凸包

目录

• 目标
• 理论
• 代码
• 说明
• 结果

上一教程: 在图像中寻找轮廓
下一教程: 为轮廓创建边界框和圆

作者	Ana Huamán
兼容性	OpenCV >= 3.0

目标

在本教程中，你将学习如何

• 使用 OpenCV 函数 cv::convexHull

理论

代码

C++ 代码

本教程的代码如下所示。你还可以从 这里下载该代码

 
#include "opencv2/imgcodecs.hpp"
#include "opencv2/highgui.hpp"
#include "opencv2/imgproc.hpp"
#include <iostream>
 
using namespace cv;
using namespace std;
 
Mat src_gray;
int thresh = 100;
RNG rng(12345);
 
void thresh_callback(int, void* );
 
int main( int argc, char** argv )
{
    CommandLineParser parser( argc, argv, "{@input | stuff.jpg | input image}" );
    Mat src = imread( samples::findFile( parser.get<String>( "@input" ) ) );
    if( src.empty() )
    {
cout << "Could not open or find the image!\n" << endl;
cout << "Usage: " << argv[0] << " <Input image>" << endl;
        return -1;
    }
 
cvtColor( src, src_gray, COLOR_BGR2GRAY );
blur( src_gray, src_gray, Size(3,3) );
 
    const char* source_window = "源";
namedWindow( source_window );
imshow( source_window, src );
 
    const int max_thresh = 255;
createTrackbar( "Canny 阈值:", source_window, &thresh, max_thresh, thresh_callback );
thresh_callback( 0, 0 );
 
waitKey();
    return 0;
}
 
void thresh_callback(int, void* )
{
    矩阵 canny_output;
Canny( src_gray, canny_output, thresh, thresh*2 );
 
vector<vector<点> > 轮廓;
findContours( canny_output, 轮廓, RETR_TREE, CHAIN_APPROX_SIMPLE );
 
vector<vector<点> >hull( 轮廓.size() );
    对于( 大小 i = 0; i < 轮廓.size(); i++ )
    {
convexHull( 轮廓[i], hull[i] );
    }
 
    矩阵 drawing = 矩阵::zeros( canny_output.尺寸(), CV_8UC3 );
    对于( 大小 i = 0; i< 轮廓.size(); i++ )
    {
        标量 颜色 = 标量( rng.uniform(0, 256), rng.uniform(0,256), rng.uniform(0,256) );
drawContours( drawing, 轮廓, (int)i, 颜色 );
drawContours( drawing, hull, (int)i, 颜色 );
    }
 
    imshow( "Hull 演示", drawing );
}

Java

此教程的代码如下所示。您还可以从 此处 下载

import java.awt.BorderLayout;
import java.awt.Container;
import java.awt.Image;
import java.util.ArrayList;
import java.util.List;
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.MatOfInt;
import org.opencv.core.MatOfPoint;
import org.opencv.core.Point;
import org.opencv.core.Scalar;
import org.opencv.core.Size;
import org.opencv.highgui.HighGui;
import org.opencv.imgcodecs.Imgcodecs;
import org.opencv.imgproc.Imgproc;
 
class Hull {
    private Mat srcGray = new Mat();
    private JFrame frame;
    private JLabel imgSrcLabel;
    private JLabel imgContoursLabel;
    private static final int MAX_THRESHOLD = 255;
    private int threshold = 100;
    private Random rng = new Random(12345);
 
    public Hull(String[] args) {
String filename = args.length > 0 ? args[0] : "../data/stuff.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);
Imgproc.blur(srcGray, srcGray, new Size(3, 3));
 
        // 创建并设置窗口。
frame = new JFrame("凸包演示");
frame.setDefaultCloseOperation(JFrame.EXIT_ON_CLOSE);
        // 设置内容面板。
Image img = HighGui.toBufferedImage(src);
addComponentsToPane(frame.getContentPane(), img);
        // 使用内容面板的默认 BorderLayout。不需要
        // setLayout(new BorderLayout());
        // 显示窗口。
frame.pack();
frame.setVisible(true);
update();
    }
 
    private void addComponentsToPane(Container pane, Image img) {
        if (!(pane.getLayout() instanceof BorderLayout)) {
pane.add(new JLabel("容器未使用 BorderLayout!"));
            return;
        }
 
JPanel sliderPanel = new JPanel();
sliderPanel.setLayout(new BoxLayout(sliderPanel, BoxLayout.PAGE_AXIS));
 
sliderPanel.add(new JLabel("Canny 阈值: "));
JSlider slider = new JSlider(0, MAX_THRESHOLD, 阈值);
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();
阈值 = source.getValue();
update();
            }
        });
sliderPanel.add(slider);
pane.add(sliderPanel, BorderLayout.PAGE_START);
 
JPanel imgPanel = new JPanel();
imgSrcLabel = new JLabel(new ImageIcon(img));
imgPanel.add(imgSrcLabel);
 
Mat blackImg = Mat.zeros(srcGray.size(), CvType.CV_8U);
imgContoursLabel = new JLabel(new ImageIcon(HighGui.toBufferedImage(blackImg)));
imgPanel.add(imgContoursLabel);
 
pane.add(imgPanel, BorderLayout.CENTER);
    }
 
    private void update() {
Mat cannyOutput = new Mat();
Imgproc.Canny(srcGray, cannyOutput, 阈值, 阈值 * 2);
 
List<MatOfPoint> contours = new ArrayList<>();
Mat hierarchy = new Mat();
Imgproc.findContours(cannyOutput, contours, hierarchy, Imgproc.RETR_TREE, Imgproc.CHAIN_APPROX_SIMPLE);
 
List<MatOfPoint> hullList = new ArrayList<>();
        for (MatOfPoint contour : contours) {
MatOfInt hull = new MatOfInt();
Imgproc.convexHull(contour, hull);
 
            Point[] contourArray = contour.toArray();
            Point[] hullPoints = new Point[hull.rows()];
List<Integer> hullContourIdxList = hull.toList();
            for (int i = 0; i < hullContourIdxList.size(); i++) {
hullPoints[i] = contourArray[hullContourIdxList.get(i)];
            }
hullList.add(new MatOfPoint(hullPoints));
        }
 
Mat drawing = Mat.zeros(cannyOutput.size(), CvType.CV_8UC3);
        for (int i = 0; i < contours.size(); i++) {
            Scalar color = new Scalar(rng.nextInt(256), rng.nextInt(256), rng.nextInt(256));
Imgproc.drawContours(drawing, contours, i, color);
Imgproc.drawContours(drawing, hullList, i, color );
        }
 
imgContoursLabel.setIcon(new ImageIcon(HighGui.toBufferedImage(drawing)));
frame.repaint();
    }
}
 
public class HullDemo {
    public static void main(String[] args) {
        // 加载本机 OpenCV 库
System.loadLibrary(Core.NATIVE_LIBRARY_NAME);
 
        // 为事件分发线程安排一项任务
        // 创建和显示本应用程序的 GUI。
javax.swing.SwingUtilities.invokeLater(new Runnable() {
@Override
            public void run() {
                new Hull(args);
            }
        });
    }
}

Python

本教程代码显示在下面的行中。您还可以从 此处 下载它

from __future__ import print_function
import cv2 as cv
import numpy as np
import argparse
import random as rng
 
rng.seed(12345)
 
def thresh_callback(val)
threshold = val
 
    # 使用 Canny 检测边缘
canny_output = cv.Canny(src_gray, threshold, threshold * 2)
 
    # 查找轮廓
contours, _ = cv.findContours(canny_output, cv.RETR_TREE, cv.CHAIN_APPROX_SIMPLE)
 
    # 找到每个轮廓的凸包对象
hull_list = []
    for i in range(len(contours))
hull = cv.convexHull(contours[i])
hull_list.append(hull)
 
    # 绘制轮廓 + 包络结果
drawing = np.zeros((canny_output.shape[0], canny_output.shape[1], 3), dtype=np.uint8)
    for i in range(len(contours))
color = (rng.randint(0,256), rng.randint(0,256), rng.randint(0,256))
        cv.drawContours(drawing, contours, i, color)
        cv.drawContours(drawing, hull_list, i, color)
 
    # 在窗口中显示
    cv.imshow('Contours', drawing)
 
# 加载源图
parser = argparse.ArgumentParser(description='用于凸包教程的代码。')
parser.add_argument('--input', help='输入图像的路径。', default='stuff.jpg')
args = parser.parse_args()
 
src = cv.imread(cv.samples.findFile(args.input))
if src is None
print('无法打开或找到图像：', args.input)
exit(0)
 
# 将图像转换为灰度并模糊处理
src_gray = cv.cvtColor(src, cv.COLOR_BGR2GRAY)
src_gray = cv.blur(src_gray, (3,3))
 
# 创建窗口
source_window = 'Source'
cv.namedWindow(source_window)
cv.imshow(source_window, src)
max_thresh = 255
thresh = 100 # 初始阈值
cv.createTrackbar('Canny thresh:', source_window, thresh, max_thresh, thresh_callback)
thresh_callback(thresh)
 
cv.waitKey()

解释

结果

这就是它