创建多线程加速处理这一段for循环vector<Edge1D_Result>edges;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); } }保护变量edges

可以通过使用互斥锁（mutex）来保护变量edges，确保每个线程在访问edges时都会先获得锁。具体实现如下：

1. 定义一个互斥锁

#include <mutex>

std::mutex mtx;

2. 创建多个线程，并在线程中访问edges前先获得锁

#include <thread>

std::vector<std::thread> threads;

for (int t = 0; t < num_threads; t++) {
    threads.emplace_back([&, t]() {
        for (int i = t; i < m; i += num_threads) {
            std::vector<Edge1D_Result> local_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);
            
            // 获得锁并将local_edges合并到全局变量edges中
            std::lock_guard<std::mutex> guard(mtx);
            edges.insert(edges.end(), local_edges.begin(), local_edges.end());
        }
    });
}

3. 等待所有线程执行完毕

for (auto& t : threads) {
    t.join();
}

这样，就可以在多线程的情况下保护变量edges了。注意，由于需要频繁地获得和释放锁，使用过多的线程可能会导致性能下降。可以根据实际情况调整线程数量。