use of net.imglib2.algorithm.neighborhood.DiamondShape in project imagej-ops by imagej.
the class MorphologyOpsTest method testFillHoles1.
@Test
public void testFillHoles1() {
Img<BitType> result = ops.create().img(invertedImgWithFilledHoles);
Img<BitType> inverted = ops.create().img(invertedImgWithFilledHoles);
ops.image().invert(inverted, imgWithHoles);
ops.morphology().fillHoles(result, inverted, new DiamondShape(1));
Cursor<BitType> resultC = result.localizingCursor();
RandomAccess<BitType> groundTruthRA = invertedImgWithFilledHoles.randomAccess();
while (resultC.hasNext()) {
boolean r = resultC.next().get();
groundTruthRA.setPosition(resultC);
assertEquals(groundTruthRA.get().get(), r);
}
}
use of net.imglib2.algorithm.neighborhood.DiamondShape in project imagej-ops by imagej.
the class Watershed method compute.
@Override
public void compute(final RandomAccessibleInterval<T> in, final ImgLabeling<Integer, IntType> out) {
final RandomAccess<T> raIn = in.randomAccess();
RandomAccess<B> raMask = null;
if (mask != null) {
raMask = mask.randomAccess();
}
// stores the size of each dimension
final long[] dimensSizes = new long[in.numDimensions()];
in.dimensions(dimensSizes);
// calculates the number of points in the n-d space
long numPixels = Intervals.numElements(in);
// the pixels indices are stored in an array, which is sorted depending
// on the pixel values
final List<Long> imiList = new ArrayList<>();
if (mask != null) {
final Cursor<Void> c = Regions.iterable(mask).localizingCursor();
while (c.hasNext()) {
c.next();
imiList.add(IntervalIndexer.positionToIndex(c, in));
}
} else {
for (long i = 0; i < numPixels; i++) {
imiList.add(i);
}
}
final Long[] imi = imiList.toArray(new Long[imiList.size()]);
/*
* Sort the pixels of imi in the increasing order of their grey value
* (only the pixel indices are stored)
*/
Arrays.sort(imi, new Comparator<Long>() {
@Override
public int compare(final Long o1, final Long o2) {
IntervalIndexer.indexToPosition(o1, in, raIn);
final T value = raIn.get().copy();
IntervalIndexer.indexToPosition(o2, in, raIn);
return value.compareTo(raIn.get());
}
});
// lab and dist store the values calculated after each phase
final RandomAccessibleInterval<IntType> lab = ops().create().img(in, new IntType());
// extend border to be able to do a quick check, if a voxel is inside
final ExtendedRandomAccessibleInterval<IntType, RandomAccessibleInterval<IntType>> labExt = Views.extendBorder(lab);
final OutOfBounds<IntType> raLab = labExt.randomAccess();
final RandomAccessibleInterval<IntType> dist = ops().create().img(in, new IntType());
final RandomAccess<IntType> raDist = dist.randomAccess();
// initial values
for (final IntType pixel : Views.flatIterable(lab)) {
pixel.set(INIT);
}
int current_label = 0;
int current_dist;
final ArrayList<Long> fifo = new ArrayList<>();
// RandomAccess for Neighborhoods
final Shape shape;
if (useEightConnectivity) {
shape = new RectangleShape(1, true);
} else {
shape = new DiamondShape(1);
}
final RandomAccessible<Neighborhood<T>> neighborhoods = shape.neighborhoodsRandomAccessible(in);
final RandomAccess<Neighborhood<T>> raNeighbor = neighborhoods.randomAccess();
/*
* Start flooding
*/
for (int j = 0; j < imi.length; j++) {
IntervalIndexer.indexToPosition(imi[j], in, raIn);
final T actualH = raIn.get().copy();
int i = j;
while (actualH.compareTo(raIn.get()) == 0) {
final long p = imi[i];
IntervalIndexer.indexToPosition(p, in, raIn);
raLab.setPosition(raIn);
raLab.get().set(MASK);
raNeighbor.setPosition(raIn);
final Cursor<T> neighborHood = raNeighbor.get().cursor();
while (neighborHood.hasNext()) {
neighborHood.fwd();
raLab.setPosition(neighborHood);
if (!raLab.isOutOfBounds()) {
final int f = raLab.get().get();
if ((f > 0) || (f == WSHED)) {
raDist.setPosition(raIn);
raDist.get().set(1);
fifo.add(p);
break;
}
}
}
i++;
if (i == imi.length) {
break;
}
IntervalIndexer.indexToPosition(imi[i], in, raIn);
}
current_dist = 1;
// add fictitious pixel
fifo.add(-1l);
while (true) {
long p = fifo.remove(0);
if (p == -1) {
if (fifo.isEmpty()) {
break;
}
fifo.add(-1l);
current_dist++;
p = fifo.remove(0);
}
IntervalIndexer.indexToPosition(p, in, raNeighbor);
final Cursor<T> neighborHood = raNeighbor.get().cursor();
raLab.setPosition(raNeighbor);
int labp = raLab.get().get();
final long[] posNeighbor = new long[neighborHood.numDimensions()];
while (neighborHood.hasNext()) {
neighborHood.fwd();
neighborHood.localize(posNeighbor);
raLab.setPosition(posNeighbor);
if (!raLab.isOutOfBounds()) {
raDist.setPosition(posNeighbor);
final int labq = raLab.get().get();
final int distq = raDist.get().get();
if ((distq < current_dist) && ((labq > 0) || (labq == WSHED))) {
// the watersheds
if (labq > 0) {
if ((labp == MASK) || (labp == WSHED)) {
labp = labq;
} else {
if (labp != labq) {
labp = WSHED;
}
}
} else {
if (labp == MASK) {
labp = WSHED;
}
}
raLab.setPosition(raNeighbor);
raLab.get().set(labp);
} else {
if ((labq == MASK) && (distq == 0)) {
raDist.setPosition(posNeighbor);
raDist.get().set(current_dist + 1);
fifo.add(IntervalIndexer.positionToIndex(posNeighbor, dimensSizes));
}
}
}
}
}
// checks if new minima have been discovered
IntervalIndexer.indexToPosition(imi[j], in, raIn);
i = j;
while (actualH.compareTo(raIn.get()) == 0) {
final long p = imi[i];
IntervalIndexer.indexToPosition(p, dist, raDist);
// the distance associated with p is reseted to 0
raDist.get().set(0);
raLab.setPosition(raDist);
if (raLab.get().get() == MASK) {
current_label++;
fifo.add(p);
raLab.get().set(current_label);
while (!fifo.isEmpty()) {
final long q = fifo.remove(0);
IntervalIndexer.indexToPosition(q, in, raNeighbor);
final Cursor<T> neighborHood = raNeighbor.get().cursor();
final long[] posNeighbor = new long[neighborHood.numDimensions()];
while (neighborHood.hasNext()) {
neighborHood.fwd();
neighborHood.localize(posNeighbor);
raLab.setPosition(posNeighbor);
if (!raLab.isOutOfBounds()) {
final long r = IntervalIndexer.positionToIndex(posNeighbor, dimensSizes);
if (raLab.get().get() == MASK) {
fifo.add(r);
raLab.get().set(current_label);
}
}
}
}
}
i++;
if (i == imi.length) {
break;
}
IntervalIndexer.indexToPosition(imi[i], in, raIn);
}
j = i - 1;
}
/*
* Draw output and remove as the case may be the watersheds
*/
final Cursor<LabelingType<Integer>> cursorOut = out.cursor();
while (cursorOut.hasNext()) {
cursorOut.fwd();
boolean maskValue = true;
if (mask != null) {
raMask.setPosition(cursorOut);
if (!raMask.get().get()) {
maskValue = false;
}
}
raLab.setPosition(cursorOut);
if (!maskValue) {
cursorOut.get().clear();
} else {
if (!drawWatersheds && raLab.get().get() == WSHED) {
raNeighbor.setPosition(cursorOut);
final Cursor<T> neighborHood = raNeighbor.get().cursor();
int newLab = WSHED;
while (neighborHood.hasNext()) {
neighborHood.fwd();
raLab.setPosition(neighborHood);
if (!raLab.isOutOfBounds()) {
newLab = raLab.get().get();
if (newLab > WSHED) {
break;
}
}
}
if (newLab == WSHED) {
cursorOut.get().clear();
} else {
cursorOut.get().add(newLab);
}
} else {
cursorOut.get().add(raLab.get().get());
}
}
}
/*
* Merge already present labels before calculation of watershed
*/
if (out() != null) {
final Cursor<LabelingType<Integer>> cursor = out().cursor();
final RandomAccess<LabelingType<Integer>> raOut = out.randomAccess();
while (cursor.hasNext()) {
cursor.fwd();
raOut.setPosition(cursor);
final List<Integer> labels = new ArrayList<>();
cursor.get().iterator().forEachRemaining(labels::add);
raOut.get().addAll(labels);
}
}
}
use of net.imglib2.algorithm.neighborhood.DiamondShape in project imagej-ops by imagej.
the class WatershedSeeded method compute.
@SuppressWarnings("unchecked")
@Override
public void compute(final RandomAccessibleInterval<T> in, final ImgLabeling<Integer, IntType> out) {
// extend border to be able to do a quick check, if a voxel is inside
final LabelingType<Integer> oustide = out.firstElement().copy();
oustide.clear();
oustide.add(OUTSIDE);
final ExtendedRandomAccessibleInterval<LabelingType<Integer>, ImgLabeling<Integer, IntType>> outExt = Views.extendValue(out, oustide);
final OutOfBounds<LabelingType<Integer>> raOut = outExt.randomAccess();
// if no mask provided, set the mask to the whole image
if (mask == null) {
mask = (RandomAccessibleInterval<B>) ops().create().img(in, new BitType());
for (B b : Views.flatIterable(mask)) {
b.set(true);
}
}
// initialize output labels
final Cursor<B> maskCursor = Views.flatIterable(mask).cursor();
while (maskCursor.hasNext()) {
maskCursor.fwd();
if (maskCursor.get().get()) {
raOut.setPosition(maskCursor);
raOut.get().clear();
raOut.get().add(INIT);
}
}
// RandomAccess for Mask, Seeds and Neighborhoods
final RandomAccess<B> raMask = mask.randomAccess();
final RandomAccess<LabelingType<Integer>> raSeeds = seeds.randomAccess();
final Shape shape;
if (useEightConnectivity) {
shape = new RectangleShape(1, true);
} else {
shape = new DiamondShape(1);
}
final RandomAccessible<Neighborhood<T>> neighborhoods = shape.neighborhoodsRandomAccessible(in);
final RandomAccess<Neighborhood<T>> raNeigh = neighborhoods.randomAccess();
/*
* Carry over the seeding points to the new label and adds them to a
* voxel priority queue
*/
final PriorityQueue<WatershedVoxel> pq = new PriorityQueue<>();
// Only iterate seeds that are not excluded by the mask
final IterableRegion<B> maskRegions = Regions.iterable(mask);
final IterableInterval<LabelingType<Integer>> seedsMasked = Regions.sample(maskRegions, seeds);
final Cursor<LabelingType<Integer>> cursorSeeds = seedsMasked.localizingCursor();
while (cursorSeeds.hasNext()) {
final Set<Integer> l = cursorSeeds.next();
if (l.isEmpty()) {
continue;
}
if (l.size() > 1) {
throw new IllegalArgumentException("Seeds must have exactly one label!");
}
final Integer label = l.iterator().next();
if (label < 0) {
throw new IllegalArgumentException("Seeds must have positive integers as labels!");
}
raNeigh.setPosition(cursorSeeds);
final Cursor<T> neighborhood = raNeigh.get().cursor();
// Add unlabeled neighbors to priority queue
while (neighborhood.hasNext()) {
neighborhood.fwd();
raSeeds.setPosition(neighborhood);
raMask.setPosition(neighborhood);
raOut.setPosition(neighborhood);
final Integer labelNeigh = raOut.get().iterator().next();
if (labelNeigh != INQUEUE && labelNeigh != OUTSIDE && !raOut.isOutOfBounds() && raMask.get().get() && raSeeds.get().isEmpty()) {
raOut.setPosition(neighborhood);
pq.add(new WatershedVoxel(IntervalIndexer.positionToIndex(neighborhood, in), neighborhood.get().getRealDouble()));
raOut.get().clear();
raOut.get().add(INQUEUE);
}
}
// Overwrite label in output with the seed label
raOut.setPosition(cursorSeeds);
raOut.get().clear();
raOut.get().add(label);
}
/*
* Pop the head of the priority queue, label and push all unlabeled
* neighbored pixels.
*/
// list to store neighbor labels
final ArrayList<Integer> neighborLabels = new ArrayList<>();
// list to store neighbor voxels
final ArrayList<WatershedVoxel> neighborVoxels = new ArrayList<>();
// iterate the queue
final Point pos = new Point(in.numDimensions());
while (!pq.isEmpty()) {
IntervalIndexer.indexToPosition(pq.poll().getPos(), out, pos);
// reset list of neighbor labels
neighborLabels.clear();
// reset list of neighbor voxels
neighborVoxels.clear();
// iterate the neighborhood of the pixel
raNeigh.setPosition(pos);
final Cursor<T> neighborhood = raNeigh.get().cursor();
while (neighborhood.hasNext()) {
neighborhood.fwd();
// Unlabeled neighbors go into the queue if they are not there
// yet
raOut.setPosition(neighborhood);
raMask.setPosition(raOut);
if (!raOut.get().isEmpty()) {
final Integer label = raOut.get().iterator().next();
if (label == INIT && raMask.get().get()) {
neighborVoxels.add(new WatershedVoxel(IntervalIndexer.positionToIndex(neighborhood, out), neighborhood.get().getRealDouble()));
} else {
if (label > WSHED && (!drawWatersheds || !neighborLabels.contains(label))) {
// store labels of neighbors in a list
neighborLabels.add(label);
}
}
}
}
if (drawWatersheds) {
// if the neighbors of the extracted voxel that have already
// been labeled
// all have the same label, then the voxel is labeled with their
// label.
raOut.setPosition(pos);
raOut.get().clear();
if (neighborLabels.size() == 1) {
raOut.get().add(neighborLabels.get(0));
// list
for (final WatershedVoxel v : neighborVoxels) {
IntervalIndexer.indexToPosition(v.getPos(), out, raOut);
raOut.get().clear();
raOut.get().add(INQUEUE);
pq.add(v);
}
} else if (neighborLabels.size() > 1)
raOut.get().add(WSHED);
} else {
if (neighborLabels.size() > 0) {
raOut.setPosition(pos);
raOut.get().clear();
// take the label which most of the neighbors have
if (neighborLabels.size() > 2) {
final Map<Integer, Long> countLabels = neighborLabels.stream().collect(Collectors.groupingBy(e -> e, Collectors.counting()));
final Integer keyMax = Collections.max(countLabels.entrySet(), Comparator.comparingLong(Map.Entry::getValue)).getKey();
raOut.get().add(keyMax);
} else {
raOut.get().add(neighborLabels.get(0));
}
// list
for (final WatershedVoxel v : neighborVoxels) {
IntervalIndexer.indexToPosition(v.getPos(), out, raOut);
raOut.get().clear();
raOut.get().add(INQUEUE);
pq.add(v);
}
}
}
}
/*
* Merge already present labels before calculation of watershed
*/
if (out() != null) {
final Cursor<LabelingType<Integer>> cursor = out().cursor();
while (cursor.hasNext()) {
cursor.fwd();
raOut.setPosition(cursor);
final List<Integer> labels = new ArrayList<>();
cursor.get().iterator().forEachRemaining(labels::add);
raOut.get().addAll(labels);
}
}
}
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