OpenCV 3 中的 PCA 错误

Error with PCA in OpenCV 3

本文关键字:错误 PCA 中的 OpenCV      更新时间:2023-10-16

我正在尝试从此链接运行OpenCV for PCA的示例代码PCA 示例。

但是在我运行后它崩溃了。我调试了,我看到它在下面的for loop里面崩溃了,这是getOrientation函数:

    for (int i = 0; i < 2; ++i)
{
    eigen_vecs[i] = Point2d(pca_analysis.eigenvectors.at<double>(i, 0),
        pca_analysis.eigenvectors.at<double>(i, 1));
    eigen_val[i] = pca_analysis.eigenvalues.at<double>(0, i);
}

我之前在stackoverflow中搜索过,有一些标题相似但错误不同的问题。有什么帮助吗?谢谢

下面是示例代码:

#include <iostream>
#include <opencv2/opencv.hpp>
using namespace std;
using namespace cv;
// Function declarations
void drawAxis(Mat&, Point, Point, Scalar, const float);
double getOrientation(const vector<Point> &, Mat&);
void drawAxis(Mat& img, Point p, Point q, Scalar colour, const float scale = 0.2)
{
    double angle;
    double hypotenuse;
    angle = atan2((double)p.y - q.y, (double)p.x - q.x); // angle in radians
    hypotenuse = sqrt((double)(p.y - q.y) * (p.y - q.y) + (p.x - q.x) * (p.x - q.x));
    //    double degrees = angle * 180 / CV_PI; // convert radians to degrees (0-180 range)
    //    cout << "Degrees: " << abs(degrees - 180) << endl; // angle in 0-360 degrees range
    // Here we lengthen the arrow by a factor of scale
    q.x = (int)(p.x - scale * hypotenuse * cos(angle));
    q.y = (int)(p.y - scale * hypotenuse * sin(angle));
    line(img, p, q, colour, 1, CV_AA);
    // create the arrow hooks
    p.x = (int)(q.x + 9 * cos(angle + CV_PI / 4));
    p.y = (int)(q.y + 9 * sin(angle + CV_PI / 4));
    line(img, p, q, colour, 1, CV_AA);
    p.x = (int)(q.x + 9 * cos(angle - CV_PI / 4));
    p.y = (int)(q.y + 9 * sin(angle - CV_PI / 4));
    line(img, p, q, colour, 1, CV_AA);
}
double getOrientation(const vector<Point> &pts, Mat &img)
{
    //Construct a buffer used by the pca analysis
    int sz = static_cast<int>(pts.size());
    Mat data_pts = Mat(sz, 2, CV_64FC1);
    for (int i = 0; i < data_pts.rows; ++i)
    {
        data_pts.at<double>(i, 0) = pts[i].x;
        data_pts.at<double>(i, 1) = pts[i].y;
    }
    //Perform PCA analysis
    PCA pca_analysis(data_pts, Mat(), CV_PCA_DATA_AS_ROW);
    //Store the center of the object
    Point cntr = Point(static_cast<int>(pca_analysis.mean.at<double>(0, 0)),
        static_cast<int>(pca_analysis.mean.at<double>(0, 1)));
    //Store the eigenvalues and eigenvectors
    vector<Point2d> eigen_vecs(2);
    vector<double> eigen_val(2);
    *for (int i = 0; i < 2; ++i)
    {
        eigen_vecs[i] = Point2d(pca_analysis.eigenvectors.at<double>(i, 0),
            pca_analysis.eigenvectors.at<double>(i, 1));
        eigen_val[i] = pca_analysis.eigenvalues.at<double>(0, i);
    }*
    // Draw the principal components
    circle(img, cntr, 3, Scalar(255, 0, 255), 2);
    Point p1 = cntr + 0.02 * Point(static_cast<int>(eigen_vecs[0].x * eigen_val[0]), static_cast<int>(eigen_vecs[0].y * eigen_val[0]));
    Point p2 = cntr - 0.02 * Point(static_cast<int>(eigen_vecs[1].x * eigen_val[1]), static_cast<int>(eigen_vecs[1].y * eigen_val[1]));
    drawAxis(img, cntr, p1, Scalar(0, 255, 0), 1);
    drawAxis(img, cntr, p2, Scalar(255, 255, 0), 5);
    double angle = atan2(eigen_vecs[0].y, eigen_vecs[0].x); // orientation in radians
    return angle;
}
int main(int, char** argv)
{
    // Load image
    Mat src = imread("C:/Users/aydin/Desktop/c++/pictures/pca_test1.jpg");
    //Mat src = imread(argv[1]);
    // Check if image is loaded successfully
    if (!src.data || src.empty())
    {
        cout << "Problem loading image!!!" << endl;
        return EXIT_FAILURE;
    }
    imshow("src", src);
    // Convert image to grayscale
    Mat gray;
    cvtColor(src, gray, COLOR_BGR2GRAY);
    // Convert image to binary
    Mat bw;
    threshold(gray, bw, 50, 255, CV_THRESH_BINARY | CV_THRESH_OTSU);
    // Find all the contours in the thresholded image
    vector<Vec4i> hierarchy;
    vector<vector<Point> > contours;
    findContours(bw, contours, hierarchy, CV_RETR_LIST, CV_CHAIN_APPROX_NONE);
    for (size_t i = 0; i < contours.size(); ++i)
    {
        // Calculate the area of each contour
        double area = contourArea(contours[i]);
        // Ignore contours that are too small or too large
        if (area < 1e2 || 1e5 < area) continue;
        // Draw each contour only for visualisation purposes
        drawContours(src, contours, static_cast<int>(i), Scalar(0, 0, 255), 2, 8, hierarchy, 0);
        // Find the orientation of each shape
        //getOrientation(contours[i], src);
    }
    imshow("output", src);
    waitKey(0);
    return 0;
}

不,这与环境无关;I不知道,你是如何让它工作的,但后来我在这里看到了同样的错误,他放了正确的代码说它有错误.但是将此代码与原始代码进行比较,我发现在我提到的"for loop"中有问题

   for (int i = 0; i < 2; ++i)
    {
        eigen_vecs[i] = Point2d(pca_analysis.eigenvectors.at<double>(i, 0),
                                pca_analysis.eigenvectors.at<double>(i, 1));
        eigen_val[i] = pca_analysis.eigenvalues.at<double>(0,i);
    }

他将最后一个偏执从(0,i)改为(i)。 我做了同样的事情并且它有效,但我不明白为什么,你能告诉我为什么吗?