opencv:提取样本的两种方式

1 利用icvGetIdxAt直接从矩阵中提取

for( j = 0; j < numtrimmed; j++ )  
                {  
                    // 获取训练样本  
                    idx = icvGetIdxAt( trimmedIdx, j );  

                    // 对每个训练样本计算Haar特征  
                    eval.data.fl[idx] = cvEvalFastHaarFeature( &classifier->fastfeature[i],  
                                        (sum_type*) (data->sum.data.ptr + idx * data->sum.step),  
                                        (sum_type*) (data->tilted.data.ptr + idx * data->tilted.step) );   

                    // 归一化因子  
                    normfactor = data->normfactor.data.fl[idx];  

                    // 对Haar特征归一化  
                    eval.data.fl[idx] = ( normfactor == 0.0F )  
                        ? 0.0F : (eval.data.fl[idx] / normfactor);  
                }  

2 利用宏CV_MAT2VEC把矩阵转化为向量

 CV_MAT2VEC( *trainClasses, ydata, ystep, ynum );
    CV_MAT2VEC( *weights, wdata, wstep, wnum );

    CV_Assert( m == ynum );
    CV_Assert( m == wnum );

    sumw = 0.0F;
    err = 0.0F;
    for( i = 0; i < trainer->count; i++ )
    {
        idx = (trainer->idx) ? trainer->idx[i] : i;

        sumw += *((float*) (wdata + idx*wstep));
        err += (*((float*) (wdata + idx*wstep))) *
            ( (*((float*) (evaldata + idx*evalstep))) !=
                2.0F * (*((float*) (ydata + idx*ystep))) - 1.0F );
    }
    err /= sumw;
    err = -cvLogRatio( err );