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Merge pull request #11598 from catree:add_tutorial_features2d_java_python

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This commit is contained in:
Alexander Alekhin
2018-05-29 15:18:44 +00:00
parent c90e65ce4b ade21f142e
commit d738f56d83
43 changed files with 2140 additions and 583 deletions
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samples/java/tutorial_code/TrackingMotion/corner_subpixels/CornerSubPixDemo.java
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import java.awt.BorderLayout;
import java.awt.Container;
import java.awt.Image;
import java.util.Random;
import javax.swing.BoxLayout;
import javax.swing.ImageIcon;
import javax.swing.JFrame;
import javax.swing.JLabel;
import javax.swing.JPanel;
import javax.swing.JSlider;
import javax.swing.event.ChangeEvent;
import javax.swing.event.ChangeListener;
import org.opencv.core.Core;
import org.opencv.core.CvType;
import org.opencv.core.Mat;
import org.opencv.core.MatOfPoint;
import org.opencv.core.Point;
import org.opencv.core.Scalar;
import org.opencv.core.Size;
import org.opencv.core.TermCriteria;
import org.opencv.highgui.HighGui;
import org.opencv.imgcodecs.Imgcodecs;
import org.opencv.imgproc.Imgproc;
class CornerSubPix {
private Mat src = new Mat();
private Mat srcGray = new Mat();
private JFrame frame;
private JLabel imgLabel;
private static final int MAX_CORNERS = 25;
private int maxCorners = 10;
private Random rng = new Random(12345);
public CornerSubPix(String[] args) {
/// Load source image and convert it to gray
String filename = args.length > 0 ? args[0] : "../data/pic3.png";
src = Imgcodecs.imread(filename);
if (src.empty()) {
System.err.println("Cannot read image: " + filename);
System.exit(0);
}
Imgproc.cvtColor(src, srcGray, Imgproc.COLOR_BGR2GRAY);
// Create and set up the window.
frame = new JFrame("Shi-Tomasi corner detector demo");
frame.setDefaultCloseOperation(JFrame.EXIT_ON_CLOSE);
// Set up the content pane.
Image img = HighGui.toBufferedImage(src);
addComponentsToPane(frame.getContentPane(), img);
// Use the content pane's default BorderLayout. No need for
// setLayout(new BorderLayout());
// Display the window.
frame.pack();
frame.setVisible(true);
update();
}
private void addComponentsToPane(Container pane, Image img) {
if (!(pane.getLayout() instanceof BorderLayout)) {
pane.add(new JLabel("Container doesn't use BorderLayout!"));
return;
}
JPanel sliderPanel = new JPanel();
sliderPanel.setLayout(new BoxLayout(sliderPanel, BoxLayout.PAGE_AXIS));
sliderPanel.add(new JLabel("Max corners:"));
JSlider slider = new JSlider(0, MAX_CORNERS, maxCorners);
slider.setMajorTickSpacing(20);
slider.setMinorTickSpacing(10);
slider.setPaintTicks(true);
slider.setPaintLabels(true);
slider.addChangeListener(new ChangeListener() {
@Override
public void stateChanged(ChangeEvent e) {
JSlider source = (JSlider) e.getSource();
maxCorners = source.getValue();
update();
}
});
sliderPanel.add(slider);
pane.add(sliderPanel, BorderLayout.PAGE_START);
imgLabel = new JLabel(new ImageIcon(img));
pane.add(imgLabel, BorderLayout.CENTER);
}
private void update() {
/// Parameters for Shi-Tomasi algorithm
maxCorners = Math.max(maxCorners, 1);
MatOfPoint corners = new MatOfPoint();
double qualityLevel = 0.01;
double minDistance = 10;
int blockSize = 3, gradientSize = 3;
boolean useHarrisDetector = false;
double k = 0.04;
/// Copy the source image
Mat copy = src.clone();
/// Apply corner detection
Imgproc.goodFeaturesToTrack(srcGray, corners, maxCorners, qualityLevel, minDistance, new Mat(),
blockSize, gradientSize, useHarrisDetector, k);
/// Draw corners detected
System.out.println("** Number of corners detected: " + corners.rows());
int[] cornersData = new int[(int) (corners.total() * corners.channels())];
corners.get(0, 0, cornersData);
int radius = 4;
Mat matCorners = new Mat(corners.rows(), 2, CvType.CV_32F);
float[] matCornersData = new float[(int) (matCorners.total() * matCorners.channels())];
matCorners.get(0, 0, matCornersData);
for (int i = 0; i < corners.rows(); i++) {
Imgproc.circle(copy, new Point(cornersData[i * 2], cornersData[i * 2 + 1]), radius,
new Scalar(rng.nextInt(256), rng.nextInt(256), rng.nextInt(256)), Core.FILLED);
matCornersData[i * 2] = cornersData[i * 2];
matCornersData[i * 2 + 1] = cornersData[i * 2 + 1];
}
matCorners.put(0, 0, matCornersData);
imgLabel.setIcon(new ImageIcon(HighGui.toBufferedImage(copy)));
frame.repaint();
/// Set the needed parameters to find the refined corners
Size winSize = new Size(5, 5);
Size zeroZone = new Size(-1, -1);
TermCriteria criteria = new TermCriteria(TermCriteria.EPS + TermCriteria.COUNT, 40, 0.001);
/// Calculate the refined corner locations
Imgproc.cornerSubPix(srcGray, matCorners, winSize, zeroZone, criteria);
/// Write them down
matCorners.get(0, 0, matCornersData);
for (int i = 0; i < corners.rows(); i++) {
System.out.println(
" -- Refined Corner [" + i + "] (" + matCornersData[i * 2] + "," + matCornersData[i * 2 + 1] + ")");
}
}
}
public class CornerSubPixDemo {
public static void main(String[] args) {
// Load the native OpenCV library
System.loadLibrary(Core.NATIVE_LIBRARY_NAME);
// Schedule a job for the event dispatch thread:
// creating and showing this application's GUI.
javax.swing.SwingUtilities.invokeLater(new Runnable() {
@Override
public void run() {
new CornerSubPix(args);
}
});
}
}
samples/java/tutorial_code/TrackingMotion/generic_corner_detector/CornerDetectorDemo.java
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import java.awt.BorderLayout;
import java.awt.Container;
import java.awt.Image;
import java.util.Random;
import javax.swing.BoxLayout;
import javax.swing.ImageIcon;
import javax.swing.JFrame;
import javax.swing.JLabel;
import javax.swing.JPanel;
import javax.swing.JSlider;
import javax.swing.event.ChangeEvent;
import javax.swing.event.ChangeListener;
import org.opencv.core.Core;
import org.opencv.core.Core.MinMaxLocResult;
import org.opencv.core.CvType;
import org.opencv.core.Mat;
import org.opencv.core.Point;
import org.opencv.core.Scalar;
import org.opencv.highgui.HighGui;
import org.opencv.imgcodecs.Imgcodecs;
import org.opencv.imgproc.Imgproc;
class CornerDetector {
private Mat src = new Mat();
private Mat srcGray = new Mat();
private Mat harrisDst = new Mat();
private Mat shiTomasiDst = new Mat();
private Mat harrisCopy = new Mat();
private Mat shiTomasiCopy = new Mat();
private Mat Mc = new Mat();
private JFrame frame;
private JLabel harrisImgLabel;
private JLabel shiTomasiImgLabel;
private static final int MAX_QUALITY_LEVEL = 100;
private int qualityLevel = 50;
private double harrisMinVal;
private double harrisMaxVal;
private double shiTomasiMinVal;
private double shiTomasiMaxVal;
private Random rng = new Random(12345);
public CornerDetector(String[] args) {
/// Load source image and convert it to gray
String filename = args.length > 0 ? args[0] : "../data/building.jpg";
src = Imgcodecs.imread(filename);
if (src.empty()) {
System.err.println("Cannot read image: " + filename);
System.exit(0);
}
Imgproc.cvtColor(src, srcGray, Imgproc.COLOR_BGR2GRAY);
// Create and set up the window.
frame = new JFrame("Creating your own corner detector demo");
frame.setDefaultCloseOperation(JFrame.EXIT_ON_CLOSE);
// Set up the content pane.
Image img = HighGui.toBufferedImage(src);
addComponentsToPane(frame.getContentPane(), img);
// Use the content pane's default BorderLayout. No need for
// setLayout(new BorderLayout());
// Display the window.
frame.pack();
frame.setVisible(true);
/// Set some parameters
int blockSize = 3, apertureSize = 3;
/// My Harris matrix -- Using cornerEigenValsAndVecs
Imgproc.cornerEigenValsAndVecs(srcGray, harrisDst, blockSize, apertureSize);
/* calculate Mc */
Mc = Mat.zeros(srcGray.size(), CvType.CV_32F);
float[] harrisData = new float[(int) (harrisDst.total() * harrisDst.channels())];
harrisDst.get(0, 0, harrisData);
float[] McData = new float[(int) (Mc.total() * Mc.channels())];
Mc.get(0, 0, McData);
for( int i = 0; i < srcGray.rows(); i++ ) {
for( int j = 0; j < srcGray.cols(); j++ ) {
float lambda1 = harrisData[(i*srcGray.cols() + j) * 6];
float lambda2 = harrisData[(i*srcGray.cols() + j) * 6 + 1];
McData[i*srcGray.cols()+j] = (float) (lambda1*lambda2 - 0.04f*Math.pow( ( lambda1 + lambda2 ), 2 ));
}
}
Mc.put(0, 0, McData);
MinMaxLocResult res = Core.minMaxLoc(Mc);
harrisMinVal = res.minVal;
harrisMaxVal = res.maxVal;
/// My Shi-Tomasi -- Using cornerMinEigenVal
Imgproc.cornerMinEigenVal(srcGray, shiTomasiDst, blockSize, apertureSize);
res = Core.minMaxLoc(shiTomasiDst);
shiTomasiMinVal = res.minVal;
shiTomasiMaxVal = res.maxVal;
update();
}
private void addComponentsToPane(Container pane, Image img) {
if (!(pane.getLayout() instanceof BorderLayout)) {
pane.add(new JLabel("Container doesn't use BorderLayout!"));
return;
}
JPanel sliderPanel = new JPanel();
sliderPanel.setLayout(new BoxLayout(sliderPanel, BoxLayout.PAGE_AXIS));
sliderPanel.add(new JLabel("Max corners:"));
JSlider slider = new JSlider(0, MAX_QUALITY_LEVEL, qualityLevel);
slider.setMajorTickSpacing(20);
slider.setMinorTickSpacing(10);
slider.setPaintTicks(true);
slider.setPaintLabels(true);
slider.addChangeListener(new ChangeListener() {
@Override
public void stateChanged(ChangeEvent e) {
JSlider source = (JSlider) e.getSource();
qualityLevel = source.getValue();
update();
}
});
sliderPanel.add(slider);
pane.add(sliderPanel, BorderLayout.PAGE_START);
JPanel imgPanel = new JPanel();
harrisImgLabel = new JLabel(new ImageIcon(img));
shiTomasiImgLabel = new JLabel(new ImageIcon(img));
imgPanel.add(harrisImgLabel);
imgPanel.add(shiTomasiImgLabel);
pane.add(imgPanel, BorderLayout.CENTER);
}
private void update() {
int qualityLevelVal = Math.max(qualityLevel, 1);
//Harris
harrisCopy = src.clone();
float[] McData = new float[(int) (Mc.total() * Mc.channels())];
Mc.get(0, 0, McData);
for (int i = 0; i < srcGray.rows(); i++) {
for (int j = 0; j < srcGray.cols(); j++) {
if (McData[i * srcGray.cols() + j] > harrisMinVal
+ (harrisMaxVal - harrisMinVal) * qualityLevelVal / MAX_QUALITY_LEVEL) {
Imgproc.circle(harrisCopy, new Point(j, i), 4,
new Scalar(rng.nextInt(256), rng.nextInt(256), rng.nextInt(256)), Core.FILLED);
}
}
}
//Shi-Tomasi
shiTomasiCopy = src.clone();
float[] shiTomasiData = new float[(int) (shiTomasiDst.total() * shiTomasiDst.channels())];
shiTomasiDst.get(0, 0, shiTomasiData);
for (int i = 0; i < srcGray.rows(); i++) {
for (int j = 0; j < srcGray.cols(); j++) {
if (shiTomasiData[i * srcGray.cols() + j] > shiTomasiMinVal
+ (shiTomasiMaxVal - shiTomasiMinVal) * qualityLevelVal / MAX_QUALITY_LEVEL) {
Imgproc.circle(shiTomasiCopy, new Point(j, i), 4,
new Scalar(rng.nextInt(256), rng.nextInt(256), rng.nextInt(256)), Core.FILLED);
}
}
}
harrisImgLabel.setIcon(new ImageIcon(HighGui.toBufferedImage(harrisCopy)));
shiTomasiImgLabel.setIcon(new ImageIcon(HighGui.toBufferedImage(shiTomasiCopy)));
frame.repaint();
}
}
public class CornerDetectorDemo {
public static void main(String[] args) {
// Load the native OpenCV library
System.loadLibrary(Core.NATIVE_LIBRARY_NAME);
// Schedule a job for the event dispatch thread:
// creating and showing this application's GUI.
javax.swing.SwingUtilities.invokeLater(new Runnable() {
@Override
public void run() {
new CornerDetector(args);
}
});
}
}
samples/java/tutorial_code/TrackingMotion/good_features_to_track/GoodFeaturesToTrackDemo.java
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import java.awt.BorderLayout;
import java.awt.Container;
import java.awt.Image;
import java.util.Random;
import javax.swing.BoxLayout;
import javax.swing.ImageIcon;
import javax.swing.JFrame;
import javax.swing.JLabel;
import javax.swing.JPanel;
import javax.swing.JSlider;
import javax.swing.event.ChangeEvent;
import javax.swing.event.ChangeListener;
import org.opencv.core.Core;
import org.opencv.core.Mat;
import org.opencv.core.MatOfPoint;
import org.opencv.core.Point;
import org.opencv.core.Scalar;
import org.opencv.highgui.HighGui;
import org.opencv.imgcodecs.Imgcodecs;
import org.opencv.imgproc.Imgproc;
class GoodFeaturesToTrack {
private Mat src = new Mat();
private Mat srcGray = new Mat();
private JFrame frame;
private JLabel imgLabel;
private static final int MAX_THRESHOLD = 100;
private int maxCorners = 23;
private Random rng = new Random(12345);
public GoodFeaturesToTrack(String[] args) {
/// Load source image and convert it to gray
String filename = args.length > 0 ? args[0] : "../data/pic3.png";
src = Imgcodecs.imread(filename);
if (src.empty()) {
System.err.println("Cannot read image: " + filename);
System.exit(0);
}
Imgproc.cvtColor(src, srcGray, Imgproc.COLOR_BGR2GRAY);
// Create and set up the window.
frame = new JFrame("Shi-Tomasi corner detector demo");
frame.setDefaultCloseOperation(JFrame.EXIT_ON_CLOSE);
// Set up the content pane.
Image img = HighGui.toBufferedImage(src);
addComponentsToPane(frame.getContentPane(), img);
// Use the content pane's default BorderLayout. No need for
// setLayout(new BorderLayout());
// Display the window.
frame.pack();
frame.setVisible(true);
update();
}
private void addComponentsToPane(Container pane, Image img) {
if (!(pane.getLayout() instanceof BorderLayout)) {
pane.add(new JLabel("Container doesn't use BorderLayout!"));
return;
}
JPanel sliderPanel = new JPanel();
sliderPanel.setLayout(new BoxLayout(sliderPanel, BoxLayout.PAGE_AXIS));
sliderPanel.add(new JLabel("Max corners:"));
JSlider slider = new JSlider(0, MAX_THRESHOLD, maxCorners);
slider.setMajorTickSpacing(20);
slider.setMinorTickSpacing(10);
slider.setPaintTicks(true);
slider.setPaintLabels(true);
slider.addChangeListener(new ChangeListener() {
@Override
public void stateChanged(ChangeEvent e) {
JSlider source = (JSlider) e.getSource();
maxCorners = source.getValue();
update();
}
});
sliderPanel.add(slider);
pane.add(sliderPanel, BorderLayout.PAGE_START);
imgLabel = new JLabel(new ImageIcon(img));
pane.add(imgLabel, BorderLayout.CENTER);
}
private void update() {
/// Parameters for Shi-Tomasi algorithm
maxCorners = Math.max(maxCorners, 1);
MatOfPoint corners = new MatOfPoint();
double qualityLevel = 0.01;
double minDistance = 10;
int blockSize = 3, gradientSize = 3;
boolean useHarrisDetector = false;
double k = 0.04;
/// Copy the source image
Mat copy = src.clone();
/// Apply corner detection
Imgproc.goodFeaturesToTrack(srcGray, corners, maxCorners, qualityLevel, minDistance, new Mat(),
blockSize, gradientSize, useHarrisDetector, k);
/// Draw corners detected
System.out.println("** Number of corners detected: " + corners.rows());
int[] cornersData = new int[(int) (corners.total() * corners.channels())];
corners.get(0, 0, cornersData);
int radius = 4;
for (int i = 0; i < corners.rows(); i++) {
Imgproc.circle(copy, new Point(cornersData[i * 2], cornersData[i * 2 + 1]), radius,
new Scalar(rng.nextInt(256), rng.nextInt(256), rng.nextInt(256)), Core.FILLED);
}
imgLabel.setIcon(new ImageIcon(HighGui.toBufferedImage(copy)));
frame.repaint();
}
}
public class GoodFeaturesToTrackDemo {
public static void main(String[] args) {
// Load the native OpenCV library
System.loadLibrary(Core.NATIVE_LIBRARY_NAME);
// Schedule a job for the event dispatch thread:
// creating and showing this application's GUI.
javax.swing.SwingUtilities.invokeLater(new Runnable() {
@Override
public void run() {
new GoodFeaturesToTrack(args);
}
});
}
}
samples/java/tutorial_code/TrackingMotion/harris_detector/CornerHarrisDemo.java
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import java.awt.BorderLayout;
import java.awt.Container;
import java.awt.Image;
import javax.swing.BoxLayout;
import javax.swing.ImageIcon;
import javax.swing.JFrame;
import javax.swing.JLabel;
import javax.swing.JPanel;
import javax.swing.JSlider;
import javax.swing.event.ChangeEvent;
import javax.swing.event.ChangeListener;
import org.opencv.core.Core;
import org.opencv.core.CvType;
import org.opencv.core.Mat;
import org.opencv.core.Point;
import org.opencv.core.Scalar;
import org.opencv.highgui.HighGui;
import org.opencv.imgcodecs.Imgcodecs;
import org.opencv.imgproc.Imgproc;
class CornerHarris {
private Mat srcGray = new Mat();
private Mat dst = new Mat();
private Mat dstNorm = new Mat();
private Mat dstNormScaled = new Mat();
private JFrame frame;
private JLabel imgLabel;
private JLabel cornerLabel;
private static final int MAX_THRESHOLD = 255;
private int threshold = 200;
public CornerHarris(String[] args) {
/// Load source image and convert it to gray
String filename = args.length > 0 ? args[0] : "../data/building.jpg";
Mat src = Imgcodecs.imread(filename);
if (src.empty()) {
System.err.println("Cannot read image: " + filename);
System.exit(0);
}
Imgproc.cvtColor(src, srcGray, Imgproc.COLOR_BGR2GRAY);
// Create and set up the window.
frame = new JFrame("Harris corner detector demo");
frame.setDefaultCloseOperation(JFrame.EXIT_ON_CLOSE);
// Set up the content pane.
Image img = HighGui.toBufferedImage(src);
addComponentsToPane(frame.getContentPane(), img);
// Use the content pane's default BorderLayout. No need for
// setLayout(new BorderLayout());
// Display the window.
frame.pack();
frame.setVisible(true);
update();
}
private void addComponentsToPane(Container pane, Image img) {
if (!(pane.getLayout() instanceof BorderLayout)) {
pane.add(new JLabel("Container doesn't use BorderLayout!"));
return;
}
JPanel sliderPanel = new JPanel();
sliderPanel.setLayout(new BoxLayout(sliderPanel, BoxLayout.PAGE_AXIS));
sliderPanel.add(new JLabel("Threshold: "));
JSlider slider = new JSlider(0, MAX_THRESHOLD, threshold);
slider.setMajorTickSpacing(20);
slider.setMinorTickSpacing(10);
slider.setPaintTicks(true);
slider.setPaintLabels(true);
slider.addChangeListener(new ChangeListener() {
@Override
public void stateChanged(ChangeEvent e) {
JSlider source = (JSlider) e.getSource();
threshold = source.getValue();
update();
}
});
sliderPanel.add(slider);
pane.add(sliderPanel, BorderLayout.PAGE_START);
JPanel imgPanel = new JPanel();
imgLabel = new JLabel(new ImageIcon(img));
imgPanel.add(imgLabel);
Mat blackImg = Mat.zeros(srcGray.size(), CvType.CV_8U);
cornerLabel = new JLabel(new ImageIcon(HighGui.toBufferedImage(blackImg)));
imgPanel.add(cornerLabel);
pane.add(imgPanel, BorderLayout.CENTER);
}
private void update() {
dst = Mat.zeros(srcGray.size(), CvType.CV_32F);
/// Detector parameters
int blockSize = 2;
int apertureSize = 3;
double k = 0.04;
/// Detecting corners
Imgproc.cornerHarris(srcGray, dst, blockSize, apertureSize, k);
/// Normalizing
Core.normalize(dst, dstNorm, 0, 255, Core.NORM_MINMAX);
Core.convertScaleAbs(dstNorm, dstNormScaled);
/// Drawing a circle around corners
float[] dstNormData = new float[(int) (dstNorm.total() * dstNorm.channels())];
dstNorm.get(0, 0, dstNormData);
for (int i = 0; i < dstNorm.rows(); i++) {
for (int j = 0; j < dstNorm.cols(); j++) {
if ((int) dstNormData[i * dstNorm.cols() + j] > threshold) {
Imgproc.circle(dstNormScaled, new Point(j, i), 5, new Scalar(0), 2, 8, 0);
}
}
}
cornerLabel.setIcon(new ImageIcon(HighGui.toBufferedImage(dstNormScaled)));
frame.repaint();
}
}
public class CornerHarrisDemo {
public static void main(String[] args) {
// Load the native OpenCV library
System.loadLibrary(Core.NATIVE_LIBRARY_NAME);
// Schedule a job for the event dispatch thread:
// creating and showing this application's GUI.
javax.swing.SwingUtilities.invokeLater(new Runnable() {
@Override
public void run() {
new CornerHarris(args);
}
});
}
}
samples/java/tutorial_code/features2D/feature_description/SURFMatchingDemo.java
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import org.opencv.core.Core;
import org.opencv.core.Mat;
import org.opencv.core.MatOfDMatch;
import org.opencv.core.MatOfKeyPoint;
import org.opencv.features2d.DescriptorMatcher;
import org.opencv.features2d.Features2d;
import org.opencv.highgui.HighGui;
import org.opencv.imgcodecs.Imgcodecs;
import org.opencv.xfeatures2d.SURF;
class SURFMatching {
public void run(String[] args) {
String filename1 = args.length > 1 ? args[0] : "../data/box.png";
String filename2 = args.length > 1 ? args[1] : "../data/box_in_scene.png";
Mat img1 = Imgcodecs.imread(filename1, Imgcodecs.IMREAD_GRAYSCALE);
Mat img2 = Imgcodecs.imread(filename2, Imgcodecs.IMREAD_GRAYSCALE);
if (img1.empty() || img2.empty()) {
System.err.println("Cannot read images!");
System.exit(0);
}
//-- Step 1: Detect the keypoints using SURF Detector, compute the descriptors
double hessianThreshold = 400;
int nOctaves = 4, nOctaveLayers = 3;
boolean extended = false, upright = false;
SURF detector = SURF.create(hessianThreshold, nOctaves, nOctaveLayers, extended, upright);
MatOfKeyPoint keypoints1 = new MatOfKeyPoint(), keypoints2 = new MatOfKeyPoint();
Mat descriptors1 = new Mat(), descriptors2 = new Mat();
detector.detectAndCompute(img1, new Mat(), keypoints1, descriptors1);
detector.detectAndCompute(img2, new Mat(), keypoints2, descriptors2);
//-- Step 2: Matching descriptor vectors with a brute force matcher
// Since SURF is a floating-point descriptor NORM_L2 is used
DescriptorMatcher matcher = DescriptorMatcher.create(DescriptorMatcher.BRUTEFORCE);
MatOfDMatch matches = new MatOfDMatch();
matcher.match(descriptors1, descriptors2, matches);
//-- Draw matches
Mat imgMatches = new Mat();
Features2d.drawMatches(img1, keypoints1, img2, keypoints2, matches, imgMatches);
HighGui.imshow("Matches", imgMatches);
HighGui.waitKey(0);
System.exit(0);
}
}
public class SURFMatchingDemo {
public static void main(String[] args) {
// Load the native OpenCV library
System.loadLibrary(Core.NATIVE_LIBRARY_NAME);
new SURFMatching().run(args);
}
}
samples/java/tutorial_code/features2D/feature_detection/SURFDetectionDemo.java
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import org.opencv.core.Core;
import org.opencv.core.Mat;
import org.opencv.core.MatOfKeyPoint;
import org.opencv.features2d.Features2d;
import org.opencv.highgui.HighGui;
import org.opencv.imgcodecs.Imgcodecs;
import org.opencv.xfeatures2d.SURF;
class SURFDetection {
public void run(String[] args) {
String filename = args.length > 0 ? args[0] : "../data/box.png";
Mat src = Imgcodecs.imread(filename, Imgcodecs.IMREAD_GRAYSCALE);
if (src.empty()) {
System.err.println("Cannot read image: " + filename);
System.exit(0);
}
//-- Step 1: Detect the keypoints using SURF Detector
double hessianThreshold = 400;
int nOctaves = 4, nOctaveLayers = 3;
boolean extended = false, upright = false;
SURF detector = SURF.create(hessianThreshold, nOctaves, nOctaveLayers, extended, upright);
MatOfKeyPoint keypoints = new MatOfKeyPoint();
detector.detect(src, keypoints);
//-- Draw keypoints
Features2d.drawKeypoints(src, keypoints, src);
//-- Show detected (drawn) keypoints
HighGui.imshow("SURF Keypoints", src);
HighGui.waitKey(0);
System.exit(0);
}
}
public class SURFDetectionDemo {
public static void main(String[] args) {
// Load the native OpenCV library
System.loadLibrary(Core.NATIVE_LIBRARY_NAME);
new SURFDetection().run(args);
}
}
samples/java/tutorial_code/features2D/feature_flann_matcher/SURFFLANNMatchingDemo.java
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import java.util.ArrayList;
import java.util.List;
import org.opencv.core.Core;
import org.opencv.core.DMatch;
import org.opencv.core.Mat;
import org.opencv.core.MatOfByte;
import org.opencv.core.MatOfDMatch;
import org.opencv.core.MatOfKeyPoint;
import org.opencv.core.Scalar;
import org.opencv.features2d.DescriptorMatcher;
import org.opencv.features2d.Features2d;
import org.opencv.highgui.HighGui;
import org.opencv.imgcodecs.Imgcodecs;
import org.opencv.xfeatures2d.SURF;
class SURFFLANNMatching {
public void run(String[] args) {
String filename1 = args.length > 1 ? args[0] : "../data/box.png";
String filename2 = args.length > 1 ? args[1] : "../data/box_in_scene.png";
Mat img1 = Imgcodecs.imread(filename1, Imgcodecs.IMREAD_GRAYSCALE);
Mat img2 = Imgcodecs.imread(filename2, Imgcodecs.IMREAD_GRAYSCALE);
if (img1.empty() || img2.empty()) {
System.err.println("Cannot read images!");
System.exit(0);
}
//-- Step 1: Detect the keypoints using SURF Detector, compute the descriptors
double hessianThreshold = 400;
int nOctaves = 4, nOctaveLayers = 3;
boolean extended = false, upright = false;
SURF detector = SURF.create(hessianThreshold, nOctaves, nOctaveLayers, extended, upright);
MatOfKeyPoint keypoints1 = new MatOfKeyPoint(), keypoints2 = new MatOfKeyPoint();
Mat descriptors1 = new Mat(), descriptors2 = new Mat();
detector.detectAndCompute(img1, new Mat(), keypoints1, descriptors1);
detector.detectAndCompute(img2, new Mat(), keypoints2, descriptors2);
//-- Step 2: Matching descriptor vectors with a FLANN based matcher
// Since SURF is a floating-point descriptor NORM_L2 is used
DescriptorMatcher matcher = DescriptorMatcher.create(DescriptorMatcher.FLANNBASED);
List<MatOfDMatch> knnMatches = new ArrayList<>();
matcher.knnMatch(descriptors1, descriptors2, knnMatches, 2);
//-- Filter matches using the Lowe's ratio test
float ratio_thresh = 0.7f;
List<DMatch> listOfGoodMatches = new ArrayList<>();
for (int i = 0; i < knnMatches.size(); i++) {
if (knnMatches.get(i).rows() > 1) {
DMatch[] matches = knnMatches.get(i).toArray();
if (matches[0].distance / matches[1].distance <= ratio_thresh) {
listOfGoodMatches.add(matches[0]);
}
}
}
MatOfDMatch goodMatches = new MatOfDMatch();
goodMatches.fromList(listOfGoodMatches);
//-- Draw matches
Mat imgMatches = new Mat();
Features2d.drawMatches(img1, keypoints1, img2, keypoints2, goodMatches, imgMatches, Scalar.all(-1),
Scalar.all(-1), new MatOfByte(), Features2d.NOT_DRAW_SINGLE_POINTS);
//-- Show detected matches
HighGui.imshow("Good Matches", imgMatches);
HighGui.waitKey(0);
System.exit(0);
}
}
public class SURFFLANNMatchingDemo {
public static void main(String[] args) {
// Load the native OpenCV library
System.loadLibrary(Core.NATIVE_LIBRARY_NAME);
new SURFFLANNMatching().run(args);
}
}
samples/java/tutorial_code/features2D/feature_homography/SURFFLANNMatchingHomographyDemo.java
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import java.util.ArrayList;
import java.util.List;
import org.opencv.calib3d.Calib3d;
import org.opencv.core.Core;
import org.opencv.core.CvType;
import org.opencv.core.DMatch;
import org.opencv.core.KeyPoint;
import org.opencv.core.Mat;
import org.opencv.core.MatOfByte;
import org.opencv.core.MatOfDMatch;
import org.opencv.core.MatOfKeyPoint;
import org.opencv.core.MatOfPoint2f;
import org.opencv.core.Point;
import org.opencv.core.Scalar;
import org.opencv.features2d.DescriptorMatcher;
import org.opencv.features2d.Features2d;
import org.opencv.highgui.HighGui;
import org.opencv.imgcodecs.Imgcodecs;
import org.opencv.imgproc.Imgproc;
import org.opencv.xfeatures2d.SURF;
class SURFFLANNMatchingHomography {
public void run(String[] args) {
String filenameObject = args.length > 1 ? args[0] : "../data/box.png";
String filenameScene = args.length > 1 ? args[1] : "../data/box_in_scene.png";
Mat imgObject = Imgcodecs.imread(filenameObject, Imgcodecs.IMREAD_GRAYSCALE);
Mat imgScene = Imgcodecs.imread(filenameScene, Imgcodecs.IMREAD_GRAYSCALE);
if (imgObject.empty() || imgScene.empty()) {
System.err.println("Cannot read images!");
System.exit(0);
}
//-- Step 1: Detect the keypoints using SURF Detector, compute the descriptors
double hessianThreshold = 400;
int nOctaves = 4, nOctaveLayers = 3;
boolean extended = false, upright = false;
SURF detector = SURF.create(hessianThreshold, nOctaves, nOctaveLayers, extended, upright);
MatOfKeyPoint keypointsObject = new MatOfKeyPoint(), keypointsScene = new MatOfKeyPoint();
Mat descriptorsObject = new Mat(), descriptorsScene = new Mat();
detector.detectAndCompute(imgObject, new Mat(), keypointsObject, descriptorsObject);
detector.detectAndCompute(imgScene, new Mat(), keypointsScene, descriptorsScene);
//-- Step 2: Matching descriptor vectors with a FLANN based matcher
// Since SURF is a floating-point descriptor NORM_L2 is used
DescriptorMatcher matcher = DescriptorMatcher.create(DescriptorMatcher.FLANNBASED);
List<MatOfDMatch> knnMatches = new ArrayList<>();
matcher.knnMatch(descriptorsObject, descriptorsScene, knnMatches, 2);
//-- Filter matches using the Lowe's ratio test
float ratio_thresh = 0.75f;
List<DMatch> listOfGoodMatches = new ArrayList<>();
for (int i = 0; i < knnMatches.size(); i++) {
if (knnMatches.get(i).rows() > 1) {
DMatch[] matches = knnMatches.get(i).toArray();
if (matches[0].distance / matches[1].distance <= ratio_thresh) {
listOfGoodMatches.add(matches[0]);
}
}
}
MatOfDMatch goodMatches = new MatOfDMatch();
goodMatches.fromList(listOfGoodMatches);
//-- Draw matches
Mat imgMatches = new Mat();
Features2d.drawMatches(imgObject, keypointsObject, imgScene, keypointsScene, goodMatches, imgMatches, Scalar.all(-1),
Scalar.all(-1), new MatOfByte(), Features2d.NOT_DRAW_SINGLE_POINTS);
//-- Localize the object
List<Point> obj = new ArrayList<>();
List<Point> scene = new ArrayList<>();
List<KeyPoint> listOfKeypointsObject = keypointsObject.toList();
List<KeyPoint> listOfKeypointsScene = keypointsScene.toList();
for (int i = 0; i < listOfGoodMatches.size(); i++) {
//-- Get the keypoints from the good matches
obj.add(listOfKeypointsObject.get(listOfGoodMatches.get(i).queryIdx).pt);
scene.add(listOfKeypointsScene.get(listOfGoodMatches.get(i).trainIdx).pt);
}
MatOfPoint2f objMat = new MatOfPoint2f(), sceneMat = new MatOfPoint2f();
objMat.fromList(obj);
sceneMat.fromList(scene);
double ransacReprojThreshold = 3.0;
Mat H = Calib3d.findHomography( objMat, sceneMat, Calib3d.RANSAC, ransacReprojThreshold );
//-- Get the corners from the image_1 ( the object to be "detected" )
Mat objCorners = new Mat(4, 1, CvType.CV_32FC2), sceneCorners = new Mat();
float[] objCornersData = new float[(int) (objCorners.total() * objCorners.channels())];
objCorners.get(0, 0, objCornersData);
objCornersData[0] = 0;
objCornersData[1] = 0;
objCornersData[2] = imgObject.cols();
objCornersData[3] = 0;
objCornersData[4] = imgObject.cols();
objCornersData[5] = imgObject.rows();
objCornersData[6] = 0;
objCornersData[7] = imgObject.rows();
objCorners.put(0, 0, objCornersData);
Core.perspectiveTransform(objCorners, sceneCorners, H);
float[] sceneCornersData = new float[(int) (sceneCorners.total() * sceneCorners.channels())];
sceneCorners.get(0, 0, sceneCornersData);
//-- Draw lines between the corners (the mapped object in the scene - image_2 )
Imgproc.line(imgMatches, new Point(sceneCornersData[0] + imgObject.cols(), sceneCornersData[1]),
new Point(sceneCornersData[2] + imgObject.cols(), sceneCornersData[3]), new Scalar(0, 255, 0), 4);
Imgproc.line(imgMatches, new Point(sceneCornersData[2] + imgObject.cols(), sceneCornersData[3]),
new Point(sceneCornersData[4] + imgObject.cols(), sceneCornersData[5]), new Scalar(0, 255, 0), 4);
Imgproc.line(imgMatches, new Point(sceneCornersData[4] + imgObject.cols(), sceneCornersData[5]),
new Point(sceneCornersData[6] + imgObject.cols(), sceneCornersData[7]), new Scalar(0, 255, 0), 4);
Imgproc.line(imgMatches, new Point(sceneCornersData[6] + imgObject.cols(), sceneCornersData[7]),
new Point(sceneCornersData[0] + imgObject.cols(), sceneCornersData[1]), new Scalar(0, 255, 0), 4);
//-- Show detected matches
HighGui.imshow("Good Matches & Object detection", imgMatches);
HighGui.waitKey(0);
System.exit(0);
}
}
public class SURFFLANNMatchingHomographyDemo {
public static void main(String[] args) {
// Load the native OpenCV library
System.loadLibrary(Core.NATIVE_LIBRARY_NAME);
new SURFFLANNMatchingHomography().run(args);
}
}