cvhistogram.cpp.svn-base

来自「非结构化路识别」· SVN-BASE 代码 · 共 2,118 行 · 第 1/5 页

    for( i = 0; i < dims1; i++ )
    {
        if( size1[i] != size2[i] )
            CV_ERROR( CV_StsUnmatchedSizes, "The histograms have different sizes" );
        total *= size1[i];
    }


    if( !CV_IS_SPARSE_MAT(hist1->bins))
    {
        float *ptr1 = 0, *ptr2 = 0;
        CV_CALL( cvGetRawData( hist1->bins, (uchar**)&ptr1 ));
        CV_CALL( cvGetRawData( hist2->bins, (uchar**)&ptr2 ));

        switch( method )
        {
        case CV_COMP_CHISQR:
            for( i = 0; i < total; i++ )
            {
                double a = ptr1[i] - ptr2[i];
                double b = ptr1[i] + ptr2[i];
                if( b != 0 )
                    result += a*a/b;
            }
            break;
        case CV_COMP_CORREL:
            {
                double s1 = 0, s11 = 0;
                double s2 = 0, s22 = 0;
                double s12 = 0;
                double num, denom2, scale = 1./total;
                
                for( i = 0; i < total; i++ )
                {
                    double a = ptr1[i];
                    double b = ptr2[i];

                    s12 += a*b;
                    s1 += a;
                    s11 += a*a;
                    s2 += b;
                    s22 += b*b;
                }

                num = s12 - s1*s2*scale;
                denom2 = (s11 - s1*s1*scale)*(s22 - s2*s2*scale);
                result = denom2 != 0 ? num/sqrt(denom2) : 1;
            }
            break;
        case CV_COMP_INTERSECT:
            for( i = 0; i < total; i++ )
            {
                float a = ptr1[i];
                float b = ptr2[i];
                if( a <= b )
                    result += a;
                else
                    result += b;
            }
            break;
        default:
            CV_ERROR( CV_StsBadArg, "Unknown comparison method" );
        }
    }
    else
    {
        CvSparseMat* mat1 = (CvSparseMat*)(hist1->bins);
        CvSparseMat* mat2 = (CvSparseMat*)(hist2->bins);
        CvSparseMatIterator iterator;
        CvSparseNode *node1, *node2;

        if( mat1->total > mat2->total )
        {
            CvSparseMat* t;
            CV_SWAP( mat1, mat2, t );
        }

        switch( method )
        {
        case CV_COMP_CHISQR:
            for( node1 = cvInitSparseMatIterator( mat1, &iterator );
                 node1 != 0; node1 = cvGetNextSparseNode( &iterator ))
            {
                double v1 = *(float*)CV_NODE_VAL(mat1,node1);
                uchar* node2 = icvGetNodePtr( mat2, CV_NODE_IDX(mat1,node1),
                                              0, 0, &node1->hashval );
                if( !node2 )
                    result += v1;
                else
                {
                    double v2 = *(float*)node2;
                    double a = v1 - v2;
                    double b = v1 + v2;
                    if( b != 0 )
                        result += a*a/b;
                }
            }

            for( node2 = cvInitSparseMatIterator( mat2, &iterator );
                 node2 != 0; node2 = cvGetNextSparseNode( &iterator ))
            {
                double v2 = *(float*)CV_NODE_VAL(mat2,node2);
                if( !icvGetNodePtr( mat1, CV_NODE_IDX(mat2,node2),
                                    0, 0, &node2->hashval ))
                {
                    result += v2;
                }
            }
            break;
        case CV_COMP_CORREL:
            {
                double s1 = 0, s11 = 0;
                double s2 = 0, s22 = 0;
                double s12 = 0;
                double num, denom2, scale = 1./total;
                
                for( node1 = cvInitSparseMatIterator( mat1, &iterator );
                     node1 != 0; node1 = cvGetNextSparseNode( &iterator ))
                {
                    double v1 = *(float*)CV_NODE_VAL(mat1,node1);
                    uchar* node2 = icvGetNodePtr( mat2, CV_NODE_IDX(mat1,node1),
                                                  0, 0, &node1->hashval );
                    if( node2 )
                    {
                        double v2 = *(float*)node2;
                        s12 += v1*v2;
                    }
                    s1 += v1;
                    s11 += v1*v1;
                }

                for( node2 = cvInitSparseMatIterator( mat2, &iterator );
                     node2 != 0; node2 = cvGetNextSparseNode( &iterator ))
                {
                    double v2 = *(float*)CV_NODE_VAL(mat2,node2);
                    s2 += v2;
                    s22 += v2*v2;
                }

                num = s12 - s1*s2*scale;
                denom2 = (s11 - s1*s1*scale)*(s22 - s2*s2*scale);
                result = denom2 != 0 ? num/sqrt(denom2) : 1;
            }
            break;
        case CV_COMP_INTERSECT:
            {
                for( node1 = cvInitSparseMatIterator( mat1, &iterator );
                     node1 != 0; node1 = cvGetNextSparseNode( &iterator ))
                {
                    float v1 = *(float*)CV_NODE_VAL(mat1,node1);
                    uchar* node2 = icvGetNodePtr( mat2, CV_NODE_IDX(mat1,node1),
                                                  0, 0, &node1->hashval );
                    if( node2 )
                    {
                        float v2 = *(float*)node2;
                        if( v1 <= v2 )
                            result += v1;
                        else
                            result += v2;
                    }
                }
            }
            break;
        default:
            CV_ERROR( CV_StsBadArg, "Unknown comparison method" );
        }
    }

    _result = result;
    
    __END__;
    
    return _result;
}

// copies one histogram to another
CV_IMPL void
cvCopyHist( const CvHistogram* src, CvHistogram** _dst )
{
    CV_FUNCNAME( "cvCopyHist" );

    __BEGIN__;

    int eq = 0;
    int is_sparse;
    int i, dims1, dims2;
    int size1[CV_MAX_DIM], size2[CV_MAX_DIM], total = 1;
    float* ranges[CV_MAX_DIM];
    float** thresh = 0;
    CvHistogram* dst;
    
    if( !_dst )
        CV_ERROR( CV_StsNullPtr, "Destination double pointer is NULL" );

    dst = *_dst;

    if( !CV_IS_HIST(src) || (dst && !CV_IS_HIST(dst)) )
        CV_ERROR( CV_StsBadArg, "Invalid histogram header[s]" );

    is_sparse = CV_IS_SPARSE_MAT(src->bins);
    CV_CALL( dims1 = cvGetDims( src->bins, size1 ));
    for( i = 0; i < dims1; i++ )
        total *= size1[i];

    if( dst && is_sparse == CV_IS_SPARSE_MAT(dst->bins))
    {
        CV_CALL( dims2 = cvGetDims( dst->bins, size2 ));
    
        if( dims1 == dims2 )
        {
            for( i = 0; i < dims1; i++ )
                if( size1[i] != size2[i] )
                    break;
        }

        eq = i == dims1;
    }

    if( !eq )
    {
        cvReleaseHist( _dst );
        CV_CALL( dst = cvCreateHist( dims1, size1,
                 !is_sparse ? CV_HIST_ARRAY : CV_HIST_SPARSE, 0, 0 ));
        *_dst = dst;
    }

    if( CV_HIST_HAS_RANGES( src ))
    {
        if( CV_IS_UNIFORM_HIST( src ))
        {
            for( i = 0; i < dims1; i++ )
                ranges[i] = (float*)src->thresh[i];
            thresh = ranges;
        }
        else
            thresh = src->thresh2;
        CV_CALL( cvSetHistBinRanges( dst, thresh, CV_IS_UNIFORM_HIST(src)));
    }

    CV_CALL( cvCopy( src->bins, dst->bins ));
    
    __END__;
}


// Sets a value range for every histogram bin
CV_IMPL void
cvSetHistBinRanges( CvHistogram* hist, float** ranges, int uniform )
{
    CV_FUNCNAME( "cvSetHistBinRanges" );
    
    __BEGIN__;

    int dims, size[CV_MAX_DIM], total = 0;
    int i, j;
    
    if( !ranges )
        CV_ERROR( CV_StsNullPtr, "NULL ranges pointer" );

    if( !CV_IS_HIST(hist) )
        CV_ERROR( CV_StsBadArg, "Invalid histogram header" );

    CV_CALL( dims = cvGetDims( hist->bins, size ));
    for( i = 0; i < dims; i++ )
        total += size[i]+1;
    
    if( uniform )
    {
        for( i = 0; i < dims; i++ )
        {
            if( !ranges[i] )
                CV_ERROR( CV_StsNullPtr, "One of <ranges> elements is NULL" );
            hist->thresh[i][0] = ranges[i][0];
            hist->thresh[i][1] = ranges[i][1];
        }

        hist->type |= CV_HIST_UNIFORM_FLAG + CV_HIST_RANGES_FLAG;
    }
    else
    {
        float* dim_ranges;

        if( !hist->thresh2 )
        {
            CV_CALL( hist->thresh2 = (float**)cvAlloc(
                        dims*sizeof(hist->thresh2[0])+
                        total*sizeof(hist->thresh2[0][0])));
        }
        dim_ranges = (float*)(hist->thresh2 + dims);

        for( i = 0; i < dims; i++ )
        {
            float val0 = -FLT_MAX;

            if( !ranges[i] )
                CV_ERROR( CV_StsNullPtr, "One of <ranges> elements is NULL" );
            
            for( j = 0; j <= size[i]; j++ )
            {
                float val = ranges[i][j];
                if( val <= val0 )
                    CV_ERROR(CV_StsOutOfRange, "Bin ranges should go in ascenting order");
                val0 = dim_ranges[j] = val;
            }

            hist->thresh2[i] = dim_ranges;
            dim_ranges += size[i] + 1;
        }

        hist->type |= CV_HIST_RANGES_FLAG;
        hist->type &= ~CV_HIST_UNIFORM_FLAG;
    }

    __END__;
}


#define  ICV_HIST_DUMMY_IDX  (INT_MIN/3)

static CvStatus
icvCalcHistLookupTables8x( const CvHistogram* hist, int lo, int hi,
                           int dims, int* size, int* tab )
{
    int is_sparse = CV_IS_SPARSE_HIST( hist );
    int have_range = CV_HIST_HAS_RANGES(hist);
    int i, j;
    
    if( !have_range || CV_IS_UNIFORM_HIST(hist))
    {
        for( i = 0; i < dims; i++ )
        {
            double a = have_range ? hist->thresh[i][0] : 0;
            double b = have_range ? hist->thresh[i][1] : 256;
            int sz = size[i];
            double scale = sz/(b - a), cur = (lo - a)*scale;
            int step = 1;

            if( !is_sparse )
                step = ((CvMatND*)(hist->bins))->dim[i].step/sizeof(float);

            for( j = lo; j < hi; j++ )
            {
                int idx = cvFloor(cur);
                if( (unsigned)idx < (unsigned)sz )
                    idx *= step;
                else
                    idx = ICV_HIST_DUMMY_IDX;

                tab[i*(hi - lo) + j - lo] = idx;
                cur += scale;
            }
        }
    }
    else
    {
        for( i = 0; i < dims; i++ )
        {
            double limit = hist->thresh2[i][0];
            int idx = -1, write_idx = ICV_HIST_DUMMY_IDX, sz = size[i];
            int step = 1;

            if( !is_sparse )
                step = ((CvMatND*)(hist->bins))->dim[i].step/sizeof(float);

            if( limit > hi )
                limit = hi;
            
            j = lo;
            for(;;)
            {
                for( ; j < limit; j++ )
                    tab[i*(hi - lo) + j - lo] = write_idx;

                if( (unsigned)(++idx) < (unsigned)sz )
                {
                    limit = hist->thresh2[i][idx+1];
                    if( limit > hi )
                        limit = hi;
                    write_idx = idx*step;
                }
                else
                {
                    for( ; j < hi; j++ )
                        tab[i*(hi - lo) + j - lo] = ICV_HIST_DUMMY_IDX;
                    break;
                }
            }
        }
    }

    return CV_OK;
}


/***************************** C A L C   H I S T O G R A M *************************/

// Calculates histogram for one or more 8u arrays
static CvStatus CV_STDCALL
    icvCalcHist_8u_C1R( uchar** img, int step, uchar* mask, int maskStep,
                        CvSize size, CvHistogram* hist )
{
    int* tab;
    int is_sparse = CV_IS_SPARSE_HIST(hist);
    int dims, histsize[CV_MAX_DIM];
    int i, x;
    CvStatus status;

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

    tab = (int*)alloca( dims*256*sizeof(int));
    status = icvCalcHistLookupTables8x( hist, 0, 256, dims,
                                        histsize, tab );

    if( status < 0 )
        return status;

    if( !is_sparse )
    {
        int total = 1;
        int* bins = ((CvMatND*)(hist->bins))->data.i;

        for( i = 0; i < dims; i++ )
            total *= histsize[i];