cxmatmul.cpp

opencv库在TI DM6437上的移植,目前包括两个库cv.lib和cxcore.lib的工程

        {                                                           \
            c_data = _c_data;                                       \
            for( j = 0; j <= d_size.width - 4; j += 4, c_data += 4*c_step1 )\
            {                                                       \
                worktype t0 = alpha*d_buf[j];                       \
                worktype t1 = alpha*d_buf[j+1];                     \
                t0 += beta*worktype(c_data[0]);                     \
                t1 += beta*worktype(c_data[c_step1]);               \
                d_data[j] = arrtype(t0);                            \
                d_data[j+1] = arrtype(t1);                          \
                t0 = alpha*d_buf[j+2];                              \
                t1 = alpha*d_buf[j+3];                              \
                t0 += beta*worktype(c_data[c_step1*2]);             \
                t1 += beta*worktype(c_data[c_step1*3]);             \
                d_data[j+2] = arrtype(t0);                          \
                d_data[j+3] = arrtype(t1);                          \
            }                                                       \
            for( ; j < d_size.width; j++, c_data += c_step1 )       \
            {                                                       \
                worktype t0 = alpha*d_buf[j];                       \
                d_data[j] = arrtype(t0 + beta*c_data[0]);           \
            }                                                       \
        }                                                           \
        else                                                        \
        {                                                           \
            for( j = 0; j <= d_size.width - 4; j += 4 )             \
            {                                                       \
                worktype t0 = alpha*d_buf[j];                       \
                worktype t1 = alpha*d_buf[j+1];                     \
                d_data[j] = arrtype(t0);                            \
                d_data[j+1] = arrtype(t1);                          \
                t0 = alpha*d_buf[j+2];                              \
                t1 = alpha*d_buf[j+3];                              \
                d_data[j+2] = arrtype(t0);                          \
                d_data[j+3] = arrtype(t1);                          \
            }                                                       \
            for( ; j < d_size.width; j++ )                          \
                d_data[j] = arrtype(alpha*d_buf[j]);                \
        }                                                           \
    }                                                               \
    return CV_OK;                                                   \
}


ICV_DEF_GEMM_SINGLE_MUL( 32f_C1R, float, double)
ICV_DEF_GEMM_BLOCK_MUL( 32f_C1R, float, double)
ICV_DEF_GEMM_STORE( 32f_C1R, float, double)

ICV_DEF_GEMM_SINGLE_MUL( 64f_C1R, double, double)
ICV_DEF_GEMM_BLOCK_MUL( 64f_C1R, double, double)
ICV_DEF_GEMM_STORE( 64f_C1R, double, double)

ICV_DEF_GEMM_SINGLE_MUL( 32f_C2R, CvComplex32f, CvComplex64f)
ICV_DEF_GEMM_BLOCK_MUL( 32f_C2R, CvComplex32f, CvComplex64f)
ICV_DEF_GEMM_STORE( 32f_C2R, CvComplex32f, CvComplex64f)

ICV_DEF_GEMM_SINGLE_MUL( 64f_C2R, CvComplex64f, CvComplex64f)
ICV_DEF_GEMM_BLOCK_MUL( 64f_C2R, CvComplex64f, CvComplex64f)
ICV_DEF_GEMM_STORE( 64f_C2R, CvComplex64f, CvComplex64f)

typedef CvStatus (CV_STDCALL *CvGEMMSingleMulFunc)( const void* src1, size_t step1,
                   const void* src2, size_t step2, const void* src3, size_t step3,
                   void* dst, size_t dststep, CvSize srcsize, CvSize dstsize,
                   double alpha, double beta, int flags );

typedef CvStatus (CV_STDCALL *CvGEMMBlockMulFunc)( const void* src1, size_t step1,
                   const void* src2, size_t step2, void* dst, size_t dststep,
                   CvSize srcsize, CvSize dstsize, int flags );

typedef CvStatus (CV_STDCALL *CvGEMMStoreFunc)( const void* src1, size_t step1,
                   const void* src2, size_t step2, void* dst, size_t dststep,
                   CvSize dstsize, double alpha, double beta, int flags );


static void icvInitGEMMTable( CvBigFuncTable* single_mul_tab,
                              CvBigFuncTable* block_mul_tab,
                              CvBigFuncTable* store_tab )
{
    single_mul_tab->fn_2d[CV_32FC1] = (void*)icvGEMMSingleMul_32f_C1R;
    single_mul_tab->fn_2d[CV_64FC1] = (void*)icvGEMMSingleMul_64f_C1R;
    single_mul_tab->fn_2d[CV_32FC2] = (void*)icvGEMMSingleMul_32f_C2R;
    single_mul_tab->fn_2d[CV_64FC2] = (void*)icvGEMMSingleMul_64f_C2R;
    block_mul_tab->fn_2d[CV_32FC1] = (void*)icvGEMMBlockMul_32f_C1R;
    block_mul_tab->fn_2d[CV_64FC1] = (void*)icvGEMMBlockMul_64f_C1R;
    block_mul_tab->fn_2d[CV_32FC2] = (void*)icvGEMMBlockMul_32f_C2R;
    block_mul_tab->fn_2d[CV_64FC2] = (void*)icvGEMMBlockMul_64f_C2R;
    store_tab->fn_2d[CV_32FC1] = (void*)icvGEMMStore_32f_C1R;
    store_tab->fn_2d[CV_64FC1] = (void*)icvGEMMStore_64f_C1R;
    store_tab->fn_2d[CV_32FC2] = (void*)icvGEMMStore_32f_C2R;
    store_tab->fn_2d[CV_64FC2] = (void*)icvGEMMStore_64f_C2R;
}


CV_IMPL void
cvGEMM( const CvArr* Aarr, const CvArr* Barr, double alpha,
        const CvArr* Carr, double beta, CvArr* Darr, int flags )
{
    const int block_lin_size = 128;
    const int block_size = block_lin_size * block_lin_size;

    static CvBigFuncTable single_mul_tab, block_mul_tab, store_tab;
    static int inittab = 0;
    static double zero[] = {0,0,0,0};
    static float zerof[] = {0,0,0,0};
    
    uchar* buffer = 0;
    int local_alloc = 0;
    uchar* block_buffer = 0;

    CV_FUNCNAME( "cvGEMM" );

    __BEGIN__;

    CvMat *A = (CvMat*)Aarr;
    CvMat *B = (CvMat*)Barr;
    CvMat *C = (CvMat*)Carr;
    CvMat *D = (CvMat*)Darr;
    int len = 0;
    
    CvMat stub, stub1, stub2, stub3;
    CvSize a_size, d_size;
    int type;

    if( !CV_IS_MAT( A ))
    {
        int coi = 0;
        CV_CALL( A = cvGetMat( A, &stub1, &coi ));

        if( coi != 0 )
            CV_ERROR( CV_BadCOI, "" );
    }

    if( !CV_IS_MAT( B ))
    {
        int coi = 0;
        CV_CALL( B = cvGetMat( B, &stub2, &coi ));

        if( coi != 0 )
            CV_ERROR( CV_BadCOI, "" );
    }

    if( !CV_IS_MAT( D ))
    {
        int coi = 0;
        CV_CALL( D = cvGetMat( D, &stub, &coi ));

        if( coi != 0 )
            CV_ERROR( CV_BadCOI, "" );
    }

    if( beta == 0 )
        C = 0;

    if( C )
    {
        if( !CV_IS_MAT( C ))
        {
            int coi = 0;
            CV_CALL( C = cvGetMat( C, &stub3, &coi ));

            if( coi != 0 )
                CV_ERROR( CV_BadCOI, "" );
        }

        if( !CV_ARE_TYPES_EQ( C, D ))
            CV_ERROR( CV_StsUnmatchedFormats, "" );

        if( (flags&CV_GEMM_C_T) == 0 && (C->cols != D->cols || C->rows != D->rows) ||
            (flags&CV_GEMM_C_T) != 0 && (C->rows != D->cols || C->cols != D->rows))
            CV_ERROR( CV_StsUnmatchedSizes, "" );

        if( (flags & CV_GEMM_C_T) != 0 && C->data.ptr == D->data.ptr )
        {
            cvTranspose( C, D );
            C = D;
            flags &= ~CV_GEMM_C_T;
        }
    }
    else
    {
        C = &stub3;
        C->data.ptr = 0;
        C->step = 0;
        C->type = CV_MAT_CONT_FLAG;
    }

    type = CV_MAT_TYPE(A->type);
    if( !CV_ARE_TYPES_EQ( A, B ) || !CV_ARE_TYPES_EQ( A, D ) )
        CV_ERROR( CV_StsUnmatchedFormats, "" );

    a_size.width = A->cols;
    a_size.height = A->rows;
    d_size.width = D->cols;
    d_size.height = D->rows;

    switch( flags & (CV_GEMM_A_T|CV_GEMM_B_T) )
    {
    case 0:
        len = B->rows;
        if( a_size.width != len ||
            B->cols != d_size.width ||
            a_size.height != d_size.height )
            CV_ERROR( CV_StsUnmatchedSizes, "" );
        break;
    case 1:
        len = B->rows;
        if( a_size.height != len ||
            B->cols != d_size.width ||
            a_size.width != d_size.height )
            CV_ERROR( CV_StsUnmatchedSizes, "" );
        break;
    case 2:
        len = B->cols;
        if( a_size.width != len ||
            B->rows != d_size.width ||
            a_size.height != d_size.height )
            CV_ERROR( CV_StsUnmatchedSizes, "" );
        break;
    case 3:
        len = B->cols;
        if( a_size.height != len ||
            B->rows != d_size.width ||
            a_size.width != d_size.height )
            CV_ERROR( CV_StsUnmatchedSizes, "" );
        break;
    }

    if( flags == 0 && 2 <= len && len <= 4 && (len == d_size.width || len == d_size.height) )
    {
        int i;
        if( type == CV_64F )
        {
            double* d = D->data.db;
            const double *a = A->data.db, *b = B->data.db, *c = C->data.db;
            size_t d_step = D->step/sizeof(d[0]),
                   a_step = A->step/sizeof(a[0]),
                   b_step = B->step/sizeof(b[0]),
                   c_step = C->step/sizeof(c[0]);

            if( !c )
                c = zero;

            switch( len )
            {
            case 2:
                if( len == d_size.width && b != d )
                {
                    for( i = 0; i < d_size.height; i++, d += d_step, a += a_step, c += c_step )
                    {
                        double t0 = a[0]*b[0] + a[1]*b[b_step];
                        double t1 = a[0]*b[1] + a[1]*b[b_step+1];
                        d[0] = t0*alpha + c[0]*beta;
                        d[1] = t1*alpha + c[1]*beta;
                    }
                }