI_CALL( icvEigenValsVecsGetSize( src_size.width, aperture_size,
                                        block_size, &buf_size ));
    CV_CALL( buffer = cvAlloc( buf_size ));

    IPPI_CALL( func( src->data.ptr, src->step, eigenv->data.ptr, eigenv->step,
                     src_size, aperture_size, block_size, buffer ));

    __END__;

    cvFree( &buffer );
}

CV_IMPL void
cvCalcContrastHist( IplImage ** img, CvHistogram * hist, int dont_clear, IplImage * mask )
{
    CV_FUNCNAME( "cvCalcContrastHist" );
    uchar *data[CV_HIST_MAX_DIM];
    uchar *mask_data = 0;
    int step = 0;
    int mask_step = 0;
    CvSize roi = { 0, 0 };

    __BEGIN__;

    {
        for( int i = 0; i < hist->c_dims; i++ )
            CV_CALL( CV_CHECK_IMAGE( img[i] ));
    }
    if( mask )
    {
        CV_CALL( CV_CHECK_IMAGE( mask ));
        if( mask->depth != IPL_DEPTH_8U )
            CV_ERROR( CV_BadDepth, "bad mask depth" );
        cvGetImageRawData( mask, &mask_data, &mask_step, 0 );
    }


    {
        for( int i = 0; i < hist->c_dims; i++ )
            cvGetImageRawData( img[i], &data[i], &step, &roi );
    }

    if( img[0]->nChannels != 1 )
        CV_ERROR( CV_BadNumChannels, "bad channels numbers" );

    if( img[0]->depth != IPL_DEPTH_8U )
        CV_ERROR( CV_BadDepth, "bad image depth" );


    switch (img[0]->depth)
    {
    case IPL_DEPTH_8U:
        if( !mask )
        {
            IPPI_CALL( icvCalcContrastHist8uC1R( data, step, roi, hist, dont_clear ));
        }
        else
        {
            IPPI_CALL( icvCalcContrastHistMask8uC1R( data, step, mask_data,
                                                     mask_step, roi, hist, dont_clear ));
        }
        break;
    default:
        CV_ERROR( CV_BadDepth, "bad image depth" );
    }

    __CLEANUP__;
    __END__;
}

CV_IMPL void
cvCornerMinEigenVal( const void* srcarr, void* eigenvarr,
                     int block_size, int aperture_size )
{
    static CvFuncTable eig_tab;
    static int inittab = 0;
    void *buffer = 0;

    CV_FUNCNAME( "cvCornerMinEigenVal" );

    __BEGIN__;

    CvSize src_size;
    int buf_size;
    CvEigFunc func = 0;

    CvMat stub, *src = (CvMat*)srcarr;
    CvMat eigstub, *eigenv = (CvMat*)eigenvarr;

    if( !inittab )
    {
        icvInitMinEigenValTable( &eig_tab );
        inittab = 1;
    }

    CV_CALL( src = cvGetMat( srcarr, &stub ));
    CV_CALL( eigenv = cvGetMat( eigenv, &eigstub ));

    if( CV_ARR_CN(src->type) != 1 || CV_ARR_CN(eigenv->type) != 1 )
        CV_ERROR(CV_StsBadArg, "Source or min-eigen-val images have more than 1 channel");

    if( CV_ARR_DEPTH(eigenv->type) != CV_32F )
        CV_ERROR( CV_BadDepth, "min-eigen-val image does not have IPL_DEPTH_32F depth" );

    if( !CV_ARE_SIZES_EQ( src, eigenv ))
        CV_ERROR( CV_StsUnmatchedSizes, "" );

    func = (CvEigFunc)(eig_tab.fn_2d[CV_ARR_DEPTH(src->type)]);
    if( !func )
        CV_ERROR( CV_StsUnsupportedFormat, "" );

    src_size = icvGetMatSize( src );

    IPPI_CALL( icvMinEigenValGetSize( src_size.width, aperture_size, block_size, &buf_size ));
    CV_CALL( buffer = cvAlloc( buf_size ));

    IPPI_CALL( func( src->data.ptr, src->step, eigenv->data.ptr, eigenv->step,
                     src_size, aperture_size, block_size, buffer ));

    __END__;

    cvFree( &buffer );
}

/*F///////////////////////////////////////////////////////////////////////////////////////
//    Name:     cvFindHandRegion
//    Purpose:  finds hand region in range image data
//    Context:
//    Parameters:
//      points - pointer to the input point's set.
//      count  - the number of the input points.
//      indexs - pointer to the input sequence of the point's indexes
//      line   - pointer to the 3D-line
//      size   - size of the hand in meters
//      flag   - hand direction's flag (0 - left, -1 - right,
//               otherwise j-index of the initial image center)
//      center - pointer to the output hand center
//      storage - pointer to the memory storage
//      numbers - pointer to the output sequence of the point's indexes inside
//                hand region
//
//    Notes:
//F*/
CV_IMPL void
cvFindHandRegion( CvPoint3D32f * points, int count,
                  CvSeq * indexs,
                  float *line, CvSize2D32f size, int flag,
                  CvPoint3D32f * center, CvMemStorage * storage, CvSeq ** numbers )
{
    if(flag == 0 || flag == -1)
    {
        IPPI_CALL( icvFindHandRegion( points, count, indexs, line, size, -flag,
                                       center, storage, numbers ));
    }
    else
        IPPI_CALL( icvFindHandRegionA( points, count, indexs, line, size, flag,
                                        center, storage, numbers ));
}

CV_IMPL CvPOSITObject *
cvCreatePOSITObject( CvPoint3D32f * points, int numPoints )
{
    CvPOSITObject *pObject = 0;
    IPPI_CALL( icvCreatePOSITObject( points, numPoints, &pObject ));
    return pObject;
}

CV_IMPL void
cvCalcPGH( const CvSeq * contour, CvHistogram * hist )
{
    CV_FUNCNAME( "cvCalcPGH" );

    __BEGIN__;

    int size[CV_MAX_DIM];
    int dims;
    
    if( !CV_IS_HIST(hist))
        CV_ERROR( CV_StsBadArg, "The histogram header is invalid " );

    if( CV_IS_SPARSE_HIST( hist ))
        CV_ERROR( CV_StsUnsupportedFormat, "Sparse histogram are not supported" );

    dims = cvGetDims( hist->bins, size ); 

    if( dims != 2 )
        CV_ERROR( CV_StsBadSize, "The histogram must be two-dimensional" );

    if( !CV_IS_SEQ_POINT_SET( contour ) || CV_SEQ_ELTYPE( contour ) != CV_32SC2 )
        CV_ERROR( CV_StsUnsupportedFormat, "The contour is not valid or the point type is not supported" );

    IPPI_CALL( icvCalcPGH( contour, ((CvMatND*)(hist->bins))->data.fl, size[0], size[1] ));

    __END__;
}

/*F///////////////////////////////////////////////////////////////////////////////////////
//    Name:    cvCalcOpticalFlowLK
//    Purpose: Optical flow implementation
//    Context:
//    Parameters:
//             srcA, srcB - source image
//             velx, vely - destination image
//    Returns:
//
//    Notes:
//F*/
CV_IMPL void
cvCalcOpticalFlowLK(const void* srcarrA, const void* srcarrB, CvSize winSize,
                    void* velarrx, void* velarry) {
    CvMat stubA, *srcA = cvGetMat(srcarrA, &stubA);
    CvMat stubB, *srcB = cvGetMat(srcarrB, &stubB);
    CvMat stubx, *velx = cvGetMat(velarrx, &stubx);
    CvMat stuby, *vely = cvGetMat(velarry, &stuby);

    if (!CV_ARE_TYPES_EQ(srcA, srcB)) {
        CV_Error(CV_StsUnmatchedFormats, "Source images have different formats");
    }

    if (!CV_ARE_TYPES_EQ(velx, vely)) {
        CV_Error(CV_StsUnmatchedFormats, "Destination images have different formats");
    }

    if (!CV_ARE_SIZES_EQ(srcA, srcB) ||
            !CV_ARE_SIZES_EQ(velx, vely) ||
            !CV_ARE_SIZES_EQ(srcA, velx)) {
        CV_Error(CV_StsUnmatchedSizes, "");
    }

    if (CV_MAT_TYPE(srcA->type) != CV_8UC1 ||
            CV_MAT_TYPE(velx->type) != CV_32FC1)
        CV_Error(CV_StsUnsupportedFormat, "Source images must have 8uC1 type and "
                 "destination images must have 32fC1 type");

    if (srcA->step != srcB->step || velx->step != vely->step) {
        CV_Error(CV_BadStep, "source and destination images have different step");
    }

    IPPI_CALL(icvCalcOpticalFlowLK_8u32fR((uchar*)srcA->data.ptr, (uchar*)srcB->data.ptr,
                                          srcA->step, cvGetMatSize(srcA), winSize,
                                          velx->data.fl, vely->data.fl, velx->step));
}

CV_IMPL  CvSeq*
cvContourConvexHullApprox( CvSeq * sequence, int bandwidth,
                           int orientation, CvMemStorage * storage )
{
    CvSeq *hull = 0;
    
    CV_FUNCNAME( "cvContourConvexHullApprox" );

    __BEGIN__;

    /* check arguments */
    if( !sequence || !storage )
        CV_ERROR_FROM_STATUS( CV_NULLPTR_ERR );

    if( bandwidth < 1 )
        CV_ERROR_FROM_STATUS( CV_BADSIZE_ERR );

    if( orientation != CV_CLOCKWISE && orientation != CV_COUNTER_CLOCKWISE )
        CV_ERROR_FROM_STATUS( CV_BADFLAG_ERR );

    IPPI_CALL( icvConvexHull_Approx_Contour( sequence, bandwidth,
                                             orientation, storage, &hull ));
    __CLEANUP__;
    __END__;

    return hull;
}

/* 改变轮廓位置使得它的能量最小 

void cvSnakeImage( const IplImage* image, CvPoint* points, int length,
                   float* alpha, float* beta, float* gamma, int coeff_usage,
                   CvSize win, CvTermCriteria criteria, int calc_gradient=1 );
image 
输入图像或外部能量域 
points 
轮廓点 (snake). 
length 
轮廓点的数目 
alpha 
连续性能量的权 Weight[s]，单个浮点数或长度为 length 的浮点数数组，每个轮廓点有一个权 
beta 
曲率能量的权 Weight[s]，与 alpha 类似 
gamma 
图像能量的权 Weight[s]，与 alpha 类似 
coeff_usage 
前面三个参数的不同使用方法： 
CV_VALUE 表示每个 alpha, beta, gamma 都是指向为所有点所用的一个单独数值; 
CV_ARRAY 表示每个 alpha, beta, gamma 是一个指向系数数组的指针，snake 上面各点的系数都不相同。因此，各个系数数组必须与轮廓具有同样的大小。所有数组必须与轮廓具有同样大小 
win 
每个点用于搜索最小值的邻域尺寸，两个 win.width 和 win.height 都必须是奇数 
criteria 
终止条件 
calc_gradient 
梯度符号。如果非零，函数为每一个图像象素计算梯度幅值，且把它当成能量场，否则考虑输入图像本身。 
函数 cvSnakeImage 更新 snake 是为了最小化 snake 的整个能量，其中能量是依赖于轮廓形状的内部能量(轮廓越光滑，内部能量越小)以及依赖于能量场的外部能量之和，外部能量通常在哪些局部能量极值点中达到最小值(这些局部能量极值点与图像梯度表示的图像边缘相对应)。 

参数 criteria.epsilon 用来定义必须从迭代中除掉以保证迭代正常运行的点的最少数目。 

如果在迭代中去掉的点数目小于 criteria.epsilon 或者函数达到了最大的迭代次数 criteria.max_iter ，则终止函数。 

 */
CV_IMPL void
cvSnakeImage( const IplImage* src, CvPoint* points,
              int length, float *alpha,
              float *beta, float *gamma,
              int coeffUsage, CvSize win,
              CvTermCriteria criteria, int calcGradient )
{

    CV_FUNCNAME( "cvSnakeImage" );

    __BEGIN__;

    uchar *data;
    CvSize size;
    int step;

    if( src->nChannels != 1 )
        CV_ERROR( CV_BadNumChannels, "input image has more than one channel" );

    if( src->depth != IPL_DEPTH_8U )
        CV_ERROR( CV_BadDepth, cvUnsupportedFormat );

    cvGetRawData( src, &data, &step, &size );

    IPPI_CALL( icvSnake8uC1R( data, step, size, points, length,
                              alpha, beta, gamma, coeffUsage, win, criteria,
                              calcGradient ? _CV_SNAKE_GRAD : _CV_SNAKE_IMAGE ));
    __END__;
}

CV_IMPL void
cvConvexHullApprox( CvPoint * points,
                    int num_points,
                    CvRect * bound_rect,
                    int bandwidth, int orientation, int *hullpoints, int *hullsize )
{
    CV_FUNCNAME( "cvConvexHullApprox" );

    __BEGIN__;

    if( !points || !hullpoints || !hullsize )
        CV_ERROR_FROM_STATUS( CV_NULLPTR_ERR );

    if( bandwidth < 1 )
        CV_ERROR_FROM_STATUS( CV_BADSIZE_ERR );

    IPPI_CALL( icvConvexHull_Approx( points,
                                     num_points,
                                     bound_rect,
                                     bandwidth, orientation, hullpoints, hullsize ));

    __CLEANUP__;
    __END__;

}

static void
icxLogicSM( const void* srcarr, CxScalar* scalar, void* dstarr,
            const void* maskarr, CxArithmUniMaskFunc2D func )
{
    CX_FUNCNAME( "icxLogicSM" );
    
    __BEGIN__;

    double buf[12];
    int coi1 = 0, coi2 = 0;
    CxMat  srcstub, *src = (CxMat*)srcarr;
    CxMat  dststub, *dst = (CxMat*)dstarr;
    CxMat  maskstub, *mask = (CxMat*)maskarr;
    int pix_size, type;
    int dst_step, mask_step;
    CxSize size;

    if( !CX_IS_MAT(src))
        CX_CALL( src = cxGetMat( src, &srcstub, &coi1 ));

    if( !CX_IS_MAT(dst))
        CX_CALL( dst = cxGetMat( dst, &dststub ));

    if( coi1 != 0 || coi2 != 0 )
        CX_ERROR( CX_BadCOI, "" );

    CX_CALL( mask = cxGetMat( mask, &maskstub ));

    if( !CX_IS_MASK_ARR(mask) )
        CX_ERROR_FROM_CODE( CX_StsBadMask );

    if( !CX_ARE_SIZES_EQ( mask, dst ) )
        CX_ERROR_FROM_CODE( CX_StsUnmatchedSizes );

    if( src->data.ptr != dst->data.ptr )
    {
        CX_CALL( cxCopy( src, dst, mask ));
    }

    size = cxGetMatSize( dst );
    dst_step = dst->step;
    mask_step = mask->step;

    if( CX_IS_MAT_CONT( mask->type & dst->type ))
    {
        size.width *= size.height;
        dst_step = mask_step = CX_STUB_STEP;
        size.height = 1;
    }

    type = CX_MAT_TYPE( src->type );
    pix_size = icxPixSize[type];
    
    CX_CALL( cxScalarToRawData( scalar, buf, type, 0 ));
    IPPI_CALL( func( dst->data.ptr, dst_step, mask->data.ptr,
                     mask_step, size, buf, pix_size ));

    __END__;
}

CV_IMPL void
cvPOSIT( CvPOSITObject * pObject, CvPoint2D32f * imagePoints,
         double focalLength, CvTermCriteria criteria,
         float* rotation, float* translation )
{
    IPPI_CALL( icvPOSIT( pObject, imagePoints,(float) focalLength, criteria,
                         rotation, translation ));
}

/*F///////////////////////////////////////////////////////////////////////////////////////
//    Name: cvCreateContourTree
//    Purpose:
//    Create binary tree representation for the contour 
//    Context:
//    Parameters:
//      contour - pointer to input contour object.
//      storage - pointer to the current storage block
//      tree   -  output pointer to the binary tree representation 
//      threshold - threshold for the binary tree building 
//
//F*/
CV_IMPL CvContourTree*
cvCreateContourTree( const CvSeq* contour, CvMemStorage* storage, double threshold )
{
    CvContourTree* tree = 0;
    
    IPPI_CALL( icvCreateContourTree( contour, storage, &tree, threshold ));

    return tree;
}