bool CvCascadeClassifier::load( const string cascadeDirName )
{
FileStorage fs( cascadeDirName + CC_PARAMS_FILENAME, FileStorage::READ );
if ( !fs.isOpened() )
return false;
FileNode node = fs.getFirstTopLevelNode();
if ( !readParams( node ) )
return false;
featureEvaluator = CvFeatureEvaluator::create(cascadeParams.featureType);
featureEvaluator->init( ((CvFeatureParams*)featureParams), numPos + numNeg, cascadeParams.winSize );
fs.release();
char buf[10];
for ( int si = 0; si < numStages; si++ )
{
sprintf( buf, "%s%d", "stage", si);
fs.open( cascadeDirName + buf + ".xml", FileStorage::READ );
node = fs.getFirstTopLevelNode();
if ( !fs.isOpened() )
break;
CvCascadeBoost *tempStage = new CvCascadeBoost;
if ( !tempStage->read( node, (CvFeatureEvaluator*)featureEvaluator, *((CvCascadeBoostParams*)stageParams )) )
{
delete tempStage;
fs.release();
break;
}
stageClassifiers.push_back(tempStage);
}
return true;
}
bool CvCascadeClassifier::readStages( const FileNode &node)
{
FileNode rnode = node[CC_STAGES];
if (!rnode.empty() || !rnode.isSeq())
return false;
stageClassifiers.reserve(numStages);
FileNodeIterator it = rnode.begin();
for( int i = 0; i < min( (int)rnode.size(), numStages ); i++, it++ )
{
CvCascadeBoost* tempStage = new CvCascadeBoost;
if ( !tempStage->read( *it, (CvFeatureEvaluator *)featureEvaluator, *((CvCascadeBoostParams*)stageParams) ) )
{
delete tempStage;
return false;
}
stageClassifiers.push_back(tempStage);
}
return true;
}
bool CvCascadeClassifier::train( const string _cascadeDirName,
const string _posFilename,
const string _negFilename,
int _numPos, int _numNeg,
int _precalcValBufSize, int _precalcIdxBufSize,
int _numStages,
const CvCascadeParams& _cascadeParams,
const CvFeatureParams& _featureParams,
const CvCascadeBoostParams& _stageParams,
bool baseFormatSave,
double acceptanceRatioBreakValue)
{
// Start recording clock ticks for training time output
const clock_t begin_time = clock();
if( _cascadeDirName.empty() || _posFilename.empty() || _negFilename.empty() )
CV_Error( CV_StsBadArg, "_cascadeDirName or _bgfileName or _vecFileName is NULL" );
string dirName;
if (_cascadeDirName.find_last_of("/\\") == (_cascadeDirName.length() - 1) )
dirName = _cascadeDirName;
else
dirName = _cascadeDirName + '/';
numPos = _numPos;
numNeg = _numNeg;
numStages = _numStages;
if ( !imgReader.create( _posFilename, _negFilename, _cascadeParams.winSize ) )
{
cout << "Image reader can not be created from -vec " << _posFilename
<< " and -bg " << _negFilename << "." << endl;
return false;
}
if ( !load( dirName ) )
{
cascadeParams = _cascadeParams;
featureParams = CvFeatureParams::create(cascadeParams.featureType);
featureParams->init(_featureParams);
stageParams = new CvCascadeBoostParams;
*stageParams = _stageParams;
featureEvaluator = CvFeatureEvaluator::create(cascadeParams.featureType);
featureEvaluator->init( (CvFeatureParams*)featureParams, numPos + numNeg, cascadeParams.winSize );
stageClassifiers.reserve( numStages );
}else{
// Make sure that if model parameters are preloaded, that people are aware of this,
// even when passing other parameters to the training command
cout << "---------------------------------------------------------------------------------" << endl;
cout << "Training parameters are pre-loaded from the parameter file in data folder!" << endl;
cout << "Please empty this folder if you want to use a NEW set of training parameters." << endl;
cout << "---------------------------------------------------------------------------------" << endl;
}
cout << "PARAMETERS:" << endl;
cout << "cascadeDirName: " << _cascadeDirName << endl;
cout << "vecFileName: " << _posFilename << endl;
cout << "bgFileName: " << _negFilename << endl;
cout << "numPos: " << _numPos << endl;
cout << "numNeg: " << _numNeg << endl;
cout << "numStages: " << numStages << endl;
cout << "precalcValBufSize[Mb] : " << _precalcValBufSize << endl;
cout << "precalcIdxBufSize[Mb] : " << _precalcIdxBufSize << endl;
cout << "acceptanceRatioBreakValue : " << acceptanceRatioBreakValue << endl;
cascadeParams.printAttrs();
stageParams->printAttrs();
featureParams->printAttrs();
cout << "Number of unique features given windowSize [" << _cascadeParams.winSize.width << "," << _cascadeParams.winSize.height << "] : " << featureEvaluator->getNumFeatures() << "" << endl;
int startNumStages = (int)stageClassifiers.size();
if ( startNumStages > 1 )
cout << endl << "Stages 0-" << startNumStages-1 << " are loaded" << endl;
else if ( startNumStages == 1)
cout << endl << "Stage 0 is loaded" << endl;
double requiredLeafFARate = pow( (double) stageParams->maxFalseAlarm, (double) numStages ) /
(double)stageParams->max_depth;
double tempLeafFARate;
for( int i = startNumStages; i < numStages; i++ )
{
cout << endl << "===== TRAINING " << i << "-stage =====" << endl;
cout << "<BEGIN" << endl;
if ( !updateTrainingSet( requiredLeafFARate, tempLeafFARate ) )
{
cout << "Train dataset for temp stage can not be filled. "
"Branch training terminated." << endl;
break;
}
if( tempLeafFARate <= requiredLeafFARate )
{
cout << "Required leaf false alarm rate achieved. "
"Branch training terminated." << endl;
break;
}
if( (tempLeafFARate <= acceptanceRatioBreakValue) && (acceptanceRatioBreakValue >= 0) ){
cout << "The required acceptanceRatio for the model has been reached to avoid overfitting of trainingdata. "
"Branch training terminated." << endl;
break;
}
CvCascadeBoost* tempStage = new CvCascadeBoost;
bool isStageTrained = tempStage->train( (CvFeatureEvaluator*)featureEvaluator,
curNumSamples, _precalcValBufSize, _precalcIdxBufSize,
*((CvCascadeBoostParams*)stageParams) );
cout << "END>" << endl;
if(!isStageTrained)
break;
stageClassifiers.push_back( tempStage );
// save params
if( i == 0)
{
std::string paramsFilename = dirName + CC_PARAMS_FILENAME;
FileStorage fs( paramsFilename, FileStorage::WRITE);
if ( !fs.isOpened() )
{
cout << "Parameters can not be written, because file " << paramsFilename
<< " can not be opened." << endl;
return false;
}
fs << FileStorage::getDefaultObjectName(paramsFilename) << "{";
writeParams( fs );
fs << "}";
}
// save current stage
char buf[10];
sprintf(buf, "%s%d", "stage", i );
string stageFilename = dirName + buf + ".xml";
FileStorage fs( stageFilename, FileStorage::WRITE );
if ( !fs.isOpened() )
{
cout << "Current stage can not be written, because file " << stageFilename
<< " can not be opened." << endl;
return false;
}
fs << FileStorage::getDefaultObjectName(stageFilename) << "{";
tempStage->write( fs, Mat() );
fs << "}";
// Output training time up till now
float seconds = float( clock () - begin_time ) / CLOCKS_PER_SEC;
int days = int(seconds) / 60 / 60 / 24;
int hours = (int(seconds) / 60 / 60) % 24;
int minutes = (int(seconds) / 60) % 60;
int seconds_left = int(seconds) % 60;
cout << "Training until now has taken " << days << " days " << hours << " hours " << minutes << " minutes " << seconds_left <<" seconds." << endl;
}
if(stageClassifiers.size() == 0)
{
cout << "Cascade classifier can't be trained. Check the used training parameters." << endl;
return false;
}
save( dirName + CC_CASCADE_FILENAME, baseFormatSave );
return true;
}
bool CvCascadeClassifier::train( const String _cascadeDirName,
const String _posFilename,
const String _negFilename,
int _numPos, int _numNeg,
int _precalcValBufSize, int _precalcIdxBufSize,
int _numStages,
const CvCascadeParams& _cascadeParams,
const CvFeatureParams& _featureParams,
const CvCascadeBoostParams& _stageParams,
bool baseFormatSave )
{
if( _cascadeDirName.empty() || _posFilename.empty() || _negFilename.empty() )
CV_Error( CV_StsBadArg, "_cascadeDirName or _bgfileName or _vecFileName is NULL" );
string dirName;
if (_cascadeDirName.find_last_of("/\\") == (_cascadeDirName.length() - 1) )
dirName = _cascadeDirName;
else
dirName = _cascadeDirName + '/';
numPos = _numPos;
numNeg = _numNeg;
numStages = _numStages;
if ( !imgReader.create( _posFilename, _negFilename, _cascadeParams.winSize ) )
{
cout << "Image reader can not be created from -vec " << _posFilename
<< " and -bg " << _negFilename << "." << endl;
return false;
}
if ( !load( dirName ) )
{
cascadeParams = _cascadeParams;
featureParams = CvFeatureParams::create(cascadeParams.featureType);
featureParams->init(_featureParams);
stageParams = new CvCascadeBoostParams;
*stageParams = _stageParams;
featureEvaluator = CvFeatureEvaluator::create(cascadeParams.featureType);
featureEvaluator->init( (CvFeatureParams*)featureParams, numPos + numNeg, cascadeParams.winSize );
stageClassifiers.reserve( numStages );
}
cout << "PARAMETERS:" << endl;
cout << "cascadeDirName: " << _cascadeDirName << endl;
cout << "vecFileName: " << _posFilename << endl;
cout << "bgFileName: " << _negFilename << endl;
cout << "numPos: " << _numPos << endl;
cout << "numNeg: " << _numNeg << endl;
cout << "numStages: " << numStages << endl;
cout << "precalcValBufSize[Mb] : " << _precalcValBufSize << endl;
cout << "precalcIdxBufSize[Mb] : " << _precalcIdxBufSize << endl;
cascadeParams.printAttrs();
stageParams->printAttrs();
featureParams->printAttrs();
int startNumStages = (int)stageClassifiers.size();
if ( startNumStages > 1 )
cout << endl << "Stages 0-" << startNumStages-1 << " are loaded" << endl;
else if ( startNumStages == 1)
cout << endl << "Stage 0 is loaded" << endl;
double requiredLeafFARate = pow( (double) stageParams->maxFalseAlarm, (double) numStages ) /
(double)stageParams->max_depth;
double tempLeafFARate;
for( int i = startNumStages; i < numStages; i++ )
{
cout << endl << "===== TRAINING " << i << "-stage =====" << endl;
cout << "<BEGIN" << endl;
if ( !updateTrainingSet( tempLeafFARate ) )
{
cout << "Train dataset for temp stage can not be filled. "
"Branch training terminated." << endl;
break;
}
if( tempLeafFARate <= requiredLeafFARate )
{
cout << "Required leaf false alarm rate achieved. "
"Branch training terminated." << endl;
break;
}
CvCascadeBoost* tempStage = new CvCascadeBoost;
bool isStageTrained = tempStage->train( (CvFeatureEvaluator*)featureEvaluator,
curNumSamples, _precalcValBufSize, _precalcIdxBufSize,
*((CvCascadeBoostParams*)stageParams) );
cout << "END>" << endl;
if(!isStageTrained)
break;
stageClassifiers.push_back( tempStage );
// save params
if( i == 0)
{
std::string paramsFilename = dirName + CC_PARAMS_FILENAME;
FileStorage fs( paramsFilename, FileStorage::WRITE);
if ( !fs.isOpened() )
{
cout << "Parameters can not be written, because file " << paramsFilename
<< " can not be opened." << endl;
return false;
}
fs << FileStorage::getDefaultObjectName(paramsFilename) << "{";
writeParams( fs );
fs << "}";
}
// save current stage
char buf[10];
sprintf(buf, "%s%d", "stage", i );
string stageFilename = dirName + buf + ".xml";
FileStorage fs( stageFilename, FileStorage::WRITE );
if ( !fs.isOpened() )
{
cout << "Current stage can not be written, because file " << stageFilename
<< " can not be opened." << endl;
return false;
}
fs << FileStorage::getDefaultObjectName(stageFilename) << "{";
tempStage->write( fs, Mat() );
fs << "}";
}
if(stageClassifiers.size() == 0)
{
cout << "Cascade classifier can't be trained. Check the used training parameters." << endl;
return false;
}
cout << "Save to " << dirName + CC_CASCADE_FILENAME <<endl;
save( dirName + CC_CASCADE_FILENAME, baseFormatSave );
return true;
}
