1、pca 找到图像某个区域的垂直线，并画出来

    // 1、 斑块的框+ 血管二值化图，pca 找到垂直血管壁的直线,  还是根据斑块找主轴方向吧// Step 1: 提取斑块左右范围内的血管像素点坐标，std::vector<cv::Point> points;for (int y = 0; y < binaryVessel.rows; y++) {for (int x = x1; x <= x2; x++) {if (binaryVessel.at<uchar>(y, x) == 255) {points.push_back(cv::Point(x, y));}}}if (points.empty()) {std::cout << "====================>error No valid pixels in the specified range.  斑块附近的血管分割区域不存在，结束函数功能 " << std::endl;return;}// 转换为 cv::Mat 格式cv::Mat pointsMat(points.size(), 2, CV_32F);for (int i = 0; i < points.size(); i++) {pointsMat.at<float>(i, 0) = points[i].x;pointsMat.at<float>(i, 1) = points[i].y;}// Step 2: 使用 PCA  获取垂直线段斜率，感觉有点异常，不要了，改成用最小外接矩形// binaryPlaque    pointsMatcv::PCA pca(pointsMat, cv::noArray(), cv::PCA::DATA_AS_ROW);// Step 3: 获取主成分（直线的方向）和主成分对应的直线上的点cv::Mat directions = pca.eigenvectors;cv::Mat linePoints = pca.mean;// Step 4: 计算垂直线的斜率和截距float kVertical = -directions.at<float>(0,0) / directions.at<float>(0,1);float interceptHorizontal = linePoints.at<float>(0, 1) - kVertical * linePoints.at<float>(0, 0);// Step 5: 绘制垂直线float x;cv::Mat image22;  // 存储处理后的图像cv::cvtColor(binaryVessel, image22, cv::COLOR_GRAY2BGR);  // binaryVessel 转换为彩色图像  image22，存储for (int i = 0; i < image22.cols; i++) {x = static_cast<float>(i);float yVertical = kVertical * x + interceptHorizontal;cv::circle(image22, cv::Point(static_cast<int>(x), static_cast<int>(yVertical)), 1, cv::Scalar(0, 255, 0), -1);}cv::imwrite("/home/hebin/Desktop/shiyuanyin/image2.png", image22);  // 保存画图的直线

2、使用最小外接矩形的框，来找到水平线和垂直线