/**
* @brief Left over from BitReduction days; removed all code except that which processed the NO bit reduction option.
* @param[in] examples_list The list of examples you want to attempt to reduce
* @param[out] compressed_examples_list The reduced list of examples
*/
void FeatureEncoder::CompressExamples (FeatureVectorListPtr srcExamples,
FeatureVectorListPtr compressedExamples,
ClassAssignments& assignments
)
{
double time_before, time_after;
time_before = osGetSystemTimeUsed ();
compressedExamples->AddQueue (*srcExamples);
time_after = osGetSystemTimeUsed ();
compressedExamples->Owner (false);
return;
} /* CompressExamples */
void AbundanceCorrectionStatsBuilder::RemoveDuplicateImages ()
{
*report << endl << endl;
FeatureVectorListPtr allExamples = new FeatureVectorList (fileDesc,
false, // 'false' = will not own contents.
log
);
allExamples->AddQueue (*trainLibData);
allExamples->AddQueue (*otherClassData);
DuplicateImages dupChecker (allExamples, log);
if (dupChecker.DuplicatesFound ())
{
*report << "DUPLICATE IMAGES DETECTED." << endl;
dupChecker.ReportDuplicates (*report);
FeatureVectorListPtr dups = dupChecker.ListOfExamplesToDelete ();
if (dups)
{
FeatureVectorList::iterator idx;
for (idx = dups->begin (); idx != dups->end (); ++idx)
{
FeatureVectorPtr fv = *idx;
trainLibData->DeleteEntry (fv);
otherClassData->DeleteEntry (fv);
}
delete dups;
dups = NULL;
}
}
else
{
*report << "No duplicates detected." << endl;
}
delete allExamples; allExamples = NULL;
*report << endl << endl;
} /* RemoveDuplicateImages */
int RandomSampleJobList::DetermineCompressedImageCount (FeatureVectorListPtr trainData,
TrainingConfigurationPtr config
)
{
FileDescPtr fileDesc = trainData->FileDesc ();
FeatureVectorListPtr srcImages = trainData->DuplicateListAndContents ();
FeatureVectorListPtr imagesToTrain = new FeatureVectorList (fileDesc, false, log, 10000);
MLClassListPtr mlClasses = srcImages->ExtractListOfClasses ();
{
MLClassList::const_iterator idx;
for (idx = mlClasses->begin (); idx != mlClasses->end (); idx++)
{
MLClassPtr mlClass = *idx;
FeatureVectorListPtr imagesThisClass = srcImages->ExtractImagesForAGivenClass (mlClass);
imagesToTrain->AddQueue (*imagesThisClass);
delete imagesThisClass;
}
}
NormalizationParms normParms (config, *imagesToTrain, log);
normParms.NormalizeImages (imagesToTrain);
ClassAssignments classAssignments (*mlClasses, log);
FeatureVectorListPtr compressedImageList = new FeatureVectorList (fileDesc, true, log, 10000);
BitReduction br (config->SVMparamREF (), fileDesc, trainData->AllFeatures ());
CompressionStats compressionStats
= br.compress (*imagesToTrain,
compressedImageList,
classAssignments
);
int compressedImageCount = compressionStats.num_images_after;
log.Level (10) << "DetermineCompressedImageCount compressedImageCount[" << compressedImageCount << "]" << endl;
delete compressedImageList; compressedImageList = NULL;
delete mlClasses; mlClasses = NULL;
delete imagesToTrain; imagesToTrain = NULL;
delete srcImages; srcImages = NULL;
return compressedImageCount;
} /* DetermineCompressedImageCount */
FeatureVectorListPtr FeatureFileIO::LoadInSubDirectoryTree
(FactoryFVProducerPtr _fvProducerFactory,
KKStr _rootDir,
MLClassList& _mlClasses,
bool _useDirectoryNameForClassName,
VolConstBool& _cancelFlag,
bool _rewiteRootFeatureFile,
RunLog& _log
)
{
_log.Level (10) << "FeatureFileIO::LoadInSubDirectoryTree rootDir[" << _rootDir << "]." << endl;
osAddLastSlash (_rootDir);
KKStr featureFileName ("");
KKStr fullFeatureFileName ("");
if (!_rootDir.Empty ())
{
featureFileName = osGetRootNameOfDirectory (_rootDir) + ".data";
fullFeatureFileName = _rootDir + featureFileName;
}
else
{
featureFileName = "Root.data";
fullFeatureFileName = "Root.data";
}
MLClassPtr unKnownClass = _mlClasses.GetUnKnownClass ();
if (_useDirectoryNameForClassName)
{
KKStr className = MLClass::GetClassNameFromDirName (_rootDir);
unKnownClass = _mlClasses.GetMLClassPtr (className);
}
bool changesMade = false;
FeatureVectorListPtr dirImages = NULL;
if (_rewiteRootFeatureFile)
{
DateTime timeStamp;
dirImages = FeatureDataReSink (_fvProducerFactory,
_rootDir,
featureFileName,
unKnownClass,
_useDirectoryNameForClassName,
_mlClasses,
_cancelFlag,
changesMade,
timeStamp,
_log
);
if (_useDirectoryNameForClassName)
{
FeatureVectorList::iterator idx;
for (idx = dirImages->begin (); idx != dirImages->end (); idx++)
{
if ((*idx)->MLClass () != unKnownClass)
{
(*idx)->MLClass (unKnownClass);
changesMade = true;
}
}
if (changesMade)
{
KKStr fullFileName = osAddSlash (_rootDir) + featureFileName;
kkuint32 numExamplesWritten = 0;
bool cancel = false;
bool successful = false;
SaveFeatureFile (fullFileName,
dirImages->AllFeatures (),
*dirImages,
numExamplesWritten,
cancel,
successful,
_log
);
}
}
}
else
{
dirImages = _fvProducerFactory->ManufacturFeatureVectorList (true);
}
// Now that we have processed all image files in "rootDir",
// lets process any sub-directories.
KKStr dirSearchPath = osAddSlash (_rootDir) + "*.*";
KKStrListPtr subDirectories = osGetListOfDirectories (dirSearchPath);
if (subDirectories)
{
KKStrList::iterator idx;
for (idx = subDirectories->begin (); (idx != subDirectories->end () && (!_cancelFlag)); idx++)
{
KKStr subDirName (**idx);
if (subDirName == "BorderImages")
{
// We ignore this director
continue;
}
KKStr newDirPath = osAddSlash (_rootDir) + subDirName;
FeatureVectorListPtr subDirExamples = LoadInSubDirectoryTree (_fvProducerFactory,
newDirPath,
_mlClasses,
_useDirectoryNameForClassName,
_cancelFlag,
true, // true = ReWriteRootFeatureFile
_log
);
osAddLastSlash (subDirName);
// We want to add the directory path to the ExampleFileName so that we can later locate the source image.
for (auto fv: *subDirExamples)
{
KKStr newImageFileName = subDirName + fv->ExampleFileName ();
fv->ExampleFileName (newImageFileName);
}
dirImages->AddQueue (*subDirExamples);
subDirExamples->Owner (false);
delete subDirExamples;
subDirExamples = NULL;
}
delete subDirectories; subDirectories = NULL;
}
_log.Level (10) << "LoadInSubDirectoryTree - Done" << endl;
return dirImages;
} /* LoadInSubDirectoryTree */
