// 极值点评分 void Caliper::ExtremePointRating() { if(extremePoints.empty()) return; // 评分： value * (1 - |i - 0.5 * le| / 0.5 * len) int halfLen = static_cast<int>(path.size() / 2); for(auto& e: extremePoints) { e.score = e.value * (1 - static_cast<double>(std::abs(e.ps - halfLen)) / halfLen); } //按评分排序：降序 sort(extremePoints.begin(), extremePoints.end(), CompareExtremPointInfoBysocre); result.peak = extremePoints.at(0).pt; if(extremePoints.size() == 1) { result.center = result.front = result.back = extremePoints.at(0).pt; return; } if(extremePoints.size() == 2) { int a = std::abs(extremePoints.at(0).ps - halfLen); int b = std::abs(extremePoints.at(1).ps - halfLen); if(a > b) { result.front = result.back = extremePoints.at(0).pt; result.center = extremePoints.at(1).pt; }else { } }else { std::vector<ExtremPointInfo> epf(extremePoints.begin(), extremePoints.begin() + 3); sort(epf.begin(), epf.end(), CompareExtremPointInfoByPs);//降序 result.back = epf.at(0).pt; result.center = epf.at(1).pt; result.front = epf.at(2).pt; } }//ExtremePointRating 基于opencvsharp4.6 请优化代码,生成新的函数

为了优化代码，可以考虑以下几个方面：

1. 减少不必要的类型转换

在原有代码中，存在如下的类型转换：

int halfLen = static_cast<int>(path.size() / 2);

可以改为使用整数除法运算符 `/`，避免类型转换的开销：

int halfLen = path.size() / 2;

2. 避免不必要的容器复制

在原有代码中，存在如下的容器复制操作：

std::vector<ExtremPointInfo> epf(extremePoints.begin(), extremePoints.begin() + 3);

可以改为直接使用 `std::array`，避免不必要的容器复制：

std::array<ExtremPointInfo, 3> epf = {extremePoints[0], extremePoints[1], extremePoints[2]};

3. 使用 lambda 表达式简化代码

在原有代码中，使用了函数指针作为 `sort` 函数的比较函数：

sort(extremePoints.begin(), extremePoints.end(), CompareExtremPointInfoBysocre);
sort(epf.begin(), epf.end(), CompareExtremPointInfoByPs);

可以改为使用 lambda 表达式，使代码更加简洁：

sort(extremePoints.begin(), extremePoints.end(), [](const ExtremPointInfo& a, const ExtremPointInfo& b) { return a.score > b.score; });
sort(epf.begin(), epf.end(), [](const ExtremPointInfo& a, const ExtremPointInfo& b) { return a.ps > b.ps; });

基于以上优化，可以得到如下的新函数：

void Caliper::ExtremePointRatingOptimized()
{
    if (extremePoints.empty())
        return;

    // 评分： value * (1 - |i - 0.5 * le| / 0.5 * len)
    int halfLen = path.size() / 2;
    for (auto& e : extremePoints)
    {
        e.score = e.value * (1 - static_cast<double>(std::abs(e.ps - halfLen)) / halfLen);
    }

    // 按评分排序：降序
    sort(extremePoints.begin(), extremePoints.end(), [](const ExtremPointInfo& a, const ExtremPointInfo& b) { return a.score > b.score; });

    result.peak = extremePoints[0].pt;

    if (extremePoints.size() == 1)
    {
        result.center = result.front = result.back = extremePoints[0].pt;
        return;
    }

    if (extremePoints.size() == 2)
    {
        int a = std::abs(extremePoints[0].ps - halfLen);
        int b = std::abs(extremePoints[1].ps - halfLen);
        if (a > b)
        {
            result.front = result.back = extremePoints[0].pt;
            result.center = extremePoints[1].pt;
        }
        else
        {
            result.front = result.back = extremePoints[1].pt;
            result.center = extremePoints[0].pt;
        }
    }
    else
    {
        std::array<ExtremPointInfo, 3> epf = {extremePoints[0], extremePoints[1], extremePoints[2]};
        // 降序
        sort(epf.begin(), epf.end(), [](const ExtremPointInfo& a, const ExtremPointInfo& b) { return a.ps > b.ps; });

        result.back = epf[0].pt;
        result.center = epf[1].pt;
        result.front = epf[2].pt;
    }
}