Resize_with_pad

1. 构造一个目标大小[size_h, size_w]的全0 Mat ResizedImg
2. 按照原始图片src长宽比将图片resize到某条边等于目标尺寸，另一条边小于目标尺寸
3. 在ResizedImg找到一个Roi区域，大小等于resize后的src，若需要pad宽，则找到roi的宽边起始位置x：
   这里假设src中H>W：resize后的src宽为w，则x = (size_w - w) / 2
4. 将resize后的src复制到roi中，相当于全0的ResizedImg中有了原图，也就等价于原图左右pad了全0的像素。

void CPreProcess::Resize_with_Pad(Mat srcImg,Mat & ResizedImg,cv::Size size)
//yinyong diaoyong
{
    Mat src;
    srcImg.copyTo(src);
    src.convertTo(src,CV_32FC3);
    int H=0,W=0,C=0;
    H=src.size().height; //src_image_size
    W=src.size().width;
    C=src.channels();

    int size_w= size.width;  // dst_image_size
    int size_h= size.height;
    assert (size_w==size_h);
    // initialization
    ResizedImg=cv::Mat::zeros(size,CV_32FC3); // create dst_image and initialization
    int h=0,w=0;
    if (H>W)
    {
        float rate=(float)H/W;
        h=size_h; //dst_image_size
        w=(int)(h/rate); // calculate dst_image_width with src h/w percent  before resized
        cv::resize(src,src,cv::Size(w,h)); //adjust to  h/w percent  the same as src_image
        Rect rect;
        int pad_x=(size_w-w)/2; // w = h/rate = (size_h * W) /H
        rect.x=pad_x;
        rect.y=0;
        rect.width=w;
        rect.height=h;
        Mat roi=ResizedImg(rect);// select an area of interest in  ResizedImg
        src.copyTo(roi); // copy src to roi
    }
    else
    {
        float rate=(float)H/W;
        w=size_w;
        h=(int)(w*rate);
        cv::resize(src,src,cv::Size(w,h));
        Rect rect;
        int pad_y=(size_h-h)/2;
        rect.x=0;
        rect.y=pad_y;
        rect.width=w;
        rect.height=h;
        Mat roi=ResizedImg(rect);
        src.copyTo(roi);

    }


}