为轮廓创建边界框和圆形

目录

• 目标
• 理论
• 代码
• 解释
• 结果

上一个教程： 凸包
下一个教程： 为轮廓创建边界旋转框和椭圆

原始作者	Ana Huamán
兼容性	OpenCV >= 3.0

目标

在本教程中，你将了解如何：

• 使用 OpenCV 函数 cv::boundingRect
• 使用 OpenCV 函数 cv::minEnclosingCircle

理论

代码

C++

本教程代码显示在以下行中。你还可以从此处下载代码：此处

 
#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 = "Source";
namedWindow(source_window);
imshow(source_window, src);
 
    const int max_thresh = 255;
createTrackbar( "Canny thresh:", source_window, &thresh, max_thresh, thresh_callback);
thresh_callback(0, 0);
 
waitKey();
    return 0;
}
 
void thresh_callback(int, void*);
{
    Mat canny_output;
Canny(src_gray, canny_output, thresh, thresh*2);
 
vector<vector<Point> > contours;
findContours(canny_output, contours, RETR_TREE, CHAIN_APPROX_SIMPLE);
 
vector<vector<Point> > contours_poly(contours.size());
vector<Rect> boundRect(contours.size());
vector<Point2f>centers(contours.size());
vector<float>radius(contours.size());
 
    for(size_t i = 0; i < contours.size(); i++)
    {
approxPolyDP(contours[i], contours_poly[i], 3, true);
boundRect[i] = boundingRect(contours_poly[i]);
minEnclosingCircle(contours_poly[i], centers[i], radius[i]);
    }
 
    Mat drawing = Mat::zeros(canny_output.size(), CV_8UC3);
 
    for( size_t i = 0; i< contours.size(); i++)
    {
        Scalar color = Scalar(rng.uniform(0, 256), rng.uniform(0,256), rng.uniform(0,256));
drawContours(drawing, contours_poly, (int)i, color);
rectangle(drawing, boundRect[i].tl(), boundRect[i].br(), color, 2);
circle(drawing, centers[i], (int)radius[i], color, 2);
    }
 
    imshow( "Contours", drawing);
}

Java

本教程代码显示在下面的行中。您还可以从 此处 下载它

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.MatOfPoint;
import org.opencv.core.MatOfPoint2f;
import org.opencv.core.Point;
import org.opencv.core.Rect;
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 GeneralContours1 {
    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 GeneralContours1(String[] args) {
String filename = args.length > 0 ? args[0] : "../data/stuff.jpg";
Mat src = Imgcodecs.imread(filename);
        if (src.empty()) {
System.err.println("无法读取图像： " + 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("创建轮廓的边界框和圆形演示");
frame.setDefaultCloseOperation(JFrame.EXIT_ON_CLOSE);
        // 设置内容窗格。
Image img = HighGui.toBufferedImage(src);
addComponentsToPane(frame.getContentPane(), img);
        // 使用内容窗格的默认 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("Container doesn't use 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, 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();
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, threshold, threshold * 2);
 
List<MatOfPoint> contours = new ArrayList<>();
Mat hierarchy = new Mat();
Imgproc.findContours(cannyOutput, contours, hierarchy, Imgproc.RETR_TREE, Imgproc.CHAIN_APPROX_SIMPLE);
 
MatOfPoint2f[] contoursPoly = new MatOfPoint2f[contours.size()];
        Rect[] boundRect = new Rect[contours.size()];
        Point[] centers = new Point[contours.size()];
        float[][] radius = new float[contours.size()][1];
 
        for (int i = 0; i < contours.size(); i++) {
contoursPoly[i] = new MatOfPoint2f();
Imgproc.approxPolyDP(new MatOfPoint2f(contours.get(i).toArray()), contoursPoly[i], 3, true);
boundRect[i] = Imgproc.boundingRect(new MatOfPoint(contoursPoly[i].toArray()));
centers[i] = new Point();
Imgproc.minEnclosingCircle(contoursPoly[i], centers[i], radius[i]);
        }
 
Mat drawing = Mat.zeros(cannyOutput.size(), CvType.CV_8UC3);
List<MatOfPoint> contoursPolyList = new ArrayList<>(contoursPoly.length);
        for (MatOfPoint2f poly : contoursPoly) {
contoursPolyList.add(new MatOfPoint(poly.toArray()));
        }
 
        for (int i = 0; i < contours.size(); i++) {
            Scalar color = new Scalar(rng.nextInt(256), rng.nextInt(256), rng.nextInt(256));
Imgproc.drawContours(drawing, contoursPolyList, i, color);
Imgproc.rectangle(drawing, boundRect[i].tl(), boundRect[i].br(), color, 2);
Imgproc.circle(drawing, centers[i], (int) radius[i][0], color, 2);
        }
 
imgContoursLabel.setIcon(new ImageIcon(HighGui.toBufferedImage(drawing)));
frame.repaint();
    }
}
 
public class GeneralContoursDemo1 {
    public static void main(String[] args) {
        // 加载本机 OpenCV 库
System.loadLibrary(Core.NATIVE_LIBRARY_NAME);
 
        // 为事件分发线程计划一项作业
        // 创建并显示此应用程序的 GUI。
javax.swing.SwingUtilities.invokeLater(new Runnable() {
@Override
            public void run() {
                new GeneralContours1(args);
            }
        });
    }
}

Python

此教程代码可查看下面几行。还可以从 此处 下载

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
 
    
canny_output = cv.Canny(src_gray, threshold, threshold * 2)
    
 
    
contours, _ = cv.findContours(canny_output, cv.RETR_TREE, cv.CHAIN_APPROX_SIMPLE)
    
 
    
contours_poly = [None]*len(contours)
boundRect = [None]*len(contours)
centers = [None]*len(contours)
radius = [None]*len(contours)
    for i, c in enumerate(contours)
contours_poly[i] = cv.approxPolyDP(c, 3, True)
boundRect[i] = cv.boundingRect(contours_poly[i])
centers[i], radius[i] = cv.minEnclosingCircle(contours_poly[i])
    
 
    
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_poly, i, color)
        cv.rectangle(drawing, (int(boundRect[i][0]), int(boundRect[i][1])), \
(int(boundRect[i][0]+boundRect[i][2]), int(boundRect[i][1]+boundRect[i][3])), color, 2)
        cv.circle(drawing, (int(centers[i][0]), int(centers[i][1])), int(radius[i]), color, 2)
    
 
    
    cv.imshow('Contours', drawing)
    
 
 
parser = argparse.ArgumentParser(description='代码可创建轮廓包围框和圆形教程.')
parser.add_argument('--input', help='输入图像路径.', default='stuff.jpg')
args = parser.parse_args()
 
src = cv.imread(cv.samples.findFile(args.input))
if src is None
print('无法打开或查找图像:', 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))
 
 
 
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

主函数相当简单，从这儿我们可以看到评论

• 打开图像，将其转换为灰度并对其模糊处理以去除噪点。

C++

 
    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);

Java

 
String filename = args.length > 0 ? args[0] : "../data/stuff.jpg";
Mat src = Imgcodecs.imread(filename);
        if (src.empty()) {
System.err.println("无法读取图像： " + filename);
System.exit(0);
        }
 
Imgproc.cvtColor(src, srcGray, Imgproc.COLOR_BGR2GRAY);
Imgproc.blur(srcGray, srcGray, new Size(3, 3));

Python

# 加载源图像
parser = argparse.ArgumentParser(description='代码可创建轮廓包围框和圆形教程.')
parser.add_argument('--input', help='输入图像路径.', default='stuff.jpg')
args = parser.parse_args()
 
src = cv.imread(cv.samples.findFile(args.input))
if src is None
print('无法打开或查找图像:', 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))

• 创建一个标题为“Source”的窗口，并在其中显示源文件。

C++

 
    const char* source_window = "Source";
namedWindow(source_window);
imshow(source_window, src);

Java

        // 创建并设置窗口。
frame = new JFrame("创建轮廓的边界框和圆形演示");
frame.setDefaultCloseOperation(JFrame.EXIT_ON_CLOSE);
        // 设置内容窗格。
Image img = HighGui.toBufferedImage(src);
addComponentsToPane(frame.getContentPane(), img);

Python

# 创建窗口
source_window = 'Source'
cv.namedWindow(source_window)
cv.imshow(source_window, src)

• 在source_window上创建一个轨迹条并给它分配一个回调函数。一般来说，回调函数用于对某种信号做出反应，在我们的例子中是轨迹条的状态改变。显式地一次调用thresh_callback即可同时显示“轮廓”窗口和“源”窗口。

C++

    const int max_thresh = 255;
createTrackbar( "Canny thresh:", source_window, &thresh, max_thresh, thresh_callback);
thresh_callback(0, 0);

Java

sliderPanel.add(new JLabel("Canny 阈值: "));
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();
            }
        });

Python

max_thresh = 255
thresh = 100 # 初始阈值
cv.createTrackbar('Canny thresh:', source_window, thresh, max_thresh, thresh_callback)
thresh_callback(thresh)

回调函数完成所有有趣的工作。

• 使用 cv::Canny在图像中检测边缘。

C++

 
    Mat canny_output;
Canny(src_gray, canny_output, thresh, thresh*2);

Java

 
Mat cannyOutput = new Mat();
Imgproc.Canny(srcGray, cannyOutput, threshold, threshold * 2);

Python

    # 使用 Canny 检测边缘
canny_output = cv.Canny(src_gray, threshold, threshold * 2)

• 查找轮廓并将它们保存到向量contour和hierarchy。

C++

 
vector<vector<Point> > contours;
findContours(canny_output, contours, RETR_TREE, CHAIN_APPROX_SIMPLE);

Java

 
List<MatOfPoint> contours = new ArrayList<>();
Mat hierarchy = new Mat();
Imgproc.findContours(cannyOutput, contours, hierarchy, Imgproc.RETR_TREE, Imgproc.CHAIN_APPROX_SIMPLE);

Python

    # 查找轮廓
contours, _ = cv.findContours(canny_output, cv.RETR_TREE, cv.CHAIN_APPROX_SIMPLE)

• 对于每一个找到的轮廓，我们现在对多边形进行逼近，精度为 +-3，并声明曲线必须闭合。此后，我们为每一个多边形找到一个边界矩形并将其保存到 boundRect。最后，我们为每一个多边形找到一个最小外接圆，并将它保存在 center 和 radius 向量中。

C++

 
vector<vector<Point> > contours_poly(contours.size());
vector<Rect> boundRect(contours.size());
vector<Point2f>centers(contours.size());
vector<float>radius(contours.size());
 
    for(size_t i = 0; i < contours.size(); i++)
    {
approxPolyDP(contours[i], contours_poly[i], 3, true);
boundRect[i] = boundingRect(contours_poly[i]);
minEnclosingCircle(contours_poly[i], centers[i], radius[i]);
    }

Java

 
MatOfPoint2f[] contoursPoly = new MatOfPoint2f[contours.size()];
Rect[] boundRect = new Rect[contours.size()];
Point[] centers = new Point[contours.size()];
        float[][] radius = new float[contours.size()][1];
 
        for (int i = 0; i < contours.size(); i++) {
contoursPoly[i] = new MatOfPoint2f();
Imgproc.approxPolyDP(new MatOfPoint2f(contours.get(i).toArray()), contoursPoly[i], 3, true);
boundRect[i] = Imgproc.boundingRect(new MatOfPoint(contoursPoly[i].toArray()));
centers[i] = new Point();
Imgproc.minEnclosingCircle(contoursPoly[i], centers[i], radius[i]);
        }

Python

    # 将轮廓逼近到多边形 + 获取包围矩形和圆
contours_poly = [None]*len(contours)
boundRect = [None]*len(contours)
centers = [None]*len(contours)
radius = [None]*len(contours)
    for i, c in enumerate(contours)
contours_poly[i] = cv.approxPolyDP(c, 3, True)
boundRect[i] = cv.boundingRect(contours_poly[i])
centers[i], radius[i] = cv.minEnclosingCircle(contours_poly[i])

我们找到了我们需要的所有内容，我们所要做的就是绘制。

• 创建新的无符号 8 位字符 Mat，并用零填充。它将包含我们准备进行的所有绘图（矩形和圆）。

C++

    Mat drawing = Mat::zeros(canny_output.size(), CV_8UC3);

Java

Mat drawing = Mat.zeros(cannyOutput.size(), CvType.CV_8UC3);

Python

drawing = np.zeros((canny_output.shape[0], canny_output.shape[1], 3), dtype=np.uint8)

• 对于每一个轮廓：选择一个随机颜色，绘制轮廓、包围矩形和带它的最小外接圆。

C++

 
    for( size_t i = 0; i< contours.size(); i++)
    {
        Scalar color = Scalar(rng.uniform(0, 256), rng.uniform(0,256), rng.uniform(0,256));
drawContours(drawing, contours_poly, (int)i, color);
rectangle(drawing, boundRect[i].tl(), boundRect[i].br(), color, 2);
circle(drawing, centers[i], (int)radius[i], color, 2);
    }

Java

 
List<MatOfPoint> contoursPolyList = new ArrayList<>(contoursPoly.length);
        for (MatOfPoint2f poly : contoursPoly) {
contoursPolyList.add(new MatOfPoint(poly.toArray()));
        }
 
        for (int i = 0; i < contours.size(); i++) {
Scalar color = new Scalar(rng.nextInt(256), rng.nextInt(256), rng.nextInt(256));
Imgproc.drawContours(drawing, contoursPolyList, i, color);
Imgproc.rectangle(drawing, boundRect[i].tl(), boundRect[i].br(), color, 2);
Imgproc.circle(drawing, centers[i], (int) radius[i][0], color, 2);
        }

Python

    # 绘制多边形轮廓 + 粘合矩形 + 圆
    for i in range(len(contours))
color = (rng.randint(0,256), rng.randint(0,256), rng.randint(0,256))
        cv.drawContours(drawing, contours_poly, i, color)
        cv.rectangle(drawing, (int(boundRect[i][0]), int(boundRect[i][1])), \
(int(boundRect[i][0]+boundRect[i][2]), int(boundRect[i][1]+boundRect[i][3])), color, 2)
        cv.circle(drawing, (int(centers[i][0]), int(centers[i][1])), int(radius[i]), color, 2)

• 显示结果：创建一个新窗口“Contours”并在其上显示我们添加到绘图中的所有内容。

C++

 
imshow( "Contours", drawing );

Java

 
imgContoursLabel.setIcon(new ImageIcon(HighGui.toBufferedImage(drawing)));
frame.repaint();

Python

    # 在窗口中显示
    cv.imshow('Contours', drawing)

结果

如下所示：