如何正確使用cv :: Mat和Eigen :: Matrix？ （OpenCV +本征）

Question

我能夠將OpenCV mat對象轉換為Eigen對象，然后再轉換。 但是，當我嘗試在屏幕上顯示Eigen-> Mat時，我得到了一個空白窗口，但我不知道為什么。 我可以將圖像保存到文件中，這樣我就可以正確地進行轉換。

關於如何使轉換后的圖像顯示在屏幕上的任何建議？

這是我當前的代碼：

#include <iostream>
#include <opencv2/opencv.hpp>
#include <Eigen/Dense>
#include <opencv2/core/eigen.hpp>


int main(int argc, char **argv) {
    if ( argc != 2 )
    {
        printf("usage: DisplayImage.out <Image_Path>\n");
        return -1;
    }
    cv::Mat image;

    image = cv::imread( argv[1], cv::ImreadModes::IMREAD_GRAYSCALE);
    if ( !image.data )
    {
        printf("No image data \n");
        return -1;
    }
    cv::namedWindow("Display Image", cv::WINDOW_AUTOSIZE );
    cv::imshow("Display Image", image);
    cv::waitKey(0);
    Eigen::MatrixXd eigen_matrix;
    cv::cv2eigen(image, eigen_matrix);

    // std::cout << eigen_matrix << std::endl;

    cv::Mat test_image;
    cv::eigen2cv(eigen_matrix, test_image);
    // This is blank
    cv::namedWindow("Display Image2", cv::WINDOW_AUTOSIZE );
    cv::imshow("Display Image2", test_image);
    cv::waitKey(0);
    cv::imwrite("test.png", test_image);
    return 0;
}

Answer 1

從Eigen文檔中 ，我們可以找到以下內容：

typedef Matrix<double, Dynamic, Dynamic> MatrixXd;

也就是說，您將灰度圖像轉換為double 。 雖然OpenCV的顯示浮動/在范圍雙[0, 1.0]保存浮點值/在范圍雙[0, 255.0]

有兩種解決方法：

1. imshow CV_32F|CV_64F乘以(1.0/255)

    cv::imshow("doube image ", test_image*(1.0/255)); 

2. 將特征矩陣元素類型更改為unsigned char

    typedef Eigen::Matrix<unsigned char, Eigen::Dynamic, Eigen::Dynamic> MatrixXuc; MatrixXuc eigen_matrix; 

---

這是我的結果：

---

編碼：

#include <iostream>
#include <opencv2/opencv.hpp>
#include <Eigen/Dense>
#include <opencv2/core/eigen.hpp>

int main(int argc, char **argv) {
    cv::Mat image = cv::imread( "Knight.jpg", cv::ImreadModes::IMREAD_GRAYSCALE);
    if ( !image.data )
    {
        printf("No image data \n");
        return -1;
    }

    cv::imshow("Source", image);

    // (1) display multiplied by (1.0/255)
    {
        Eigen::MatrixXd eigen_matrix;
        cv::cv2eigen(image, eigen_matrix);
        cv::Mat test_image;
        cv::eigen2cv(eigen_matrix, test_image);
        cv::imshow("doube image ", test_image*(1.0/255));
        cv::imwrite("dst_double.png", test_image);
    }

    // (2) change Eigen Matrix type
    {
        typedef Eigen::Matrix<unsigned char, Eigen::Dynamic, Eigen::Dynamic> MatrixXuc;
        MatrixXuc eigen_matrix;
        cv::cv2eigen(image, eigen_matrix);
        cv::Mat test_image;
        cv::eigen2cv(eigen_matrix, test_image);
        cv::imshow("uchar image", test_image);
        cv::imwrite("dst_uchar.png", test_image);
    }

    cv::waitKey(0);
    return 0;
}

---

注意：

關於cv2.imshow幫助

imshow(...)
    imshow(winname, mat) -> None
    .   @brief Displays an image in the specified window.
    .
    .   The function imshow displays an image in the specified window. If the window was created with the
    .   cv::WINDOW_AUTOSIZE flag, the image is shown with its original size, however it is still limited by $
    .   Otherwise, the image is scaled to fit the window. The function may scale the image, depending on its$
    .
    .   -   If the image is 8-bit unsigned, it is displayed as is.
    .   -   If the image is 16-bit unsigned or 32-bit integer, the pixels are divided by 256. That is, the
    .   value range [0,255\*256] is mapped to [0,255].
    .   -   If the image is 32-bit or 64-bit floating-point, the pixel values are multiplied by 255. That is$
    .   value range [0,1] is mapped to [0,255].

關於cv2.imwrite幫助

imwrite(...)
    imwrite(filename, img[, params]) -> retval
    .   @brief Saves an image to a specified file.
    .
    .   The function imwrite saves the image to the specified file. The image format is chosen based on the
    .   filename extension (see cv::imread for the list of extensions). Only 8-bit (or 16-bit unsigned (CV_1$
    .   in case of PNG, JPEG 2000, and TIFF) single-channel or 3-channel (with 'BGR' channel order) images
    .   can be saved using this function. If the format, depth or channel order is different, use
    .   Mat::convertTo , and cv::cvtColor to convert it before saving. Or, use the universal FileStorage I/O
    .   functions to save the image to XML or YAML format.

Answer 2

前面的答案僅適用於GrayScale ，而這個答案適用於Color 。

關鍵是reshape cv :: Mat。

cv::Mat::reshape(int new_channel, int new_rows);

---

結果：

---

編碼：

#include <iostream>
#include <opencv2/opencv.hpp>
#include <Eigen/Dense>
#include <opencv2/core/eigen.hpp>


int main(int argc, char **argv) {
    cv::Mat image = cv::imread( "Knight.jpg");
    if ( !image.data )
    {
        printf("No image data \n");
        return -1;
    }

    cv::imshow("Source", image);

    int chs = image.channels();

    // (1) display multiplied by (1.0/255)
    {
        cv::Mat img = image.reshape(1, 0);
        std::cout << img.size() << ", " << img.channels() << std::endl;
        typedef Eigen::Matrix<double, Eigen::Dynamic, Eigen::Dynamic> MatrixXd;
        MatrixXd mat;

        cv::cv2eigen(img, mat);
        cv::Mat img2;
        cv::eigen2cv(mat, img2);
        img2 = img2.reshape(chs, 0);
        cv::imshow("doube color image ", img2*(1.0/255));
        cv::imwrite("dst_double.png", img2);

    }

    // (2) change Eigen Matrix type
    {
        cv::Mat img = image.reshape(1, 0);
        std::cout << img.size() << ", " << img.channels() << std::endl;
        typedef Eigen::Matrix<unsigned char, Eigen::Dynamic, Eigen::Dynamic> MatrixXuc;
        MatrixXuc mat;

        cv::cv2eigen(img, mat);
        cv::Mat img2;
        cv::eigen2cv(mat, img2);
        img2 = img2.reshape(chs, 0);
        std::cout << img2.size() << ", " << img2.channels() << std::endl;
        cv::imshow("uchar color image", img2);
        cv::imwrite("dst_uchar.png", img2);
    }

    cv::waitKey(0);
    return 0;
}