void AppendDataFunctor::operator()(const TrainingData::meta_datum_t &metaDatum,
const TrainingData::integral_channels_t &integralImage)
{
if(datumIndex >= dataStore->getMaxNumExamples())
{
throw std::runtime_error("AppendDataFunctor::operator() has been called "
"more times than the data store memory allocation allows");
}
dataStore->setDatum(datumIndex, metaDatum, integralImage);
datumIndex += 1;
return;
}
AppendDataFunctor::AppendDataFunctor(TrainingData::shared_ptr dataStore_)
: datumIndex(dataStore_->getNumExamples()),
dataStore(dataStore_)
{
// nothing to do here
return;
}
void calcMinMaxFeatureResponses(TrainingData::shared_ptr trainData, MinOrMaxFeaturesResponsesSharedPointer minvs,
MinOrMaxFeaturesResponsesSharedPointer maxvs){
const FeaturesResponses &featuresResponses = trainData->getFeatureResponses();
for (size_t featureIndex = 0; featureIndex < trainData->getFeaturesPoolSize(); ++featureIndex)
{
if (trainData->_validFeatures[featureIndex] == false)
continue;
int minv = std::numeric_limits<int>::max();
int maxv = -std::numeric_limits<int>::max();
for (size_t exampleIndex = 0; exampleIndex < trainData->getNumExamples(); ++exampleIndex)
{
const int val = featuresResponses[featureIndex][exampleIndex];
minv = std::min(val, minv);
maxv = std::max(val, maxv);
} // end of "for each example"
(*maxvs)[featureIndex] = maxv;
(*minvs)[featureIndex] = minv;
} // end of "for each feature"
}