在CvCascadeClassifier::train中的如下代码完成Haar特征集的初始化工作：

// （3）创建特征评估器CvHaarEvaluator
       featureEvaluator= CvFeatureEvaluator::create(cascadeParams.featureType);
       //CvHaarEvaluator 初始化，开辟内存，生成特征集
       featureEvaluator->init((CvFeatureParams*)featureParams, numPos + numNeg, cascadeParams.winSize );

        在将原理部分我们说到过haar特征，在W*H的图像区域内，每种形状的特征可以取不同的缩放比例，放在不同的位置。在来回顾一下Haar特征的形状。

        因为我们设置featureType为Haar特征，这里实际创建的是CvHaarEvaluator对象，调用它的init函数，代码如下：

void CvHaarEvaluator::init(constCvFeatureParams *_featureParams,
                          int_maxSampleCount, Size _winSize )
{
   CV_Assert(_maxSampleCount > 0);
   int cols = (_winSize.width + 1) * (_winSize.height + 1);
   sum.create((int)_maxSampleCount, cols, CV_32SC1);
   tilted.create((int)_maxSampleCount, cols, CV_32SC1);
   normfactor.create(1, (int)_maxSampleCount, CV_32FC1);
   CvFeatureEvaluator::init( _featureParams, _maxSampleCount, _winSize );
}

        最后一句调用了父类的init函数，里面创建了存放记录每个样本类别的数组cls，然后调用generateFeatures函数来生成特征集。

void CvFeatureEvaluator::init(constCvFeatureParams *_featureParams,
                              int_maxSampleCount, Size _winSize )
{
   CV_Assert(_maxSampleCount > 0);
   featureParams = (CvFeatureParams *)_featureParams;
   winSize = _winSize;
   numFeatures = 0;
   cls.create( (int)_maxSampleCount, 1, CV_32FC1 );
   generateFeatures();
}

        从CvHaarEvaluator调用过来，实际是调用它的generateFeatures函数，用来构造全部haar特征集。代码主体中有四层循环，外面两层遍历特征的起点位置，内两层遍历haar特征的大小，最里面根据mode值将对于的不同性质的haar特征加入features数组。

void CvHaarEvaluator::generateFeatures()
{
   int mode = ((constCvHaarFeatureParams*)((CvFeatureParams*)featureParams))->mode;
   int offset = winSize.width + 1;
   for( int x = 0; x < winSize.width; x++ )
    {
       for( int y = 0; y < winSize.height; y++ )
       {
           for( int dx = 1; dx <= winSize.width; dx++ )
           {
                for( int dy = 1; dy <=winSize.height; dy++ )
                {
                    // haar_x2
                    if ( (x+dx*2 <=winSize.width) && (y+dy <= winSize.height) )
                    {
                        features.push_back(Feature( offset, false,
                            x,    y, dx*2, dy, -1,
                            x+dx, y, dx  , dy, +2 ) );
                    }
                    // haar_y2
                    if ( (x+dx <=winSize.width) && (y+dy*2 <= winSize.height) )
                    {
                        features.push_back(Feature( offset, false,
                           x,    y, dx, dy*2, -1,
                            x, y+dy, dx,dy,   +2 ) );
                    }
                    // haar_x3
                    if ( (x+dx*3 <=winSize.width) && (y+dy <= winSize.height) )
                    {
                       features.push_back( Feature(offset, false,
                            x,    y, dx*3, dy, -1,
                            x+dx, y, dx  , dy, +3 ) );
                    }
                    // haar_y3
                    if ( (x+dx <= winSize.width)&& (y+dy*3 <= winSize.height) )
                    {
                        features.push_back(Feature( offset, false,
                            x, y,    dx, dy*3, -1,
                            x, y+dy, dx,dy,   +3 ) );
                    }
                    if( mode !=CvHaarFeatureParams::BASIC )
                    {
                        // haar_x4
                        if ( (x+dx*4 <=winSize.width) && (y+dy <= winSize.height) )
                        {
                            features.push_back( Feature( offset,false,
                                x,    y, dx*4, dy, -1,
                                x+dx, y, dx*2,dy, +2 ) );
                        }
                        // haar_y4
                        if ( (x+dx <=winSize.width ) && (y+dy*4 <= winSize.height) )
                        {
                            features.push_back(Feature( offset, false,
                                x, y,    dx, dy*4, -1,
                                x, y+dy, dx, dy*2,+2 ) );
                        }
                    }
                    // x2_y2
                    if ( (x+dx*2 <=winSize.width) && (y+dy*2 <= winSize.height) )
                    {
                        features.push_back(Feature( offset, false,
                            x,    y,   dx*2, dy*2, -1,
                            x,    y,   dx,   dy,   +2,
                            x+dx, y+dy,dx,   dy,   +2 ) );
                    }
                    if (mode !=CvHaarFeatureParams::BASIC)
                    {
                        if ( (x+dx*3 <=winSize.width) && (y+dy*3 <= winSize.height) )
                        {
                            features.push_back(Feature( offset, false,
                                x   , y  , dx*3, dy*3, -1,
                                x+dx, y+dy,dx  , dy , +9) );
                        }
                    }
                    if (mode ==CvHaarFeatureParams::ALL)
                    {
                        // tilted haar_x2
                       if ( (x+2*dx<= winSize.width) && (y+2*dx+dy <= winSize.height) &&(x-dy>= 0) )
                        {
                            features.push_back(Feature( offset, true,
                                x, y, dx*2, dy,-1,
                                x, y, dx,   dy, +2 ) );
                        }
                        // tilted haar_y2
                        if ( (x+dx <=winSize.width) && (y+dx+2*dy <= winSize.height) &&(x-2*dy>= 0) )
                        {
                            features.push_back(Feature( offset, true,
                                x, y, dx, 2*dy,-1,
                                x, y, dx,dy,   +2 ) );
                        }
                        // tilted haar_x3
                        if ( (x+3*dx <= winSize.width)&& (y+3*dx+dy <= winSize.height) && (x-dy>= 0) )
                        {
                            features.push_back(Feature( offset, true,
                                x,    y,   dx*3, dy, -1,
                               x+dx, y+dx,dx,   dy, +3 ) );
                        }
                        // tilted haar_y3
                        if ( (x+dx <=winSize.width) && (y+dx+3*dy <= winSize.height) &&(x-3*dy>= 0) )
                        {
                           features.push_back(Feature( offset, true,
                                x,    y,   dx, 3*dy, -1,
                                x-dy, y+dy, dx,dy,   +3 ) );
                        }
                        // tilted haar_x4
                        if ( (x+4*dx <=winSize.width) && (y+4*dx+dy <= winSize.height) &&(x-dy>= 0) )
                        {
                            features.push_back(Feature( offset, true,
                                x,    y,   dx*4, dy, -1,
                                x+dx, y+dx,dx*2, dy, +2 ) );
                        }
                        // tilted haar_y4
                        if ( (x+dx <=winSize.width) && (y+dx+4*dy <= winSize.height) &&(x-4*dy>= 0) )
                        {
                            features.push_back(Feature( offset, true,
                                x,    y,   dx, 4*dy, -1,
                                x-dy, y+dy, dx,2*dy, +2 ) );
                        }
                    }
                }
           }
       }
    }
   numFeatures = (int)features.size();
}