vendor: OpenCV 5.0.0 snapshot at 755e50675d97db9b7d449d8bd6b09888646f6c6e
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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) 2013, OpenCV Foundation, all rights reserved.
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// Third party copyrights are property of their respective owners.
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//
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// Redistribution and use in source and binary forms, with or without modification,
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// are permitted provided that the following conditions are met:
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//
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// * Redistribution's of source code must retain the above copyright notice,
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// this list of conditions and the following disclaimer.
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//
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// * Redistribution's in binary form must reproduce the above copyright notice,
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// this list of conditions and the following disclaimer in the documentation
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// and/or other materials provided with the distribution.
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//
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// * The name of the copyright holders may not be used to endorse or promote products
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// derived from this software without specific prior written permission.
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//
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// This software is provided by the copyright holders and contributors "as is" and
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// any express or implied warranties, including, but not limited to, the implied
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// warranties of merchantability and fitness for a particular purpose are disclaimed.
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// In no event shall the Intel Corporation or contributors be liable for any direct,
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// indirect, incidental, special, exemplary, or consequential damages
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// (including, but not limited to, procurement of substitute goods or services;
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// loss of use, data, or profits; or business interruption) however caused
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// and on any theory of liability, whether in contract, strict liability,
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// or tort (including negligence or otherwise) arising in any way out of
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// the use of this software, even if advised of the possibility of such damage.
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//
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//M*/
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#include "precomp.hpp"
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namespace cv {
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namespace detail {
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inline namespace tracking {
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Ptr<TrackerStateEstimator> TrackerStateEstimator::create( const String& trackeStateEstimatorType )
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{
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if( trackeStateEstimatorType.find( "SVM" ) == 0 )
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{
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return Ptr<TrackerStateEstimatorSVM>( new TrackerStateEstimatorSVM() );
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}
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if( trackeStateEstimatorType.find( "BOOSTING" ) == 0 )
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{
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CV_Error(Error::StsNotImplemented, "TrackerStateEstimatorMILBoosting API is not available");
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//return Ptr<TrackerStateEstimatorMILBoosting>( new TrackerStateEstimatorMILBoosting() );
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}
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CV_Error( cv::Error::StsError, "Tracker state estimator type not supported" );
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}
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/**
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* TrackerStateEstimatorAdaBoosting
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*/
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TrackerStateEstimatorAdaBoosting::TrackerStateEstimatorAdaBoosting( int numClassifer, int initIterations, int nFeatures, Size patchSize, const Rect& ROI )
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{
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className = "ADABOOSTING";
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numBaseClassifier = numClassifer;
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numFeatures = nFeatures;
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iterationInit = initIterations;
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initPatchSize = patchSize;
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trained = false;
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sampleROI = ROI;
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}
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Rect TrackerStateEstimatorAdaBoosting::getSampleROI() const
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{
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return sampleROI;
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}
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void TrackerStateEstimatorAdaBoosting::setSampleROI( const Rect& ROI )
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{
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sampleROI = ROI;
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}
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/**
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* TrackerAdaBoostingTargetState::TrackerAdaBoostingTargetState
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*/
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TrackerStateEstimatorAdaBoosting::TrackerAdaBoostingTargetState::TrackerAdaBoostingTargetState( const Point2f& position, int width, int height,
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bool foreground, const Mat& responses )
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{
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setTargetPosition( position );
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setTargetWidth( width );
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setTargetHeight( height );
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setTargetFg( foreground );
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setTargetResponses( responses );
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}
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void TrackerStateEstimatorAdaBoosting::TrackerAdaBoostingTargetState::setTargetFg( bool foreground )
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{
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isTarget = foreground;
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}
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bool TrackerStateEstimatorAdaBoosting::TrackerAdaBoostingTargetState::isTargetFg() const
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{
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return isTarget;
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}
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void TrackerStateEstimatorAdaBoosting::TrackerAdaBoostingTargetState::setTargetResponses( const Mat& responses )
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{
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targetResponses = responses;
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}
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Mat TrackerStateEstimatorAdaBoosting::TrackerAdaBoostingTargetState::getTargetResponses() const
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{
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return targetResponses;
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}
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TrackerStateEstimatorAdaBoosting::~TrackerStateEstimatorAdaBoosting()
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{
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}
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void TrackerStateEstimatorAdaBoosting::setCurrentConfidenceMap( ConfidenceMap& confidenceMap )
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{
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currentConfidenceMap.clear();
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currentConfidenceMap = confidenceMap;
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}
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std::vector<int> TrackerStateEstimatorAdaBoosting::computeReplacedClassifier()
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{
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return replacedClassifier;
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}
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std::vector<int> TrackerStateEstimatorAdaBoosting::computeSwappedClassifier()
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{
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return swappedClassifier;
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}
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std::vector<int> TrackerStateEstimatorAdaBoosting::computeSelectedWeakClassifier()
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{
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return boostClassifier->getSelectedWeakClassifier();
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}
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Ptr<TrackerTargetState> TrackerStateEstimatorAdaBoosting::estimateImpl( const std::vector<ConfidenceMap>& /*confidenceMaps*/ )
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{
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//run classify in order to compute next location
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if( currentConfidenceMap.empty() )
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return Ptr<TrackerTargetState>();
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std::vector<Mat> images;
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for ( size_t i = 0; i < currentConfidenceMap.size(); i++ )
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{
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Ptr<TrackerAdaBoostingTargetState> currentTargetState = currentConfidenceMap.at( i ).first.staticCast<TrackerAdaBoostingTargetState>();
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images.push_back( currentTargetState->getTargetResponses() );
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}
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int bestIndex;
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boostClassifier->classifySmooth( images, sampleROI, bestIndex );
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// get bestIndex from classifySmooth
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return currentConfidenceMap.at( bestIndex ).first;
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}
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void TrackerStateEstimatorAdaBoosting::updateImpl( std::vector<ConfidenceMap>& confidenceMaps )
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{
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if( !trained )
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{
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//this is the first time that the classifier is built
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int numWeakClassifier = numBaseClassifier * 10;
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bool useFeatureExchange = true;
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boostClassifier = Ptr<StrongClassifierDirectSelection>(
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new StrongClassifierDirectSelection( numBaseClassifier, numWeakClassifier, initPatchSize, sampleROI, useFeatureExchange, iterationInit ) );
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//init base classifiers
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boostClassifier->initBaseClassifier();
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trained = true;
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}
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ConfidenceMap lastConfidenceMap = confidenceMaps.back();
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bool featureEx = boostClassifier->getUseFeatureExchange();
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replacedClassifier.clear();
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replacedClassifier.resize( lastConfidenceMap.size(), -1 );
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swappedClassifier.clear();
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swappedClassifier.resize( lastConfidenceMap.size(), -1 );
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for ( size_t i = 0; i < lastConfidenceMap.size() / 2; i++ )
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{
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Ptr<TrackerAdaBoostingTargetState> currentTargetState = lastConfidenceMap.at( i ).first.staticCast<TrackerAdaBoostingTargetState>();
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int currentFg = 1;
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if( !currentTargetState->isTargetFg() )
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currentFg = -1;
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Mat res = currentTargetState->getTargetResponses();
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boostClassifier->update( res, currentFg );
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if( featureEx )
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{
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replacedClassifier[i] = boostClassifier->getReplacedClassifier();
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swappedClassifier[i] = boostClassifier->getSwappedClassifier();
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if( replacedClassifier[i] >= 0 && swappedClassifier[i] >= 0 )
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boostClassifier->replaceWeakClassifier( replacedClassifier[i] );
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}
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else
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{
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replacedClassifier[i] = -1;
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swappedClassifier[i] = -1;
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}
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int mapPosition = (int)(i + lastConfidenceMap.size() / 2);
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Ptr<TrackerAdaBoostingTargetState> currentTargetState2 = lastConfidenceMap.at( mapPosition ).first.staticCast<TrackerAdaBoostingTargetState>();
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currentFg = 1;
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if( !currentTargetState2->isTargetFg() )
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currentFg = -1;
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const Mat res2 = currentTargetState2->getTargetResponses();
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boostClassifier->update( res2, currentFg );
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if( featureEx )
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{
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replacedClassifier[mapPosition] = boostClassifier->getReplacedClassifier();
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swappedClassifier[mapPosition] = boostClassifier->getSwappedClassifier();
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if( replacedClassifier[mapPosition] >= 0 && swappedClassifier[mapPosition] >= 0 )
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boostClassifier->replaceWeakClassifier( replacedClassifier[mapPosition] );
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}
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else
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{
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replacedClassifier[mapPosition] = -1;
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swappedClassifier[mapPosition] = -1;
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}
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}
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}
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/**
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* TrackerStateEstimatorSVM
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*/
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TrackerStateEstimatorSVM::TrackerStateEstimatorSVM()
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{
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className = "SVM";
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}
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TrackerStateEstimatorSVM::~TrackerStateEstimatorSVM()
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{
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}
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Ptr<TrackerTargetState> TrackerStateEstimatorSVM::estimateImpl( const std::vector<ConfidenceMap>& confidenceMaps )
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{
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return confidenceMaps.back().back().first;
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}
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void TrackerStateEstimatorSVM::updateImpl( std::vector<ConfidenceMap>& /*confidenceMaps*/)
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{
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}
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}}} // namespace
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