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