How to use

UtilFeature

in

boofcv.alg.descriptor

public DdaManagerGeneralPoint(EasyGeneralFeatureDetector<I, D> detector,
               DescribeRegionPoint<I, Desc> describe,
               double scale) {
  this.detector = detector;
  this.describe = describe;
  this.scale = scale;
  descriptors = UtilFeature.createQueue(describe,100);
}

/**
 * Adjusts the descriptor.  This adds lighting invariance and reduces the affects of none-affine changes
 * in lighting.
 *
 * 1) Apply L2 normalization
 * 2) Clip using max descriptor value
 * 3) Apply L2 normalization again
 */
public static void normalizeDescriptor(TupleDesc_F64 descriptor , double maxDescriptorElementValue ) {
  // normalize descriptor to unit length
  UtilFeature.normalizeL2(descriptor);
  // clip the values
  for (int i = 0; i < descriptor.size(); i++) {
    double value = descriptor.value[i];
    if( value > maxDescriptorElementValue ) {
      descriptor.value[i] = maxDescriptorElementValue;
    }
  }
  // normalize again
  UtilFeature.normalizeL2(descriptor);
}

public DisparityCalculation(DetectDescribePoint<GrayF32, Desc> detDesc,
              AssociateDescription<Desc> associate ,
              CameraPinholeRadial intrinsic ) {
  this.detDesc = detDesc;
  this.associate = associate;
  this.intrinsic = intrinsic;
  listSrc = UtilFeature.createQueue(detDesc, 10);
  listDst = UtilFeature.createQueue(detDesc, 10);
}

/**
 * <p>
 * Computes the SURF descriptor for the specified interest point.  If the feature
 * goes outside of the image border (including convolution kernels) then null is returned.
 * </p>
 *
 * @param x Location of interest point.
 * @param y Location of interest point.
 * @param angle The angle the feature is pointing at in radians.
 * @param scale Scale of the interest point. Null is returned if the feature goes outside the image border.
 * @param ret storage for the feature. Must have 64 values.
 */
public void describe(double x, double y, double angle, double scale, BrightFeature ret)
{
  describe(x, y, angle, scale, (TupleDesc_F64) ret);
  // normalize feature vector to have an Euclidean length of 1
  // adds light invariance
  UtilFeature.normalizeL2(ret);
  // Laplacian's sign
  ret.white = computeLaplaceSign((int)(x+0.5),(int)(y+0.5), scale);
}

public AssociationProcessing( DetectDescribePoint<GrayF32,Desc> detDesc ,
               AssociateDescription<Desc> associate  ) {
  super(ImageType.single(GrayF32.class));
  this.detDesc = detDesc;
  this.associate = associate;
  listSrc = UtilFeature.createQueue(detDesc,10);
  listDst = UtilFeature.createQueue(detDesc,10);
}

public void describe(double x, double y, double angle, double scale, BrightFeature desc)
{
  int featureIndex = 0;
  for( int band = 0; band < ii.getNumBands(); band++ ) {
    describe.setImage(ii.getBand(band));
    describe.describe(x,y, angle, scale, bandDesc);
    System.arraycopy(bandDesc.value,0,desc.value,featureIndex,bandDesc.size());
    featureIndex += bandDesc.size();
  }
  UtilFeature.normalizeL2(desc);
  describe.setImage(grayII);
  desc.white = describe.computeLaplaceSign((int)(x+0.5),(int)(y+0.5),scale);
}

public DetectDescribeMultiFusion(DetectorInterestPointMulti<T> detector,
                 OrientationImage<T> orientation,
                 DescribeRegionPoint<T, TD> describe) {
  this.detector = detector;
  this.orientation = orientation;
  this.describe = describe;
  info = new SetInfo[ detector.getNumberOfSets() ];
  for( int i = 0; i < info.length; i++ ) {
    info[i] = new SetInfo<>();
    info[i].descriptors = UtilFeature.createQueue(describe,10);
  }
}

public DdaManagerGeneralPoint(EasyGeneralFeatureDetector<I, D> detector,
               DescribeRegionPoint<I, Desc> describe,
               double scale) {
  this.detector = detector;
  this.describe = describe;
  this.scale = scale;
  numSets = detector.getDetector().isDetectMinimums() ? 1 : 0;
  numSets += detector.getDetector().isDetectMaximums() ? 1 : 0;
  descriptors = UtilFeature.createQueue(describe,100);
}

private void processImage() {
  final List<Point2D_F64> leftPts = new ArrayList<>();
  final List<Point2D_F64> rightPts = new ArrayList<>();
  FastQueue<TupleDesc> leftDesc = UtilFeature.createQueue(describe, 10);
  FastQueue<TupleDesc> rightDesc = UtilFeature.createQueue(describe,10);

public DemoThreeViewStereoApp(List<PathLabel> examples) {
  super(true, false, examples, ImageType.single(GrayU8.class));
  // remove some unused items from the menu bar. This app is an exception
  JMenu fileMenu = menuBar.getMenu(0);
  fileMenu.remove(1);
  fileMenu.remove(1);
  detDesc = FactoryDetectDescribe.surfStable( new ConfigFastHessian(
      0, 4, 1000, 1, 9, 4, 2), null,null, GrayU8.class);
  for (int i = 0; i < 3; i++) {
    locations[i] = new FastQueue<>(Point2D_F64.class,true);
    features[i] = UtilFeature.createQueue(detDesc,100);
    dimensions[i] = new ImageDimension();
  }
  rectifiedPanel.setImages(visualRect1,visualRect2);
  guiDisparity.setImage(visualDisparity);
  gui.setLayout(new BorderLayout());
  updateVisibleGui();
  add(BorderLayout.WEST, controls);
  add(BorderLayout.CENTER, gui);
  setPreferredSize(new Dimension(800,600));
}