Question

我有一个图像，让我们说800x800像素，我想定义200x200像素的区域并能够处理它们。

我无法想象如何使这项工作。我试过了：

int N = 4;
Size smallSize( graySize.width / N ,graySize.height / N );

Mat region_frame;
vector<Mat> smallImages;

namedWindow( "Display window", WINDOW_AUTOSIZE );
for( int i = 0; i < graySize.height - N; i+= smallSize.height )
{
    for( int j = 0; j < graySize.width - N; j+= smallSize.width )
    {
        Rect rect = Rect( j,i, smallSize.width, smallSize.height );
        region_frame = grayImg( rect );
        smallImages.push_back( region_frame.clone() ); 

        imshow( "Display window", region_frame );           
        waitKey(0);


    }
}

但我没有收到任何输出（没有创建窗口！）。如果我对greyImg使用imshow，则显示正确。

另外，因为我想处理这些块/区域/子图像，有没有办法为它们分配标签？例如，区域[0]（包含像素0-199 x 0-199，区域[1] 200-399 x 200-399等等。

********* EDIT ****************

因此，没有显示图像的问题是我的代码之上：

if( grayImg.isContinuous() )
{
    graySize.width *= graySize.height;
    graySize.height = 1;
}

删除它，图像显示正常！

现在，仍然需要处理smallImages才能进行计算。

对于Mat对象我可以做例如

float *theData = (float*)grayImg.data;

但对于vector<Mat>这样的小像？我该如何使用指针？

Answer 1

如果您将每个子图像存储到smallImages而不进行克隆：

// Creates a new Mat header that "points" to the subimage
smallImages.push_back(grayImg(rect));

您可以像往常一样直接将子图像访问到主图像中，例如：

// Change the 3-rd subimage to be all 127
smallImages[2].setTo(127);

或使用指针（以下代码中的示例）。

示例代码：

#include <opencv2\opencv.hpp>
#include <vector>
using namespace std;
using namespace cv;

int main()
{
    Mat3b img = imread("D:\\SO\\img\\nice.jpg");
    resize(img, img, Size(800, 800));

    Mat grayImg;
    cvtColor(img, grayImg, COLOR_BGR2GRAY);
    grayImg.convertTo(grayImg, CV_32F);

    int N = 4;

    if (((grayImg.rows % N) != 0) || ((grayImg.cols % N) != 0))
    {
        // Error
        return -1;
    }

    Size graySize = grayImg.size();
    Size smallSize(grayImg.cols / N, grayImg.rows / N);

    vector<Mat> smallImages;

    for (int i = 0; i < graySize.height; i += smallSize.height)
    {
        for (int j = 0; j < graySize.width; j += smallSize.width)
        {
            Rect rect = Rect(j, i, smallSize.width, smallSize.height);
            smallImages.push_back(grayImg(rect));

            //imshow("Display window", grayImg(rect));
            //waitKey(0);
        }
    }

    // Change the 3-rd subimage to be all 127
    smallImages[2].setTo(127);

    // Iterate on all pixels in 2-nd subimage (will change also the main image)
    int idx_smallimage = 1;

    float* pdata = (float*)smallImages[idx_smallimage].data;
    int step = smallImages[idx_smallimage].step1();

    for (int i = 0; i < smallSize.height; ++i)
    {
        for (int j = 0; j < smallSize.width; ++j)
        {
            // Assign a random value to pixel (i,j) in subimage
            pdata[i * step + j] = rand() & 255;
            //smallImages[idx_smallimage](i * smallSize.width + j) = rand()&255;
        }
    }

    return 0;
}

Answer 2

你可以测试我已经实现的代码。也许你会根据自己的需要改变它。

#include <opencv2/imgproc/imgproc.hpp>
#include <opencv2/highgui/highgui.hpp>

using namespace cv;
using namespace std;

class ImageCells
{
public:
    ImageCells(int rows, int cols, int width, int height);
    virtual ~ImageCells() {}

    int cellwidth() const {return m_width;}
    int cellheight() const { return m_height;}
    int cols() const { return m_cols;}
    int rows() const { return m_rows;}

    void setCell( int col, int row, Mat img );
    void setImage( Mat img );
    Mat getCell( int col, int row );
    Mat image;

protected:
    int  m_width;
    int  m_height;
    int  m_cols;
    int  m_rows;
};

ImageCells::ImageCells( int rows, int cols, int width, int height)
{
    image = Mat::zeros( rows * height, cols * width, CV_8UC3);
    m_width = width;
    m_height = height;
    m_cols = cols;
    m_rows = rows;
}

void ImageCells::setCell( int col, int row, Mat img )
{
    if(img.cols == m_width & img.rows == m_height)
    {
        Mat roi = image( Rect(col * m_width, row * m_height, m_width, m_height) );
        img.copyTo(roi);
    }
}

Mat ImageCells::getCell( int col, int row )
{
    Mat roi = image( Rect(col * m_width, row * m_height, m_width, m_height) );
    return roi.clone();
}

void ImageCells::setImage( Mat img )
{
    if(img.cols >= image.cols & img.rows >= image.rows)
    img.copyTo(image);
}

int main( int argc, char** argv )
{
    ImageCells cells(4,3,70,90); // it creates a ImageCells class having 4 rows and 3 cols, cell witdh = 70 cell height = 90 you can change these values according your needs

    Mat img = Mat( 90, 70, CV_8UC3,Scalar(0,0,255)); // a test mat to use with cells.setCell important note is : img witdh&height must be same to cell witdh&height

for(int i=0; i < cells.cols(); i++)
    for(int j =0; j < cells.rows(); j++ )
{
   cells.setCell(i,j,img); // here you see how to use  setCell
   randu(img,30*i,160*j); // to show purpose changes img
   imshow("cells.image",cells.image);
   waitKey();
}

for(int i=0; i < cells.cols(); i++)
    for(int j =0; j < cells.rows(); j++ )
{
    imshow("cells",cells.getCell(i,j)); // here you see how to use  getCell
    waitKey();
}
    return 0;
}

将图像划分为区域，为它们分配标签？使用指针

2 个答案: