OpenCV reduce 按行、列计算图像的最大、最小、平均、求和数值

参考 文章1 文章2

一、函数定义

CvSize CvReduce(//完毕由op指定的约简
	const CvArr* src,//目标矩阵
	CvArr* dst,//结果矩阵
	int dim = -1,//因子系数,//1合并成行，0合并成列。-1转化成相应的dis
	int op = CV_REDUCE_SUM，//指定约简法则
	int dtype=-1// 如果结果矩阵没有初始化时输出数据类型
);

op的值	结果
CV_REDUCE_SUM	计算全部向量的总和
CV_REDUCE_AVG	计算全部向量的平均值
CV_REDUCE_MAX	计算全部向量中的最大值
CV_REDUCE_MIN	计算全部向量中的最小值

二、reduce() 的使用陷阱

       函数原型：void cv::reduce(InputArray _src, OutputArray _dst, int dim, int op, int dtype=-1)

       对dtype采用默认值方式使用函数reduce()，出现了点异常问题，然后追加try-catch，发现输入输出的数据类型不匹配，于是就结合着reduce() 原代码做进一步分析，先是尝试着将输出创建为各种指定的格式，不行！
原因在于对下面这条语句没有理解好：

    if( dtype < 0 )
            dtype = _dst.fixedType() ? _dst.type() : stype;

      上网、上Q，折腾许久，终于想到了要把 
dtype指定一个初值！ 由于输入的数据类型是8U，对于求和操作CV_REDUCE_SUM，那么输出是32S就可以，对应的 
dtype=CV_32S 就行，此时输出的矩阵也就只需要定义一下就行，不必再进行其它操作。例如：

Mat matIn=imread(''lena.jpg",0);
Mat matOut;
reduce(matIn, matOut, 1, CV_REDUCE_SUM, CV_32S);

以下为函数reduce() 
源码，方便对照学习。

 

void cv::reduce(InputArray _src, OutputArray _dst, int dim, int op, int dtype)
{
    Mat src = _src.getMat();
    CV_Assert( src.dims <= 2 );
    int op0 = op;
    int stype = src.type(), sdepth = src.depth(), cn = src.channels();
    if( dtype < 0 )
        dtype = _dst.fixedType() ? _dst.type() : stype;
    int ddepth = CV_MAT_DEPTH(dtype);

    _dst.create(dim == 0 ? 1 : src.rows, dim == 0 ? src.cols : 1,
                CV_MAKETYPE(dtype >= 0 ? dtype : stype, cn));
    Mat dst = _dst.getMat(), temp = dst;
    
    CV_Assert( op == CV_REDUCE_SUM || op == CV_REDUCE_MAX ||
        op == CV_REDUCE_MIN || op == CV_REDUCE_AVG );
    CV_Assert( src.channels() == dst.channels() );

    if( op == CV_REDUCE_AVG )
    {
        op = CV_REDUCE_SUM;
        if( sdepth < CV_32S && ddepth < CV_32S )
        {
            temp.create(dst.rows, dst.cols, CV_32SC(cn));
            ddepth = CV_32S;
        }
    }

    ReduceFunc func = 0;
    if( dim == 0 )
    {
        if( op == CV_REDUCE_SUM )
        {
            if(sdepth == CV_8U && ddepth == CV_32S)
                func = reduceR_ >;
            else if(sdepth == CV_8U && ddepth == CV_32F)
                func = reduceR_ >;
            else if(sdepth == CV_8U && ddepth == CV_64F)
                func = reduceR_ >;
            else if(sdepth == CV_16U && ddepth == CV_32F)
                func = reduceR_ >;
            else if(sdepth == CV_16U && ddepth == CV_64F)
                func = reduceR_ >;
            else if(sdepth == CV_16S && ddepth == CV_32F)
                func = reduceR_ >;
            else if(sdepth == CV_16S && ddepth == CV_64F)
                func = reduceR_ >;
            else if(sdepth == CV_32F && ddepth == CV_32F)
                func = reduceR_ >;
            else if(sdepth == CV_32F && ddepth == CV_64F)
                func = reduceR_ >;
            else if(sdepth == CV_64F && ddepth == CV_64F)
                func = reduceR_ >;
        }
        else if(op == CV_REDUCE_MAX)
        {
            if(sdepth == CV_8U && ddepth == CV_8U)
                func = reduceR_ >;
            else if(sdepth == CV_16U && ddepth == CV_16U)
                func = reduceR_ >;
            else if(sdepth == CV_16S && ddepth == CV_16S)
                func = reduceR_ >;
            else if(sdepth == CV_32F && ddepth == CV_32F)
                func = reduceR_ >;
            else if(sdepth == CV_64F && ddepth == CV_64F)
                func = reduceR_ >;
        }
        else if(op == CV_REDUCE_MIN)
        {
            if(sdepth == CV_8U && ddepth == CV_8U)
                func = reduceR_ >;
            else if(sdepth == CV_16U && ddepth == CV_16U)
                func = reduceR_ >;
            else if(sdepth == CV_16S && ddepth == CV_16S)
                func = reduceR_ >;
            else if(sdepth == CV_32F && ddepth == CV_32F)
                func = reduceR_ >;
            else if(sdepth == CV_64F && ddepth == CV_64F)
                func = reduceR_ >;
        }
    }
    else
    {
        if(op == CV_REDUCE_SUM)
        {
            if(sdepth == CV_8U && ddepth == CV_32S)
                func = reduceC_ >;
            else if(sdepth == CV_8U && ddepth == CV_32F)
                func = reduceC_ >;
            else if(sdepth == CV_8U && ddepth == CV_64F)
                func = reduceC_ >;
            else if(sdepth == CV_16U && ddepth == CV_32F)
                func = reduceC_ >;
            else if(sdepth == CV_16U && ddepth == CV_64F)
                func = reduceC_ >;
            else if(sdepth == CV_16S && ddepth == CV_32F)
                func = reduceC_ >;
            else if(sdepth == CV_16S && ddepth == CV_64F)
                func = reduceC_ >;
            else if(sdepth == CV_32F && ddepth == CV_32F)
                func = reduceC_ >;
            else if(sdepth == CV_32F && ddepth == CV_64F)
                func = reduceC_ >;
            else if(sdepth == CV_64F && ddepth == CV_64F)
                func = reduceC_ >;
        }
        else if(op == CV_REDUCE_MAX)
        {
            if(sdepth == CV_8U && ddepth == CV_8U)
                func = reduceC_ >;
            else if(sdepth == CV_16U && ddepth == CV_16U)
                func = reduceC_ >;
            else if(sdepth == CV_16S && ddepth == CV_16S)
                func = reduceC_ >;
            else if(sdepth == CV_32F && ddepth == CV_32F)
                func = reduceC_ >;
            else if(sdepth == CV_64F && ddepth == CV_64F)
                func = reduceC_ >;
        }
        else if(op == CV_REDUCE_MIN)
        {
            if(sdepth == CV_8U && ddepth == CV_8U)
                func = reduceC_ >;
            else if(sdepth == CV_16U && ddepth == CV_16U)
                func = reduceC_ >;
            else if(sdepth == CV_16S && ddepth == CV_16S)
                func = reduceC_ >;
            else if(sdepth == CV_32F && ddepth == CV_32F)
                func = reduceC_ >;
            else if(sdepth == CV_64F && ddepth == CV_64F)
                func = reduceC_ >;
        }
    }

    if( !func )
        CV_Error( CV_StsUnsupportedFormat,
        "Unsupported combination of input and output array formats" );

    func( src, temp );

    if( op0 == CV_REDUCE_AVG )
        temp.convertTo(dst, dst.type(), 1./(dim == 0 ? src.rows : src.cols));
}