实现openCV方法warpPerspective()

Question

我正在尝试从头开始实现openCV方法warpPerspective()，我写了下面的代码，它可以处理y和x的移位，但是，当我将单应矩阵从findHomography()传递到我创建的函数时，与warpPerspective()输出相比，它总是给出空白图像。

我按照这个定义找到了像素的新位置：

s*x' h1 h2 h3 x s*y' = h4 h5 h6 * y s h7 h8 1 1

我的映射适用于简单的移位，如{ 1，0.5，-51,0,1,50,0,0,1}

​

但是当矩阵像：[1.0340946, 0.032195676, -6.419126; 0.00302419, 1.0487343, -96.520393; 3.7013847e-06, 0.00010837225, 1]时，输出是这样的：

​

我的实现是：-Given H，和-Find A，在A中保存像素的新位置，并将它们保存在TransArry.where中。数组的索引是A的线性化索引。将A的像素转换为tranImg。

    Mat transform(Mat A, Mat H)
{
// allocate array of all locations
int Numrows = A.rows;
int Numcols = A.cols;
int channels   = A.channels();
cout << "rows " << Numrows << "col " << Numcols << "channels " << channels <<endl;
int size = Numrows*Numcols;
int MaxX,MaxY = -1000;
int MinX,MinY =  1000;
int *TransArry = (int *)malloc(sizeof(int)*size);
int Idx;

 int homeX=Idx % Numcols;
 int homeY=Idx / Numcols;
 cout << H << endl;

 waitKey();         
for (Idx=0; Idx < size; ++Idx ){

        homeX=Idx % Numcols;
        homeY=Idx / Numcols;

        float x  = (H.at<float>(0,0) * (homeX)) +( H.at<float>(0,1) * (homeY)) + ( H.at<float>(0,2) * 1) ;
        float y  = (H.at<float>(1,0) * (homeX)) +( H.at<float>(1,1) * (homeY)) + ( H.at<float>(1,2) * 1) ;
        float s  = (H.at<float>(2,0) * (homeX)) +( H.at<float>(2,1) * (homeY)) + ( H.at<float>(2,2) * 1) ;

        cout << " x = " << x << " y= " << y << " s= " << s;
        x = (x/s);

        y = y/s;

        // for the first col in TransMatrix
        if (homeX ==0){
            if (x > MaxX) MaxX = x;
            if (x < MinX) MinX = x; 
        }

        //for thee first row in TransMatrix
        if (homeY ==0){
            if (y > MaxY) MaxY = y;
            if (y < MinY) MinY = y;
        }
        if((y)>=A.rows || (y)<0 || (x)>=A.cols || (x)<0){
            TransArry[Idx]  = -1;
            cout << "x= " << x << "y= "<< y << endl;
        }else{
            TransArry[Idx] = (y * Numcols + x); 
        }           

        //cout << Numcols << endl;
        cout <<     "New index of " << Idx << "is " << TransArry[Idx] << endl;
        }

         Mat   tranImg ;

         A.copyTo(tranImg);
         tranImg = tranImg - tranImg;
        cout <<     "Rows" << tranImg.rows << "cols" << tranImg.cols << "cha" <<  A.channels() << endl;


        waitKey();
        // Remap Image
        for (Idx=0; Idx < size; Idx ++ ){

            homeX=Idx % Numcols;
            homeY=Idx / Numcols;                
            //tranImg.at<uchar>(homeY, homeX) =0;
            if(TransArry[Idx] != -1){   
                //cout << "Index " << Idx << "Passed " << endl;
                int newhomeX=TransArry[Idx] % Numcols; // Col ID
                int newhomeY=TransArry[Idx] / Numcols;  // Row ID


                 cout << "Index is " << Idx << endl;
                 cout << "HomeX is " << homeX << " and HomeY is " << homeY << endl;
                 cout << "New Index is " << TransArry[Idx] << endl;
                 cout << "New HomeX is " << newhomeX << " and New HomeY is " << newhomeY << endl;   
                 cout << "*****************************************"<< endl; 
                // if (!(Idx%100)) sleep(20);  

                tranImg.at<uchar>(newhomeY, (newhomeX*channels)) = A.at<uchar>(homeY, homeX*channels);
                if(channels>1)
                    tranImg.at<uchar>(newhomeY, newhomeX*channels+1) = A.at<uchar>(homeY, homeX*channels+1);
                if(channels>2)
                    tranImg.at<uchar>(newhomeY, newhomeX*channels+2) = A.at<uchar>(homeY, homeX*channels+2);
                // if (!(Idx%100)){
                    // imshow("inside", tranImg);
                    // waitKey(1);
                    // }
                }
        }
        //cout << tranImg << endl;  

return tranImg;

}

H进行了计算和验证。

那么，我访问矩阵H和A的方式有问题吗？