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485 lines
14 KiB
C++
485 lines
14 KiB
C++
/* Original code has been submitted by Liu Liu.
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----------------------------------------------------------------------------------
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* Spill-Tree for Approximate KNN Search
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* Author: Liu Liu
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* mailto: liuliu.1987+opencv@gmail.com
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* Refer to Paper:
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* An Investigation of Practical Approximate Nearest Neighbor Algorithms
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* cvMergeSpillTree TBD
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*
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* Redistribution and use in source and binary forms, with or
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* without modification, are permitted provided that the following
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* conditions are met:
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* Redistributions of source code must retain the above
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* copyright notice, this list of conditions and the following
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* disclaimer.
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* Redistributions in binary form must reproduce the above
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* copyright notice, this list of conditions and the following
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* disclaimer in the documentation and/or other materials
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* provided with the distribution.
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* The name of Contributor may not be used to endorse or
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* promote products derived from this software without
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* specific prior written permission.
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*
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* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND
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* CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES,
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* INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF
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* MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
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* DISCLAIMED. IN NO EVENT SHALL THE CONTRIBUTORS BE LIABLE FOR ANY
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* DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
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* CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
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* PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA,
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* OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
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* THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR
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* TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT
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* OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY
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* OF SUCH DAMAGE.
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*/
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#include "precomp.hpp"
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#include "_featuretree.h"
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struct CvSpillTreeNode
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{
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bool leaf; // is leaf or not (leaf is the point that have no more child)
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bool spill; // is not a non-overlapping point (defeatist search)
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CvSpillTreeNode* lc; // left child (<)
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CvSpillTreeNode* rc; // right child (>)
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int cc; // child count
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CvMat* u; // projection vector
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CvMat* center; // center
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int i; // original index
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double r; // radius of remaining feature point
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double ub; // upper bound
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double lb; // lower bound
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double mp; // mean point
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double p; // projection value
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};
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struct CvSpillTree
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{
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CvSpillTreeNode* root;
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CvMat** refmat; // leaf ref matrix
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bool* cache; // visited or not
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int total; // total leaves
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int naive; // under this value, we perform naive search
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int type; // mat type
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double rho; // under this value, it is a spill tree
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double tau; // the overlapping buffer ratio
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};
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// find the farthest node in the "list" from "node"
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static inline CvSpillTreeNode*
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icvFarthestNode( CvSpillTreeNode* node,
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CvSpillTreeNode* list,
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int total )
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{
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double farthest = -1.;
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CvSpillTreeNode* result = NULL;
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for ( int i = 0; i < total; i++ )
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{
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double norm = cvNorm( node->center, list->center );
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if ( norm > farthest )
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{
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farthest = norm;
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result = list;
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}
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list = list->rc;
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}
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return result;
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}
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// clone a new tree node
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static inline CvSpillTreeNode*
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icvCloneSpillTreeNode( CvSpillTreeNode* node )
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{
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CvSpillTreeNode* result = (CvSpillTreeNode*)cvAlloc( sizeof(CvSpillTreeNode) );
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memcpy( result, node, sizeof(CvSpillTreeNode) );
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return result;
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}
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// append the link-list of a tree node
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static inline void
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icvAppendSpillTreeNode( CvSpillTreeNode* node,
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CvSpillTreeNode* append )
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{
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if ( node->lc == NULL )
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{
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node->lc = node->rc = append;
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node->lc->lc = node->rc->rc = NULL;
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} else {
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append->lc = node->rc;
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append->rc = NULL;
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node->rc->rc = append;
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node->rc = append;
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}
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node->cc++;
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}
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#define _dispatch_mat_ptr(x, step) (CV_MAT_DEPTH((x)->type) == CV_32F ? (void*)((x)->data.fl+(step)) : (CV_MAT_DEPTH((x)->type) == CV_64F ? (void*)((x)->data.db+(step)) : (void*)(0)))
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static void
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icvDFSInitSpillTreeNode( const CvSpillTree* tr,
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const int d,
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CvSpillTreeNode* node )
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{
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if ( node->cc <= tr->naive )
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{
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// already get to a leaf, terminate the recursion.
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node->leaf = true;
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node->spill = false;
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return;
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}
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// random select a node, then find a farthest node from this one, then find a farthest from that one...
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// to approximate the farthest node-pair
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static CvRNG rng_state = cvRNG(0xdeadbeef);
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int rn = cvRandInt( &rng_state ) % node->cc;
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CvSpillTreeNode* lnode = NULL;
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CvSpillTreeNode* rnode = node->lc;
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for ( int i = 0; i < rn; i++ )
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rnode = rnode->rc;
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lnode = icvFarthestNode( rnode, node->lc, node->cc );
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rnode = icvFarthestNode( lnode, node->lc, node->cc );
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// u is the projection vector
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node->u = cvCreateMat( 1, d, tr->type );
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cvSub( lnode->center, rnode->center, node->u );
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cvNormalize( node->u, node->u );
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// find the center of node in hyperspace
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node->center = cvCreateMat( 1, d, tr->type );
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cvZero( node->center );
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CvSpillTreeNode* it = node->lc;
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for ( int i = 0; i < node->cc; i++ )
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{
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cvAdd( it->center, node->center, node->center );
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it = it->rc;
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}
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cvConvertScale( node->center, node->center, 1./node->cc );
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// project every node to "u", and find the mean point "mp"
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it = node->lc;
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node->r = -1.;
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node->mp = 0;
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for ( int i = 0; i < node->cc; i++ )
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{
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node->mp += ( it->p = cvDotProduct( it->center, node->u ) );
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double norm = cvNorm( node->center, it->center );
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if ( norm > node->r )
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node->r = norm;
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it = it->rc;
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}
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node->mp = node->mp / node->cc;
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// overlapping buffer and upper bound, lower bound
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double ob = (lnode->p-rnode->p)*tr->tau*.5;
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node->ub = node->mp+ob;
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node->lb = node->mp-ob;
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int sl = 0, l = 0;
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int sr = 0, r = 0;
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it = node->lc;
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for ( int i = 0; i < node->cc; i++ )
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{
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if ( it->p <= node->ub )
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sl++;
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if ( it->p >= node->lb )
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sr++;
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if ( it->p < node->mp )
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l++;
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else
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r++;
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it = it->rc;
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}
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// precision problem, return the node as it is.
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if (( l == 0 )||( r == 0 ))
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{
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cvReleaseMat( &(node->u) );
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cvReleaseMat( &(node->center) );
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node->leaf = true;
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node->spill = false;
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return;
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}
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CvSpillTreeNode* lc = (CvSpillTreeNode*)cvAlloc( sizeof(CvSpillTreeNode) );
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memset(lc, 0, sizeof(CvSpillTreeNode));
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CvSpillTreeNode* rc = (CvSpillTreeNode*)cvAlloc( sizeof(CvSpillTreeNode) );
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memset(rc, 0, sizeof(CvSpillTreeNode));
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lc->lc = lc->rc = rc->lc = rc->rc = NULL;
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lc->cc = rc->cc = 0;
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int undo = cvRound(node->cc*tr->rho);
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if (( sl >= undo )||( sr >= undo ))
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{
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// it is not a spill point (defeatist search disabled)
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it = node->lc;
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for ( int i = 0; i < node->cc; i++ )
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{
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CvSpillTreeNode* next = it->rc;
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if ( it->p < node->mp )
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icvAppendSpillTreeNode( lc, it );
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else
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icvAppendSpillTreeNode( rc, it );
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it = next;
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}
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node->spill = false;
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} else {
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// a spill point
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it = node->lc;
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for ( int i = 0; i < node->cc; i++ )
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{
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CvSpillTreeNode* next = it->rc;
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if ( it->p < node->lb )
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icvAppendSpillTreeNode( lc, it );
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else if ( it->p > node->ub )
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icvAppendSpillTreeNode( rc, it );
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else {
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CvSpillTreeNode* cit = icvCloneSpillTreeNode( it );
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icvAppendSpillTreeNode( lc, it );
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icvAppendSpillTreeNode( rc, cit );
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}
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it = next;
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}
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node->spill = true;
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}
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node->lc = lc;
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node->rc = rc;
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// recursion process
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icvDFSInitSpillTreeNode( tr, d, node->lc );
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icvDFSInitSpillTreeNode( tr, d, node->rc );
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}
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static CvSpillTree*
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icvCreateSpillTree( const CvMat* raw_data,
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const int naive,
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const double rho,
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const double tau )
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{
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int n = raw_data->rows;
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int d = raw_data->cols;
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CvSpillTree* tr = (CvSpillTree*)cvAlloc( sizeof(CvSpillTree) );
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tr->root = (CvSpillTreeNode*)cvAlloc( sizeof(CvSpillTreeNode) );
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memset(tr->root, 0, sizeof(CvSpillTreeNode));
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tr->refmat = (CvMat**)cvAlloc( sizeof(CvMat*)*n );
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tr->cache = (bool*)cvAlloc( sizeof(bool)*n );
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tr->total = n;
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tr->naive = naive;
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tr->rho = rho;
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tr->tau = tau;
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tr->type = raw_data->type;
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// tie a link-list to the root node
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tr->root->lc = (CvSpillTreeNode*)cvAlloc( sizeof(CvSpillTreeNode) );
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memset(tr->root->lc, 0, sizeof(CvSpillTreeNode));
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tr->root->lc->center = cvCreateMatHeader( 1, d, tr->type );
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cvSetData( tr->root->lc->center, _dispatch_mat_ptr(raw_data, 0), raw_data->step );
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tr->refmat[0] = tr->root->lc->center;
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tr->root->lc->lc = NULL;
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tr->root->lc->leaf = true;
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tr->root->lc->i = 0;
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CvSpillTreeNode* node = tr->root->lc;
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for ( int i = 1; i < n; i++ )
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{
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CvSpillTreeNode* newnode = (CvSpillTreeNode*)cvAlloc( sizeof(CvSpillTreeNode) );
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memset(newnode, 0, sizeof(CvSpillTreeNode));
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newnode->center = cvCreateMatHeader( 1, d, tr->type );
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cvSetData( newnode->center, _dispatch_mat_ptr(raw_data, i*d), raw_data->step );
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tr->refmat[i] = newnode->center;
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newnode->lc = node;
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newnode->i = i;
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newnode->leaf = true;
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newnode->rc = NULL;
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node->rc = newnode;
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node = newnode;
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}
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tr->root->rc = node;
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tr->root->cc = n;
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icvDFSInitSpillTreeNode( tr, d, tr->root );
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return tr;
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}
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static void
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icvSpillTreeNodeHeapify( CvSpillTreeNode** heap,
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int i,
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const int k )
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{
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if ( heap[i] == NULL )
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return;
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int l, r, largest = i;
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CvSpillTreeNode* inp;
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do {
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i = largest;
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r = (i+1)<<1;
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l = r-1;
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if (( l < k )&&( heap[l] == NULL ))
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largest = l;
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else if (( r < k )&&( heap[r] == NULL ))
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largest = r;
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else {
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if (( l < k )&&( heap[l]->mp > heap[i]->mp ))
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largest = l;
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if (( r < k )&&( heap[r]->mp > heap[largest]->mp ))
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largest = r;
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}
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if ( largest != i )
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CV_SWAP( heap[largest], heap[i], inp );
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} while ( largest != i );
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}
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static void
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icvSpillTreeDFSearch( CvSpillTree* tr,
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CvSpillTreeNode* node,
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CvSpillTreeNode** heap,
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int* es,
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const CvMat* desc,
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const int k,
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const int emax )
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{
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if ((emax > 0)&&( *es >= emax ))
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return;
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double dist, p=0;
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while ( node->spill )
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{
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// defeatist search
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if ( !node->leaf )
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p = cvDotProduct( node->u, desc );
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if ( p < node->lb && node->lc->cc >= k ) // check the number of children larger than k otherwise you'll skip over better neighbor
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node = node->lc;
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else if ( p > node->ub && node->rc->cc >= k )
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node = node->rc;
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else
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break;
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if ( NULL == node )
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return;
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}
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if ( node->leaf )
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{
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// a leaf, naive search
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CvSpillTreeNode* it = node->lc;
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for ( int i = 0; i < node->cc; i++ )
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{
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if ( !tr->cache[it->i] )
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{
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it->mp = cvNorm( it->center, desc );
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tr->cache[it->i] = true;
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if (( heap[0] == NULL)||( it->mp < heap[0]->mp ))
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{
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heap[0] = it;
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icvSpillTreeNodeHeapify( heap, 0, k );
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(*es)++;
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}
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}
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it = it->rc;
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}
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return;
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}
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dist = cvNorm( node->center, desc );
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// impossible case, skip
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if (( heap[0] != NULL )&&( dist-node->r > heap[0]->mp ))
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return;
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p = cvDotProduct( node->u, desc );
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// guided dfs
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if ( p < node->mp )
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{
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icvSpillTreeDFSearch( tr, node->lc, heap, es, desc, k, emax );
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icvSpillTreeDFSearch( tr, node->rc, heap, es, desc, k, emax );
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} else {
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icvSpillTreeDFSearch( tr, node->rc, heap, es, desc, k, emax );
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icvSpillTreeDFSearch( tr, node->lc, heap, es, desc, k, emax );
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}
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}
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static void
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icvFindSpillTreeFeatures( CvSpillTree* tr,
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const CvMat* desc,
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CvMat* results,
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CvMat* dist,
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const int k,
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const int emax )
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{
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assert( desc->type == tr->type );
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CvSpillTreeNode** heap = (CvSpillTreeNode**)cvAlloc( k*sizeof(heap[0]) );
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for ( int j = 0; j < desc->rows; j++ )
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{
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CvMat _desc = cvMat( 1, desc->cols, desc->type, _dispatch_mat_ptr(desc, j*desc->cols) );
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for ( int i = 0; i < k; i++ )
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heap[i] = NULL;
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memset( tr->cache, 0, sizeof(bool)*tr->total );
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int es = 0;
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icvSpillTreeDFSearch( tr, tr->root, heap, &es, &_desc, k, emax );
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CvSpillTreeNode* inp;
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for ( int i = k-1; i > 0; i-- )
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{
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CV_SWAP( heap[i], heap[0], inp );
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icvSpillTreeNodeHeapify( heap, 0, i );
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}
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int* rs = results->data.i+j*results->cols;
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double* dt = dist->data.db+j*dist->cols;
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for ( int i = 0; i < k; i++, rs++, dt++ )
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if ( heap[i] != NULL )
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{
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*rs = heap[i]->i;
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*dt = heap[i]->mp;
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} else
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*rs = -1;
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}
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cvFree( &heap );
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}
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static void
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icvDFSReleaseSpillTreeNode( CvSpillTreeNode* node )
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{
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if ( node->leaf )
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{
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CvSpillTreeNode* it = node->lc;
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for ( int i = 0; i < node->cc; i++ )
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{
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CvSpillTreeNode* s = it;
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it = it->rc;
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cvFree( &s );
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}
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} else {
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cvReleaseMat( &node->u );
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cvReleaseMat( &node->center );
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icvDFSReleaseSpillTreeNode( node->lc );
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icvDFSReleaseSpillTreeNode( node->rc );
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}
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cvFree( &node );
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}
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static void
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icvReleaseSpillTree( CvSpillTree** tr )
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{
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for ( int i = 0; i < (*tr)->total; i++ )
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cvReleaseMat( &((*tr)->refmat[i]) );
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cvFree( &((*tr)->refmat) );
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cvFree( &((*tr)->cache) );
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icvDFSReleaseSpillTreeNode( (*tr)->root );
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cvFree( tr );
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}
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class CvSpillTreeWrap : public CvFeatureTree {
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CvSpillTree* tr;
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public:
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CvSpillTreeWrap(const CvMat* raw_data,
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const int naive,
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const double rho,
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const double tau) {
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tr = icvCreateSpillTree(raw_data, naive, rho, tau);
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}
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~CvSpillTreeWrap() {
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icvReleaseSpillTree(&tr);
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}
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void FindFeatures(const CvMat* desc, int k, int emax, CvMat* results, CvMat* dist) {
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icvFindSpillTreeFeatures(tr, desc, results, dist, k, emax);
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}
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};
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CvFeatureTree* cvCreateSpillTree( const CvMat* raw_data,
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const int naive,
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const double rho,
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const double tau ) {
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return new CvSpillTreeWrap(raw_data, naive, rho, tau);
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}
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