opencv c++写一个mali调用gpu和cpu对比的代码

下面是一个使用OpenCL Mali和CPU对比的OpenCV C++示例代码：

#include <opencv2/opencv.hpp>
#include <opencv2/ocl/ocl.hpp>
#include <iostream>
#include <chrono>

using namespace std;
using namespace std::chrono;
using namespace cv;

int main(int argc, char** argv)
{
    Mat src = imread("test.jpg");
    UMat dst;

    // Enable OpenCL Mali
    ocl::setUseOpenCL(true);

    // Create OpenCL Mali filter
    Ptr<ocl::Filter> filter = ocl::createGaussianFilter(src.type(), Size(5, 5), 1.5);

    // Run OpenCL Mali filter
    high_resolution_clock::time_point t1 = high_resolution_clock::now();
    filter->apply(UMat(src), UMat(dst));
    high_resolution_clock::time_point t2 = high_resolution_clock::now();

    // Display OpenCL Mali result
    imshow("OpenCL Mali Result", dst);

    // Run CPU filter
    Mat dst_cpu;
    t1 = high_resolution_clock::now();
    GaussianBlur(src, dst_cpu, Size(5, 5), 1.5);
    t2 = high_resolution_clock::now();

    // Display CPU result
    imshow("CPU Result", dst_cpu);

    // Calculate time taken by OpenCL Mali and CPU filters
    auto duration_mali = duration_cast<microseconds>(t2 - t1).count();
    auto duration_cpu = duration_cast<microseconds>(t2 - t1).count();

    // Display time taken by OpenCL Mali and CPU filters
    cout << "Time taken by OpenCL Mali filter: " << duration_mali << " microseconds" << endl;
    cout << "Time taken by CPU filter: " << duration_cpu << " microseconds" << endl;

    waitKey();

    return 0;
}

在上述代码中，使用了`cv::ocl::setUseOpenCL(true)`来启用OpenCL Mali加速，使用`cv::ocl::createGaussianFilter`来创建一个OpenCL Mali加速的高斯滤波器。同时，还使用了CPU的`GaussianBlur`函数作为对照组进行对比。

在执行完OpenCL Mali和CPU的滤波后，计算并输出了它们的运行时间。