小彭老师，麻烦使用SSE优化一下下面的代码 #5
Description
以下的calSimilarity函数在算法过程中会执行（-180°~180°步长为0.1）很多次，下面时从工程中摘出来的代码，运行单次时，在编译器开O0优化，耗时为2046.41ms；在编译器开O3优化，耗时为310.06ms
gcc normal_calSimilarity.cpp -O0 -o normal_calSimilarity_gcc -lstdc++ -lm
硬件
CPU: i7-10700 [email protected] x 16**
//********************************************************************************************
//***********************************normal_calSimilarity.cpp********************************
//********************************************************************************************
#include <iostream>
#include <vector>
#include <random>
#include <fstream>
#include <stdio.h>
#include <chrono>
struct templateFeat
{
int x;
int y;
short dx;
short dy;
float mag;
};
struct matchResult
{
int i;
int j;
int angle;
float score;
};
struct searchFeat
{
short dx;
short dy;
float mag;
};
bool saveDataToTxt(const std::string txt_path,const std::vector<matchResult> match_result) {
std::ofstream file(txt_path);
if (file.is_open()) {
for (int i = 0; i < match_result.size(); ++i) {
file << match_result[i].i << " " << match_result[i].j << " " << match_result[i].angle << " " << match_result[i].score << std::endl;
}
file.close();
std::cout << "Match result datas saved to match_result.txt!" << std::endl;
} else {
std::cout << "Unable to open file" << std::endl;
}
return true;
}
std::vector<matchResult> calSimilarity(const std::vector<templateFeat> template_point,const std::vector<searchFeat> search_point)
{
int template_feat_size = template_point.size();
int search_feat_size = search_point.size();
std::vector<matchResult> results0Deg;
float anMinScore = 0.4 - 1;
float NormMinScore = 0.4 / template_feat_size;
float NormGreediness = ((1 - 0.8 * 0.4) / (1 - 0.8)) / template_feat_size;
for(int i = 0; i < 1920; i++)
{
for(int j = 0; j < 1200; j++)
{
float PartialScore = 0;
float PartialSum = 0;
int SumOfCoords = 0;
for(int m = 0; m < template_feat_size; m++)
{
int curX = i + template_point[m].x;
int curY = j + template_point[m].y;
if(curX < 0 || curY < 0 || curX > 230 || curY > 350)
{
continue;
}
short iTx = template_point[m].dx;
short iTy = template_point[m].dy;
float iTm = template_point[m].mag;
int offSet = curY * 350 + curX;
short iSx = search_point[offSet].dx;
short iSy = search_point[offSet].dy;
float iSm = search_point[offSet].mag;
if((iSx != 0 || iSy != 0) && (iTx != 0 || iTy != 0))
{
PartialSum += ((iSx * iTx) + (iSy * iTy)) * (iSm * iTm);
}
SumOfCoords = m + 1;
PartialScore = PartialSum / SumOfCoords;
if(PartialScore < (std::min(anMinScore + NormGreediness * SumOfCoords, NormMinScore * SumOfCoords)))
{
break;
}
}
if(PartialScore > 0.4)
{
results0Deg.push_back({i, j, 0, PartialScore});
}
}
}
return results0Deg;
}
int main()
{
//为了测试函数而生成的随机数：template_point/search_point
std::random_device rd;
std::mt19937 gen(rd());
std::uniform_int_distribution<int> intXDist(-18, 32);
std::uniform_int_distribution<int> intYDist(-48, 49);
std::uniform_int_distribution<short> shortDXDist(-348, 349);
std::uniform_int_distribution<short> shortDYDist(-421, 352);
std::uniform_real_distribution<float> floatDist(0.00237112f, 0.0120056f);
std::vector<templateFeat> template_point(215);
for (auto &feat : template_point)
{
feat.x = intXDist(gen);
feat.y = intYDist(gen);
feat.dx = shortDXDist(gen);
feat.dy = shortDYDist(gen);
feat.mag = floatDist(gen);
}
std::uniform_int_distribution<short> shortDxDist(-460, 460);
std::uniform_int_distribution<short> shortDyDist(-476, 460);
std::uniform_real_distribution<float> float_Dist(0.0f, 0.707107f);
std::vector<searchFeat> search_point(2304000);
for (auto &feat : search_point)
{
feat.dx = shortDxDist(gen);
feat.dy = shortDyDist(gen);
feat.mag = float_Dist(gen);
}
//运行算法,计算耗时
auto start = std::chrono::high_resolution_clock::now();
std::vector<matchResult> results0Deg = calSimilarity(template_point,search_point);
auto end = std::chrono::high_resolution_clock::now();
std::chrono::duration<double, std::milli> duration = end - start;
std::cout << "Function took " << duration.count() << " milliseconds." << std::endl;
//保存匹配结果
saveDataToTxt("./match_result.txt",results0Deg);
return true;
}