bool ClassificationDataStream::addSample(const UINT classLabel,const MatrixFloat &sample){
if( numDimensions != sample.getNumCols() ){
errorLog << "addSample(const UINT classLabel, const MatrixFloat &sample) - the number of columns in the sample (" << sample.getNumCols() << ") does not match the number of dimensions of the dataset (" << numDimensions << ")" << std::endl;
return false;
}
bool searchForNewClass = true;
if( trackingClass ){
if( classLabel != lastClassID ){
//The class ID has changed so update the time series tracker
timeSeriesPositionTracker[ timeSeriesPositionTracker.size()-1 ].setEndIndex( totalNumSamples-1 );
}else searchForNewClass = false;
}
if( searchForNewClass ){
bool newClass = true;
//Search to see if this class has been found before
for(UINT k=0; k<classTracker.size(); k++){
if( classTracker[k].classLabel == classLabel ){
newClass = false;
classTracker[k].counter += sample.getNumRows();
}
}
if( newClass ){
ClassTracker newCounter(classLabel,1);
classTracker.push_back( newCounter );
}
//Set the timeSeriesPositionTracker start position
trackingClass = true;
lastClassID = classLabel;
TimeSeriesPositionTracker newTracker(totalNumSamples,0,classLabel);
timeSeriesPositionTracker.push_back( newTracker );
}
ClassificationSample labelledSample( numDimensions );
for(UINT i=0; i<sample.getNumRows(); i++){
data.push_back( labelledSample );
data.back().setClassLabel( classLabel );
for(UINT j=0; j<numDimensions; j++){
data.back()[j] = sample[i][j];
}
}
totalNumSamples += sample.getNumRows();
return true;
}
bool Registry::registerTrackerType(std::string name,
std::shared_ptr<NewTrackerFactory> f) {
if (m_typeByString.find(name) != m_typeByString.end()) {
//throw std::invalid_argument("Tracker with same name already registered");
Q_EMIT trackerIsAlreadyLoaded(name);
return false;
} else {
const TrackerType type = getNextId();
m_typeByString.emplace(name, type);
m_stringByType.emplace(type, name);
m_trackerByType.emplace(type, f);
Q_EMIT newTracker(type);
return true;
}
}
bool TimeSeriesClassificationDataStream::addSample(const UINT classLabel,const VectorDouble &sample){
if( numDimensions != sample.size() ){
errorLog << "addSample(const UINT classLabel, vector<double> sample) - the size of the new sample (" << sample.size() << ") does not match the number of dimensions of the dataset (" << numDimensions << ")" << endl;
return false;
}
bool searchForNewClass = true;
if( trackingClass ){
if( classLabel != lastClassID ){
//The class ID has changed so update the time series tracker
timeSeriesPositionTracker[ timeSeriesPositionTracker.size()-1 ].setEndIndex( totalNumSamples-1 );
}else searchForNewClass = false;
}
if( searchForNewClass ){
bool newClass = true;
//Search to see if this class has been found before
for(UINT k=0; k<classTracker.size(); k++){
if( classTracker[k].classLabel == classLabel ){
newClass = false;
classTracker[k].counter++;
}
}
if( newClass ){
ClassTracker newCounter(classLabel,1);
classTracker.push_back( newCounter );
}
//Set the timeSeriesPositionTracker start position
trackingClass = true;
lastClassID = classLabel;
TimeSeriesPositionTracker newTracker(totalNumSamples,0,classLabel);
timeSeriesPositionTracker.push_back( newTracker );
}
ClassificationSample labelledSample(classLabel,sample);
data.push_back( labelledSample );
totalNumSamples++;
return true;
}
void rgb_pcl::getTracker(std::vector<PointCloudPtr> object_clouds, Mat displayImage){
//Assign tracker to the clouds
for(unsigned int count1 = 0; count1 < trackerList.size(); count1++){
cv::Point3d position(0, 0, 0);
double maxScore = 0;
int id_cloud = -1;
cv::Point3d pos_tracker;
int size_tracker;
double hue_tracker;
for(unsigned int count2 = 0; count2 < object_clouds.size(); count2 ++){
int size = object_clouds[count2]->points.size();
cv::Point3d position(0, 0, 0);
double hue = 0;
getCloudFeatures(position, hue, object_clouds[count2]);
double score = trackerList[count1].isRecognized(position, 0, size);
if(score > maxScore){
maxScore = score;
id_cloud = count2;
pos_tracker = position;
size_tracker = size;
hue_tracker = hue;
}
}
if(id_cloud != -1){
trackerList[count1].updateTracker(pos_tracker, hue_tracker, size_tracker, object_clouds[id_cloud]);
object_clouds.erase(object_clouds.begin()+id_cloud);
}
}
// cout<<trackerList.size()<<endl;
//Create new tracker for the remaining clouds
for(auto cloudCluster: object_clouds){
int size = object_clouds[0]->points.size();
cv::Point3d position(0, 0, 0);
double hue = 0;
getCloudFeatures(position, hue, cloudCluster);
track_3d newTracker(position, hue, size);
trackerList.push_back(newTracker);
}
//Delete lost tracker and display tracked clouds
for(unsigned int count = 0; count < trackerList.size(); count ++){
trackerList[count].step();
if(!trackerList[count].isAlive()){
trackerList.erase(trackerList.begin()+count);
count --;
}else if(trackerList[count].isFound() && !trackerList[count].isGone()){
#if DISPLAY
drawTrackers(displayImage, trackerList[count], to_string(count));
#endif
}
}
}
