Previous tutorial: Create your own corner detector
Next tutorial: Feature Detection
| Original author | Ana Huamán |
|---|---|
| Compatibility | OpenCV >= 3.0 |
Goals
In this tutorial you will learn how to
- Use the OpenCV function cv::cornerSubPix to find a more precise corner position (more precise than integer pixels).
Code
C++
The tutorial code is shown below. You can also download it from here
#include "opencv2/highgui.hpp"
#include "opencv2/imgproc.hpp"
#include <iostream>
using namespace cv;
using namespace std;
Mat src, src_gray;
int maxCorners = 10;
int maxTrackbar = 25;
RNG rng(12345);
const char* source_window = "Image";
void goodFeaturesToTrack_Demo( int, void* );
int main(int argc, char** argv)
{<!-- -->
CommandLineParser parser( argc, argv, "{@input | pic3.png | input image}" );
src = imread( samples::findFile( parser.get<String>( "@input" ) ) );
if( src.empty() )
{<!-- -->
cout << "Could not open or find the image!\
" << endl;
cout << "Usage: " << argv[0] << " <Input image>" << endl;
return -1;
}
cvtColor( src, src_gray, COLOR_BGR2GRAY );
namedWindow( source_window );
createTrackbar( "Max corners:", source_window, & amp;maxCorners, maxTrackbar, goodFeaturesToTrack_Demo );
imshow( source_window, src );
goodFeaturesToTrack_Demo(0, 0);
waitKey();
return 0;
}
void goodFeaturesToTrack_Demo( int, void* )
{<!-- -->
maxCorners = MAX(maxCorners, 1);
vector<Point2f> corners;
double qualityLevel = 0.01;
double minDistance = 10;
int blockSize = 3, gradientSize = 3;
bool useHarrisDetector = false;
double k = 0.04;
Mat copy = src.clone();
goodFeaturesToTrack( src_gray,
corners,
maxCorners,
qualityLevel,
minDistance,
Mat(),
blockSize,
gradientSize,
useHarrisDetector,
k );
cout << "** Number of corners detected: " << corners.size() << endl;
int radius = 4;
for( size_t i = 0; i < corners.size(); i + + )
{<!-- -->
circle( copy, corners[i], radius, Scalar(rng.uniform(0,255), rng.uniform(0, 256), rng.uniform(0, 256)), FILLED );
}
namedWindow( source_window );
imshow( source_window, copy );
Size winSize = Size( 5, 5 );
Size zeroZone = Size( -1, -1 );
TermCriteria criteria = TermCriteria( TermCriteria::EPS + TermCriteria::COUNT, 40, 0.001 );
cornerSubPix( src_gray, corners, winSize, zeroZone, criteria );
for( size_t i = 0; i < corners.size(); i + + )
{<!-- -->
cout << " -- Refined Corner [" << i << "] (" << corners[i].x << "," << corners[i].y << ")" << endl;
}
}
Java
The tutorial code is shown below. You can also download it from here
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) {<!-- -->
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 border layout. No need
// setLayout(new BorderLayout());
//Show 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() {<!-- -->
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;
Mat copy = src.clone();
Imgproc.goodFeaturesToTrack(srcGray, corners, maxCorners, qualityLevel, minDistance, new Mat(),
blockSize, gradientSize, useHarrisDetector, k);
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)), Imgproc.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();
Size winSize = new Size(5, 5);
Size zeroZone = new Size(-1, -1);
TermCriteria criteria = new TermCriteria(TermCriteria.EPS + TermCriteria.COUNT, 40, 0.001);
Imgproc.cornerSubPix(srcGray, matCorners, winSize, zeroZone, criteria);
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 local OpenCV library
System.loadLibrary(Core.NATIVE_LIBRARY_NAME);
// Arrange tasks for the event dispatch thread:
// Create and display the graphical user interface for this application.
javax.swing.SwingUtilities.invokeLater(new Runnable() {<!-- -->
@Override
public void run() {<!-- -->
new CornerSubPix(args);
}
});
}
}
Python
The tutorial code is shown below. You can also download it from here
from __future__ import print_function
import cv2 as cv
import numpy as np
import argparse
import random as rng
source_window = 'Image'
maxTrackbar = 25
rng.seed(12345)
def goodFeaturesToTrack_Demo(val):
maxCorners = max(val, 1)
# Parameters of Shi-Tomasi algorithm
qualityLevel = 0.01
minDistance=10
blockSize = 3
gradientSize = 3
useHarrisDetector = False
k = 0.04
#Copy source image
copy = np.copy(src)
# Apply corner detection
corners = cv.goodFeaturesToTrack(src_gray, maxCorners, qualityLevel, minDistance, None, \
blockSize=blockSize, gradientSize=gradientSize, useHarrisDetector=useHarrisDetector, k=k)
# Detected drawing corners
print('** Number of corners detected:', corners.shape[0])
radius = 4
for i in range(corners.shape[0]):
cv.circle(copy, (int(corners[i,0,0]), int(corners[i,0,1])), radius, (rng.randint(0,256), rng.randint(0,256), rng .randint(0,256)), cv.FILLED)
# Display the results obtained
cv.namedWindow(source_window)
cv.imshow(source_window, copy)
# Set the required parameters to find delicate corners
winSize = (5, 5)
zeroZone = (-1, -1)
criteria = (cv.TERM_CRITERIA_EPS + cv.TermCriteria_COUNT, 40, 0.001)
# Calculate the angular position of the refinement
corners = cv.cornerSubPix(src_gray, corners, winSize, zeroZone, criteria)
# write down
for i in range(corners.shape[0]):
print(" -- Refined Corner [", i, "] (", corners[i,0,0], ",", corners[i,0,1], ")")
# Load source image and convert to grayscale image
parser = argparse.ArgumentParser(description='Code for Shi-Tomasi corner detector tutorial.')
parser.add_argument('--input', help='Path to input image.', default='pic3.png')
args = parser.parse_args()
src = cv.imread(cv.samples.findFile(args.input))
if src is None:
print('Could not open or find the image:', args.input)
exit(0)
src_gray = cv.cvtColor(src, cv.COLOR_BGR2GRAY)
#Create windows and track bars
cv.namedWindow(source_window)
maxCorners = 10 #Initial threshold
cv.createTrackbar('Threshold: ', source_window, maxCorners, maxTrackbar, goodFeaturesToTrack_Demo)
cv.imshow(source_window, src)
goodFeaturesToTrack_Demo(maxCorners)
cv.waitKey()
Results
The results are as follows
