Examples with SimilarityModel2D mpicbg.models.SimilarityModel2D used on opensource projects

Example 11 with SimilarityModel2D

use of mpicbg.models.SimilarityModel2D in project TrakEM2 by trakem2.

the class MovingLeastSquaresTransform2 method init2.

public void init2(final String s) throws Exception {
    // WARNING: assumes all whitespace is single
    final int len = s.length();
    int i = 0;
    // Advance to the first white space
    while (' ' != s.charAt(++i)) {
    }
    // Interpret model by the last letter of the name
    final char modelLastChar = s.charAt(i - 1);
    // Determine dimension 2 or 3
    final int n = (s.charAt(i + 1)) - 48;
    switch(n) {
        case 3:
            model = new AffineModel3D();
            break;
        case 2:
            switch(modelLastChar) {
                case // translation
                'n':
                    model = new TranslationModel2D();
                    break;
                case // rigid
                'd':
                    model = new RigidModel2D();
                    break;
                case // similarity
                'y':
                    model = new SimilarityModel2D();
                    break;
                case // affine
                'e':
                    model = new AffineModel2D();
                    break;
                default:
                    throw new Exception("Unknown model " + s.substring(0, i));
            }
            break;
        default:
            throw new NumberFormatException("Unsupported model dimensions: " + n + " for " + this.getClass().getCanonicalName());
    }
    // 'i' is at whitespace before n
    // Move i to whitespace before alpha
    i += 2;
    // Mark last char before whitespace
    int cut = i - 1;
    // 'i' ends up at the whitespace after alpha
    while (' ' != s.charAt(++i)) {
    }
    // Parse alpha
    float[] f = new float[1];
    parse(s, cut, i - 1, f, 0);
    this.alpha = f[0];
    // Count numbers by counting one whitespace before each number
    int nVals = 0;
    for (int k = i; k < len; ++k) {
        if (' ' == s.charAt(k))
            ++nVals;
    }
    // The size of a unit of numbers
    final int cell = n + n + 1;
    // Detect inconsistency:
    if (0 != nVals % cell) {
        throw new NumberFormatException("Inappropriate parameters for " + this.getClass().getCanonicalName());
    }
    // Create arrays
    this.p = new float[n][nVals / cell];
    this.q = new float[n][this.p[0].length];
    this.w = new float[this.p[0].length];
    // Mark the whitespace char before the first number
    cut = i - 1;
    // Start parsing from the end
    i = len - 1;
    int count = 0;
    if (2 == n) {
        while (i > cut) {
            // Determine which array from {p,q,w} and which position in the array, using n and count:
            switch(// n for dimensions, +1 for the weight
            count % cell) {
                case 0:
                    f = this.w;
                    break;
                case 1:
                    f = this.q[1];
                    break;
                case 2:
                    f = this.q[0];
                    break;
                case 3:
                    f = this.p[1];
                    break;
                case 4:
                    f = this.p[0];
                    break;
            }
            i = parse(s, cut, i, f, this.w.length - (count / cell) - 1);
            ++count;
        }
    } else {
        while (i > cut) {
            // Determine which array from {p,q,w} and which position in the array, using n and count:
            switch(// n for dimensions, +1 for the weight
            count % (n + n + 1)) {
                case 0:
                    f = this.w;
                    break;
                case 1:
                    f = this.q[2];
                    break;
                case 2:
                    f = this.q[1];
                    break;
                case 3:
                    f = this.q[0];
                    break;
                case 4:
                    f = this.p[2];
                    break;
                case 5:
                    f = this.p[1];
                    break;
                case 6:
                    f = this.p[0];
                    break;
            }
            i = parse(s, cut, i, f, this.w.length - (count / cell) - 1);
            ++count;
        }
    }
}

Example 12 with SimilarityModel2D

use of mpicbg.models.SimilarityModel2D in project TrakEM2 by trakem2.

the class Distortion_Correction method extractSIFTPointsThreaded.

protected static void extractSIFTPointsThreaded(final int index, final List<Feature>[] siftFeatures, final List<PointMatch>[] inliers, final AbstractAffineModel2D<?>[] models) {
    // save all matching candidates
    final List<PointMatch>[] candidates = new List[siftFeatures.length - 1];
    final Thread[] threads = MultiThreading.newThreads();
    // start at second
    final AtomicInteger ai = new AtomicInteger(0);
    for (int ithread = 0; ithread < threads.length; ++ithread) {
        threads[ithread] = new Thread() {

            @Override
            public void run() {
                setPriority(Thread.NORM_PRIORITY);
                for (int j = ai.getAndIncrement(); j < candidates.length; j = ai.getAndIncrement()) {
                    final int i = (j < index ? j : j + 1);
                    candidates[j] = FloatArray2DSIFT.createMatches(siftFeatures[index], siftFeatures[i], 1.5f, null, Float.MAX_VALUE, 0.5f);
                }
            }
        };
    }
    MultiThreading.startAndJoin(threads);
    // get rid of the outliers and save the rigid transformations to match
    // the inliers
    final AtomicInteger ai2 = new AtomicInteger(0);
    for (int ithread = 0; ithread < threads.length; ++ithread) {
        threads[ithread] = new Thread() {

            @Override
            public void run() {
                setPriority(Thread.NORM_PRIORITY);
                for (int i = ai2.getAndIncrement(); i < candidates.length; i = ai2.getAndIncrement()) {
                    final List<PointMatch> tmpInliers = new ArrayList<PointMatch>();
                    // RigidModel2D m =
                    // RigidModel2D.estimateBestModel(candidates.get(i),
                    // tmpInliers, sp.min_epsilon, sp.max_epsilon,
                    // sp.min_inlier_ratio);
                    final AbstractAffineModel2D<?> m;
                    switch(sp.expectedModelIndex) {
                        case 0:
                            m = new TranslationModel2D();
                            break;
                        case 1:
                            m = new RigidModel2D();
                            break;
                        case 2:
                            m = new SimilarityModel2D();
                            break;
                        case 3:
                            m = new AffineModel2D();
                            break;
                        default:
                            return;
                    }
                    boolean modelFound = false;
                    try {
                        modelFound = m.filterRansac(candidates[i], tmpInliers, 1000, sp.maxEpsilon, sp.minInlierRatio, 10);
                    } catch (final NotEnoughDataPointsException e) {
                        modelFound = false;
                    }
                    if (modelFound)
                        IJ.log("Model found:\n  " + candidates[i].size() + " candidates\n  " + tmpInliers.size() + " inliers\n  " + String.format("%.2f", m.getCost()) + "px average displacement");
                    else
                        IJ.log("No Model found.");
                    inliers[index * (sp.numberOfImages - 1) + i] = tmpInliers;
                    models[index * (sp.numberOfImages - 1) + i] = m;
                // System.out.println("**** MODEL ADDED: " +
                // (index*(sp.numberOfImages-1)+i));
                }
            }
        };
    }
    MultiThreading.startAndJoin(threads);
}

Example 13 with SimilarityModel2D

use of mpicbg.models.SimilarityModel2D in project TrakEM2 by trakem2.

the class Distortion_Correction method extractSIFTPoints.

protected void extractSIFTPoints(final int index, final List<Feature>[] siftFeatures, final List<List<PointMatch>> inliers, final List<AbstractAffineModel2D<?>> models) {
    // save all matching candidates
    final List<List<PointMatch>> candidates = new ArrayList<List<PointMatch>>();
    for (int j = 0; j < siftFeatures.length; j++) {
        if (index == j)
            continue;
        candidates.add(FloatArray2DSIFT.createMatches(siftFeatures[index], siftFeatures[j], 1.5f, null, Float.MAX_VALUE, 0.5f));
    }
    // get rid of the outliers and save the transformations to match the inliers
    for (int i = 0; i < candidates.size(); ++i) {
        final List<PointMatch> tmpInliers = new ArrayList<PointMatch>();
        final AbstractAffineModel2D<?> m;
        switch(sp.expectedModelIndex) {
            case 0:
                m = new TranslationModel2D();
                break;
            case 1:
                m = new RigidModel2D();
                break;
            case 2:
                m = new SimilarityModel2D();
                break;
            case 3:
                m = new AffineModel2D();
                break;
            default:
                return;
        }
        try {
            m.filterRansac(candidates.get(i), tmpInliers, 1000, sp.maxEpsilon, sp.minInlierRatio, 10);
        } catch (final NotEnoughDataPointsException e) {
            e.printStackTrace();
        }
        inliers.add(tmpInliers);
        models.add(m);
    }
}

Example 14 with SimilarityModel2D

use of mpicbg.models.SimilarityModel2D in project TrakEM2 by trakem2.

the class Align method alignLayersLinearly.

/**
 * Align a range of layers by accumulating pairwise alignments of contiguous layers.
 *
 * @param layers The range of layers to align pairwise.
 * @param numThreads The number of threads to use.
 * @param filter The {@link Filter} to decide which {@link Patch} instances to use in each {@link Layer}. Can be null.
 */
public static final void alignLayersLinearly(final List<Layer> layers, final int numThreads, final Filter<Patch> filter) {
    param.sift.maxOctaveSize = 1600;
    if (!param.setup("Align layers linearly"))
        return;
    final Rectangle box = layers.get(0).getParent().getMinimalBoundingBox(Patch.class);
    final double scale = Math.min(1.0, Math.min((double) param.sift.maxOctaveSize / box.width, (double) param.sift.maxOctaveSize / box.height));
    final Param p = param.clone();
    p.maxEpsilon *= scale;
    final FloatArray2DSIFT sift = new FloatArray2DSIFT(p.sift);
    final SIFT ijSIFT = new SIFT(sift);
    Rectangle box1 = null;
    Rectangle box2 = null;
    final Collection<Feature> features1 = new ArrayList<Feature>();
    final Collection<Feature> features2 = new ArrayList<Feature>();
    final List<PointMatch> candidates = new ArrayList<PointMatch>();
    final List<PointMatch> inliers = new ArrayList<PointMatch>();
    final AffineTransform a = new AffineTransform();
    int i = 0;
    for (final Layer l : layers) {
        long s = System.currentTimeMillis();
        features1.clear();
        features1.addAll(features2);
        features2.clear();
        final Rectangle box3 = l.getMinimalBoundingBox(Patch.class);
        if (box3 == null)
            continue;
        box1 = box2;
        box2 = box3;
        final List<Patch> patches = l.getAll(Patch.class);
        if (null != filter) {
            for (final Iterator<Patch> it = patches.iterator(); it.hasNext(); ) {
                if (!filter.accept(it.next()))
                    it.remove();
            }
        }
        ijSIFT.extractFeatures(l.getProject().getLoader().getFlatImage(l, box2, scale, 0xffffffff, ImagePlus.GRAY8, Patch.class, patches, true).getProcessor(), features2);
        Utils.log(features2.size() + " features extracted in layer \"" + l.getTitle() + "\" (took " + (System.currentTimeMillis() - s) + " ms).");
        if (features1.size() > 0) {
            s = System.currentTimeMillis();
            candidates.clear();
            FeatureTransform.matchFeatures(features2, features1, candidates, p.rod);
            final AbstractAffineModel2D<?> model;
            switch(p.expectedModelIndex) {
                case 0:
                    model = new TranslationModel2D();
                    break;
                case 1:
                    model = new RigidModel2D();
                    break;
                case 2:
                    model = new SimilarityModel2D();
                    break;
                case 3:
                    model = new AffineModel2D();
                    break;
                default:
                    return;
            }
            boolean modelFound;
            boolean again = false;
            try {
                do {
                    again = false;
                    modelFound = model.filterRansac(candidates, inliers, 1000, p.maxEpsilon, p.minInlierRatio, p.minNumInliers, 3);
                    if (modelFound && p.rejectIdentity) {
                        final ArrayList<Point> points = new ArrayList<Point>();
                        PointMatch.sourcePoints(inliers, points);
                        if (Transforms.isIdentity(model, points, p.identityTolerance)) {
                            Utils.log("Identity transform for " + inliers.size() + " matches rejected.");
                            candidates.removeAll(inliers);
                            inliers.clear();
                            again = true;
                        }
                    }
                } while (again);
            } catch (final NotEnoughDataPointsException e) {
                modelFound = false;
            }
            if (modelFound) {
                Utils.log("Model found for layer \"" + l.getTitle() + "\" and its predecessor:\n  correspondences  " + inliers.size() + " of " + candidates.size() + "\n  average residual error  " + (model.getCost() / scale) + " px\n  took " + (System.currentTimeMillis() - s) + " ms");
                final AffineTransform b = new AffineTransform();
                b.translate(box1.x, box1.y);
                b.scale(1.0f / scale, 1.0f / scale);
                b.concatenate(model.createAffine());
                b.scale(scale, scale);
                b.translate(-box2.x, -box2.y);
                a.concatenate(b);
                l.apply(Displayable.class, a);
                Display.repaint(l);
            } else {
                Utils.log("No model found for layer \"" + l.getTitle() + "\" and its predecessor:\n  correspondence candidates  " + candidates.size() + "\n  took " + (System.currentTimeMillis() - s) + " ms");
                a.setToIdentity();
            }
        }
        IJ.showProgress(++i, layers.size());
    }
}

Example 15 with SimilarityModel2D

use of mpicbg.models.SimilarityModel2D in project TrakEM2 by trakem2.

the class Align method alignTileCollections.

/**
 * Align two collections of tiles
 * @param p
 * @param a
 * @param b
 */
public static final void alignTileCollections(final Param p, final Collection<AbstractAffineTile2D<?>> a, final Collection<AbstractAffineTile2D<?>> b) {
    final ArrayList<Patch> pa = new ArrayList<Patch>();
    final ArrayList<Patch> pb = new ArrayList<Patch>();
    for (final AbstractAffineTile2D<?> t : a) pa.add(t.getPatch());
    for (final AbstractAffineTile2D<?> t : b) pb.add(t.getPatch());
    final Layer la = pa.iterator().next().getLayer();
    final Layer lb = pb.iterator().next().getLayer();
    final Rectangle boxA = Displayable.getBoundingBox(pa, null);
    final Rectangle boxB = Displayable.getBoundingBox(pb, null);
    final double scale = Math.min(1.0, Math.min(Math.min((double) p.sift.maxOctaveSize / boxA.width, (double) p.sift.maxOctaveSize / boxA.height), Math.min((double) p.sift.maxOctaveSize / boxB.width, (double) p.sift.maxOctaveSize / boxB.height)));
    final Param pp = p.clone();
    pp.maxEpsilon *= scale;
    final FloatArray2DSIFT sift = new FloatArray2DSIFT(pp.sift);
    final SIFT ijSIFT = new SIFT(sift);
    final Collection<Feature> featuresA = new ArrayList<Feature>();
    final Collection<Feature> featuresB = new ArrayList<Feature>();
    final List<PointMatch> candidates = new ArrayList<PointMatch>();
    final List<PointMatch> inliers = new ArrayList<PointMatch>();
    long s = System.currentTimeMillis();
    ijSIFT.extractFeatures(la.getProject().getLoader().getFlatImage(la, boxA, scale, 0xffffffff, ImagePlus.GRAY8, null, pa, true, Color.GRAY).getProcessor(), featuresA);
    Utils.log(featuresA.size() + " features extracted in graph A in layer \"" + la.getTitle() + "\" (took " + (System.currentTimeMillis() - s) + " ms).");
    s = System.currentTimeMillis();
    ijSIFT.extractFeatures(lb.getProject().getLoader().getFlatImage(lb, boxB, scale, 0xffffffff, ImagePlus.GRAY8, null, pb, true, Color.GRAY).getProcessor(), featuresB);
    Utils.log(featuresB.size() + " features extracted in graph B in layer \"" + lb.getTitle() + "\" (took " + (System.currentTimeMillis() - s) + " ms).");
    if (featuresA.size() > 0 && featuresB.size() > 0) {
        s = System.currentTimeMillis();
        FeatureTransform.matchFeatures(featuresA, featuresB, candidates, pp.rod);
        final AbstractAffineModel2D<?> model;
        switch(p.expectedModelIndex) {
            case 0:
                model = new TranslationModel2D();
                break;
            case 1:
                model = new RigidModel2D();
                break;
            case 2:
                model = new SimilarityModel2D();
                break;
            case 3:
                model = new AffineModel2D();
                break;
            default:
                return;
        }
        boolean modelFound;
        boolean again = false;
        try {
            do {
                again = false;
                modelFound = model.filterRansac(candidates, inliers, 1000, p.maxEpsilon, p.minInlierRatio, p.minNumInliers, 3);
                if (modelFound && p.rejectIdentity) {
                    final ArrayList<Point> points = new ArrayList<Point>();
                    PointMatch.sourcePoints(inliers, points);
                    if (Transforms.isIdentity(model, points, p.identityTolerance)) {
                        Utils.log("Identity transform for " + inliers.size() + " matches rejected.");
                        candidates.removeAll(inliers);
                        inliers.clear();
                        again = true;
                    }
                }
            } while (again);
        } catch (final NotEnoughDataPointsException e) {
            modelFound = false;
        }
        if (modelFound) {
            Utils.log("Model found for graph A and B in layers \"" + la.getTitle() + "\" and \"" + lb.getTitle() + "\":\n  correspondences  " + inliers.size() + " of " + candidates.size() + "\n  average residual error  " + (model.getCost() / scale) + " px\n  took " + (System.currentTimeMillis() - s) + " ms");
            final AffineTransform at = new AffineTransform();
            at.translate(boxA.x, boxA.y);
            at.scale(1.0f / scale, 1.0f / scale);
            at.concatenate(model.createAffine());
            at.scale(scale, scale);
            at.translate(-boxB.x, -boxB.y);
            for (final Patch t : pa) t.preTransform(at, false);
            Display.repaint(la);
        } else
            Utils.log("No model found for graph A and B in layers \"" + la.getTitle() + "\" and \"" + lb.getTitle() + "\":\n  correspondence candidates  " + candidates.size() + "\n  took " + (System.currentTimeMillis() - s) + " ms");
    }
}