Java ViewRegistrations.getViewRegistration方法代码示例

import mpicbg.spim.data.registration.ViewRegistrations; //导入方法依赖的package包/类
public static void setModelToCalibration( final SpimData spimData, final ViewId viewId, final double minResolution )
{
	setModelToIdentity( spimData, viewId );
	
	final ViewRegistrations viewRegistrations = spimData.getViewRegistrations();
	final ViewRegistration r = viewRegistrations.getViewRegistration( viewId );
	
	final ViewDescription viewDescription = spimData.getSequenceDescription().getViewDescription( 
			viewId.getTimePointId(), viewId.getViewSetupId() );

	VoxelDimensions voxelSize = ViewSetupUtils.getVoxelSizeOrLoad( viewDescription.getViewSetup(), viewDescription.getTimePoint(), spimData.getSequenceDescription().getImgLoader() );
	final double calX = voxelSize.dimension( 0 ) / minResolution;
	final double calY = voxelSize.dimension( 1 ) / minResolution;
	final double calZ = voxelSize.dimension( 2 ) / minResolution;
	
	final AffineTransform3D m = new AffineTransform3D();
	m.set( calX, 0.0f, 0.0f, 0.0f, 
		   0.0f, calY, 0.0f, 0.0f,
		   0.0f, 0.0f, calZ, 0.0f );
	final ViewTransform vt = new ViewTransformAffine( "calibration", m );
	r.preconcatenateTransform( vt );
}
 

import mpicbg.spim.data.registration.ViewRegistrations; //导入方法依赖的package包/类
protected Pair< Integer, Integer > numReorientated()
{
	final ViewRegistrations vrs = spimData.getViewRegistrations();

	int isReorientated = 0;
	int sumViews = 0;

	for ( final ViewId viewId : viewIdsToProcess )
	{
		final ViewDescription vd = spimData.getSequenceDescription().getViewDescription( viewId );
		
		if ( !vd.isPresent() )
			continue;

		final ViewRegistration vr = vrs.getViewRegistration( viewId );
		final ViewTransform vt = vr.getTransformList().get( 0 );

		++sumViews;

		if ( vt.hasName() && vt.getName().startsWith( reorientationDescription ) )
				++isReorientated;
	}

	return new ValuePair< Integer, Integer >( isReorientated, sumViews );
}
 

import mpicbg.spim.data.registration.ViewRegistrations; //导入方法依赖的package包/类
public static void preConcatenateTransform( final SpimData spimData, final ViewId viewId, final AffineTransform3D model, final String name )
{
	final ViewRegistrations viewRegistrations = spimData.getViewRegistrations();

	// update the view registration
	final ViewRegistration vr = viewRegistrations.getViewRegistration( viewId );
	final ViewTransform vt = new ViewTransformAffine( name, model );
	vr.preconcatenateTransform( vt );
}
 

import mpicbg.spim.data.registration.ViewRegistrations; //导入方法依赖的package包/类
public static HashMap< String, Integer > assembleRegistrationNames( final SpimData data, final List< ViewId > viewIds )
{
	final ViewRegistrations vr = data.getViewRegistrations();
	final SequenceDescription sd = data.getSequenceDescription();

	final HashMap< String, Integer > names = new HashMap< String, Integer >();

	for ( final ViewId viewId: viewIds )
	{
		final ViewDescription vd = sd.getViewDescription( viewId );

		if ( !vd.isPresent() )
			continue;

		final ViewRegistration r = vr.getViewRegistration( vd );
		final String rName = r.getTransformList().get( 0 ).getName();

		if ( rName != null )
		{
			if ( names.containsKey( rName ) )
				names.put( rName, names.get( rName ) + 1 );
			else
				names.put( rName, 1 );
		}
	}

	return names;
}
 

import mpicbg.spim.data.registration.ViewRegistrations; //导入方法依赖的package包/类
public static < T extends RealType< T > > Pair<Pair< AffineGet, Double >, RealInterval> computeStitching(
		final Group<? extends ViewId> viewIdsA,
		final Group<? extends ViewId> viewIdsB,
		final ViewRegistrations vrs,
		final PairwiseStitchingParameters params,
		final AbstractSequenceDescription< ?,? extends BasicViewDescription<?>, ? > sd,
		final GroupedViewAggregator gva,
		final long[] downsampleFactors,
		final ExecutorService service )
{
	
	// the transformation that maps the downsampled image coordinates back to the original input(!) image space
	final AffineTransform3D dsCorrectionT1 = new AffineTransform3D();
	final AffineTransform3D dsCorrectionT2 = new AffineTransform3D();

	// get Overlap Bounding Box
	final List<List<ViewId>> views = new ArrayList<>();
	views.add( new ArrayList<>(viewIdsA.getViews()) );
	views.add( new ArrayList<>(viewIdsB.getViews()) );
	BoundingBoxMaximalGroupOverlap< ViewId > bbDet = new BoundingBoxMaximalGroupOverlap<ViewId>( views, sd, vrs );
	BoundingBox bbOverlap = bbDet.estimate( "Max Overlap" );

	// this should be caught outside of this method already, but check nonetheless
	if (bbOverlap == null)
		return null;

	// get one image per group
	final RandomAccessibleInterval<T> img1 = gva.aggregate( viewIdsA, sd, downsampleFactors, dsCorrectionT1 );	
	final RandomAccessibleInterval<T> img2 = gva.aggregate( viewIdsB, sd, downsampleFactors, dsCorrectionT2 );

	if (img1 == null || img2 == null)
	{
		IOFunctions.println( "WARNING: Tried to open missing View when computing Stitching for " + viewIdsA + " and " + 
					viewIdsB + ". No link between those could be determined");
		return null;
	}

	// get translations
	// TODO: is the 2d check here meaningful?
	// everything will probably be 3d at this point, since ImgLoaders return 3d images
	boolean is2d = img1.numDimensions() == 2;
	Pair< AffineGet, TranslationGet > t1 = TransformTools.getInitialTransforms( vrs.getViewRegistration(viewIdsA.iterator().next()), is2d, dsCorrectionT1 );
	Pair< AffineGet, TranslationGet > t2 = TransformTools.getInitialTransforms( vrs.getViewRegistration(viewIdsB.iterator().next()), is2d, dsCorrectionT2 );

	final Pair< Translation, Double > result  = PairwiseStitching.getShift( img1, img2, t1.getB(), t2.getB(), params, service );

	if (result == null)
		return null;
	
	for (int i = 0; i< result.getA().numDimensions(); ++i)			
		result.getA().set( result.getA().get(i, result.getA().numDimensions()) * downsampleFactors[i], i ); 

	// TODO (?): Different translational part of downsample Transformations should be considered via TransformTools.getInitialTransforms
	// we probalbly do not have to correct for them ?

	// NB: as we will deal in global coordinates, not pixel coordinates in global optimization,
	// calculate global R' = VT^-1 * R * VT from pixel transformation R 
	ViewRegistration vrOld = vrs.getViewRegistration(viewIdsB.iterator().next());
	AffineTransform3D resTransform = new AffineTransform3D();
	resTransform.set( result.getA().getRowPackedCopy() );
	resTransform.concatenate( vrOld.getModel().inverse() );
	resTransform.preConcatenate( vrOld.getModel() );

	System.out.println("shift (pixel coordinates): " + Util.printCoordinates(result.getA().getTranslationCopy()));
	System.out.println("shift (global coordinates): " + Util.printCoordinates(resTransform.getRowPackedCopy()));
	System.out.print("cross-corr: " + result.getB());

	return new ValuePair<>( new ValuePair<>( resTransform, result.getB() ), bbOverlap );
}
 

import mpicbg.spim.data.registration.ViewRegistrations; //导入方法依赖的package包/类
public static < T extends RealType< T > > Pair<Pair< AffineGet, Double >, RealInterval> computeStitchingLucasKanade(
		final Group<? extends ViewId> viewIdsA,
		final Group<? extends ViewId> viewIdsB,
		final ViewRegistrations vrs,
		final LucasKanadeParameters params,
		final AbstractSequenceDescription< ?,? extends BasicViewDescription<?>, ? > sd,
		final GroupedViewAggregator gva,
		final long[] downsampleFactors,
		final ExecutorService service )
{
	
	// the transformation that maps the downsampled image coordinates back to the original input(!) image space
	final AffineTransform3D dsCorrectionT1 = new AffineTransform3D();
	final AffineTransform3D dsCorrectionT2 = new AffineTransform3D();

	// get Overlap Bounding Box
	final List<List<ViewId>> views = new ArrayList<>();
	views.add( new ArrayList<>(viewIdsA.getViews()) );
	views.add( new ArrayList<>(viewIdsB.getViews()) );
	BoundingBoxMaximalGroupOverlap< ViewId > bbDet = new BoundingBoxMaximalGroupOverlap<ViewId>( views, sd, vrs );
	BoundingBox bbOverlap = bbDet.estimate( "Max Overlap" );

	// this should be caught outside of this method already, but check nonetheless
	if (bbOverlap == null)
		return null;

	// get one image per group
	final RandomAccessibleInterval<T> img1 = gva.aggregate( viewIdsA, sd, downsampleFactors, dsCorrectionT1 );	
	final RandomAccessibleInterval<T> img2 = gva.aggregate( viewIdsB, sd, downsampleFactors, dsCorrectionT2 );

	if (img1 == null || img2 == null)
	{
		IOFunctions.println( "WARNING: Tried to open missing View when computing Stitching for " + viewIdsA + " and " + 
					viewIdsB + ". No link between those could be determined");
		return null;
	}

	// get translations
	// TODO: is the 2d check here meaningful?
	boolean is2d = img1.numDimensions() == 2;
	Pair< AffineGet, TranslationGet > t1 = TransformTools.getInitialTransforms( vrs.getViewRegistration(viewIdsA.iterator().next()), is2d, dsCorrectionT1 );
	Pair< AffineGet, TranslationGet > t2 = TransformTools.getInitialTransforms( vrs.getViewRegistration(viewIdsB.iterator().next()), is2d, dsCorrectionT2 );

	final Pair< AffineTransform, Double > result  = PairwiseStitching.getShiftLucasKanade(  img1, img2, t1.getB(), t2.getB(), params, service );

	if (result == null)
		return null;

	// TODO: is scaling just the translational part okay here?
	for (int i = 0; i< result.getA().numDimensions(); ++i)			
		result.getA().set( result.getA().get(i, result.getA().numDimensions()) * downsampleFactors[i], i, result.getA().numDimensions() ); 

	// TODO (?): Different translational part of downsample Transformations should be considered via TransformTools.getInitialTransforms
	// we probalbly do not have to correct for them ?

	// NB: as we will deal in global coordinates, not pixel coordinates in global optimization,
	// calculate global R' = VT^-1 * R * VT from pixel transformation R 
	ViewRegistration vrOld = vrs.getViewRegistration(viewIdsB.iterator().next());
	AffineTransform3D resTransform = new AffineTransform3D();
	resTransform.set( result.getA().getRowPackedCopy() );
	resTransform.concatenate( vrOld.getModel().inverse() );
	resTransform.preConcatenate( vrOld.getModel() );

	IOFunctions.println("resulting transformation (pixel coordinates): " + Util.printCoordinates(result.getA().getRowPackedCopy()));
	IOFunctions.println("resulting transformation (global coordinates): " + Util.printCoordinates(resTransform.getRowPackedCopy()));

	return new ValuePair<>( new ValuePair<>( resTransform, result.getB() ), bbOverlap );
}
 

import mpicbg.spim.data.registration.ViewRegistrations; //导入方法依赖的package包/类
public static <S extends AbstractSequenceDescription< ?,? extends BasicViewDescription<? extends BasicViewSetup>, ?  >>
	List<RandomAccessibleInterval< FloatType >> openVirtuallyFused(
			S sd,
			ViewRegistrations vrs,
			Collection<? extends Collection<ViewId>> views,
			Interval boundingBox,
			double[] downsamplingFactors)
{
	final BasicImgLoader imgLoader = sd.getImgLoader();
	
	final List<RandomAccessibleInterval< FloatType >> openImgs = new ArrayList<>();
	final Interval bbSc = TransformVirtual.scaleBoundingBox( new FinalInterval( boundingBox ), inverse( downsamplingFactors ));
	
	final long[] dim = new long[ bbSc.numDimensions() ];
	bbSc.dimensions( dim );
	
	
	for (Collection<ViewId> viewGroup : views)
	{
		final ArrayList< RandomAccessibleInterval< FloatType > > images = new ArrayList<>();
		final ArrayList< RandomAccessibleInterval< FloatType > > weights = new ArrayList<>();
		
		for ( final ViewId viewId : viewGroup )
		{
			final ViewRegistration vr = vrs.getViewRegistration( viewId );
			vr.updateModel();
			AffineTransform3D model = vr.getModel();

			final float[] blending = Util.getArrayFromValue( FusionTools.defaultBlendingRange, 3 );
			final float[] border = Util.getArrayFromValue( FusionTools.defaultBlendingBorder, 3 );

			model = model.copy();
			TransformVirtual.scaleTransform( model, inverse(downsamplingFactors) );

			final RandomAccessibleInterval inputImg = DownsampleTools.openDownsampled( imgLoader, viewId, model );

			System.out.println( model.inverse() );

			FusionTools.adjustBlending( sd.getViewDescriptions().get( viewId ), blending, border, model );

			images.add( TransformView.transformView( inputImg, model, bbSc, 0, 1 ) );
			weights.add( TransformWeight.transformBlending( inputImg, border, blending, model, bbSc ) );
		}
		
		openImgs.add( new FusedRandomAccessibleInterval( new FinalInterval( dim ), images, weights ) );
		
	}		
	
	return openImgs;
	
}
 

import mpicbg.spim.data.registration.ViewRegistrations; //导入方法依赖的package包/类
public static void setModelToIdentity( final SpimData spimData, final ViewId viewId )
{
	final ViewRegistrations viewRegistrations = spimData.getViewRegistrations();
	final ViewRegistration r = viewRegistrations.getViewRegistration( viewId );
	r.identity();
}
 

import mpicbg.spim.data.registration.ViewRegistrations; //导入方法依赖的package包/类
/**
 * Creates lists of input points for the registration, based on the current transformation of the views
 * 
 * Note: this always duplicates the location array from the input List> InterestPoint < !!!
 * 
 * @param timepoint
 */
protected HashMap< ViewId, MatchPointList > getInterestPoints( final TimePoint timepoint )
{
	final HashMap< ViewId, MatchPointList > interestPoints = new HashMap< ViewId, MatchPointList >();
	final ViewRegistrations registrations = spimData.getViewRegistrations();
	final ViewInterestPoints interestpoints = spimData.getViewInterestPoints();
	
	for ( final ViewDescription vd : SpimData2.getAllViewIdsForTimePointSorted( spimData, viewIdsToProcess, timepoint) )
	{
		if ( !vd.isPresent() )
			continue;

		final ChannelProcess c = getChannelProcessForChannel( channelsToProcess, vd.getViewSetup().getChannel() );

		// no registration for this viewdescription
		if ( c == null )
			continue;

		final Angle a = vd.getViewSetup().getAngle();
		final Illumination i = vd.getViewSetup().getIllumination();

		// assemble a new list
		final ArrayList< InterestPoint > list = new ArrayList< InterestPoint >();

		// check the existing lists of points
		final ViewInterestPointLists lists = interestpoints.getViewInterestPointLists( vd );

		if ( !lists.contains( c.getLabel() ) )
		{
			IOFunctions.println( "Interest points for label '" + c.getLabel() + "' not found for timepoint: " + timepoint.getId() + " angle: " + 
					a.getId() + " channel: " + c.getChannel().getId() + " illum: " + i.getId() );
			
			continue;
		}
		
		if ( lists.getInterestPointList( c.getLabel() ).getInterestPoints() == null )
		{
			if ( !lists.getInterestPointList( c.getLabel() ).loadInterestPoints() )
			{
				IOFunctions.println( "Interest points for label '" + c.getLabel() + "' could not be loaded for timepoint: " + timepoint.getId() + " angle: " + 
						a.getId() + " channel: " + c.getChannel().getId() + " illum: " + i.getId() );
				
				continue;
			}
		}
		
		final List< InterestPoint > ptList = lists.getInterestPointList( c.getLabel() ).getInterestPoints();
		
		final ViewRegistration r = registrations.getViewRegistration( vd );
		r.updateModel();
		final AffineTransform3D m = r.getModel();
		
		for ( final InterestPoint p : ptList )
		{
			final double[] l = new double[ 3 ];
			m.apply( p.getL(), l );
			
			list.add( new InterestPoint( p.getId(), l ) );
		}
		
		interestPoints.put( vd, new MatchPointList( list, c ) );
	}

	return interestPoints;
}