opencv 暴力线性查找，kmeans查找，LSH查找

opencv 暴力线性查找，kmeans查找与LSH查找测试。

#include <stdio.h>
#include <sys/time.h>
#include <iostream>
#include "opencv2/opencv.hpp"
using namespace std;
using namespace cv;
inline timeval cpu_time(){
timeval t1;
gettimeofday(&t1,NULL);
return t1;
}
inline double cost_time(timeval t1,timeval t2){
double t = 1000*(t2.tv_sec-t1.tv_sec)+(t2.tv_usec-t1.tv_usec)/1000;
return t;
}
void generate_data(Mat& data){
int DIM = 1024;
int samples = 50000;
RNG rng((unsigned int)time(NULL));
//generate data randomly
data.create(samples,DIM,CV_32FC1);
Point center;
center.x = rng.uniform(0,data.cols);
center.y = rng.uniform(0, data.rows);
rng.fill(data, RNG::NORMAL, Scalar(center.x,center.y), Scalar(data.cols*0.05,data.rows*0.05));
//cout<<data<<endl;
//data.convertTo(data,CV_32FC1);
}
//lsh need data type:CV_8U
void lsh_search(const Mat& data,const Mat& point, Mat& indices, Mat& dists, const int k){
timeval t1,t2;
cout<<"Begin build LSHindex: "<<endl;
// t1 = cpu_time();
flann::Index flannIndex(data,flann::LshIndexParams(10,20,2),cvflann::FLANN_DIST_EUCLIDEAN);
flannIndex.save("lshIndex.xml");
// t2 = cpu_time();
cout<<"Finish build LSHindex: n";//<<cost_time(t1,t2)<<"ms"<<endl;
t1 = cpu_time();
flannIndex.knnSearch(point, indices, dists, k,flann::SearchParams(64));
t2 = cpu_time();
cout<<"Finish lshSearch: "<<cost_time(t1,t2)<<"ms"<<endl;
}
//linear need data type: CV_32FC1
void linear_search(const Mat& data,const Mat& point, Mat& indices, Mat& dists, const int k){
//data.convertTo(data,CV_32FC1);
timeval t1,t2;
flann::Index flannIndex(data,flann::LinearIndexParams(),cvflann::FLANN_DIST_EUCLIDEAN);
t1 = cpu_time();
cout<<"Begin LinearSearch: "<<endl;
flannIndex.knnSearch(point, indices, dists, k, flann::SearchParams(64));
t2 = cpu_time();
cout<<"Finish linearSearch: "<<cost_time(t1,t2)<<"ms"<<endl;
}
//kmeans need data type CV_32FC1
void kmeans_search(const Mat& data,const Mat& point, Mat& indices, Mat& dists, const int k){
timeval t1,t2;
cout<<"Begin build kmeansIndex "<<endl;
flann::Index flannIndex(data,flann::KMeansIndexParams(64,-1),cvflann::FLANN_DIST_EUCLIDEAN);
cout<<"Finish build kmeansIndex"<<endl;
t1 = cpu_time();
cout<<"Begin KmeansSearch: "<<endl;
flannIndex.knnSearch(point, indices, dists, k, flann::SearchParams(64));
t2 = cpu_time();
cout<<"Finish KmeansSearch: "<<cost_time(t1,t2)<<"ms"<<endl;
}
int main(){
//Mat data = generate_data();
Mat data;
generate_data(data);
int k = 5;//knn
Mat indices(1,k,CV_32SC1);
Mat point = data.row(1).clone()+0.1;
Mat dists(point.rows,k,CV_64FC1);
linear_search(data,point,indices,dists,k);
cout<<indices<<endl;
cout<<dists<<endl;
kmeans_search(data,point,indices,dists,k);
cout<<indices<<endl;
cout<<dists<<endl;
data.convertTo(data,CV_8U);
point.convertTo(point,CV_8U);
lsh_search(data,point,indices,dists,k);
cout<<indices<<endl;
cout<<dists<<endl;
return 0;
}

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