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