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vadim 10, 16, 17

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pull/55/head
Alex Leontiev 11 years ago
parent 79fa530f16
commit b6b8196261
2 changed files with 45 additions and 49 deletions
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  1. 87
      modules/tracking/src/tld_tracker.cpp
  2. 7
      modules/tracking/src/tld_utils.cpp

87
modules/tracking/src/tld_tracker.cpp
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@ -86,10 +86,8 @@ using namespace tld;
* 6. comment logical sections
* 11. group decls logically, order of statements
*
* ?10. all in one class
*
* 16. loops limits
* 17. inner scope loops
* ?10. all in one class
*/
/* design decisions:
@ -144,34 +142,6 @@ protected:
TrackerTLD::Params params_;
};
class Pexpert{
public:
Pexpert(const Mat& img,const Mat& imgBlurred,Rect2d& resultBox,const TLDDetector* detector,TrackerTLD::Params params,Size initSize):
img_(img),imgBlurred_(imgBlurred),resultBox_(resultBox),detector_(detector),params_(params),initSize_(initSize){}
bool operator()(Rect2d /*box*/){return false;}
int additionalExamples(std::vector<Mat_<uchar> >& examplesForModel,std::vector<Mat_<uchar> >& examplesForEnsemble);
protected:
Mat img_,imgBlurred_;
Rect2d resultBox_;
const TLDDetector* detector_;
TrackerTLD::Params params_;
RNG rng;
Size initSize_;
};
class Nexpert{
public:
Nexpert(const Mat& img,Rect2d& resultBox,const TLDDetector* detector,TrackerTLD::Params params):img_(img),resultBox_(resultBox),
detector_(detector),params_(params){}
bool operator()(Rect2d box);
int additionalExamples(std::vector<Mat_<uchar> >& examplesForModel,std::vector<Mat_<uchar> >& examplesForEnsemble){
examplesForModel.clear();examplesForEnsemble.clear();return 0;}
protected:
Mat img_;
Rect2d resultBox_;
const TLDDetector* detector_;
TrackerTLD::Params params_;
};
template <class T,class Tparams>
class TrackerProxyImpl : public TrackerProxy{
@ -228,6 +198,30 @@ class TrackerTLDImpl : public TrackerTLD
void write( FileStorage& fs ) const;
protected:
class Pexpert{
public:
Pexpert(const Mat& img,const Mat& imgBlurred,Rect2d& resultBox,const TLDDetector* detector,TrackerTLD::Params params,Size initSize):
img_(img),imgBlurred_(imgBlurred),resultBox_(resultBox),detector_(detector),params_(params),initSize_(initSize){}
bool operator()(Rect2d /*box*/){return false;}
int additionalExamples(std::vector<Mat_<uchar> >& examplesForModel,std::vector<Mat_<uchar> >& examplesForEnsemble);
protected:
Pexpert(){}
Mat img_,imgBlurred_;
Rect2d resultBox_;
const TLDDetector* detector_;
TrackerTLD::Params params_;
RNG rng;
Size initSize_;
};
class Nexpert : public Pexpert{
public:
Nexpert(const Mat& img,Rect2d& resultBox,const TLDDetector* detector,TrackerTLD::Params params){
img_=img; resultBox_=resultBox; detector_=detector; params_=params;}
bool operator()(Rect2d box);
int additionalExamples(std::vector<Mat_<uchar> >& examplesForModel,std::vector<Mat_<uchar> >& examplesForEnsemble){
examplesForModel.clear();examplesForEnsemble.clear();return 0;}
};
bool initImpl( const Mat& image, const Rect2d& boundingBox );
bool updateImpl( const Mat& image, Rect2d& boundingBox );
@ -309,11 +303,11 @@ bool TrackerTLDImpl::updateImpl(const Mat& image, Rect2d& boundingBox){
std::vector<TLDDetector::LabeledPatch> detectorResults;
//best overlap around 92%
Rect2d tmpCandid=boundingBox;
std::vector<Rect2d> candidates;
std::vector<double> candidatesRes;
bool trackerNeedsReInit=false;
for(int i=0;i<2;i++){
Rect2d tmpCandid=boundingBox;
if(((i==0)&&!(data->failedLastTime)&&trackerProxy->update(image,tmpCandid)) ||
((i==1)&&(detector->detect(imageForDetector,image_blurred,tmpCandid,detectorResults)))){
candidates.push_back(tmpCandid);
@ -367,11 +361,11 @@ bool TrackerTLDImpl::updateImpl(const Mat& image, Rect2d& boundingBox){
if(data->confident){
Pexpert pExpert(imageForDetector,image_blurred,boundingBox,detector,params,data->getMinSize());
Nexpert nExpert(imageForDetector,boundingBox,detector,params);
bool expertResult;
std::vector<Mat_<uchar> > examplesForModel,examplesForEnsemble;
examplesForModel.reserve(100);examplesForEnsemble.reserve(100);
int negRelabeled=0;
for(int i=0;i<(int)detectorResults.size();i++){
bool expertResult;
if(detectorResults[i].isObject){
expertResult=nExpert(detectorResults[i].rect);
if(expertResult!=detectorResults[i].isObject){negRelabeled++;}
@ -399,8 +393,7 @@ bool TrackerTLDImpl::updateImpl(const Mat& image, Rect2d& boundingBox){
}
TrackerTLDModel::TrackerTLDModel(TrackerTLD::Params params,const Mat& image, const Rect2d& boundingBox,Size minSize):minSize_(minSize),
timeStampPositiveNext(0),timeStampNegativeNext(0),params_(params){
boundingBox_=boundingBox;
timeStampPositiveNext(0),timeStampNegativeNext(0),params_(params),boundingBox_(boundingBox){
originalVariance_=variance(image(boundingBox));
std::vector<Rect2d> closest,scanGrid;
Mat scaledImg,blurredImg,image_blurred;
@ -414,10 +407,10 @@ timeStampPositiveNext(0),timeStampNegativeNext(0),params_(params){
TLDEnsembleClassifier::makeClassifiers(minSize,MEASURES_PER_CLASSIFIER,GRIDSIZE,classifiers);
positiveExamples.reserve(200);
Point2f center;
Size2f size;
for(int i=0;i<(int)closest.size();i++){
for(int j=0;j<20;j++){
Point2f center;
Size2f size;
Mat_<uchar> standardPatch(STANDARD_PATCH_SIZE,STANDARD_PATCH_SIZE);
center.x=(float)(closest[i].x+closest[i].width*(0.5+rng.uniform(-0.01,0.01)));
center.y=(float)(closest[i].y+closest[i].height*(0.5+rng.uniform(-0.01,0.01)));
@ -471,8 +464,8 @@ void TLDDetector::generateScanGrid(int rows,int cols,Size initBox,std::vector<Re
res.clear();
//scales step: SCALE_STEP; hor step: 10% of width; verstep: 10% of height; minsize: 20pix
for(double h=initBox.height, w=initBox.width;h<cols && w<rows;){
for(double x=0;(x+w)<=(cols-1.0);x+=(0.1*w)){
for(double y=0;(y+h)<=(rows-1.0);y+=(0.1*h)){
for(double x=0;(x+w+1.0)<=cols;x+=(0.1*w)){
for(double y=0;(y+h+1.0)<=rows;y+=(0.1*h)){
res.push_back(Rect2d(x,y,w,h));
}
}
@ -510,6 +503,7 @@ bool TLDDetector::detect(const Mat& img,const Mat& imgBlurred,Rect2d& res,std::v
int npos=0,nneg=0;
double tmp=0,maxSc=-5.0;
Rect2d maxScRect;
START_TICK("detector");
do{
Mat_<double> intImgP,intImgP2;
@ -560,6 +554,7 @@ bool TLDDetector::detect(const Mat& img,const Mat& imgBlurred,Rect2d& res,std::v
dfprintf((stdout,"after NCC: nneg=%d npos=%d\n",nneg,npos));
#if !0
std::vector<Rect2d> poss,negs;
for(int i=0;i<(int)patches.size();i++){
if(patches[i].isObject)
poss.push_back(patches[i].rect);
@ -612,11 +607,10 @@ double TrackerTLDModel::ensembleClassifierNum(const uchar* data){
}
double TrackerTLDModel::Sr(const Mat_<uchar>& patch){
double splus=0.0;
double splus=0.0, sminus=0.0;
for(int i=0;i<(int)positiveExamples.size();i++){
splus=std::max(splus,0.5*(NCC(positiveExamples[i],patch)+1.0));
}
double sminus=0.0;
for(int i=0;i<(int)negativeExamples.size();i++){
sminus=std::max(sminus,0.5*(NCC(negativeExamples[i],patch)+1.0));
}
@ -627,14 +621,13 @@ double TrackerTLDModel::Sr(const Mat_<uchar>& patch){
}
double TrackerTLDModel::Sc(const Mat_<uchar>& patch){
double splus=0.0;
double splus=0.0,sminus=0.0;
int med=getMedian(timeStampsPositive);
for(int i=0;i<(int)positiveExamples.size();i++){
if((int)timeStampsPositive[i]<=med){
splus=std::max(splus,0.5*(NCC(positiveExamples[i],patch)+1.0));
}
}
double sminus=0.0;
for(int i=0;i<(int)negativeExamples.size();i++){
sminus=std::max(sminus,0.5*(NCC(negativeExamples[i],patch)+1.0));
}
@ -726,7 +719,7 @@ void TrackerTLDModel::integrateAdditional(const std::vector<Mat_<uchar> >& eForM
dfprintf((stdout,"\n"));
}
int Pexpert::additionalExamples(std::vector<Mat_<uchar> >& examplesForModel,std::vector<Mat_<uchar> >& examplesForEnsemble){
int TrackerTLDImpl::Pexpert::additionalExamples(std::vector<Mat_<uchar> >& examplesForModel,std::vector<Mat_<uchar> >& examplesForEnsemble){
examplesForModel.clear();examplesForEnsemble.clear();
examplesForModel.reserve(100);examplesForEnsemble.reserve(100);
@ -737,10 +730,10 @@ int Pexpert::additionalExamples(std::vector<Mat_<uchar> >& examplesForModel,std:
TLDDetector::generateScanGrid(img_.rows,img_.cols,initSize_,scanGrid);
getClosestN(scanGrid,Rect2d(resultBox_.x/scale,resultBox_.y/scale,resultBox_.width/scale,resultBox_.height/scale),10,closest);
Point2f center;
Size2f size;
for(int i=0;i<(int)closest.size();i++){
for(int j=0;j<10;j++){
Point2f center;
Size2f size;
Mat_<uchar> standardPatch(STANDARD_PATCH_SIZE,STANDARD_PATCH_SIZE),blurredPatch(initSize_);
center.x=(float)(closest[i].x+closest[i].width*(0.5+rng.uniform(-0.01,0.01)));
center.y=(float)(closest[i].y+closest[i].height*(0.5+rng.uniform(-0.01,0.01)));
@ -767,7 +760,7 @@ int Pexpert::additionalExamples(std::vector<Mat_<uchar> >& examplesForModel,std:
return 0;
}
bool Nexpert::operator()(Rect2d box){
bool TrackerTLDImpl::Nexpert::operator()(Rect2d box){
if(overlap(resultBox_,box)<0.2){
return false;
}

7
modules/tracking/src/tld_utils.cpp
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@ -160,13 +160,16 @@ void getClosestN(std::vector<Rect2d>& scanGrid,Rect2d bBox,int n,std::vector<Rec
}
}
double o=0.0;
for(int i=n;i<(int)scanGrid.size();i++){
double o=0.0;
if((o=overlap(scanGrid[i],bBox))<=overlaps[0]){
continue;
}
int j=0;
for(j=0;j<n && overlaps[j]<o;j++);
while( j < n && overlaps[j] < o )
{
j++;
}
j--;
for(int k=0;k<j;overlaps[k]=overlaps[k+1],res[k]=res[k+1],k++);
overlaps[j]=o;res[j]=scanGrid[i];

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