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modules/surface_matching/samples/ppf_load_match.cpp
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//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2014, OpenCV Foundation, all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
// Author: Tolga Birdal <tbirdal AT gmail.com>
#include "opencv2/surface_matching.hpp"
#include <iostream>
#include "opencv2/surface_matching/ppf_helpers.hpp"
#include "opencv2/core/utility.hpp"
using namespace std;
using namespace cv;
using namespace ppf_match_3d;
static void help(const string& errorMessage)
{
cout << "Program init error : "<< errorMessage << endl;
cout << "\nUsage : ppf_matching [input model file] [input scene file]"<< endl;
cout << "\nPlease start again with new parameters"<< endl;
}
int main(int argc, char** argv)
{
// welcome message
cout << "****************************************************" << endl;
cout << "* Surface Matching demonstration : demonstrates the use of surface matching"
" using point pair features." << endl;
cout << "* The sample loads a model and a scene, where the model lies in a different"
" pose than the training.\n* It then trains the model and searches for it in the"
" input scene. The detected poses are further refined by ICP\n* and printed to the "
" standard output." << endl;
cout << "****************************************************" << endl;
if (argc < 3)
{
help("Not enough input arguments");
exit(1);
}
#if (defined __x86_64__ || defined _M_X64)
cout << "Running on 64 bits" << endl;
#else
cout << "Running on 32 bits" << endl;
#endif
#ifdef _OPENMP
cout << "Running with OpenMP" << endl;
#else
cout << "Running without OpenMP and without TBB" << endl;
#endif
string modelFileName = (string)argv[1];
string sceneFileName = (string)argv[2];
Mat pc = loadPLYSimple(modelFileName.c_str(), 1);
// Now train the model
cout << "Training..." << endl;
int64 tick1 = cv::getTickCount();
ppf_match_3d::PPF3DDetector detector(0.025, 0.05);
detector.trainModel(pc);
int64 tick2 = cv::getTickCount();
cout << endl << "Training complete in "
<< (double)(tick2-tick1)/ cv::getTickFrequency()
<< " sec" << endl << "Loading model..." << endl;
// Read the scene
Mat pcTest = loadPLYSimple(sceneFileName.c_str(), 1);
// Match the model to the scene and get the pose
cout << endl << "Starting matching..." << endl;
vector<Pose3DPtr> results;
tick1 = cv::getTickCount();
detector.match(pcTest, results, 1.0/40.0, 0.05);
tick2 = cv::getTickCount();
cout << endl << "PPF Elapsed Time " <<
(tick2-tick1)/cv::getTickFrequency() << " sec" << endl;
//check results size from match call above
size_t results_size = results.size();
cout << "Number of matching poses: " << results_size;
if (results_size == 0) {
cout << endl << "No matching poses found. Exiting." << endl;
exit(0);
}
// Get only first N results - but adjust to results size if num of results are less than that specified by N
size_t N = 2;
if (results_size < N) {
cout << endl << "Reducing matching poses to be reported (as specified in code): "
<< N << " to the number of matches found: " << results_size << endl;
N = results_size;
}
vector<Pose3DPtr> resultsSub(results.begin(),results.begin()+N);
// Create an instance of ICP
ICP icp(100, 0.005f, 2.5f, 8);
int64 t1 = cv::getTickCount();
// Register for all selected poses
cout << endl << "Performing ICP on " << N << " poses..." << endl;
icp.registerModelToScene(pc, pcTest, resultsSub);
int64 t2 = cv::getTickCount();
cout << endl << "ICP Elapsed Time " <<
(t2-t1)/cv::getTickFrequency() << " sec" << endl;
cout << "Poses: " << endl;
// debug first five poses
for (size_t i=0; i<resultsSub.size(); i++)
{
Pose3DPtr result = resultsSub[i];
cout << "Pose Result " << i << endl;
result->printPose();
if (i==0)
{
Mat pct = transformPCPose(pc, result->pose);
writePLY(pct, "para6700PCTrans.ply");
}
}
return 0;
}