Examples with ConfigExtract boofcv.abst.feature.detect.extract.ConfigExtract used on opensource projects

Example 1 with ConfigExtract

use of boofcv.abst.feature.detect.extract.ConfigExtract in project BoofCV by lessthanoptimal.

the class ConfigSiftDetector method createPaper.

/**
 * Creates a configuration similar to how it was originally described in the paper
 */
public static ConfigSiftDetector createPaper() {
    ConfigSiftDetector config = new ConfigSiftDetector();
    config.extract = new ConfigExtract(1, 0, 1, true, true, true);
    config.extract.ignoreBorder = 1;
    config.maxFeaturesPerScale = 0;
    config.edgeR = 10;
    return config;
}

Example 2 with ConfigExtract

use of boofcv.abst.feature.detect.extract.ConfigExtract in project BoofCV by lessthanoptimal.

the class FactoryInterestPointAlgs method hessianLaplace.

/**
 * Creates a {@link boofcv.alg.feature.detect.interest.FeatureLaplacePyramid} which is uses a hessian blob detector.
 *
 * @param extractRadius   Size of the feature used to detect the corners.
 * @param detectThreshold Minimum corner intensity required
 * @param maxFeatures     Max number of features that can be found.
 * @param imageType       Type of input image.
 * @param derivType       Image derivative type.
 * @return CornerLaplaceScaleSpace
 */
public static <T extends ImageGray<T>, D extends ImageGray<D>> FeatureLaplacePyramid<T, D> hessianLaplace(int extractRadius, float detectThreshold, int maxFeatures, Class<T> imageType, Class<D> derivType) {
    GeneralFeatureIntensity<T, D> intensity = new WrapperHessianBlobIntensity<>(HessianBlobIntensity.Type.DETERMINANT, derivType);
    NonMaxSuppression extractor = FactoryFeatureExtractor.nonmax(new ConfigExtract(extractRadius, detectThreshold, extractRadius, true));
    GeneralFeatureDetector<T, D> detector = new GeneralFeatureDetector<>(intensity, extractor);
    detector.setMaxFeatures(maxFeatures);
    AnyImageDerivative<T, D> deriv = GImageDerivativeOps.derivativeForScaleSpace(imageType, derivType);
    ImageFunctionSparse<T> sparseLaplace = FactoryDerivativeSparse.createLaplacian(imageType, null);
    return new FeatureLaplacePyramid<>(detector, sparseLaplace, deriv, 2);
}

Example 3 with ConfigExtract

use of boofcv.abst.feature.detect.extract.ConfigExtract in project BoofCV by lessthanoptimal.

the class FactoryInterestPointAlgs method harrisPyramid.

/**
 * Creates a {@link FeaturePyramid} which is uses the Harris corner detector.
 *
 * @param extractRadius   Size of the feature used to detect the corners.
 * @param detectThreshold Minimum corner intensity required
 * @param maxFeatures     Max number of features that can be found.
 * @param imageType       Type of input image.
 * @param derivType       Image derivative type.
 * @return CornerLaplaceScaleSpace
 */
public static <T extends ImageGray<T>, D extends ImageGray<D>> FeaturePyramid<T, D> harrisPyramid(int extractRadius, float detectThreshold, int maxFeatures, Class<T> imageType, Class<D> derivType) {
    GradientCornerIntensity<D> harris = FactoryIntensityPointAlg.harris(extractRadius, 0.04f, false, derivType);
    GeneralFeatureIntensity<T, D> intensity = new WrapperGradientCornerIntensity<>(harris);
    NonMaxSuppression extractor = FactoryFeatureExtractor.nonmax(new ConfigExtract(extractRadius, detectThreshold, extractRadius, true));
    GeneralFeatureDetector<T, D> detector = new GeneralFeatureDetector<>(intensity, extractor);
    detector.setMaxFeatures(maxFeatures);
    AnyImageDerivative<T, D> deriv = GImageDerivativeOps.derivativeForScaleSpace(imageType, derivType);
    return new FeaturePyramid<>(detector, deriv, 2);
}

Example 4 with ConfigExtract

use of boofcv.abst.feature.detect.extract.ConfigExtract in project BoofCV by lessthanoptimal.

the class FactoryInterestPointAlgs method hessianPyramid.

/**
 * Creates a {@link FeaturePyramid} which is uses a hessian blob detector.
 *
 * @param extractRadius   Size of the feature used to detect the corners.
 * @param detectThreshold Minimum corner intensity required
 * @param maxFeatures     Max number of features that can be found.
 * @param imageType       Type of input image.
 * @param derivType       Image derivative type.
 * @return CornerLaplaceScaleSpace
 */
public static <T extends ImageGray<T>, D extends ImageGray<D>> FeaturePyramid<T, D> hessianPyramid(int extractRadius, float detectThreshold, int maxFeatures, Class<T> imageType, Class<D> derivType) {
    GeneralFeatureIntensity<T, D> intensity = new WrapperHessianBlobIntensity<>(HessianBlobIntensity.Type.DETERMINANT, derivType);
    NonMaxSuppression extractor = FactoryFeatureExtractor.nonmax(new ConfigExtract(extractRadius, detectThreshold, extractRadius, true));
    GeneralFeatureDetector<T, D> detector = new GeneralFeatureDetector<>(intensity, extractor);
    detector.setMaxFeatures(maxFeatures);
    AnyImageDerivative<T, D> deriv = GImageDerivativeOps.derivativeForScaleSpace(imageType, derivType);
    return new FeaturePyramid<>(detector, deriv, 2);
}

Example 5 with ConfigExtract

use of boofcv.abst.feature.detect.extract.ConfigExtract in project BoofCV by lessthanoptimal.

the class CompareFeatureExtractorApp method doProcess.

private synchronized void doProcess() {
    // System.out.println("radius "+radius+" min separation "+minSeparation+" thresholdFraction "+thresholdFraction+" numFeatures "+numFeatures);
    deriv.setInput(grayImage);
    D derivX = deriv.getDerivative(true);
    D derivY = deriv.getDerivative(false);
    D derivXX = deriv.getDerivative(true, true);
    D derivYY = deriv.getDerivative(false, false);
    D derivXY = deriv.getDerivative(true, false);
    // todo modifying buffered images which might be actively being displayed, could mess up swing
    intensityAlg.process(grayImage, derivX, derivY, derivXX, derivYY, derivXY);
    GrayF32 intensity = intensityAlg.getIntensity();
    intensityImage = VisualizeImageData.colorizeSign(intensityAlg.getIntensity(), null, ImageStatistics.maxAbs(intensity));
    float max = ImageStatistics.maxAbs(intensity);
    float threshold = max * thresholdFraction;
    NonMaxSuppression extractor = FactoryFeatureExtractor.nonmax(new ConfigExtract(minSeparation, threshold, radius, true));
    GeneralFeatureDetector<T, D> detector = new GeneralFeatureDetector<>(intensityAlg, extractor);
    detector.setMaxFeatures(numFeatures);
    detector.process(grayImage, derivX, derivY, derivXX, derivYY, derivXY);
    QueueCorner foundCorners = detector.getMaximums();
    render.reset();
    for (int i = 0; i < foundCorners.size(); i++) {
        Point2D_I16 p = foundCorners.get(i);
        render.addPoint(p.x, p.y, 3, Color.RED);
    }
    Graphics2D g2 = workImage.createGraphics();
    g2.drawImage(input, 0, 0, grayImage.width, grayImage.height, null);
    render.draw(g2);
    drawImage();
}