Extending template_matching tutorial with Java (#8043)
* Extending template_matching tutorial with Java * adding mask to java version of the tutorial * adding the python toggle and code * updating table of content * adding py and java to table of content * adding mask to python * going back to markdown with duplicated text * non duplicated text
This commit is contained in:
Cartucho
committed by
Maksim Shabunin
Maksim Shabunin
parent
3b669149d2
commit
2055bcc807
@@ -0,0 +1,196 @@
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import org.opencv.core.*;
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import org.opencv.core.Point;
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import org.opencv.imgcodecs.Imgcodecs;
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import org.opencv.imgproc.Imgproc;
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import javax.swing.*;
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import javax.swing.event.ChangeEvent;
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import javax.swing.event.ChangeListener;
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import java.awt.*;
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import java.awt.image.BufferedImage;
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import java.awt.image.DataBufferByte;
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import java.util.*;
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class MatchTemplateDemoRun implements ChangeListener{
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//! [declare]
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/// Global Variables
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Boolean use_mask = false;
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Mat img = new Mat(), templ = new Mat();
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Mat mask = new Mat();
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int match_method;
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JLabel imgDisplay = new JLabel(), resultDisplay = new JLabel();
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//! [declare]
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public void run(String[] args) {
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if (args.length < 2)
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{
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System.out.println("Not enough parameters");
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System.out.println("Program arguments:\n<image_name> <template_name> [<mask_name>]");
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System.exit(-1);
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}
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//! [load_image]
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/// Load image and template
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img = Imgcodecs.imread( args[0], Imgcodecs.IMREAD_COLOR );
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templ = Imgcodecs.imread( args[1], Imgcodecs.IMREAD_COLOR );
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//! [load_image]
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if(args.length > 2) {
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use_mask = true;
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mask = Imgcodecs.imread( args[2], Imgcodecs.IMREAD_COLOR );
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}
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if(img.empty() || templ.empty() || (use_mask && mask.empty()))
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{
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System.out.println("Can't read one of the images");
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System.exit(-1);
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}
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matchingMethod();
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createJFrame();
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}
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private void matchingMethod() {
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Mat result = new Mat();
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//! [copy_source]
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/// Source image to display
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Mat img_display = new Mat();
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img.copyTo( img_display );
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//! [copy_source]
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//! [create_result_matrix]
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/// Create the result matrix
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int result_cols = img.cols() - templ.cols() + 1;
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int result_rows = img.rows() - templ.rows() + 1;
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result.create( result_rows, result_cols, CvType.CV_32FC1 );
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//! [create_result_matrix]
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//! [match_template]
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/// Do the Matching and Normalize
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Boolean method_accepts_mask = (Imgproc.TM_SQDIFF == match_method ||
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match_method == Imgproc.TM_CCORR_NORMED);
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if (use_mask && method_accepts_mask)
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{ Imgproc.matchTemplate( img, templ, result, match_method, mask); }
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else
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{ Imgproc.matchTemplate( img, templ, result, match_method); }
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//! [match_template]
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//! [normalize]
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Core.normalize( result, result, 0, 1, Core.NORM_MINMAX, -1, new Mat() );
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//! [normalize]
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//! [best_match]
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/// Localizing the best match with minMaxLoc
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double minVal; double maxVal;
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Point matchLoc;
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Core.MinMaxLocResult mmr = Core.minMaxLoc( result );
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//! [best_match]
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//! [match_loc]
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/// For SQDIFF and SQDIFF_NORMED, the best matches are lower values.
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// For all the other methods, the higher the better
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if( match_method == Imgproc.TM_SQDIFF || match_method == Imgproc.TM_SQDIFF_NORMED )
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{ matchLoc = mmr.minLoc; }
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else
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{ matchLoc = mmr.maxLoc; }
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//! [match_loc]
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//! [imshow]
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/// Show me what you got
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Imgproc.rectangle(img_display, matchLoc, new Point(matchLoc.x + templ.cols(),
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matchLoc.y + templ.rows()), new Scalar(0, 0, 0), 2, 8, 0);
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Imgproc.rectangle(result, matchLoc, new Point(matchLoc.x + templ.cols(),
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matchLoc.y + templ.rows()), new Scalar(0, 0, 0), 2, 8, 0);
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Image tmpImg = toBufferedImage(img_display);
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ImageIcon icon = new ImageIcon(tmpImg);
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imgDisplay.setIcon(icon);
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result.convertTo(result, CvType.CV_8UC1, 255.0);
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tmpImg = toBufferedImage(result);
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icon = new ImageIcon(tmpImg);
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resultDisplay.setIcon(icon);
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//! [imshow]
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}
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public void stateChanged(ChangeEvent e) {
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JSlider source = (JSlider) e.getSource();
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if (!source.getValueIsAdjusting()) {
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match_method = (int)source.getValue();
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matchingMethod();
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}
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}
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public Image toBufferedImage(Mat m) {
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int type = BufferedImage.TYPE_BYTE_GRAY;
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if ( m.channels() > 1 ) {
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type = BufferedImage.TYPE_3BYTE_BGR;
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}
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int bufferSize = m.channels()*m.cols()*m.rows();
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byte [] b = new byte[bufferSize];
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m.get(0,0,b); // get all the pixels
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BufferedImage image = new BufferedImage(m.cols(),m.rows(), type);
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final byte[] targetPixels = ((DataBufferByte) image.getRaster().getDataBuffer()).getData();
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System.arraycopy(b, 0, targetPixels, 0, b.length);
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return image;
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}
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private void createJFrame() {
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String title = "Source image; Control; Result image";
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JFrame frame = new JFrame(title);
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frame.setLayout(new GridLayout(2, 2));
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frame.add(imgDisplay);
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//! [create_trackbar]
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int min = 0, max = 5;
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JSlider slider = new JSlider(JSlider.VERTICAL, min, max, match_method);
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//! [create_trackbar]
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slider.setPaintTicks(true);
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slider.setPaintLabels(true);
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// Set the spacing for the minor tick mark
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slider.setMinorTickSpacing(1);
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// Customizing the labels
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Hashtable labelTable = new Hashtable();
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labelTable.put( new Integer( 0 ), new JLabel("0 - SQDIFF") );
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labelTable.put( new Integer( 1 ), new JLabel("1 - SQDIFF NORMED") );
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labelTable.put( new Integer( 2 ), new JLabel("2 - TM CCORR") );
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labelTable.put( new Integer( 3 ), new JLabel("3 - TM CCORR NORMED") );
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labelTable.put( new Integer( 4 ), new JLabel("4 - TM COEFF") );
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labelTable.put( new Integer( 5 ), new JLabel("5 - TM COEFF NORMED : (Method)") );
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slider.setLabelTable( labelTable );
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slider.addChangeListener(this);
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frame.add(slider);
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frame.add(resultDisplay);
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frame.setDefaultCloseOperation(JFrame.EXIT_ON_CLOSE);
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frame.pack();
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frame.setVisible(true);
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}
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}
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public class MatchTemplateDemo
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{
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public static void main(String[] args) {
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// load the native OpenCV library
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System.loadLibrary(Core.NATIVE_LIBRARY_NAME);
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// run code
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new MatchTemplateDemoRun().run(args);
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}
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}
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