背景

有一张图像，很大，假设10000x10000，需要找其中的最大值和最小值，可以使用opencv的cv::minMaxLoc，但是对于这样的大图来说太慢了。可以多线程并行找。

方法

参考：How to atomically update a maximum value ?

void findMinMax(const cv::Mat& image, double& minV, double& maxV)
{
	const auto updateMax = [](std::atomic<float> &z, const float depth)
    {
        float oldZ = z.load();
        while (oldZ < depth && !z.compare_exchange_weak(oldZ, depth))
        {
        }
    };

    const auto updateMin = [](std::atomic<float> &z, const float depth)
    {
        float oldZ = z.load();
        while (oldZ > depth && !z.compare_exchange_weak(oldZ, depth))
        {
        }
    };
	
	std::atomic<float> minVal, maxVal;
	image.forEach<float>([&](const float d, const int* pos){
		updateMin(minVal, d);
		updateMax(maxVal, d);
	});
	minV = minVal;
	maxV = maxVal;
}

int main()
{
    constexpr int rows = 10000;
    constexpr int cols = 10000;
    cv::Mat image = cv::Mat(rows, cols, CV_32FC1);

    image.forEach<float>([&](float &z, const int *pos)
                         {
                            const int r = pos[0];
                            const int c = pos[1];
                            z = ((r * cols + c) % 321) * 0.321 - 0.321; });

    double minV, maxV;

    auto start = clock();
    cv::minMaxLoc(image, &minV, &maxV);
    std::cout << "cvMinMax cost " << clock() - start << " ms" << std::endl;
    std::cout << "cv min " << minV << " max " << maxV << std::endl;

    minV = maxV = -1;

    start = clock();
    findMinMax(image, minV, maxV);
    std::cout << "findMinMax cost " << clock() - start << " ms" << std::endl;
    std::cout << "find min " << minV << " max " << maxV << std::endl;
}

结果自己定义的findMinMax比cv::minMaxLoc快一倍！

理解compare_exchange_weak这个函数是关键，需要稍微想想多个线程来更新最大最小值的这个过程。