851 lines
24 KiB
C++
851 lines
24 KiB
C++
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/*M///////////////////////////////////////////////////////////////////////////////////////
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//
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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) 2000-2008, Intel Corporation, all rights reserved.
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// Copyright (C) 2009, Willow Garage Inc., 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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//M*/
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#include "circlesgrid.hpp"
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using namespace cv;
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Graph::Graph(int n)
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{
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for (int i = 0; i < n; i++)
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{
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addVertex(i);
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}
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}
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bool Graph::doesVertexExist(int id) const
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{
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return (vertices.find(id) != vertices.end());
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}
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void Graph::addVertex(int id)
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{
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assert( !doesVertexExist( id ) );
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vertices.insert(pair<int, Vertex> (id, Vertex()));
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}
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void Graph::addEdge(int id1, int id2)
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{
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assert( doesVertexExist( id1 ) );
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assert( doesVertexExist( id2 ) );
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vertices[id1].neighbors.insert(id2);
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vertices[id2].neighbors.insert(id1);
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}
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bool Graph::areVerticesAdjacent(int id1, int id2) const
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{
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assert( doesVertexExist( id1 ) );
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assert( doesVertexExist( id2 ) );
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Vertices::const_iterator it = vertices.find(id1);
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return it->second.neighbors.find(id2) != it->second.neighbors.end();
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}
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size_t Graph::getVerticesCount() const
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{
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return vertices.size();
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}
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size_t Graph::getDegree(int id) const
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{
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assert( doesVertexExist(id) );
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Vertices::const_iterator it = vertices.find(id);
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return it->second.neighbors.size();
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}
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void Graph::floydWarshall(cv::Mat &distanceMatrix, int infinity) const
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{
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const int edgeWeight = 1;
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const size_t n = getVerticesCount();
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distanceMatrix.create(n, n, CV_32SC1);
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distanceMatrix.setTo(infinity);
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for (Vertices::const_iterator it1 = vertices.begin(); it1 != vertices.end(); it1++)
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{
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distanceMatrix.at<int> (it1->first, it1->first) = 0;
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for (Neighbors::iterator it2 = it1->second.neighbors.begin(); it2 != it1->second.neighbors.end(); it2++)
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{
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assert( it1->first != *it2 );
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distanceMatrix.at<int> (it1->first, *it2) = edgeWeight;
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}
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}
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for (Vertices::const_iterator it1 = vertices.begin(); it1 != vertices.end(); it1++)
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{
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for (Vertices::const_iterator it2 = vertices.begin(); it2 != vertices.end(); it2++)
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{
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for (Vertices::const_iterator it3 = vertices.begin(); it3 != vertices.end(); it3++)
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{
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int val1 = distanceMatrix.at<int> (it2->first, it3->first);
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int val2;
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if (distanceMatrix.at<int> (it2->first, it1->first) == infinity || distanceMatrix.at<int> (it1->first,
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it3->first)
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== infinity)
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val2 = val1;
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else
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val2 = distanceMatrix.at<int> (it2->first, it1->first) + distanceMatrix.at<int> (it1->first, it3->first);
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distanceMatrix.at<int> (it2->first, it3->first) = std::min(val1, val2);
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}
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}
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}
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}
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void computeShortestPath(Mat &predecessorMatrix, int v1, int v2, vector<int> &path);
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void computePredecessorMatrix(const Mat &dm, int verticesCount, Mat &predecessorMatrix);
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CirclesGridFinderParameters::CirclesGridFinderParameters()
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{
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minDensity = 10;
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densityNeighborhoodSize = Size2f(16, 16);
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minDistanceToAddKeypoint = 20;
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kmeansAttempts = 100;
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convexHullFactor = 1.1;
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keypointScale = 1;
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minGraphConfidence = 9;
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vertexGain = 2;
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vertexPenalty = -5;
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edgeGain = 1;
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edgePenalty = -5;
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existingVertexGain = 0;
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}
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CirclesGridFinder::CirclesGridFinder(Size _patternSize, const vector<KeyPoint> &testKeypoints,
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const CirclesGridFinderParameters &_parameters) :
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patternSize(_patternSize)
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{
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keypoints = testKeypoints;
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parameters = _parameters;
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}
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bool CirclesGridFinder::findHoles()
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{
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vector<Point2f> vectors, filteredVectors, basis;
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computeEdgeVectorsOfRNG(vectors);
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filterOutliersByDensity(vectors, filteredVectors);
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vector<Graph> basisGraphs;
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findBasis(filteredVectors, basis, basisGraphs);
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findMCS(basis, basisGraphs);
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return (isDetectionCorrect());
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//CV_Error( 0, "Detection is not correct" );
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}
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bool CirclesGridFinder::isDetectionCorrect()
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{
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if (holes.size() != patternSize.height)
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return false;
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set<int> vertices;
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for (size_t i = 0; i < holes.size(); i++)
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{
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if (holes[i].size() != patternSize.width)
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return false;
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for (size_t j = 0; j < holes[i].size(); j++)
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{
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vertices.insert(holes[i][j]);
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}
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}
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return vertices.size() == patternSize.area();
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}
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void CirclesGridFinder::findMCS(const vector<Point2f> &basis, vector<Graph> &basisGraphs)
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{
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Path longestPath;
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size_t bestGraphIdx = findLongestPath(basisGraphs, longestPath);
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vector<int> holesRow = longestPath.vertices;
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while (holesRow.size() > std::max(patternSize.width, patternSize.height))
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{
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holesRow.pop_back();
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holesRow.erase(holesRow.begin());
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}
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if (bestGraphIdx == 0)
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{
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holes.push_back(holesRow);
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int w = holes[0].size();
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int h = holes.size();
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//parameters.minGraphConfidence = holes[0].size() * parameters.vertexGain + (holes[0].size() - 1) * parameters.edgeGain;
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//parameters.minGraphConfidence = holes[0].size() * parameters.vertexGain + (holes[0].size() / 2) * parameters.edgeGain;
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//parameters.minGraphConfidence = holes[0].size() * parameters.existingVertexGain + (holes[0].size() / 2) * parameters.edgeGain;
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parameters.minGraphConfidence = holes[0].size() * parameters.existingVertexGain;
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for (int i = h; i < patternSize.height; i++)
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{
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addHolesByGraph(basisGraphs, true, basis[1]);
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}
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//parameters.minGraphConfidence = holes.size() * parameters.existingVertexGain + (holes.size() / 2) * parameters.edgeGain;
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parameters.minGraphConfidence = holes.size() * parameters.existingVertexGain;
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for (int i = w; i < patternSize.width; i++)
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{
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addHolesByGraph(basisGraphs, false, basis[0]);
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}
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}
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else
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{
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holes.resize(holesRow.size());
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for (size_t i = 0; i < holesRow.size(); i++)
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holes[i].push_back(holesRow[i]);
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int w = holes[0].size();
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int h = holes.size();
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parameters.minGraphConfidence = holes.size() * parameters.existingVertexGain;
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for (int i = w; i < patternSize.width; i++)
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{
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addHolesByGraph(basisGraphs, false, basis[0]);
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}
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parameters.minGraphConfidence = holes[0].size() * parameters.existingVertexGain;
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for (int i = h; i < patternSize.height; i++)
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{
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addHolesByGraph(basisGraphs, true, basis[1]);
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}
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}
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}
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Mat CirclesGridFinder::rectifyGrid(Size detectedGridSize, const vector<Point2f>& centers,
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const vector<KeyPoint> &keypoints, vector<KeyPoint> &warpedKeypoints)
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{
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assert( !centers.empty() );
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const float edgeLength = 30;
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const Point2f offset(150, 150);
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const int keypointScale = 1;
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vector<Point2f> dstPoints;
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for (int i = 0; i < detectedGridSize.height; i++)
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{
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for (int j = 0; j < detectedGridSize.width; j++)
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{
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dstPoints.push_back(offset + Point2f(edgeLength * j, edgeLength * i));
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}
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}
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Mat H = findHomography(Mat(centers), Mat(dstPoints), CV_RANSAC);
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//Mat H = findHomography( Mat( corners ), Mat( dstPoints ) );
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vector<Point2f> srcKeypoints;
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for (size_t i = 0; i < keypoints.size(); i++)
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{
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srcKeypoints.push_back(keypoints[i].pt);
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}
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Mat dstKeypointsMat;
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transform(Mat(srcKeypoints), dstKeypointsMat, H);
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vector<Point2f> dstKeypoints;
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convertPointsHomogeneous(dstKeypointsMat, dstKeypoints);
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warpedKeypoints.clear();
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for (size_t i = 0; i < dstKeypoints.size(); i++)
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{
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Point2f pt = dstKeypoints[i];
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warpedKeypoints.push_back(KeyPoint(pt, keypointScale));
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}
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return H;
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}
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int CirclesGridFinder::findNearestKeypoint(Point2f pt) const
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{
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int bestIdx = -1;
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float minDist = std::numeric_limits<float>::max();
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for (size_t i = 0; i < keypoints.size(); i++)
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{
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float dist = norm(pt - keypoints[i].pt);
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if (dist < minDist)
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{
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minDist = dist;
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bestIdx = i;
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}
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}
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return bestIdx;
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}
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void CirclesGridFinder::addPoint(Point2f pt, vector<int> &points)
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{
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int ptIdx = findNearestKeypoint(pt);
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if (norm(keypoints[ptIdx].pt - pt) > parameters.minDistanceToAddKeypoint)
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{
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KeyPoint kpt = KeyPoint(pt, parameters.keypointScale);
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keypoints.push_back(kpt);
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points.push_back(keypoints.size() - 1);
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}
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else
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{
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points.push_back(ptIdx);
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}
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}
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void CirclesGridFinder::findCandidateLine(vector<int> &line, int seedLineIdx, bool addRow, Point2f basisVec,
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vector<int> &seeds)
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{
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line.clear();
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seeds.clear();
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if (addRow)
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{
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for (size_t i = 0; i < holes[seedLineIdx].size(); i++)
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{
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Point2f pt = keypoints[holes[seedLineIdx][i]].pt + basisVec;
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addPoint(pt, line);
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seeds.push_back(holes[seedLineIdx][i]);
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}
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}
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else
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{
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for (size_t i = 0; i < holes.size(); i++)
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{
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Point2f pt = keypoints[holes[i][seedLineIdx]].pt + basisVec;
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addPoint(pt, line);
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seeds.push_back(holes[i][seedLineIdx]);
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}
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}
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assert( line.size() == seeds.size() );
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}
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void CirclesGridFinder::findCandidateHoles(vector<int> &above, vector<int> &below, bool addRow, Point2f basisVec,
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vector<int> &aboveSeeds, vector<int> &belowSeeds)
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{
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above.clear();
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below.clear();
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aboveSeeds.clear();
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belowSeeds.clear();
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findCandidateLine(above, 0, addRow, -basisVec, aboveSeeds);
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int lastIdx = addRow ? holes.size() - 1 : holes[0].size() - 1;
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findCandidateLine(below, lastIdx, addRow, basisVec, belowSeeds);
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assert( below.size() == above.size() );
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assert( belowSeeds.size() == aboveSeeds.size() );
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assert( below.size() == belowSeeds.size() );
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}
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bool CirclesGridFinder::areCentersNew(const vector<int> &newCenters, const vector<vector<int> > &holes)
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{
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for (size_t i = 0; i < newCenters.size(); i++)
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{
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for (size_t j = 0; j < holes.size(); j++)
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{
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if (holes[j].end() != std::find(holes[j].begin(), holes[j].end(), newCenters[i]))
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{
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return false;
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}
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}
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}
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return true;
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}
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void CirclesGridFinder::insertWinner(float aboveConfidence, float belowConfidence, float minConfidence, bool addRow,
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const vector<int> &above, const vector<int> &below, vector<vector<int> > &holes)
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{
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if (aboveConfidence < minConfidence && belowConfidence < minConfidence)
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return;
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if (addRow)
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{
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if (aboveConfidence >= belowConfidence)
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{
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if (!areCentersNew(above, holes))
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CV_Error( 0, "Centers are not new" );
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holes.insert(holes.begin(), above);
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}
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else
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{
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if (!areCentersNew(below, holes))
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CV_Error( 0, "Centers are not new" );
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holes.insert(holes.end(), below);
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}
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}
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else
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{
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if (aboveConfidence >= belowConfidence)
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{
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if (!areCentersNew(above, holes))
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CV_Error( 0, "Centers are not new" );
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for (size_t i = 0; i < holes.size(); i++)
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{
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holes[i].insert(holes[i].begin(), above[i]);
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}
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}
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else
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{
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if (!areCentersNew(below, holes))
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CV_Error( 0, "Centers are not new" );
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for (size_t i = 0; i < holes.size(); i++)
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{
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holes[i].insert(holes[i].end(), below[i]);
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}
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}
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}
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|
}
|
||
|
|
||
|
/*
|
||
|
bool CirclesGridFinder::areVerticesAdjacent(const Graph &graph, int vertex1, int vertex2)
|
||
|
{
|
||
|
property_map<Graph, vertex_index_t>::type index = get(vertex_index, graph);
|
||
|
|
||
|
bool areAdjacent = false;
|
||
|
graph_traits<Graph>::adjacency_iterator ai;
|
||
|
graph_traits<Graph>::adjacency_iterator ai_end;
|
||
|
|
||
|
for (tie(ai, ai_end) = adjacent_vertices(vertex1, graph); ai != ai_end; ++ai)
|
||
|
{
|
||
|
if (*ai == index[vertex2])
|
||
|
areAdjacent = true;
|
||
|
}
|
||
|
|
||
|
return areAdjacent;
|
||
|
}*/
|
||
|
|
||
|
float CirclesGridFinder::computeGraphConfidence(const vector<Graph> &basisGraphs, bool addRow,
|
||
|
const vector<int> &points, const vector<int> &seeds)
|
||
|
{
|
||
|
assert( points.size() == seeds.size() );
|
||
|
float confidence = 0;
|
||
|
const int vCount = basisGraphs[0].getVerticesCount();
|
||
|
assert( basisGraphs[0].getVerticesCount() == basisGraphs[1].getVerticesCount() );
|
||
|
|
||
|
for (size_t i = 0; i < seeds.size(); i++)
|
||
|
{
|
||
|
if (seeds[i] < vCount && points[i] < vCount)
|
||
|
{
|
||
|
if (!basisGraphs[addRow].areVerticesAdjacent(seeds[i], points[i]))
|
||
|
{
|
||
|
confidence += parameters.vertexPenalty;
|
||
|
}
|
||
|
else
|
||
|
{
|
||
|
confidence += parameters.vertexGain;
|
||
|
}
|
||
|
}
|
||
|
|
||
|
if (points[i] < vCount)
|
||
|
{
|
||
|
confidence += parameters.existingVertexGain;
|
||
|
}
|
||
|
}
|
||
|
|
||
|
for (size_t i = 1; i < points.size(); i++)
|
||
|
{
|
||
|
if (points[i - 1] < vCount && points[i] < vCount)
|
||
|
{
|
||
|
if (!basisGraphs[!addRow].areVerticesAdjacent(points[i - 1], points[i]))
|
||
|
{
|
||
|
confidence += parameters.edgePenalty;
|
||
|
}
|
||
|
else
|
||
|
{
|
||
|
confidence += parameters.edgeGain;
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
return confidence;
|
||
|
|
||
|
}
|
||
|
|
||
|
void CirclesGridFinder::addHolesByGraph(const vector<Graph> &basisGraphs, bool addRow, Point2f basisVec)
|
||
|
{
|
||
|
vector<int> above, below, aboveSeeds, belowSeeds;
|
||
|
findCandidateHoles(above, below, addRow, basisVec, aboveSeeds, belowSeeds);
|
||
|
float aboveConfidence = computeGraphConfidence(basisGraphs, addRow, above, aboveSeeds);
|
||
|
float belowConfidence = computeGraphConfidence(basisGraphs, addRow, below, belowSeeds);
|
||
|
|
||
|
insertWinner(aboveConfidence, belowConfidence, parameters.minGraphConfidence, addRow, above, below, holes);
|
||
|
}
|
||
|
|
||
|
void CirclesGridFinder::filterOutliersByDensity(const vector<Point2f> &samples, vector<Point2f> &filteredSamples)
|
||
|
{
|
||
|
if (samples.empty())
|
||
|
CV_Error( 0, "samples is empty" );
|
||
|
|
||
|
filteredSamples.clear();
|
||
|
|
||
|
for (size_t i = 0; i < samples.size(); i++)
|
||
|
{
|
||
|
Rect_<float> rect(samples[i] - Point2f(parameters.densityNeighborhoodSize) * 0.5,
|
||
|
parameters.densityNeighborhoodSize);
|
||
|
int neighborsCount = 0;
|
||
|
for (size_t j = 0; j < samples.size(); j++)
|
||
|
{
|
||
|
if (rect.contains(samples[j]))
|
||
|
neighborsCount++;
|
||
|
}
|
||
|
if (neighborsCount >= parameters.minDensity)
|
||
|
filteredSamples.push_back(samples[i]);
|
||
|
}
|
||
|
|
||
|
if (filteredSamples.empty())
|
||
|
CV_Error( 0, "filteredSamples is empty" );
|
||
|
}
|
||
|
|
||
|
void CirclesGridFinder::findBasis(const vector<Point2f> &samples, vector<Point2f> &basis, vector<Graph> &basisGraphs)
|
||
|
{
|
||
|
basis.clear();
|
||
|
Mat bestLabels;
|
||
|
TermCriteria termCriteria;
|
||
|
Mat centers;
|
||
|
int clustersCount = 4;
|
||
|
kmeans(Mat(samples).reshape(1, 0), clustersCount, bestLabels, termCriteria, parameters.kmeansAttempts,
|
||
|
KMEANS_RANDOM_CENTERS, ¢ers);
|
||
|
assert( centers.type() == CV_32FC1 );
|
||
|
|
||
|
vector<int> basisIndices;
|
||
|
//TODO: only remove duplicate
|
||
|
for (int i = 0; i < clustersCount; i++)
|
||
|
{
|
||
|
int maxIdx = (fabs(centers.at<float> (i, 0)) < fabs(centers.at<float> (i, 1)));
|
||
|
if (centers.at<float> (i, maxIdx) > 0)
|
||
|
{
|
||
|
Point2f vec(centers.at<float> (i, 0), centers.at<float> (i, 1));
|
||
|
basis.push_back(vec);
|
||
|
basisIndices.push_back(i);
|
||
|
}
|
||
|
}
|
||
|
if (basis.size() != 2)
|
||
|
CV_Error( 0, "Basis size is not 2");
|
||
|
|
||
|
if (basis[1].x > basis[0].x)
|
||
|
{
|
||
|
std::swap(basis[0], basis[1]);
|
||
|
std::swap(basisIndices[0], basisIndices[1]);
|
||
|
}
|
||
|
|
||
|
const float minBasisDif = 2;
|
||
|
if (norm(basis[0] - basis[1]) < minBasisDif)
|
||
|
CV_Error( 0, "degenerate basis" );
|
||
|
|
||
|
vector<vector<Point2f> > clusters(2), hulls(2);
|
||
|
for (size_t k = 0; k < samples.size(); k++)
|
||
|
{
|
||
|
int label = bestLabels.at<int> (k, 0);
|
||
|
int idx = -1;
|
||
|
if (label == basisIndices[0])
|
||
|
idx = 0;
|
||
|
if (label == basisIndices[1])
|
||
|
idx = 1;
|
||
|
if (idx >= 0)
|
||
|
{
|
||
|
clusters[idx].push_back(basis[idx] + parameters.convexHullFactor * (samples[k] - basis[idx]));
|
||
|
}
|
||
|
}
|
||
|
for (size_t i = 0; i < basis.size(); i++)
|
||
|
{
|
||
|
convexHull(Mat(clusters[i]), hulls[i]);
|
||
|
}
|
||
|
|
||
|
basisGraphs.resize(basis.size(), Graph(keypoints.size()));
|
||
|
for (size_t i = 0; i < keypoints.size(); i++)
|
||
|
{
|
||
|
for (size_t j = 0; j < keypoints.size(); j++)
|
||
|
{
|
||
|
if (i == j)
|
||
|
continue;
|
||
|
|
||
|
Point2f vec = keypoints[i].pt - keypoints[j].pt;
|
||
|
|
||
|
for (size_t k = 0; k < hulls.size(); k++)
|
||
|
{
|
||
|
if (pointPolygonTest(Mat(hulls[k]), vec, false) >= 0)
|
||
|
{
|
||
|
basisGraphs[k].addEdge(i, j);
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
|
||
|
void CirclesGridFinder::computeEdgeVectorsOfRNG(vector<Point2f> &vectors, Mat *drawImage) const
|
||
|
{
|
||
|
vectors.clear();
|
||
|
|
||
|
//TODO: use more fast algorithm instead of naive N^3
|
||
|
for (size_t i = 0; i < keypoints.size(); i++)
|
||
|
{
|
||
|
for (size_t j = 0; j < keypoints.size(); j++)
|
||
|
{
|
||
|
if (i == j)
|
||
|
continue;
|
||
|
|
||
|
Point2f vec = keypoints[i].pt - keypoints[j].pt;
|
||
|
float dist = norm(vec);
|
||
|
|
||
|
bool isNeighbors = true;
|
||
|
for (size_t k = 0; k < keypoints.size(); k++)
|
||
|
{
|
||
|
if (k == i || k == j)
|
||
|
continue;
|
||
|
|
||
|
float dist1 = norm(keypoints[i].pt - keypoints[k].pt);
|
||
|
float dist2 = norm(keypoints[j].pt - keypoints[k].pt);
|
||
|
if (dist1 < dist && dist2 < dist)
|
||
|
{
|
||
|
isNeighbors = false;
|
||
|
break;
|
||
|
}
|
||
|
}
|
||
|
|
||
|
if (isNeighbors)
|
||
|
{
|
||
|
vectors.push_back(keypoints[i].pt - keypoints[j].pt);
|
||
|
if (drawImage != 0)
|
||
|
{
|
||
|
line(*drawImage, keypoints[i].pt, keypoints[j].pt, Scalar(255, 0, 0), 2);
|
||
|
circle(*drawImage, keypoints[i].pt, 3, Scalar(0, 0, 255), -1);
|
||
|
circle(*drawImage, keypoints[j].pt, 3, Scalar(0, 0, 255), -1);
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
|
||
|
void computePredecessorMatrix(const Mat &dm, int verticesCount, Mat &predecessorMatrix)
|
||
|
{
|
||
|
assert( dm.type() == CV_32SC1 );
|
||
|
predecessorMatrix.create(verticesCount, verticesCount, CV_32SC1);
|
||
|
predecessorMatrix = -1;
|
||
|
for (int i = 0; i < predecessorMatrix.rows; i++)
|
||
|
{
|
||
|
for (int j = 0; j < predecessorMatrix.cols; j++)
|
||
|
{
|
||
|
int dist = dm.at<int> (i, j);
|
||
|
for (int k = 0; k < verticesCount; k++)
|
||
|
{
|
||
|
if (dm.at<int> (i, k) == dist - 1 && dm.at<int> (k, j) == 1)
|
||
|
{
|
||
|
predecessorMatrix.at<int> (i, j) = k;
|
||
|
break;
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
|
||
|
void computeShortestPath(Mat &predecessorMatrix, int v1, int v2, vector<int> &path)
|
||
|
{
|
||
|
if (predecessorMatrix.at<int> (v1, v2) < 0)
|
||
|
{
|
||
|
path.push_back(v1);
|
||
|
return;
|
||
|
}
|
||
|
|
||
|
computeShortestPath(predecessorMatrix, v1, predecessorMatrix.at<int> (v1, v2), path);
|
||
|
path.push_back(v2);
|
||
|
}
|
||
|
|
||
|
size_t CirclesGridFinder::findLongestPath(vector<Graph> &basisGraphs, Path &bestPath)
|
||
|
{
|
||
|
vector<Path> longestPaths(1);
|
||
|
vector<int> confidences;
|
||
|
|
||
|
size_t bestGraphIdx = 0;
|
||
|
const int infinity = -1;
|
||
|
for (size_t graphIdx = 0; graphIdx < basisGraphs.size(); graphIdx++)
|
||
|
{
|
||
|
const Graph &g = basisGraphs[graphIdx];
|
||
|
Mat distanceMatrix;
|
||
|
g.floydWarshall(distanceMatrix, infinity);
|
||
|
Mat predecessorMatrix;
|
||
|
computePredecessorMatrix(distanceMatrix, g.getVerticesCount(), predecessorMatrix);
|
||
|
|
||
|
double maxVal;
|
||
|
Point maxLoc;
|
||
|
assert (infinity < 0);
|
||
|
minMaxLoc(distanceMatrix, 0, &maxVal, 0, &maxLoc);
|
||
|
|
||
|
if (maxVal > longestPaths[0].length)
|
||
|
{
|
||
|
longestPaths.clear();
|
||
|
confidences.clear();
|
||
|
bestGraphIdx = graphIdx;
|
||
|
}
|
||
|
if (longestPaths.empty() || (maxVal == longestPaths[0].length && graphIdx == bestGraphIdx))
|
||
|
{
|
||
|
Path path = Path(maxLoc.x, maxLoc.y, maxVal);
|
||
|
computeShortestPath(predecessorMatrix, maxLoc.x, maxLoc.y, path.vertices);
|
||
|
longestPaths.push_back(path);
|
||
|
|
||
|
int conf = 0;
|
||
|
for (size_t v2 = 0; v2 < path.vertices.size(); v2++)
|
||
|
{
|
||
|
conf += basisGraphs[1 - (int)graphIdx].getDegree(v2);
|
||
|
}
|
||
|
confidences.push_back(conf);
|
||
|
}
|
||
|
}
|
||
|
//if( bestGraphIdx != 0 )
|
||
|
//CV_Error( 0, "" );
|
||
|
|
||
|
int maxConf = -1;
|
||
|
int bestPathIdx = -1;
|
||
|
for (size_t i = 0; i < confidences.size(); i++)
|
||
|
{
|
||
|
if (confidences[i] > maxConf)
|
||
|
{
|
||
|
maxConf = confidences[i];
|
||
|
bestPathIdx = i;
|
||
|
}
|
||
|
}
|
||
|
|
||
|
//int bestPathIdx = rand() % longestPaths.size();
|
||
|
bestPath = longestPaths.at(bestPathIdx);
|
||
|
bool needReverse = (bestGraphIdx == 0 && keypoints[bestPath.lastVertex].pt.x < keypoints[bestPath.firstVertex].pt.x)
|
||
|
|| (bestGraphIdx == 1 && keypoints[bestPath.lastVertex].pt.y < keypoints[bestPath.firstVertex].pt.y);
|
||
|
if (needReverse)
|
||
|
{
|
||
|
std::swap(bestPath.lastVertex, bestPath.firstVertex);
|
||
|
std::reverse(bestPath.vertices.begin(), bestPath.vertices.end());
|
||
|
}
|
||
|
return bestGraphIdx;
|
||
|
}
|
||
|
|
||
|
void CirclesGridFinder::drawBasis(const vector<Point2f> &basis, Point2f origin, Mat &drawImg) const
|
||
|
{
|
||
|
for (size_t i = 0; i < basis.size(); i++)
|
||
|
{
|
||
|
Point2f pt(basis[i]);
|
||
|
line(drawImg, origin, origin + pt, Scalar(0, i * 255, 0), 2);
|
||
|
}
|
||
|
}
|
||
|
|
||
|
void CirclesGridFinder::drawBasisGraphs(const vector<Graph> &basisGraphs, Mat &drawImage, bool drawEdges,
|
||
|
bool drawVertices) const
|
||
|
{
|
||
|
//const int vertexRadius = 1;
|
||
|
const int vertexRadius = 3;
|
||
|
const Scalar vertexColor = Scalar(0, 0, 255);
|
||
|
const int vertexThickness = -1;
|
||
|
|
||
|
const Scalar edgeColor = Scalar(255, 0, 0);
|
||
|
//const int edgeThickness = 1;
|
||
|
const int edgeThickness = 2;
|
||
|
|
||
|
if (drawEdges)
|
||
|
{
|
||
|
for (size_t i = 0; i < basisGraphs.size(); i++)
|
||
|
{
|
||
|
for (size_t v1 = 0; v1 < basisGraphs[i].getVerticesCount(); v1++)
|
||
|
{
|
||
|
for (size_t v2 = 0; v2 < basisGraphs[i].getVerticesCount(); v2++)
|
||
|
{
|
||
|
if (basisGraphs[i].areVerticesAdjacent(v1, v2))
|
||
|
{
|
||
|
line(drawImage, keypoints[v1].pt, keypoints[v2].pt, edgeColor, edgeThickness);
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
if (drawVertices)
|
||
|
{
|
||
|
for (size_t v = 0; v < basisGraphs[0].getVerticesCount(); v++)
|
||
|
{
|
||
|
circle(drawImage, keypoints[v].pt, vertexRadius, vertexColor, vertexThickness);
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
|
||
|
void CirclesGridFinder::drawHoles(const Mat &srcImage, Mat &drawImage) const
|
||
|
{
|
||
|
//const int holeRadius = 4;
|
||
|
//const int holeRadius = 2;
|
||
|
//const int holeThickness = 1;
|
||
|
const int holeRadius = 3;
|
||
|
const int holeThickness = -1;
|
||
|
|
||
|
//const Scalar holeColor = Scalar(0, 0, 255);
|
||
|
const Scalar holeColor = Scalar(0, 255, 0);
|
||
|
|
||
|
if (srcImage.channels() == 1)
|
||
|
cvtColor(srcImage, drawImage, CV_GRAY2RGB);
|
||
|
else
|
||
|
srcImage.copyTo(drawImage);
|
||
|
|
||
|
for (size_t i = 0; i < holes.size(); i++)
|
||
|
{
|
||
|
for (size_t j = 0; j < holes[i].size(); j++)
|
||
|
{
|
||
|
if (j != holes[i].size() - 1)
|
||
|
line(drawImage, keypoints[holes[i][j]].pt, keypoints[holes[i][j + 1]].pt, Scalar(255, 0, 0), 2);
|
||
|
if (i != holes.size() - 1)
|
||
|
line(drawImage, keypoints[holes[i][j]].pt, keypoints[holes[i + 1][j]].pt, Scalar(255, 0, 0), 2);
|
||
|
|
||
|
//circle(drawImage, keypoints[holes[i][j]].pt, holeRadius, holeColor, holeThickness);
|
||
|
circle(drawImage, keypoints[holes[i][j]].pt, holeRadius, holeColor, holeThickness);
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
|
||
|
Size CirclesGridFinder::getDetectedGridSize() const
|
||
|
{
|
||
|
if (holes.size() == 0)
|
||
|
return Size(0, 0);
|
||
|
|
||
|
return Size(holes[0].size(), holes.size());
|
||
|
}
|
||
|
|
||
|
void CirclesGridFinder::getHoles(vector<Point2f> &outHoles) const
|
||
|
{
|
||
|
outHoles.clear();
|
||
|
|
||
|
for (size_t i = 0; i < holes.size(); i++)
|
||
|
{
|
||
|
for (size_t j = 0; j < holes[i].size(); j++)
|
||
|
{
|
||
|
outHoles.push_back(keypoints[holes[i][j]].pt);
|
||
|
}
|
||
|
}
|
||
|
}
|