diff --git a/modules/tracking/src/tld_tracker.cpp b/modules/tracking/src/tld_tracker.cpp index 2508e326d..eb23e86bc 100644 --- a/modules/tracking/src/tld_tracker.cpp +++ b/modules/tracking/src/tld_tracker.cpp @@ -88,12 +88,11 @@ using namespace tld; * 11. group decls logically, order of statements * * ?10. all in one class -* todo: initializer lists; const methods +* todo: +* initializer lists; +* const methods * * ?( ) -* -* ?vadim: for{1command} can omit {}; if( a != (b + c) ) vs ( a != ( b + c ) ); if{} for{} method{} oneline:spaces, omit{}; -* 1-statement for/if without {} */ /* design decisions: @@ -178,7 +177,7 @@ public: void setBoudingBox(Rect2d boundingBox){ boundingBox_ = boundingBox; } double getOriginalVariance(){ return originalVariance_; } inline double ensembleClassifierNum(const uchar* data); - inline void prepareClassifiers(int rowstep){ for( int i = 0; i < (int)classifiers.size(); i++ ) classifiers[i].prepareClassifier(rowstep); } + inline void prepareClassifiers(int rowstep); double Sr(const Mat_& patch); double Sc(const Mat_& patch); void integrateRelabeled(Mat& img, Mat& imgBlurred, const std::vector& patches); @@ -326,7 +325,7 @@ bool TrackerTLDImpl::updateImpl(const Mat& image, Rect2d& boundingBox) for( int i = 0; i < 2; i++ ) { Rect2d tmpCandid = boundingBox; - if( ( (i == 0) && !(data->failedLastTime) && trackerProxy->update(image, tmpCandid) ) || + if( ( (i == 0) && !data->failedLastTime && trackerProxy->update(image, tmpCandid) ) || ( (i == 1) && detector->detect(imageForDetector, image_blurred, tmpCandid, detectorResults) ) ) { candidates.push_back(tmpCandid); @@ -395,7 +394,8 @@ bool TrackerTLDImpl::updateImpl(const Mat& image, Rect2d& boundingBox) if( detectorResults[i].isObject ) { expertResult = nExpert(detectorResults[i].rect); - if( expertResult != detectorResults[i].isObject ){ negRelabeled++; } + if( expertResult != detectorResults[i].isObject ) + negRelabeled++; } else { @@ -758,7 +758,7 @@ void TrackerTLDModel::integrateAdditional(const std::vector >& eForM for( int i = 0; i < (int)classifiers.size(); i++ ) p += classifiers[i].posteriorProbability(eForEnsemble[k].data, (int)eForEnsemble[k].step[0]); p /= classifiers.size(); - if( (p > ENSEMBLE_THRESHOLD) != isPositive ) + if( ( p > ENSEMBLE_THRESHOLD ) != isPositive ) { if( isPositive ) positiveIntoEnsemble++; @@ -935,5 +935,10 @@ void TrackerTLDModel::pushIntoModel(const Mat_& example, bool positive) } (*proxyN)++; } +void TrackerTLDModel::prepareClassifiers(int rowstep) +{ + for( int i = 0; i < (int)classifiers.size(); i++ ) + classifiers[i].prepareClassifier(rowstep); +} } /* namespace cv */