c++ - Fastest way to copy some rows from one matrix to another in OpenCV -

i have [32678 x 10] matrix (w2c) , want copy 24700 rows of matrix(out). have index of rows copied in vector(index). doing in matlab do:

out = w2c(index_im,:); 

it takes approximately 0.002622 seconds.

in opencv:

mat out(index.cols, w2c.cols, w2c.type()); (int = 0; < index.cols; ++i) {     w2c.row(index.at<int>(i) - 1).copyto(out.row(i)); } 

it takes approximately 0.015121 seconds.

as can see matlab 6 times faster. how can make opencv code efficient?

i using cmake-2.9, g++-4.8, opencv-2.4.9, ubuntu 14.04

update:

i ran code in release mode, here result ( still slower matlab )

release     debug       matlab 0.008183    0.010070    0.001604     0.009630    0.010050    0.001679 0.009120    0.009890    0.001566 0.007534    0.009567    0.001635 0.007886    0.009886    0.001840 

based on our discussion in chat not compiling optimization enabled. if this, see notable performance increase. also, make sure linking against release build of opencv.

i measured execution time following example both without , optimization enabled:

main.cpp

#include <algorithm> #include <iostream> #include <iterator> #include <numeric> #include <random> #include <vector> #include <chrono> #include <opencv2/opencv.hpp>   int main(int argc, char **argv) {     const int num_rows = 32678;     const int num_cols = 10;     const int index_size = 24700;      const int num_runs = 1000;     const int seed = 42;      std::vector<int> index_vec(num_rows);      // fill index sequence     std::iota (index_vec.begin(), index_vec.end(), 0);      // randomize sequence     std::random_device rd;     std::mt19937 g(rd());     g.seed(seed);     std::shuffle(index_vec.begin(), index_vec.end(), g);      // trunkate index     index_vec.resize(index_size);      cv::mat w2c(num_rows, num_cols, cv_32f);      // copy     cv::mat out(index_size, w2c.cols, w2c.type());      auto start = std::chrono::high_resolution_clock::now();     (int k = 0; k<num_runs; ++k)     {         (int = 0; < index_size; ++i)         {             w2c.row(index_vec[i]).copyto(out.row(i));         }     }      auto end = std::chrono::high_resolution_clock::now();      auto duration = std::chrono::duration_cast<std::chrono::microseconds>(end - start);      std::cout << duration.count()/num_runs << " microseconds" << std::endl;      return 0; } 

cmakelists.txt

project(copy) find_package(opencv required) add_executable(copy main.cpp) set(cmake_cxx_flags "${cmake_cxx_flags} -std=c++11") include_directories(${opencv_include_dirs}) target_link_libraries(copy ${opencv_libs}) 

compile , run without optimization

cmake . -dcmake_build_type=debug make ./copy 3924 microseconds 

compile , run optimization

cmake . -dcmake_build_type=release make ./copy 2664 microseconds 

i ran these tests on

• intel core i7-4600u cpu
• ubuntu 14.04 (x64)
• gcc 4.8.2
• opencv 3.0.0 (release build)