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Classifier.java
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Classifier.java
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package org.genericsystem.cv;
import java.io.File;
import java.util.Arrays;
import java.util.List;
import java.util.stream.Collectors;
import org.opencv.core.Core;
import org.opencv.core.DMatch;
import org.opencv.core.Mat;
import org.opencv.core.MatOfDMatch;
import org.opencv.core.MatOfKeyPoint;
import org.opencv.features2d.DescriptorExtractor;
import org.opencv.features2d.DescriptorMatcher;
import org.opencv.features2d.FeatureDetector;
import org.opencv.imgcodecs.Imgcodecs;
public class Classifier {
private final static String sourceDirectoryPath = "png";
static {
System.loadLibrary(Core.NATIVE_LIBRARY_NAME);
}
public static void main(String[] args) {
doWork(sourceDirectoryPath);
}
public static void doWork(String sourceDirectoryPath) {
List<File> images = Arrays.stream(new File(sourceDirectoryPath).listFiles()).filter(img -> img.getName().endsWith(".png")).collect(Collectors.toList());
for (File img1 : images) {
for (File img2 : images) {
compareFeature(img1.getPath(), img2.getPath());
}
}
};
public static int compareFeature(String filename1, String filename2) {
int retVal = 0;
long startTime = System.currentTimeMillis();
System.loadLibrary(Core.NATIVE_LIBRARY_NAME);
// Load images to compare
Mat img1 = Imgcodecs.imread(filename1, Imgcodecs.CV_LOAD_IMAGE_COLOR);
Mat img2 = Imgcodecs.imread(filename2, Imgcodecs.CV_LOAD_IMAGE_COLOR);
// Declare key point of images
MatOfKeyPoint keypoints1 = new MatOfKeyPoint();
MatOfKeyPoint keypoints2 = new MatOfKeyPoint();
Mat descriptors1 = new Mat();
Mat descriptors2 = new Mat();
// Definition of ORB key point detector and descriptor extractors
FeatureDetector detector = FeatureDetector.create(FeatureDetector.ORB);
DescriptorExtractor extractor = DescriptorExtractor.create(DescriptorExtractor.ORB);
// Detect key points
detector.detect(img1, keypoints1);
detector.detect(img2, keypoints2);
// Extract descriptors
extractor.compute(img1, keypoints1, descriptors1);
extractor.compute(img2, keypoints2, descriptors2);
// Definition of descriptor matcher
DescriptorMatcher matcher = DescriptorMatcher.create(DescriptorMatcher.BRUTEFORCE_HAMMING);
// Match points of two images
MatOfDMatch matches = new MatOfDMatch();
System.out.println("Type of Image1= " + descriptors1.type() + ", Type of Image2= " + descriptors2.type());
System.out.println("Cols of Image1= " + descriptors1.cols() + ", Cols of Image2= " + descriptors2.cols());
// Avoid to assertion failed
// Assertion failed (type == src2.type() && src1.cols == src2.cols && (type == CV_32F || type == CV_8U)
if (descriptors2.cols() == descriptors1.cols()) {
matcher.match(descriptors1, descriptors2, matches);
// Check matches of key points
DMatch[] match = matches.toArray();
double max_dist = 0;
double min_dist = 100;
for (int i = 0; i < descriptors1.rows(); i++) {
double dist = match[i].distance;
if (dist < min_dist)
min_dist = dist;
if (dist > max_dist)
max_dist = dist;
}
System.out.println("max_dist=" + max_dist + ", min_dist=" + min_dist);
// Extract good images (distances are under 10)
for (int i = 0; i < descriptors1.rows(); i++) {
if (match[i].distance <= 10) {
retVal++;
}
}
System.out.println("matching count=" + retVal);
}
long estimatedTime = System.currentTimeMillis() - startTime;
System.out.println("estimatedTime=" + estimatedTime + "ms");
return retVal;
}
}