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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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#ifndef CIRCLESGRID_HPP_
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#define CIRCLESGRID_HPP_
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#include <fstream>
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#include <set>
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#include "precomp.hpp"
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class Graph
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{
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public:
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typedef std::set<int> Neighbors;
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struct Vertex
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{
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Neighbors neighbors;
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};
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typedef std::map<int, Vertex> Vertices;
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Graph( int n);
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bool doesVertexExist( int id ) const;
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void addVertex( int id );
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void addEdge( int id1, int id2 );
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bool areVerticesAdjacent( int id1, int id2 ) const;
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size_t getVerticesCount() const;
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size_t getDegree( int id ) const;
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void floydWarshall(cv::Mat &distanceMatrix, int infinity = -1) const;
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private:
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Vertices vertices;
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};
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struct Path
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{
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int firstVertex;
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int lastVertex;
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int length;
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std::vector<int> vertices;
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Path(int first = -1, int last = -1, int len = -1)
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{
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firstVertex = first;
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lastVertex = last;
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length = len;
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}
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};
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struct CirclesGridFinderParameters
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{
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CirclesGridFinderParameters();
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cv::Size2f densityNeighborhoodSize;
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float minDensity;
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int kmeansAttempts;
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int minDistanceToAddKeypoint;
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int keypointScale;
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float minGraphConfidence;
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float vertexGain;
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float vertexPenalty;
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float existingVertexGain;
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float edgeGain;
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float edgePenalty;
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float convexHullFactor;
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};
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class CirclesGridFinder
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{
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public:
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CirclesGridFinder(cv::Size patternSize, const std::vector<cv::Point2f> &testKeypoints,
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const CirclesGridFinderParameters ¶meters = CirclesGridFinderParameters());
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bool findHoles();
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static cv::Mat rectifyGrid(cv::Size detectedGridSize, const std::vector<cv::Point2f>& centers,
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const std::vector<cv::Point2f> &keypoint, std::vector<cv::Point2f> &warpedKeypoints);
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void getHoles(std::vector<cv::Point2f> &holes) const;
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cv::Size getDetectedGridSize() const;
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void drawBasis(const std::vector<cv::Point2f> &basis, cv::Point2f origin, cv::Mat &drawImg) const;
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void drawBasisGraphs(const std::vector<Graph> &basisGraphs, cv::Mat &drawImg, bool drawEdges = true, bool drawVertices =
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true) const;
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void drawHoles(const cv::Mat &srcImage, cv::Mat &drawImage) const;
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private:
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void computeEdgeVectorsOfRNG(std::vector<cv::Point2f> &vectors, cv::Mat *drawImage = 0) const;
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void filterOutliersByDensity(const std::vector<cv::Point2f> &samples, std::vector<cv::Point2f> &filteredSamples);
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void findBasis(const std::vector<cv::Point2f> &samples, std::vector<cv::Point2f> &basis, std::vector<Graph> &basisGraphs);
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void findMCS(const std::vector<cv::Point2f> &basis, std::vector<Graph> &basisGraphs);
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size_t findLongestPath(std::vector<Graph> &basisGraphs, Path &bestPath);
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float computeGraphConfidence(const std::vector<Graph> &basisGraphs, bool addRow, const std::vector<int> &points, const std::vector<
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int> &seeds);
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void addHolesByGraph(const std::vector<Graph> &basisGraphs, bool addRow, cv::Point2f basisVec);
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int findNearestKeypoint(cv::Point2f pt) const;
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void addPoint(cv::Point2f pt, std::vector<int> &points);
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void findCandidateLine(std::vector<int> &line, int seedLineIdx, bool addRow, cv::Point2f basisVec, std::vector<int> &seeds);
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void findCandidateHoles(std::vector<int> &above, std::vector<int> &below, bool addRow, cv::Point2f basisVec,
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std::vector<int> &aboveSeeds, std::vector<int> &belowSeeds);
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static bool areCentersNew( const std::vector<int> &newCenters, const std::vector<std::vector<int> > &holes );
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bool isDetectionCorrect();
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static void insertWinner(float aboveConfidence, float belowConfidence, float minConfidence,
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bool addRow,
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const std::vector<int> &above, const std::vector<int> &below, std::vector<std::vector<int> > &holes);
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static bool areVerticesAdjacent(const Graph &graph, int vertex1, int vertex2);
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std::vector<cv::Point2f> keypoints;
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std::vector<std::vector<int> > holes;
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const cv::Size patternSize;
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CirclesGridFinderParameters parameters;
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};
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#endif /* CIRCLESGRID_HPP_ */
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