C++ CV_MAT_CN函数代码示例

CV_IMPL void
cvInitUndistortMap( const CvMat* A, const CvMat* dist_coeffs,
                    CvArr* mapxarr, CvArr* mapyarr )
{
    uchar* buffer = 0;

    CV_FUNCNAME( "cvInitUndistortMap" );

    __BEGIN__;
    
    float a[9], k[4];
    int coi1 = 0, coi2 = 0;
    CvMat mapxstub, *_mapx = (CvMat*)mapxarr;
    CvMat mapystub, *_mapy = (CvMat*)mapyarr;
    float *mapx, *mapy;
    CvMat _a = cvMat( 3, 3, CV_32F, a ), _k;
    int mapxstep, mapystep;
    int u, v;
    float u0, v0, fx, fy, _fx, _fy, k1, k2, p1, p2;
    CvSize size;

    CV_CALL( _mapx = cvGetMat( _mapx, &mapxstub, &coi1 ));
    CV_CALL( _mapy = cvGetMat( _mapy, &mapystub, &coi2 ));

    if( coi1 != 0 || coi2 != 0 )
        CV_ERROR( CV_BadCOI, "The function does not support COI" );

    if( CV_MAT_TYPE(_mapx->type) != CV_32FC1 )
        CV_ERROR( CV_StsUnsupportedFormat, "Both maps must have 32fC1 type" );

    if( !CV_ARE_TYPES_EQ( _mapx, _mapy ))
        CV_ERROR( CV_StsUnmatchedFormats, "" );

    if( !CV_ARE_SIZES_EQ( _mapx, _mapy ))
        CV_ERROR( CV_StsUnmatchedSizes, "" );

    if( !CV_IS_MAT(A) || A->rows != 3 || A->cols != 3  ||
        CV_MAT_TYPE(A->type) != CV_32FC1 && CV_MAT_TYPE(A->type) != CV_64FC1 )
        CV_ERROR( CV_StsBadArg, "Intrinsic matrix must be a valid 3x3 floating-point matrix" );

    if( !CV_IS_MAT(dist_coeffs) || dist_coeffs->rows != 1 && dist_coeffs->cols != 1 ||
        dist_coeffs->rows*dist_coeffs->cols*CV_MAT_CN(dist_coeffs->type) != 4 ||
        CV_MAT_DEPTH(dist_coeffs->type) != CV_64F &&
        CV_MAT_DEPTH(dist_coeffs->type) != CV_32F )
        CV_ERROR( CV_StsBadArg,
            "Distortion coefficients must be 1x4 or 4x1 floating-point vector" );

    cvConvert( A, &_a );
    _k = cvMat( dist_coeffs->rows, dist_coeffs->cols,
                CV_MAKETYPE(CV_32F, CV_MAT_CN(dist_coeffs->type)), k );
    cvConvert( dist_coeffs, &_k );

    u0 = a[2]; v0 = a[5];
    fx = a[0]; fy = a[4];
    _fx = 1.f/fx; _fy = 1.f/fy;
    k1 = k[0]; k2 = k[1];
    p1 = k[2]; p2 = k[3];

    mapxstep = _mapx->step ? _mapx->step : CV_STUB_STEP;
    mapystep = _mapy->step ? _mapy->step : CV_STUB_STEP;
    mapx = _mapx->data.fl;
    mapy = _mapy->data.fl;

    size = cvGetMatSize(_mapx);
    
    /*if( icvUndistortGetSize_p && icvCreateMapCameraUndistort_32f_C1R_p )
    {
        int buf_size = 0;
        if( icvUndistortGetSize_p( size, &buf_size ) && buf_size > 0 )
        {
            CV_CALL( buffer = (uchar*)cvAlloc( buf_size ));
            if( icvCreateMapCameraUndistort_32f_C1R_p(
                mapx, mapxstep, mapy, mapystep, size,
                a[0], a[4], a[2], a[5], k[0], k[1], k[2], k[3], buffer ) >= 0 )
                EXIT;
        }
    }*/
    
    mapxstep /= sizeof(mapx[0]);
    mapystep /= sizeof(mapy[0]);

    for( v = 0; v < size.height; v++, mapx += mapxstep, mapy += mapystep )
    {
        float y = (v - v0)*_fy;
        float y2 = y*y;
        float _2p1y = 2*p1*y;
        float _3p1y2 = 3*p1*y2;
        float p2y2 = p2*y2;

        for( u = 0; u < size.width; u++ )
        {
            float x = (u - u0)*_fx;
            float x2 = x*x;
            float r2 = x2 + y2;
            float d = 1 + (k1 + k2*r2)*r2;
            float _u = fx*(x*(d + _2p1y) + p2y2 + (3*p2)*x2) + u0;
            float _v = fy*(y*(d + (2*p2)*x) + _3p1y2 + p1*x2) + v0;
            mapx[u] = _u;
            mapy[u] = _v;
        }
//.........这里部分代码省略.........

bool  PngDecoder::readData( Mat& img )
{
    bool result = false;
    AutoBuffer<uchar*> _buffer(m_height);
    uchar** buffer = _buffer;
    int color = img.channels() > 1;
    uchar* data = img.data;
    int step = (int)img.step;

    if( m_png_ptr && m_info_ptr && m_end_info && m_width && m_height )
    {
        png_structp png_ptr = (png_structp)m_png_ptr;
        png_infop info_ptr = (png_infop)m_info_ptr;
        png_infop end_info = (png_infop)m_end_info;

        if( setjmp( png_jmpbuf ( png_ptr ) ) == 0 )
        {
            int y;

            if( img.depth() == CV_8U && m_bit_depth == 16 )
                png_set_strip_16( png_ptr );
            else if( !isBigEndian() )
                png_set_swap( png_ptr );

            if(img.channels() < 4) 
            {
                /* observation: png_read_image() writes 400 bytes beyond
                 * end of data when reading a 400x118 color png
                 * "mpplus_sand.png".  OpenCV crashes even with demo
                 * programs.  Looking at the loaded image I'd say we get 4
                 * bytes per pixel instead of 3 bytes per pixel.  Test
                 * indicate that it is a good idea to always ask for
                 * stripping alpha..  18.11.2004 Axel Walthelm
                 */
                 png_set_strip_alpha( png_ptr );
            }

            if( m_color_type == PNG_COLOR_TYPE_PALETTE )
                png_set_palette_to_rgb( png_ptr );

            if( m_color_type == PNG_COLOR_TYPE_GRAY && m_bit_depth < 8 )
#if PNG_LIBPNG_VER_MAJOR*100 + PNG_LIBPNG_VER_MINOR >= 104
                png_set_expand_gray_1_2_4_to_8( png_ptr );
#else
                png_set_gray_1_2_4_to_8( png_ptr );
#endif
            
            if( CV_MAT_CN(m_type) > 1 && color )
                png_set_bgr( png_ptr ); // convert RGB to BGR
            else if( color )
                png_set_gray_to_rgb( png_ptr ); // Gray->RGB
            else
                png_set_rgb_to_gray( png_ptr, 1, 0.299, 0.587 ); // RGB->Gray

            png_read_update_info( png_ptr, info_ptr );

            for( y = 0; y < m_height; y++ )
                buffer[y] = data + y*step;

            png_read_image( png_ptr, buffer );
            png_read_end( png_ptr, end_info );

            result = true;
        }
    }

    close();
    return result;
}

void cv::Laplacian( InputArray _src, OutputArray _dst, int ddepth, int ksize,
                    double scale, double delta, int borderType )
{
    int stype = _src.type(), sdepth = CV_MAT_DEPTH(stype), cn = CV_MAT_CN(stype);
    if (ddepth < 0)
        ddepth = sdepth;
    _dst.create( _src.size(), CV_MAKETYPE(ddepth, cn) );

#ifdef HAVE_TEGRA_OPTIMIZATION
    if (scale == 1.0 && delta == 0)
    {
        Mat src = _src.getMat(), dst = _dst.getMat();
        if (ksize == 1 && tegra::laplace1(src, dst, borderType))
            return;
        if (ksize == 3 && tegra::laplace3(src, dst, borderType))
            return;
        if (ksize == 5 && tegra::laplace5(src, dst, borderType))
            return;
    }
#endif

    if( ksize == 1 || ksize == 3 )
    {
        float K[2][9] =
        {
            { 0, 1, 0, 1, -4, 1, 0, 1, 0 },
            { 2, 0, 2, 0, -8, 0, 2, 0, 2 }
        };
        Mat kernel(3, 3, CV_32F, K[ksize == 3]);
        if( scale != 1 )
            kernel *= scale;
        filter2D( _src, _dst, ddepth, kernel, Point(-1, -1), delta, borderType );
    }
    else
    {
        int ktype = std::max(CV_32F, std::max(ddepth, sdepth));
        int wdepth = sdepth == CV_8U && ksize <= 5 ? CV_16S : sdepth <= CV_32F ? CV_32F : CV_64F;
        int wtype = CV_MAKETYPE(wdepth, cn);
        Mat kd, ks;
        getSobelKernels( kd, ks, 2, 0, ksize, false, ktype );

        CV_OCL_RUN(_dst.isUMat(),
                   ocl_Laplacian5(_src, _dst, kd, ks, scale,
                                  delta, borderType, wdepth, ddepth))

        const size_t STRIPE_SIZE = 1 << 14;
        Ptr<FilterEngine> fx = createSeparableLinearFilter(stype,
            wtype, kd, ks, Point(-1,-1), 0, borderType, borderType, Scalar() );
        Ptr<FilterEngine> fy = createSeparableLinearFilter(stype,
            wtype, ks, kd, Point(-1,-1), 0, borderType, borderType, Scalar() );

        Mat src = _src.getMat(), dst = _dst.getMat();
        int y = fx->start(src), dsty = 0, dy = 0;
        fy->start(src);
        const uchar* sptr = src.data + y*src.step;

        int dy0 = std::min(std::max((int)(STRIPE_SIZE/(CV_ELEM_SIZE(stype)*src.cols)), 1), src.rows);
        Mat d2x( dy0 + kd.rows - 1, src.cols, wtype );
        Mat d2y( dy0 + kd.rows - 1, src.cols, wtype );

        for( ; dsty < src.rows; sptr += dy0*src.step, dsty += dy )
        {
            fx->proceed( sptr, (int)src.step, dy0, d2x.data, (int)d2x.step );
            dy = fy->proceed( sptr, (int)src.step, dy0, d2y.data, (int)d2y.step );
            if( dy > 0 )
            {
                Mat dstripe = dst.rowRange(dsty, dsty + dy);
                d2x.rows = d2y.rows = dy; // modify the headers, which should work
                d2x += d2y;
                d2x.convertTo( dstripe, ddepth, scale, delta );
            }
        }
    }
}

inline
int CudaMem::channels() const
{
    return CV_MAT_CN(flags);
}

static void*
imread_( const string& filename, int flags, int hdrtype, Mat* mat=0 )
{
    IplImage* image = 0;
    CvMat *matrix = 0;
    Mat temp, *data = &temp;

    ImageDecoder decoder = findDecoder(filename);
    if( decoder.empty() )
        return 0;
    decoder->setSource(filename);
    if( !decoder->readHeader() )
        return 0;

    CvSize size;
    size.width = decoder->width();
    size.height = decoder->height();

    int type = decoder->type();
    if( flags != -1 )
    {
        if( (flags & CV_LOAD_IMAGE_ANYDEPTH) == 0 )
            type = CV_MAKETYPE(CV_8U, CV_MAT_CN(type));

        if( (flags & CV_LOAD_IMAGE_COLOR) != 0 ||
           ((flags & CV_LOAD_IMAGE_ANYCOLOR) != 0 && CV_MAT_CN(type) > 1) )
            type = CV_MAKETYPE(CV_MAT_DEPTH(type), 3);
        else
            type = CV_MAKETYPE(CV_MAT_DEPTH(type), 1);
    }

    if( hdrtype == LOAD_CVMAT || hdrtype == LOAD_MAT )
    {
        if( hdrtype == LOAD_CVMAT )
        {
            matrix = cvCreateMat( size.height, size.width, type );
            temp = cvarrToMat(matrix);
        }
        else
        {
            mat->create( size.height, size.width, type );
            data = mat;
        }
    }
    else
    {
        image = cvCreateImage( size, cvIplDepth(type), CV_MAT_CN(type) );
        temp = cvarrToMat(image);
    }

    if( !decoder->readData( *data ))
    {
        cvReleaseImage( &image );
        cvReleaseMat( &matrix );
        if( mat )
            mat->release();
        return 0;
    }

    return hdrtype == LOAD_CVMAT ? (void*)matrix :
        hdrtype == LOAD_IMAGE ? (void*)image : (void*)mat;
}

CV_IMPL void
cvGetRectSubPix( const void* srcarr, void* dstarr, CvPoint2D32f center )
{
    static CvFuncTable gr_tab[2];
    static int inittab = 0;
    CV_FUNCNAME( "cvGetRectSubPix" );

    __BEGIN__;

    CvMat srcstub, *src = (CvMat*)srcarr;
    CvMat dststub, *dst = (CvMat*)dstarr;
    CvSize src_size, dst_size;
    CvGetRectSubPixFunc func;
    int cn, src_step, dst_step;

    if( !inittab )
    {
        icvInitGetRectSubPixC1RTable( gr_tab + 0 );
        icvInitGetRectSubPixC3RTable( gr_tab + 1 );
        inittab = 1;
    }

    if( !CV_IS_MAT(src))
        CV_CALL( src = cvGetMat( src, &srcstub ));

    if( !CV_IS_MAT(dst))
        CV_CALL( dst = cvGetMat( dst, &dststub ));

    cn = CV_MAT_CN( src->type );

    if( (cn != 1 && cn != 3) || !CV_ARE_CNS_EQ( src, dst ))
        CV_ERROR( CV_StsUnsupportedFormat, "" );

    src_size = cvGetMatSize( src );
    dst_size = cvGetMatSize( dst );
    src_step = src->step ? src->step : CV_STUB_STEP;
    dst_step = dst->step ? dst->step : CV_STUB_STEP;

    //if( dst_size.width > src_size.width || dst_size.height > src_size.height )
    //    CV_ERROR( CV_StsBadSize, "destination ROI must be smaller than source ROI" );

    if( CV_ARE_DEPTHS_EQ( src, dst ))
    {
        func = (CvGetRectSubPixFunc)(gr_tab[cn != 1].fn_2d[CV_MAT_DEPTH(src->type)]);
    }
    else
    {
        if( CV_MAT_DEPTH( src->type ) != CV_8U || CV_MAT_DEPTH( dst->type ) != CV_32F )
            CV_ERROR( CV_StsUnsupportedFormat, "" );

        func = (CvGetRectSubPixFunc)(gr_tab[cn != 1].fn_2d[1]);
    }

    if( !func )
        CV_ERROR( CV_StsUnsupportedFormat, "" );

    IPPI_CALL( func( src->data.ptr, src_step, src_size,
                     dst->data.ptr, dst_step, dst_size, center ));

    __END__;
}

CV_IMPL void
cvIntegral( const CvArr* image, CvArr* sumImage,
            CvArr* sumSqImage, CvArr* tiltedSumImage )
{
    
    CV_FUNCNAME( "cvIntegralImage" );

    __BEGIN__;

    CvMat src_stub, *src = (CvMat*)image;
    CvMat sum_stub, *sum = (CvMat*)sumImage;
    CvMat sqsum_stub, *sqsum = (CvMat*)sumSqImage;
    CvMat tilted_stub, *tilted = (CvMat*)tiltedSumImage;
    int coi0 = 0, coi1 = 0, coi2 = 0, coi3 = 0;
    //int depth;
    int cn;
    int src_step, sum_step, sqsum_step, tilted_step;
    CvSize size;


    CV_CALL( src = cvGetMat( src, &src_stub, &coi0 ));
    CV_CALL( sum = cvGetMat( sum, &sum_stub, &coi1 ));
    
    if( sum->width != src->width + 1 ||
        sum->height != src->height + 1 )
        CV_ERROR( CV_StsUnmatchedSizes, "" );

	if(CV_MAT_DEPTH(src->type)!=CV_8U || CV_MAT_CN(src->type)!=1)
		CV_ERROR( CV_StsUnsupportedFormat, "the source array must be 8UC1");

    if( CV_MAT_DEPTH( sum->type ) != CV_32S ||
        !CV_ARE_CNS_EQ( src, sum ))
        CV_ERROR( CV_StsUnsupportedFormat,
        "Sum array must have 32s type in case of 8u source array"
        "and the same number of channels as the source array" );

    if( sqsum )
    {
        CV_CALL( sqsum = cvGetMat( sqsum, &sqsum_stub, &coi2 ));
        if( !CV_ARE_SIZES_EQ( sum, sqsum ) )
            CV_ERROR( CV_StsUnmatchedSizes, "" );
        if( CV_MAT_DEPTH( sqsum->type ) != CV_64S || !CV_ARE_CNS_EQ( src, sqsum ))
            CV_ERROR( CV_StsUnsupportedFormat,
                      "Squares sum array must be 64s "
                      "and the same number of channels as the source array" );
    }

    if( tilted )
    {
        if( !sqsum )
            CV_ERROR( CV_StsNullPtr,
            "Squared sum array must be passed if tilted sum array is passed" );

        CV_CALL( tilted = cvGetMat( tilted, &tilted_stub, &coi3 ));
        if( !CV_ARE_SIZES_EQ( sum, tilted ) )
            CV_ERROR( CV_StsUnmatchedSizes, "" );
        if( !CV_ARE_TYPES_EQ( sum, tilted ) )
            CV_ERROR( CV_StsUnmatchedFormats,
                      "Sum and tilted sum must have the same types" );
        if( CV_MAT_CN(tilted->type) != 1 )
            CV_ERROR( CV_StsNotImplemented,
                      "Tilted sum can not be computed for multi-channel arrays" );
    }

    if( coi0 || coi1 || coi2 || coi3 )
        CV_ERROR( CV_BadCOI, "COI is not supported by the function" );

    //depth = CV_MAT_DEPTH(src->type);
    cn = CV_MAT_CN(src->type);


    size = cvGetMatSize(src);
    src_step = src->step ? src->step : CV_STUB_STEP;
    sum_step = sum->step ? sum->step : CV_STUB_STEP;
    sqsum_step = !sqsum ? 0 : sqsum->step ? sqsum->step : CV_STUB_STEP;
    tilted_step = !tilted ? 0 : tilted->step ? tilted->step : CV_STUB_STEP;

    if( cn == 1 )
    {
        
        cvIntegralImage_8u32s64s_C1R( src->data.ptr, src_step, (int*)(sum->data.ptr), sum_step,
                        sqsum ? (int64*)(sqsum->data.ptr) : 0, sqsum_step,
                        tilted ? (int*)(tilted->data.ptr) : 0, tilted_step, size );
    }

    __END__;
}

void CvBoxFilter::init( int _max_width, int _src_type, int _dst_type,
                        bool _normalized, CvSize _ksize,
                        CvPoint _anchor, int _border_mode,
                        CvScalar _border_value )
{
    CV_FUNCNAME( "CvBoxFilter::init" );

    __BEGIN__;
    
    sum = 0;
    normalized = _normalized;

    if( normalized && CV_MAT_TYPE(_src_type) != CV_MAT_TYPE(_dst_type) ||
        !normalized && CV_MAT_CN(_src_type) != CV_MAT_CN(_dst_type))
        CV_ERROR( CV_StsUnmatchedFormats,
        "In case of normalized box filter input and output must have the same type.\n"
        "In case of unnormalized box filter the number of input and output channels must be the same" );

    min_depth = CV_MAT_DEPTH(_src_type) == CV_8U ? CV_32S : CV_64F;

    CvBaseImageFilter::init( _max_width, _src_type, _dst_type, 1, _ksize,
                             _anchor, _border_mode, _border_value );
    
    scale = normalized ? 1./(ksize.width*ksize.height) : 1;

    if( CV_MAT_DEPTH(src_type) == CV_8U )
        x_func = (CvRowFilterFunc)icvSumRow_8u32s;
    else if( CV_MAT_DEPTH(src_type) == CV_32F )
        x_func = (CvRowFilterFunc)icvSumRow_32f64f;
    else
        CV_ERROR( CV_StsUnsupportedFormat, "Unknown/unsupported input image format" );

    if( CV_MAT_DEPTH(dst_type) == CV_8U )
    {
        if( !normalized )
            CV_ERROR( CV_StsBadArg, "Only normalized box filter can be used for 8u->8u transformation" );
        y_func = (CvColumnFilterFunc)icvSumCol_32s8u;
    }
    else if( CV_MAT_DEPTH(dst_type) == CV_16S )
    {
        if( normalized || CV_MAT_DEPTH(src_type) != CV_8U )
            CV_ERROR( CV_StsBadArg, "Only 8u->16s unnormalized box filter is supported in case of 16s output" );
        y_func = (CvColumnFilterFunc)icvSumCol_32s16s;
    }
	else if( CV_MAT_DEPTH(dst_type) == CV_32S )
	{
		if( normalized || CV_MAT_DEPTH(src_type) != CV_8U )
			CV_ERROR( CV_StsBadArg, "Only 8u->32s unnormalized box filter is supported in case of 32s output");

		y_func = (CvColumnFilterFunc)icvSumCol_32s32s;
	}
    else if( CV_MAT_DEPTH(dst_type) == CV_32F )
    {
        if( CV_MAT_DEPTH(src_type) != CV_32F )
            CV_ERROR( CV_StsBadArg, "Only 32f->32f box filter (normalized or not) is supported in case of 32f output" );
        y_func = (CvColumnFilterFunc)icvSumCol_64f32f;
    }
	else{
		CV_ERROR( CV_StsBadArg, "Unknown/unsupported destination image format" );
	}

    __END__;
}

CV_IMPL CvSeq*
cvConvexHull2( const CvArr* array, void* hull_storage,
               int orientation, int return_points )
{
    CvMat* mat = 0;
    CvContour contour_header;
    CvSeq hull_header;
    CvSeqBlock block, hullblock;
    CvSeq* ptseq = 0;
    CvSeq* hullseq = 0;

    if( CV_IS_SEQ( array ))
    {
        ptseq = (CvSeq*)array;
        if( !CV_IS_SEQ_POINT_SET( ptseq ))
            CV_Error( CV_StsBadArg, "Unsupported sequence type" );
        if( hull_storage == 0 )
            hull_storage = ptseq->storage;
    }
    else
    {
        ptseq = cvPointSeqFromMat( CV_SEQ_KIND_GENERIC, array, &contour_header, &block );
    }

    bool isStorage = isStorageOrMat(hull_storage);

    if(isStorage)
    {
        if( return_points )
        {
            hullseq = cvCreateSeq(CV_SEQ_KIND_CURVE|CV_SEQ_ELTYPE(ptseq)|
                                  CV_SEQ_FLAG_CLOSED|CV_SEQ_FLAG_CONVEX,
                                  sizeof(CvContour), sizeof(CvPoint),(CvMemStorage*)hull_storage );
        }
        else
        {
            hullseq = cvCreateSeq(
                                  CV_SEQ_KIND_CURVE|CV_SEQ_ELTYPE_PPOINT|
                                  CV_SEQ_FLAG_CLOSED|CV_SEQ_FLAG_CONVEX,
                                  sizeof(CvContour), sizeof(CvPoint*), (CvMemStorage*)hull_storage );
        }
    }
    else
    {
        mat = (CvMat*)hull_storage;

        if( (mat->cols != 1 && mat->rows != 1) || !CV_IS_MAT_CONT(mat->type))
            CV_Error( CV_StsBadArg,
                     "The hull matrix should be continuous and have a single row or a single column" );

        if( mat->cols + mat->rows - 1 < ptseq->total )
            CV_Error( CV_StsBadSize, "The hull matrix size might be not enough to fit the hull" );

        if( CV_MAT_TYPE(mat->type) != CV_SEQ_ELTYPE(ptseq) &&
           CV_MAT_TYPE(mat->type) != CV_32SC1 )
            CV_Error( CV_StsUnsupportedFormat,
                     "The hull matrix must have the same type as input or 32sC1 (integers)" );

        hullseq = cvMakeSeqHeaderForArray(
                                          CV_SEQ_KIND_CURVE|CV_MAT_TYPE(mat->type)|CV_SEQ_FLAG_CLOSED,
                                          sizeof(hull_header), CV_ELEM_SIZE(mat->type), mat->data.ptr,
                                          mat->cols + mat->rows - 1, &hull_header, &hullblock );
        cvClearSeq( hullseq );
    }

    int hulltype = CV_SEQ_ELTYPE(hullseq);
    int total = ptseq->total;
    if( total == 0 )
    {
        if( !isStorage )
            CV_Error( CV_StsBadSize,
                     "Point sequence can not be empty if the output is matrix" );
        return 0;
    }

    cv::AutoBuffer<double> _ptbuf;
    cv::Mat h0;
    cv::convexHull(cv::cvarrToMat(ptseq, false, false, 0, &_ptbuf), h0,
                   orientation == CV_CLOCKWISE, CV_MAT_CN(hulltype) == 2);


    if( hulltype == CV_SEQ_ELTYPE_PPOINT )
    {
        const int* idx = h0.ptr<int>();
        int ctotal = (int)h0.total();
        for( int i = 0; i < ctotal; i++ )
        {
            void* ptr = cvGetSeqElem(ptseq, idx[i]);
            cvSeqPush( hullseq, &ptr );
        }
    }
    else
        cvSeqPushMulti(hullseq, h0.ptr(), (int)h0.total());

    if (isStorage)
    {
        return hullseq;
    }
    else
    {
//.........这里部分代码省略.........

static void
icvSumCol_32s16s( const int** src, short* dst,
                  int dst_step, int count, void* params )
{
    CvBoxFilter* state = (CvBoxFilter*)params;
    int ksize = state->get_kernel_size().height;
    int ktotal = ksize*state->get_kernel_size().width;
    int i, width = state->get_width();
    int cn = CV_MAT_CN(state->get_src_type());
    int* sum = (int*)state->get_sum_buf();
    int* _sum_count = state->get_sum_count_ptr();
    int sum_count = *_sum_count;

    dst_step /= sizeof(dst[0]);
    width *= cn;
    src += sum_count;
    count += ksize - 1 - sum_count;

    for( ; count--; src++ )
    {
        const int* sp = src[0];
        if( sum_count+1 < ksize )
        {
            for( i = 0; i <= width - 2; i += 2 )
            {
                int s0 = sum[i] + sp[i], s1 = sum[i+1] + sp[i+1];
                sum[i] = s0; sum[i+1] = s1;
            }

            for( ; i < width; i++ )
                sum[i] += sp[i];

            sum_count++;
        }
        else if( ktotal < 128 )
        {
            const int* sm = src[-ksize+1];
            for( i = 0; i <= width - 2; i += 2 )
            {
                int s0 = sum[i] + sp[i], s1 = sum[i+1] + sp[i+1];
                dst[i] = (short)s0; dst[i+1] = (short)s1;
                s0 -= sm[i]; s1 -= sm[i+1];
                sum[i] = s0; sum[i+1] = s1;
            }

            for( ; i < width; i++ )
            {
                int s0 = sum[i] + sp[i];
                dst[i] = (short)s0;
                sum[i] = s0 - sm[i];
            }
            dst += dst_step;
        }
        else
        {
            const int* sm = src[-ksize+1];
            for( i = 0; i <= width - 2; i += 2 )
            {
                int s0 = sum[i] + sp[i], s1 = sum[i+1] + sp[i+1];
                dst[i] = CV_CAST_16S(s0); dst[i+1] = CV_CAST_16S(s1);
                s0 -= sm[i]; s1 -= sm[i+1];
                sum[i] = s0; sum[i+1] = s1;
            }

            for( ; i < width; i++ )
            {
                int s0 = sum[i] + sp[i];
                dst[i] = CV_CAST_16S(s0);
                sum[i] = s0 - sm[i];
            }
            dst += dst_step;
        }
    }

    *_sum_count = sum_count;
}

static void
icvSumCol_64f32f( const double** src, float* dst,
                  int dst_step, int count, void* params )
{
    CvBoxFilter* state = (CvBoxFilter*)params;
    int ksize = state->get_kernel_size().height;
    int i, width = state->get_width();
    int cn = CV_MAT_CN(state->get_src_type());
    double scale = state->get_scale();
    bool normalized = state->is_normalized();
    double* sum = (double*)state->get_sum_buf();
    int* _sum_count = state->get_sum_count_ptr();
    int sum_count = *_sum_count;

    dst_step /= sizeof(dst[0]);
    width *= cn;
    src += sum_count;
    count += ksize - 1 - sum_count;

    for( ; count--; src++ )
    {
        const double* sp = src[0];
        if( sum_count+1 < ksize )
        {
            for( i = 0; i <= width - 2; i += 2 )
            {
                double s0 = sum[i] + sp[i], s1 = sum[i+1] + sp[i+1];
                sum[i] = s0; sum[i+1] = s1;
            }

            for( ; i < width; i++ )
                sum[i] += sp[i];

            sum_count++;
        }
        else
        {
            const double* sm = src[-ksize+1];
            if( normalized )
                for( i = 0; i <= width - 2; i += 2 )
                {
                    double s0 = sum[i] + sp[i], s1 = sum[i+1] + sp[i+1];
                    double t0 = s0*scale, t1 = s1*scale;
                    s0 -= sm[i]; s1 -= sm[i+1];
                    dst[i] = (float)t0; dst[i+1] = (float)t1;
                    sum[i] = s0; sum[i+1] = s1;
                }
            else
                for( i = 0; i <= width - 2; i += 2 )
                {
                    double s0 = sum[i] + sp[i], s1 = sum[i+1] + sp[i+1];
                    dst[i] = (float)s0; dst[i+1] = (float)s1;
                    s0 -= sm[i]; s1 -= sm[i+1];
                    sum[i] = s0; sum[i+1] = s1;
                }

            for( ; i < width; i++ )
            {
                double s0 = sum[i] + sp[i], t0 = s0*scale;
                sum[i] = s0 - sm[i]; dst[i] = (float)t0;
            }
            dst += dst_step;
        }
    }

    *_sum_count = sum_count;
}

 inline int oclMat::oclchannels() const
 {
     return (CV_MAT_CN(flags)) == 3 ? 4 : (CV_MAT_CN(flags));
 }

CV_IMPL void
cvKMeans2( const CvArr* samples_arr, int cluster_count,
           CvArr* labels_arr, CvTermCriteria termcrit )
{
    CvMat* centers = 0;
    CvMat* old_centers = 0;
    CvMat* counters = 0;

    CV_FUNCNAME( "cvKMeans2" );

    __BEGIN__;

    CvMat samples_stub, labels_stub;
    CvMat* samples = (CvMat*)samples_arr;
    CvMat* labels = (CvMat*)labels_arr;
    CvMat* temp = 0;
    CvRNG rng = CvRNG(-1);
    int i, j, k, sample_count, dims;
    int ids_delta, iter;
    double max_dist;

    if( !CV_IS_MAT( samples ))
        CV_CALL( samples = cvGetMat( samples, &samples_stub ));

    if( !CV_IS_MAT( labels ))
        CV_CALL( labels = cvGetMat( labels, &labels_stub ));

    if( cluster_count < 1 )
        CV_ERROR( CV_StsOutOfRange, "Number of clusters should be positive" );

    if( CV_MAT_DEPTH(samples->type) != CV_32F || CV_MAT_TYPE(labels->type) != CV_32SC1 )
        CV_ERROR( CV_StsUnsupportedFormat,
        "samples should be floating-point matrix, cluster_idx - integer vector" );

    if( labels->rows != 1 && (labels->cols != 1 || !CV_IS_MAT_CONT(labels->type)) ||
        labels->rows + labels->cols - 1 != samples->rows )
        CV_ERROR( CV_StsUnmatchedSizes,
        "cluster_idx should be 1D vector of the same number of elements as samples' number of rows" );

    CV_CALL( termcrit = cvCheckTermCriteria( termcrit, 1e-6, 100 ));

    termcrit.epsilon *= termcrit.epsilon;
    sample_count = samples->rows;

    if( cluster_count > sample_count )
        cluster_count = sample_count;

    dims = samples->cols*CV_MAT_CN(samples->type);
    ids_delta = labels->step ? labels->step/(int)sizeof(int) : 1;

    CV_CALL( centers = cvCreateMat( cluster_count, dims, CV_64FC1 ));
    CV_CALL( old_centers = cvCreateMat( cluster_count, dims, CV_64FC1 ));
    CV_CALL( counters = cvCreateMat( 1, cluster_count, CV_32SC1 ));

    // init centers
    for( i = 0; i < sample_count; i++ )
        labels->data.i[i] = cvRandInt(&rng) % cluster_count;

    counters->cols = cluster_count; // cut down counters
    max_dist = termcrit.epsilon*2;

    for( iter = 0; iter < termcrit.max_iter; iter++ )
    {
        // computer centers
        cvZero( centers );
        cvZero( counters );

        for( i = 0; i < sample_count; i++ )
        {
            float* s = (float*)(samples->data.ptr + i*samples->step);
            k = labels->data.i[i*ids_delta];
            double* c = (double*)(centers->data.ptr + k*centers->step);
            for( j = 0; j <= dims - 4; j += 4 )
            {
                double t0 = c[j] + s[j];
                double t1 = c[j+1] + s[j+1];

                c[j] = t0;
                c[j+1] = t1;

                t0 = c[j+2] + s[j+2];
                t1 = c[j+3] + s[j+3];

                c[j+2] = t0;
                c[j+3] = t1;
            }
            for( ; j < dims; j++ )
                c[j] += s[j];
            counters->data.i[k]++;
        }

        if( iter > 0 )
            max_dist = 0;

        for( k = 0; k < cluster_count; k++ )
        {
            double* c = (double*)(centers->data.ptr + k*centers->step);
            if( counters->data.i[k] != 0 )
            {
                double scale = 1./counters->data.i[k];
//.........这里部分代码省略.........

CV_IMPL void cvFindStereoCorrespondenceGC( const CvArr* _left, const CvArr* _right,
    CvArr* _dispLeft, CvArr* _dispRight, CvStereoGCState* state, int useDisparityGuess )
{
    CvStereoGCState2 state2;
    state2.orphans = 0;
    state2.maxOrphans = 0;

    CV_FUNCNAME( "cvFindStereoCorrespondenceGC" );

    __BEGIN__;

    CvMat lstub, *left = cvGetMat( _left, &lstub );
    CvMat rstub, *right = cvGetMat( _right, &rstub );
    CvMat dlstub, *dispLeft = cvGetMat( _dispLeft, &dlstub );
    CvMat drstub, *dispRight = cvGetMat( _dispRight, &drstub );
    CvSize size;
    int iter, i, nZeroExpansions = 0;
    CvRNG rng = cvRNG(-1);
    int* disp;
    CvMat _disp;
    int64 E;

    CV_ASSERT( state != 0 );
    CV_ASSERT( CV_ARE_SIZES_EQ(left, right) && CV_ARE_TYPES_EQ(left, right) &&
               CV_MAT_TYPE(left->type) == CV_8UC1 );
    CV_ASSERT( !dispLeft ||
        (CV_ARE_SIZES_EQ(dispLeft, left) && CV_MAT_CN(dispLeft->type) == 1) );
    CV_ASSERT( !dispRight ||
        (CV_ARE_SIZES_EQ(dispRight, left) && CV_MAT_CN(dispRight->type) == 1) );

    size = cvGetSize(left);
    if( !state->left || state->left->width != size.width || state->left->height != size.height )
    {
        int pcn = (int)(sizeof(GCVtx*)/sizeof(int));
        int vcn = (int)(sizeof(GCVtx)/sizeof(int));
        int ecn = (int)(sizeof(GCEdge)/sizeof(int));
        cvReleaseMat( &state->left );
        cvReleaseMat( &state->right );
        cvReleaseMat( &state->ptrLeft );
        cvReleaseMat( &state->ptrRight );
        cvReleaseMat( &state->dispLeft );
        cvReleaseMat( &state->dispRight );

        state->left = cvCreateMat( size.height, size.width, CV_8UC3 );
        state->right = cvCreateMat( size.height, size.width, CV_8UC3 );
        state->dispLeft = cvCreateMat( size.height, size.width, CV_16SC1 );
        state->dispRight = cvCreateMat( size.height, size.width, CV_16SC1 );
        state->ptrLeft = cvCreateMat( size.height, size.width, CV_32SC(pcn) );
        state->ptrRight = cvCreateMat( size.height, size.width, CV_32SC(pcn) );
        state->vtxBuf = cvCreateMat( 1, size.height*size.width*2, CV_32SC(vcn) );
        state->edgeBuf = cvCreateMat( 1, size.height*size.width*12 + 16, CV_32SC(ecn) );
    }

    if( !useDisparityGuess )
    {
        cvSet( state->dispLeft, cvScalarAll(OCCLUDED));
        cvSet( state->dispRight, cvScalarAll(OCCLUDED));
    }
    else
    {
        CV_ASSERT( dispLeft && dispRight );
        cvConvert( dispLeft, state->dispLeft );
        cvConvert( dispRight, state->dispRight );
    }

    state2.Ithreshold = state->Ithreshold;
    state2.interactionRadius = state->interactionRadius;
    state2.lambda = cvRound(state->lambda*DENOMINATOR);
    state2.lambda1 = cvRound(state->lambda1*DENOMINATOR);
    state2.lambda2 = cvRound(state->lambda2*DENOMINATOR);
    state2.K = cvRound(state->K*DENOMINATOR);

    icvInitStereoConstTabs();
    icvInitGraySubpix( left, right, state->left, state->right );
    disp = (int*)cvStackAlloc( state->numberOfDisparities*sizeof(disp[0]) );
    _disp = cvMat( 1, state->numberOfDisparities, CV_32S, disp );
    cvRange( &_disp, state->minDisparity, state->minDisparity + state->numberOfDisparities );
    cvRandShuffle( &_disp, &rng );

    if( state2.lambda < 0 && (state2.K < 0 || state2.lambda1 < 0 || state2.lambda2 < 0) )
    {
        float L = icvComputeK(state)*0.2f;
        state2.lambda = cvRound(L*DENOMINATOR);
    }

    if( state2.K < 0 )
        state2.K = state2.lambda*5;
    if( state2.lambda1 < 0 )
        state2.lambda1 = state2.lambda*3;
    if( state2.lambda2 < 0 )
        state2.lambda2 = state2.lambda;

    icvInitStereoTabs( &state2 );

    E = icvComputeEnergy( state, &state2, !useDisparityGuess );
    for( iter = 0; iter < state->maxIters; iter++ )
    {
        for( i = 0; i < state->numberOfDisparities; i++ )
        {
            int alpha = disp[i];
//.........这里部分代码省略.........

/**
* Read an image into memory and return the information
*
* @param[in] filename File to load
* @param[in] flags Flags
* @param[in] mats Reference to C++ vector<Mat> object to hold the images
*
*/
static bool
imreadmulti_(const String& filename, int flags, std::vector<Mat>& mats)
{
    /// Search for the relevant decoder to handle the imagery
    ImageDecoder decoder;

#ifdef HAVE_GDAL
    if (flags != IMREAD_UNCHANGED && (flags & IMREAD_LOAD_GDAL) == IMREAD_LOAD_GDAL){
        decoder = GdalDecoder().newDecoder();
    }
    else{
#endif
        decoder = findDecoder(filename);
#ifdef HAVE_GDAL
    }
#endif

    /// if no decoder was found, return nothing.
    if (!decoder){
        return 0;
    }

    /// set the filename in the driver
    decoder->setSource(filename);

    // read the header to make sure it succeeds
    if (!decoder->readHeader())
        return 0;

    for (;;)
    {
        // grab the decoded type
        int type = decoder->type();
        if( (flags & IMREAD_LOAD_GDAL) != IMREAD_LOAD_GDAL && flags != IMREAD_UNCHANGED )
        {
            if ((flags & CV_LOAD_IMAGE_ANYDEPTH) == 0)
                type = CV_MAKETYPE(CV_8U, CV_MAT_CN(type));

            if ((flags & CV_LOAD_IMAGE_COLOR) != 0 ||
                ((flags & CV_LOAD_IMAGE_ANYCOLOR) != 0 && CV_MAT_CN(type) > 1))
                type = CV_MAKETYPE(CV_MAT_DEPTH(type), 3);
            else
                type = CV_MAKETYPE(CV_MAT_DEPTH(type), 1);
        }

        // read the image data
        Mat mat(decoder->height(), decoder->width(), type);
        if (!decoder->readData(mat))
        {
            // optionally rotate the data if EXIF' orientation flag says so
            if( (flags & IMREAD_IGNORE_ORIENTATION) == 0 && flags != IMREAD_UNCHANGED )
            {
                ApplyExifOrientation(filename, mat);
            }

            break;
        }

        mats.push_back(mat);
        if (!decoder->nextPage())
        {
            break;
        }
    }

    return !mats.empty();
}