使用多线程加速处理这一段for (int i = 0; i < m; i++) { edges = Extract1DEdgeCircle.Get1DEdge(RoiMat, m_vpdEquinoxPoints[i], m_dMeasureLength, m_dMeasureHeight, m_vdMeasureAngle[i] , m_dSigma, m_nThresholdCircle, m_nTranslationCircle == 1 ? Translation::Poisitive : Translation::Negative, Selection::Strongest); for (int i = 0; i < edges.size(); i++) { m_vpdEdgePoints.push_back(edges[i].m_pdEdgePoint); m_vdEdgeGradient.push_back(edges[i].m_dGradient); } }

可以使用多线程的方式将这个for循环中的任务分配给多个线程处理，从而加速处理过程。

具体实现方式可以使用C++11中的std::thread库进行线程的创建和管理。将for循环的迭代次数分配给多个线程处理，每个线程处理一部分数据。需要注意的是，多个线程同时向同一个vector中添加元素可能会存在竞争条件，需要使用互斥锁来保证线程安全。

示例代码如下：

#include <thread>
#include <vector>
#include <mutex>

// 定义互斥锁
std::mutex mtx;

void process(int start, int end, const cv::Mat& RoiMat, const std::vector<cv::Point2d>& m_vpdEquinoxPoints, double m_dMeasureLength, double m_dMeasureHeight, double m_dSigma, double m_nThresholdCircle, int m_nTranslationCircle, const std::vector<double>& m_vdMeasureAngle, std::vector<cv::Point2d>& m_vpdEdgePoints, std::vector<double>& m_vdEdgeGradient)
{
    std::vector<Edge> edges;
    for (int i = start; i < end; i++)
    {
        edges = Extract1DEdgeCircle.Get1DEdge(RoiMat, m_vpdEquinoxPoints[i], m_dMeasureLength, m_dMeasureHeight, m_vdMeasureAngle[i], m_dSigma, m_nThresholdCircle, m_nTranslationCircle == 1 ? Translation::Poisitive : Translation::Negative, Selection::Strongest);

        // 加锁
        mtx.lock();
        for (int j = 0; j < edges.size(); j++)
        {
            m_vpdEdgePoints.push_back(edges[j].m_pdEdgePoint);
            m_vdEdgeGradient.push_back(edges[j].m_dGradient);
        }
        // 解锁
        mtx.unlock();
    }
}

int main()
{
    // 定义线程数
    const int thread_num = 4;

    // 定义任务数量
    const int task_num = m;

    // 定义每个线程处理的任务数量
    const int task_per_thread = task_num / thread_num;

    // 定义线程池
    std::vector<std::thread> threads;

    // 分配任务并启动线程
    for (int i = 0; i < thread_num; i++)
    {
        int start = i * task_per_thread;
        int end = i < thread_num - 1 ? start + task_per_thread : task_num;

        threads.emplace_back(std::thread(process, start, end, std::ref(RoiMat), std::ref(m_vpdEquinoxPoints), m_dMeasureLength, m_dMeasureHeight, m_dSigma, m_nThresholdCircle, m_nTranslationCircle, std::ref(m_vdMeasureAngle), std::ref(m_vpdEdgePoints), std::ref(m_vdEdgeGradient)));
    }

    // 等待所有线程执行完毕
    for (auto& t : threads)
    {
        t.join();
    }

    return 0;
}