按行OpenCV's Mat is saved in memory
#include <iostream>
#include <chrono>
#include <opencv2/opencv.hpp>
using namespace std;
int main(int argc, char **argv)
{
const int test_time = 100;
cv::Mat image(5000, 10000, CV_32SC3, cv::Scalar(0, 0, 0));
int width = image.cols;
int height = image.rows;
//! 1 .at<>()
cout << "1\n"
<< image.at<cv::Vec3i>(50, 50) << endl;
chrono::steady_clock::time_point t1 = chrono::steady_clock::now();
for (int k = 0; k < test_time; k++)
{
//method1 .at<>()最好理解
for (int i = 0; i < height; i++)
{
for (int j = 0; j < width; j++)
{
image.at<cv::Vec3i>(i, j) = cv::Vec3i(3 * k, 7 * k, 12 * k);
}
}
}
chrono::steady_clock::time_point t2 = chrono::steady_clock::now();
cout << image.at<cv::Vec3i>(50, 50) << endl;
chrono::duration<double> time = chrono::duration_cast<chrono::duration<double>>(t2 - t1);
cout << "time = " << time.count() << "秒" << endl;
//! 2 .ptr(row,col)
image.setTo(cv::Scalar(0, 0, 0));
cout << "2\n"
<< image.at<cv::Vec3i>(50, 50) << endl;
t1 = chrono::steady_clock::now();
for (int k = 0; k < test_time; k++)
{
//method2 .ptr<>(行,列)
for (int h = 0; h < height; h++)
{
for (int w = 0; w < width; w++)
{
cv::Vec3i *ptr = image.ptr<cv::Vec3i>(h, w);
ptr->val[0] = 3 * k;
ptr->val[1] = 7 * k;
ptr->val[2] = 12 * k;
}
}
}
t2 = chrono::steady_clock::now();
cout << image.at<cv::Vec3i>(50, 50) << endl;
time = chrono::duration_cast<chrono::duration<double>>(t2 - t1);
cout << "time = " << time.count() << "秒" << endl;
//! 3 .ptr(row,col)
image.setTo(cv::Scalar(0, 0, 0));
cout << "3\n"
<< image.at<cv::Vec3i>(50, 50) << endl;
t1 = chrono::steady_clock::now();
for (int k = 0; k < test_time; k++)
{
//method3 .ptr<>(行,列)
for (int h = 0; h < height; h++)
{
for (int w = 0; w < width; w++)
{
int *ptr = image.ptr<int>(h, w);
ptr[0] = 3 * k;
ptr[1] = 7 * k;
ptr[2] = 12 * k;
}
}
}
t2 = chrono::steady_clock::now();
cout << image.at<cv::Vec3i>(50, 50) << endl;
time = chrono::duration_cast<chrono::duration<double>>(t2 - t1);
cout << "time = " << time.count() << "秒" << endl;
//! 4 .ptr(row)
image.setTo(cv::Scalar(0, 0, 0));
cout << "4\n"
<< image.at<cv::Vec3i>(50, 50) << endl;
t1 = chrono::steady_clock::now();
for (int k = 0; k < test_time; k++)
{
//method4 .ptr<>(行)
for (int i = 0; i < height; i++)
{
int *data = image.ptr<int>(i);
for (int j = 0; j < width; j++)
{
data[3 * j] = 3 * k;
data[3 * j + 1] = 7 * k;
data[3 * j + 2] = 12 * k;
}
}
}
t2 = chrono::steady_clock::now();
cout << image.at<cv::Vec3i>(50, 50) << endl;
time = chrono::duration_cast<chrono::duration<double>>(t2 - t1);
cout << "time = " << time.count() << "秒" << endl;
//! 5 .data
image.setTo(cv::Scalar(0, 0, 0));
cout << "5\n"
<< image.at<cv::Vec3i>(50, 50) << endl;
t1 = chrono::steady_clock::now();
int *pData = (int *)image.data;
for (int k = 0; k < test_time; k++)
{
//method5 .data
for (int i = 0; i < height; i++)
{
for (int j = 0; j < width; j++)
{
pData[width * i * 3 + 3 * j] = 3 * k;
pData[width * i * 3 + 3 * j + 1] = 7 * k;
pData[width * i * 3 + 3 * j + 2] = 12 * k;
}
}
}
t2 = chrono::steady_clock::now();
cout << image.at<cv::Vec3i>(50, 50) << endl;
time = chrono::duration_cast<chrono::duration<double>>(t2 - t1);
cout << "time = " << time.count() << "秒" << endl;
return 0;
}
Test Results
1
[0, 0, 0]
[297, 693, 1188]
time = 4.42766秒
2
[0, 0, 0]
[297, 693, 1188]
time = 4.65073秒
3
[0, 0, 0]
[297, 693, 1188]
time = 4.63955秒
4
[0, 0, 0]
[297, 693, 1188]
time = 4.43108秒
5
[0, 0, 0]
[297, 693, 1188]
time = 4.44789秒
OpenCV should be optimized, all optimized to the fastest way, at least the speed of several access methods on my computer is almost different