boofcv.examples.features.ExampleInterestPoint Maven / Gradle / Ivy
/*
* Copyright (c) 2011-2017, Peter Abeles. All Rights Reserved.
*
* This file is part of BoofCV (http://boofcv.org).
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package boofcv.examples.features;
import boofcv.abst.feature.detect.interest.ConfigFastHessian;
import boofcv.abst.feature.detect.interest.InterestPointDetector;
import boofcv.factory.feature.detect.interest.FactoryInterestPoint;
import boofcv.gui.feature.FancyInterestPointRender;
import boofcv.gui.image.ShowImages;
import boofcv.io.UtilIO;
import boofcv.io.image.ConvertBufferedImage;
import boofcv.io.image.UtilImageIO;
import boofcv.struct.image.GrayF32;
import boofcv.struct.image.ImageGray;
import georegression.struct.point.Point2D_F64;
import java.awt.*;
import java.awt.image.BufferedImage;
/**
* Demonstrates how to detect interest points using the to use {@link InterestPointDetector} interface.
* InterestPointDetector makes it easy to switch between algorithms, but due to its abstraction it also cause
* calculations to be done multiple times. For example, if a detector requires the gradient and so does the description
* algorithm then that calculation will have to be done twice when using this interface. If the algorithms had
* been used directly then extra calculations could be avoided.
*
* If descriptors are also being computed, consider using the DetectDescribePoint interface instead. See
* {@link ExampleDetectDescribe}.
*
* @author Peter Abeles
*/
public class ExampleInterestPoint {
public static >
void detect( BufferedImage image , Class imageType ) {
T input = ConvertBufferedImage.convertFromSingle(image, null, imageType);
// Create a Fast Hessian detector from the SURF paper.
// Other detectors can be used in this example too.
InterestPointDetector detector = FactoryInterestPoint.fastHessian(
new ConfigFastHessian(10, 2, 100, 2, 9, 3, 4));
// find interest points in the image
detector.detect(input);
// Show the features
displayResults(image, detector);
}
private static >
void displayResults(BufferedImage image, InterestPointDetector detector)
{
Graphics2D g2 = image.createGraphics();
FancyInterestPointRender render = new FancyInterestPointRender();
for( int i = 0; i < detector.getNumberOfFeatures(); i++ ) {
Point2D_F64 pt = detector.getLocation(i);
// note how it checks the capabilities of the detector
if( detector.hasScale() ) {
int radius = (int)(detector.getRadius(i));
render.addCircle((int)pt.x,(int)pt.y,radius);
} else {
render.addPoint((int) pt.x, (int) pt.y);
}
}
// make the circle's thicker
g2.setStroke(new BasicStroke(3));
// just draw the features onto the input image
render.draw(g2);
ShowImages.showWindow(image, "Detected Features", true);
}
public static void main( String args[] ) {
BufferedImage image = UtilImageIO.loadImage(UtilIO.pathExample("sunflowers.jpg"));
detect(image, GrayF32.class);
}
}