// input: one imgPtr (float32)
// returns an IntegralImage< IntegralImagePixelType = float > image
DLL_EXPORT
void computeIntegralImage( IntegralImagePixelType *rawImgPtr,
int width, int height, int depth,
IntegralImagePixelType *integralImagePtr)
{
Matrix3D<IntegralImagePixelType> integralMatrix;
integralMatrix.fromSharedData( integralImagePtr, width, height, depth );
Matrix3D<IntegralImagePixelType> rawImageMatrix;
rawImageMatrix.fromSharedData( rawImgPtr, width, height, depth );
IntegralImage<IntegralImagePixelType>::staticCompute( integralMatrix, rawImageMatrix );
}
// Prediction
// Accepts a single integral image/channel, thus only to be used for testing
// Assumes that predPtr is already allocated, of same size as imgPtr
DLL_EXPORT
void predictWithChannel( void *modelPtr, ImagePixelType *imgPtr,
IntegralImagePixelType *chImgPtr,
int width, int height, int depth,
PredictionPixelType *predPtr )
{
Matrix3D<PredictionPixelType> predMatrix;
predMatrix.fromSharedData( predPtr, width, height, depth );
// create roi for image, no GT available
ROIData roi;
roi.init( imgPtr, 0, 0, 0, width, height, depth );
// get the precomputed integral images
ROIData::IntegralImageType ii;
ii.fromSharedData(chImgPtr, width, height, depth);
roi.addII( ii.internalImage().data() );
MultipleROIData allROIs;
allROIs.add( shared_ptr_nodelete(ROIData, &roi) );
Booster adaboost;
adaboost.setModel( *((BoosterModel *) modelPtr) );
adaboost.predict<false>( allROIs, &predMatrix );
}
// Prediction for a single ROI
// Accepts an arbitrary number of integral images/channels.
// Assumes that predPtr is already allocated, of same size as imgPtr
// Returns 0 if ok
DLL_EXPORT
int predictWithChannels( void *modelPtr, ImagePixelType *imgPtr,
void *eigVecImgPtr,
int width, int height, int depth,
IntegralImagePixelType **chImgPtr,
int numChannels, double zAnisotropyFactor,
int useEarlyStopping,
int useROI, int x1, int y1, int z1, int x2, int y2, int z2, // used only if useROI != 0
PredictionPixelType *predPtr )
{
Matrix3D<PredictionPixelType> predMatrix;
predMatrix.fromSharedData( predPtr, width, height, depth );
// create roi for image, no GT available
ROIData roi;
roi.init( imgPtr, 0, 0, 0, width, height, depth, zAnisotropyFactor, 0.0, (const ROIData::RotationMatrixType *) eigVecImgPtr );
std::unique_ptr<ROIData::IntegralImageType[]> ii(new ROIData::IntegralImageType[numChannels]); // TODO: remove
for (int ch=0; ch < numChannels; ch++)
{
ii[ch].fromSharedData(chImgPtr[ch], width, height, depth);
roi.addII( ii[ch].internalImage().data() );
}
MultipleROIData allROIs;
allROIs.add( shared_ptr_nodelete(ROIData, &roi) );
try
{
Booster adaboost;
adaboost.setModel( *((BoosterModel *) modelPtr) );
if(useEarlyStopping != 0)
{
if (useROI)
{
ROICoordinates subROI;
subROI.x1 = x1; subROI.y1 = y1; subROI.z1 = z1;
subROI.x2 = x2; subROI.y2 = y2; subROI.z2 = z2;
adaboost.predictWithFeatureOrdering<true>( allROIs, &predMatrix, 0, IIBOOST_NUM_THREADS, &subROI );
}
else
adaboost.predictWithFeatureOrdering<true>( allROIs, &predMatrix );
}
else
adaboost.predictWithFeatureOrdering<false>( allROIs, &predMatrix );
}
catch( std::exception &e )
{
printf("Error in prediction: %s\n", e.what());
return -1;
}
return 0;
}
/*** Eigenvectors of Image wrappers ****/
DLL_EXPORT
void *computeEigenVectorsOfHessianImage( ImagePixelType *imgPtr,
int width, int height, int depth,
double zAnisotropyFactor,
double sigma )
{
Matrix3D<ImagePixelType> rawImg;
rawImg.fromSharedData( imgPtr, width, height, depth );
// compute eigen stuff
ROIData::ItkEigenVectorImageType::Pointer rotImg =
AllEigenVectorsOfHessian::allEigenVectorsOfHessian<ImagePixelType>(
sigma, zAnisotropyFactor, rawImg.asItkImage(),
AllEigenVectorsOfHessian::EByMagnitude );
rotImg->GetPixelContainer()->SetContainerManageMemory(false);
return rotImg->GetPixelContainer()->GetImportPointer();
}
