396 lines
12 KiB
C++
396 lines
12 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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// Intel License Agreement
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// For Open Source Computer Vision Library
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//
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// Copyright (C) 2000, Intel Corporation, 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 Intel Corporation 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 OPENCV_IMGPROC_DETAIL_GCGRAPH_HPP
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#define OPENCV_IMGPROC_DETAIL_GCGRAPH_HPP
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//! @cond IGNORED
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namespace cv { namespace detail {
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template <class TWeight> class GCGraph
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{
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public:
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GCGraph();
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GCGraph( unsigned int vtxCount, unsigned int edgeCount );
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~GCGraph();
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void create( unsigned int vtxCount, unsigned int edgeCount );
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int addVtx();
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void addEdges( int i, int j, TWeight w, TWeight revw );
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void addTermWeights( int i, TWeight sourceW, TWeight sinkW );
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TWeight maxFlow();
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bool inSourceSegment( int i );
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private:
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class Vtx
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{
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public:
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Vtx *next; // initialized and used in maxFlow() only
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int parent;
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int first;
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int ts;
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int dist;
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TWeight weight;
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uchar t;
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};
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class Edge
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{
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public:
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int dst;
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int next;
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TWeight weight;
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};
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std::vector<Vtx> vtcs;
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std::vector<Edge> edges;
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TWeight flow;
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};
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template <class TWeight>
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GCGraph<TWeight>::GCGraph()
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{
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flow = 0;
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}
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template <class TWeight>
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GCGraph<TWeight>::GCGraph( unsigned int vtxCount, unsigned int edgeCount )
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{
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create( vtxCount, edgeCount );
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}
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template <class TWeight>
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GCGraph<TWeight>::~GCGraph()
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{
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}
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template <class TWeight>
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void GCGraph<TWeight>::create( unsigned int vtxCount, unsigned int edgeCount )
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{
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vtcs.reserve( vtxCount );
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edges.reserve( edgeCount + 2 );
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flow = 0;
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}
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template <class TWeight>
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int GCGraph<TWeight>::addVtx()
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{
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Vtx v;
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memset( &v, 0, sizeof(Vtx));
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vtcs.push_back(v);
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return (int)vtcs.size() - 1;
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}
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template <class TWeight>
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void GCGraph<TWeight>::addEdges( int i, int j, TWeight w, TWeight revw )
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{
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CV_Assert( i>=0 && i<(int)vtcs.size() );
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CV_Assert( j>=0 && j<(int)vtcs.size() );
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CV_Assert( w>=0 && revw>=0 );
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CV_Assert( i != j );
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if( !edges.size() )
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edges.resize( 2 );
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Edge fromI, toI;
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fromI.dst = j;
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fromI.next = vtcs[i].first;
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fromI.weight = w;
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vtcs[i].first = (int)edges.size();
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edges.push_back( fromI );
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toI.dst = i;
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toI.next = vtcs[j].first;
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toI.weight = revw;
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vtcs[j].first = (int)edges.size();
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edges.push_back( toI );
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}
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template <class TWeight>
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void GCGraph<TWeight>::addTermWeights( int i, TWeight sourceW, TWeight sinkW )
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{
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CV_Assert( i>=0 && i<(int)vtcs.size() );
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TWeight dw = vtcs[i].weight;
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if( dw > 0 )
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sourceW += dw;
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else
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sinkW -= dw;
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flow += (sourceW < sinkW) ? sourceW : sinkW;
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vtcs[i].weight = sourceW - sinkW;
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}
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template <class TWeight>
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TWeight GCGraph<TWeight>::maxFlow()
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{
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CV_Assert(!vtcs.empty());
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CV_Assert(!edges.empty());
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const int TERMINAL = -1, ORPHAN = -2;
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Vtx stub, *nilNode = &stub, *first = nilNode, *last = nilNode;
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int curr_ts = 0;
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stub.next = nilNode;
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Vtx *vtxPtr = &vtcs[0];
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Edge *edgePtr = &edges[0];
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std::vector<Vtx*> orphans;
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// initialize the active queue and the graph vertices
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for( int i = 0; i < (int)vtcs.size(); i++ )
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{
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Vtx* v = vtxPtr + i;
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v->ts = 0;
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if( v->weight != 0 )
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{
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last = last->next = v;
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v->dist = 1;
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v->parent = TERMINAL;
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v->t = v->weight < 0;
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}
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else
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v->parent = 0;
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}
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first = first->next;
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last->next = nilNode;
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nilNode->next = 0;
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// run the search-path -> augment-graph -> restore-trees loop
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for(;;)
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{
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Vtx* v, *u;
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int e0 = -1, ei = 0, ej = 0;
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TWeight minWeight, weight;
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uchar vt;
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// grow S & T search trees, find an edge connecting them
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while( first != nilNode )
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{
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v = first;
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if( v->parent )
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{
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vt = v->t;
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for( ei = v->first; ei != 0; ei = edgePtr[ei].next )
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{
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if( edgePtr[ei^vt].weight == 0 )
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continue;
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u = vtxPtr+edgePtr[ei].dst;
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if( !u->parent )
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{
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u->t = vt;
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u->parent = ei ^ 1;
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u->ts = v->ts;
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u->dist = v->dist + 1;
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if( !u->next )
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{
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u->next = nilNode;
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last = last->next = u;
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}
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continue;
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}
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if( u->t != vt )
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{
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e0 = ei ^ vt;
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break;
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}
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if( u->dist > v->dist+1 && u->ts <= v->ts )
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{
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// reassign the parent
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u->parent = ei ^ 1;
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u->ts = v->ts;
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u->dist = v->dist + 1;
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}
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}
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if( e0 > 0 )
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break;
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}
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// exclude the vertex from the active list
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first = first->next;
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v->next = 0;
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}
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if( e0 <= 0 )
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break;
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// find the minimum edge weight along the path
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minWeight = edgePtr[e0].weight;
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CV_Assert( minWeight > 0 );
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// k = 1: source tree, k = 0: destination tree
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for( int k = 1; k >= 0; k-- )
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{
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for( v = vtxPtr+edgePtr[e0^k].dst;; v = vtxPtr+edgePtr[ei].dst )
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{
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if( (ei = v->parent) < 0 )
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break;
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weight = edgePtr[ei^k].weight;
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minWeight = MIN(minWeight, weight);
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CV_Assert( minWeight > 0 );
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}
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weight = fabs(v->weight);
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minWeight = MIN(minWeight, weight);
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CV_Assert( minWeight > 0 );
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}
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// modify weights of the edges along the path and collect orphans
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edgePtr[e0].weight -= minWeight;
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edgePtr[e0^1].weight += minWeight;
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flow += minWeight;
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// k = 1: source tree, k = 0: destination tree
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for( int k = 1; k >= 0; k-- )
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{
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for( v = vtxPtr+edgePtr[e0^k].dst;; v = vtxPtr+edgePtr[ei].dst )
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{
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if( (ei = v->parent) < 0 )
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break;
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edgePtr[ei^(k^1)].weight += minWeight;
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if( (edgePtr[ei^k].weight -= minWeight) == 0 )
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{
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orphans.push_back(v);
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v->parent = ORPHAN;
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}
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}
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v->weight = v->weight + minWeight*(1-k*2);
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if( v->weight == 0 )
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{
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orphans.push_back(v);
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v->parent = ORPHAN;
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}
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}
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// restore the search trees by finding new parents for the orphans
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curr_ts++;
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while( !orphans.empty() )
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{
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Vtx* v2 = orphans.back();
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orphans.pop_back();
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int d, minDist = INT_MAX;
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e0 = 0;
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vt = v2->t;
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for( ei = v2->first; ei != 0; ei = edgePtr[ei].next )
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{
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if( edgePtr[ei^(vt^1)].weight == 0 )
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continue;
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u = vtxPtr+edgePtr[ei].dst;
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if( u->t != vt || u->parent == 0 )
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continue;
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// compute the distance to the tree root
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for( d = 0;; )
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{
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if( u->ts == curr_ts )
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{
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d += u->dist;
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break;
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}
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ej = u->parent;
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d++;
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if( ej < 0 )
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{
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if( ej == ORPHAN )
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d = INT_MAX-1;
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else
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{
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u->ts = curr_ts;
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u->dist = 1;
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}
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break;
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}
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u = vtxPtr+edgePtr[ej].dst;
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}
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// update the distance
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if( ++d < INT_MAX )
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{
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if( d < minDist )
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{
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minDist = d;
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e0 = ei;
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}
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for( u = vtxPtr+edgePtr[ei].dst; u->ts != curr_ts; u = vtxPtr+edgePtr[u->parent].dst )
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{
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u->ts = curr_ts;
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u->dist = --d;
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}
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}
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}
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if( (v2->parent = e0) > 0 )
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{
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v2->ts = curr_ts;
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v2->dist = minDist;
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continue;
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}
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/* no parent is found */
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v2->ts = 0;
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for( ei = v2->first; ei != 0; ei = edgePtr[ei].next )
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{
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u = vtxPtr+edgePtr[ei].dst;
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ej = u->parent;
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if( u->t != vt || !ej )
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continue;
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if( edgePtr[ei^(vt^1)].weight && !u->next )
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{
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u->next = nilNode;
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last = last->next = u;
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}
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if( ej > 0 && vtxPtr+edgePtr[ej].dst == v2 )
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{
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orphans.push_back(u);
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u->parent = ORPHAN;
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}
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}
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}
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}
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return flow;
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}
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template <class TWeight>
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bool GCGraph<TWeight>::inSourceSegment( int i )
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{
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CV_Assert( i>=0 && i<(int)vtcs.size() );
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return vtcs[i].t == 0;
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}
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}} // namespace detail, cv
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//! @endcond
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#endif // OPENCV_IMGPROC_DETAIL_GCGRAPH_HPP
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