Examples with PairwiseImageGraph boofcv.alg.structure.PairwiseImageGraph used on opensource projects

Example 6 with PairwiseImageGraph

use of boofcv.alg.structure.PairwiseImageGraph in project BoofCV by lessthanoptimal.

the class TestMultiViewIO method save_load_PairwiseImageGraph.

@Test
void save_load_PairwiseImageGraph() {
    for (int trial = 0; trial < 20; trial++) {
        PairwiseImageGraph expected = createPairwise();
        var output = new ByteArrayOutputStream();
        MultiViewIO.save(expected, new OutputStreamWriter(output, UTF_8));
        var input = new ByteArrayInputStream(output.toByteArray());
        PairwiseImageGraph found = MultiViewIO.load(new InputStreamReader(input, UTF_8), (PairwiseImageGraph) null);
        checkIdentical(expected, found);
    }
}

Example 7 with PairwiseImageGraph

use of boofcv.alg.structure.PairwiseImageGraph in project BoofCV by lessthanoptimal.

the class ViewPairwiseImageGraphApp method openFile.

@Override
public void openFile(File file, boolean addToRecent) {
    // Save the path just in case it wants to reload it later
    inputFilePath = systemToUnix(file.getPath());
    // update recent items menu
    if (addToRecent) {
        String path = inputFilePath;
        BoofSwingUtil.invokeNowOrLater(() -> {
            BoofSwingUtil.addToRecentFiles(ViewPairwiseImageGraphApp.this, selectRecentFileName(BoofMiscOps.asList(file)), BoofMiscOps.asList(path));
            updateRecentItems();
        });
    }
    stopAllInputProcessing();
    threadPool.execute(() -> {
        setMenuBarEnabled(false);
        Objects.requireNonNull(inputFilePath);
        System.out.println("Loading pairwise graph at: " + inputFilePath);
        graph = MultiViewIO.load(inputFilePath, (PairwiseImageGraph) null);
        db = MultiViewIO.loadSimilarImages(new File(new File(inputFilePath).getParentFile(), "similar.yaml").getPath());
        smartFindImagePath();
        SwingUtilities.invokeLater(() -> {
            loadPairwiseIntoGui();
            setMenuBarEnabled(true);
        });
    });
}

Example 8 with PairwiseImageGraph

use of boofcv.alg.structure.PairwiseImageGraph in project BoofCV by lessthanoptimal.

the class TestExpandByOneView method selectTwoConnections.

/**
 * Creates a more complex scenario and sees if it selects the correct two views
 */
@Test
void selectTwoConnections() {
    var working = new SceneWorkingGraph();
    var graph = new PairwiseImageGraph();
    SceneWorkingGraph.Camera camera = working.addCamera(2);
    View seed = graph.createNode("A");
    for (int i = 0; i < 6; i++) {
        View viewI = graph.createNode("" + i);
        // make sure src/dst is handled correctly
        Motion mA = i % 2 == 0 ? graph.connect(seed, viewI) : graph.connect(viewI, seed);
        // All have the same score so that the connections between the other two is what decides the winner
        mA.score3D = 2.0;
        mA.is3D = true;
        working.addView(viewI, camera);
    }
    View viewB = seed.connection(1);
    View viewC = seed.connection(2);
    View viewD = seed.connection(3);
    Motion connBC = graph.connect(viewB, viewC);
    Motion connBD = graph.connect(viewD, viewB);
    connBD.is3D = connBC.is3D = true;
    connBC.score3D = 1.2;
    // this is the more desirable connection
    connBD.score3D = 1.3;
    var alg = new ChildProjectiveExpandByOneView();
    alg.workGraph = working;
    var found = new ArrayList<Motion>();
    assertTrue(alg.selectTwoConnections(seed, found));
    assertTrue(found.contains(seed.connections.get(1)));
    assertTrue(found.contains(seed.connections.get(3)));
}

Example 9 with PairwiseImageGraph

use of boofcv.alg.structure.PairwiseImageGraph in project BoofCV by lessthanoptimal.

the class TestEstimateViewKnownCalibration method simpleKnownScenario.

/**
 * Generate a known scene and pass in everything but the location of the 3rd view. Make sure
 * it's able to estimate it. A couple of outliers will be added and checked to make sure they are removed.
 */
@Test
void simpleKnownScenario() {
    var db = new MockLookupSimilarImagesRealistic().pathLine(5, 0.3, 1.5, 2);
    PairwiseImageGraph pairwise = db.createPairwise();
    SceneWorkingGraph scene = db.createWorkingGraph(pairwise);
    var pairwiseUtils = new PairwiseGraphUtils();
    pairwiseUtils.dbSimilar = db;
    pairwiseUtils.dbCams = db.createLookUpCams();
    // Specify the 3-views it should use. viewC = target that's estimated
    pairwiseUtils.seed = pairwise.nodes.get(1);
    pairwiseUtils.viewB = pairwise.nodes.get(2);
    pairwiseUtils.viewC = pairwise.nodes.get(3);
    // Use truth for the priors
    pairwiseUtils.priorCamA.setTo(db.intrinsic);
    pairwiseUtils.priorCamB.setTo(db.intrinsic);
    pairwiseUtils.priorCamC.setTo(db.intrinsic);
    // Specifies the observations for the 3-views
    SceneWorkingGraph.View wviewA = scene.listViews.get(1);
    db.addInlierInfo(pairwise, wviewA, 2, 3);
    // Create the triplet of pixel observations using the "inlier" set created above
    SceneWorkingGraph.InlierInfo info = Objects.requireNonNull(wviewA.getBestInliers());
    int numInliers = info.getInlierCount();
    pairwiseUtils.inlierIdx.resize(numInliers, (idx) -> idx);
    assertTrue(numInliers > 20);
    for (int i = 0; i < numInliers; i++) {
        int obs1 = info.observations.get(0).get(i);
        int obs2 = info.observations.get(1).get(i);
        int obs3 = info.observations.get(2).get(i);
        AssociatedTriple a = new AssociatedTriple();
        a.p1.setTo(db.views.get(1).observations.get(obs1).pixel);
        a.p2.setTo(db.views.get(2).observations.get(obs2).pixel);
        a.p3.setTo(db.views.get(3).observations.get(obs3).pixel);
        pairwiseUtils.inliersThreeView.add(a);
    }
    // Pixels must be centered at (0,0)
    for (int i = 0; i < numInliers; i++) {
        AssociatedTriple a = pairwiseUtils.inliersThreeView.get(i);
        a.p1.x -= db.intrinsic.cx;
        a.p1.y -= db.intrinsic.cy;
        a.p2.x -= db.intrinsic.cx;
        a.p2.y -= db.intrinsic.cy;
        a.p3.x -= db.intrinsic.cx;
        a.p3.y -= db.intrinsic.cy;
    }
    var alg = new EstimateViewKnownCalibration();
    // alg.setVerbose(System.out, BoofMiscOps.hashSet(BoofVerbose.RECURSIVE));
    var solution = new MetricExpandByOneView.Solution();
    assertTrue(alg.process(pairwiseUtils, scene, solution));
    // See if the transforms are the same
    Se3_F64 expected = scene.listViews.get(3).world_to_view;
    assertEquals(0.0, expected.T.distance(solution.world_to_target.T), 1e-2);
// NOTE: The tolerance does seem a bit high for noise free observations. Could there be numeric issues?
}