给个例程
时间: 2023-08-05 17:05:28 浏览: 45
以下是一个使用 OpenCV 的 parallel_for_ 函数并行处理图像的例程:
```c++
#include <opencv2/opencv.hpp>
#include <opencv2/core/parallel.hpp>
#include <vector>
using namespace cv;
void processImage(Mat& src, Mat& dst, Mat& M)
{
warpAffine(src, dst, M, dst.size(), WARP_INVERSE_MAP);
}
int main()
{
Mat src = imread("input.jpg");
Mat dst = Mat::zeros(src.size(), src.type());
int num_threads = getNumThreads();
std::vector<Rect> blocks(num_threads);
Size block_size(src.cols / num_threads, src.rows);
int x = 0;
for (int i = 0; i < num_threads; i++)
{
blocks[i] = Rect(x, 0, block_size.width, block_size.height);
x += block_size.width;
}
blocks[num_threads - 1].width += src.cols % num_threads;
Mat M = getRotationMatrix2D(Point2f(src.cols / 2, src.rows / 2), 30, 1);
parallel_for_(cv::Range(0, num_threads), [&](const Range& range) {
for (int i = range.start; i < range.end; i++)
{
Mat sub_src = src(blocks[i]);
Mat sub_dst = dst(blocks[i]);
Mat sub_M = M.clone();
sub_M.at<double>(0, 2) -= blocks[i].x;
processImage(sub_src, sub_dst, sub_M);
}
});
imshow("Input", src);
imshow("Output", dst);
waitKey(0);
return 0;
}
```
该例程将图像分成多个块,然后在多个线程上同时调用 processImage 函数对每个块进行处理。在使用 parallel_for_ 函数时,需要注意将块的区域以及变换矩阵传递给每个线程,以便正确地处理每个块。