projectpoints tbb并行计算代码
时间: 2023-07-09 13:37:41 浏览: 183
以下是一个简单的使用TBB实现点云投影的代码示例:
```c++
#include <iostream>
#include <vector>
#include <chrono>
#include <tbb/tbb.h>
#include <Eigen/Core>
#include <Eigen/Geometry>
using namespace std;
using namespace tbb;
// 定义点云数据类型
typedef Eigen::Matrix<float, Eigen::Dynamic, 3, Eigen::RowMajor> PointCloud;
// 定义相机参数
struct CameraParams {
float fx, fy, cx, cy;
Eigen::Matrix3f K;
};
// 点云投影函数
void projectPoints(const PointCloud& points, const CameraParams& params, vector<int>& indices)
{
int num_points = points.rows();
indices.resize(num_points);
// 并行处理
parallel_for(blocked_range<int>(0, num_points), [&](const blocked_range<int>& range) {
for (int i = range.begin(); i < range.end(); ++i) {
Eigen::Vector3f pt = points.row(i).transpose();
Eigen::Vector3f pt_cam = params.K * pt;
pt_cam /= pt_cam(2);
int u = round(pt_cam(0));
int v = round(pt_cam(1));
if (u >= 0 && u < params.cx * 2 && v >= 0 && v < params.cy * 2) {
int index = v * params.cx * 2 + u;
indices[i] = index;
}
else {
indices[i] = -1;
}
}
});
}
int main()
{
// 生成点云数据
int num_points = 1000000;
PointCloud points(num_points, 3);
points.setRandom();
// 定义相机参数
CameraParams params;
params.fx = 500;
params.fy = 500;
params.cx = 320;
params.cy = 240;
params.K << params.fx, 0, params.cx,
0, params.fy, params.cy,
0, 0, 1;
// 计时
auto start = chrono::high_resolution_clock::now();
// 点云投影
vector<int> indices;
projectPoints(points, params, indices);
auto end = chrono::high_resolution_clock::now();
cout << "Time: " << chrono::duration<double>(end - start).count() << " s" << endl;
return 0;
}
```
在上面的代码中,我们使用了TBB提供的parallel_for函数对点云数据进行分块处理,并使用了lambda表达式实现并行计算。同时,在lambda表达式中使用了TBB提供的blocked_range类来指定并行计算的范围。通过这种方式,我们可以轻松地将串行代码转换为并行代码,以提高程序的运行效率。
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