Square Detector

the first demo for OpenCV

#inlucde<opencv2opencv.hpp>
using namespace cv;
int main()
{
	Mat picture=imread("wallpaper")
	imshow("测试程序",picture);
	waitKey(20180717);
}

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First Column	Second Column
wallpaper	墙纸
static	静止的['staetik]
absolute	['aebse lut]绝对的，完全的
omitted	[ou'mitid]遗漏的
omit	[e'mit]省略，遗漏
pyramid	['piremid]金字塔
image pyramid	图像金字塔
scale	[skel]规模
scaling	['skeling]缩放比例,尺度
pyramid scaling
contour	['ka:ntur]外形，轮廓
guassian pyramid	高斯金字塔
diagnosis	[daieg'nousis]诊断
fix the question	修复问题
diagnostic	诊断的
diagnostics	诊断学
counter simplification	轮廓简化[simplefe'keition]
memory storage	存储装置
folks	人们
sequence	[si:kwens]顺序
specified	指定的
dG	vim(delete all the lines behind the current line)
d$	vim(delete the cursor position to the end of the line)
cursor	['ke:rse(r)]光标

OpenCV read the picture path(The "Square Detector" program)

// The "Square Detector" program.
// It loads several images sequentially and tries to find squares in
// each image

#include "opencv2/core/core.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/imgcodecs.hpp"
#include "opencv2/highgui/highgui.hpp"

#include <iostream>
#include <math.h>
#include <string.h>

using namespace cv;
using namespace std;

static void help()
{
	cout <<
		"
A program using pyramid scaling, Canny, contours, contour simplification and
"
		"memory storage (it's got it all folks) to find
"
		"squares in a list of images pic1-6.pn1g
"
		"Returns sequence of squares detected on the image.
"
		"the sequence is stored in the specified memory storage
"
		"Call:
"
		"./squares
"
		"Using OpenCV version %s
" << CV_VERSION << "
" << endl;
}


int thresh = 50, N = 11;
const char* wndname = "Square Detection Demo";

// helper function:
// finds a cosine of angle between vectors
// from pt0->pt1 and from pt0->pt2
static double angle(Point pt1, Point pt2, Point pt0)
{
	double dx1 = pt1.x - pt0.x;
	double dy1 = pt1.y - pt0.y;
	double dx2 = pt2.x - pt0.x;
	double dy2 = pt2.y - pt0.y;
	return (dx1*dx2 + dy1*dy2) / sqrt((dx1*dx1 + dy1*dy1)*(dx2*dx2 + dy2*dy2) + 1e-10);
}

// returns sequence of squares detected on the image.
// the sequence is stored in the specified memory storage
static void findSquares(const Mat& image, vector<vector<Point> >& squares)
{
	squares.clear();

	Mat pyr, timg, gray0(image.size(), CV_8U), gray;

	// down-scale and upscale the image to filter out the noise
	pyrDown(image, pyr, Size(image.cols / 2, image.rows / 2));
	pyrUp(pyr, timg, image.size());
	vector<vector<Point> > contours;

	// find squares in every color plane of the image
	for (int c = 0; c < 3; c++)
	{
		int ch[] = { c, 0 };
		mixChannels(&timg, 1, &gray0, 1, ch, 1);

		// try several threshold levels
		for (int l = 0; l < N; l++)
		{
			// hack: use Canny instead of zero threshold level.
			// Canny helps to catch squares with gradient shading
			if (l == 0)
			{
				// apply Canny. Take the upper threshold from slider
				// and set the lower to 0 (which forces edges merging)
				Canny(gray0, gray, 0, thresh, 5);
				// dilate canny output to remove potential
				// holes between edge segments
				dilate(gray, gray, Mat(), Point(-1, -1));
			}
			else
			{
				// apply threshold if l!=0:
				//     tgray(x,y) = gray(x,y) < (l+1)*255/N ? 255 : 0
				gray = gray0 >= (l + 1) * 255 / N;
			}

			// find contours and store them all as a list
			findContours(gray, contours, RETR_LIST, CHAIN_APPROX_SIMPLE);

			vector<Point> approx;

			// test each contour
			for (size_t i = 0; i < contours.size(); i++)
			{
				// approximate contour with accuracy proportional
				// to the contour perimeter
				approxPolyDP(Mat(contours[i]), approx, arcLength(Mat(contours[i]), true)*0.02, true);

				// square contours should have 4 vertices after approximation
				// relatively large area (to filter out noisy contours)
				// and be convex.
				// Note: absolute value of an area is used because
				// area may be positive or negative - in accordance with the
				// contour orientation
				if (approx.size() == 4 &&
					fabs(contourArea(Mat(approx))) > 1000 &&
					isContourConvex(Mat(approx)))
				{
					double maxCosine = 0;

					for (int j = 2; j < 5; j++)
					{
						// find the maximum cosine of the angle between joint edges
						double cosine = fabs(angle(approx[j % 4], approx[j - 2], approx[j - 1]));
						maxCosine = MAX(maxCosine, cosine);
					}

					// if cosines of all angles are small
					// (all angles are ~90 degree) then write quandrange
					// vertices to resultant sequence
					if (maxCosine < 0.3)
						squares.push_back(approx);
				}
			}
		}
	}
}


// the function draws all the squares in the image
static void drawSquares(Mat& image, const vector<vector<Point> >& squares)
{
	for (size_t i = 0; i < squares.size(); i++)
	{
		const Point* p = &squares[i][0];
		int n = (int)squares[i].size();
		polylines(image, &p, &n, 1, true, Scalar(0, 255, 0), 3, LINE_AA);
	}

	imshow(wndname, image);
}


int main(int /*argc*/, char** /*argv*/)
{
	static const char* names[] = { "D:/OpenCV 3.1/opencv/sources/samples/data/pic1.png",
		"D:/OpenCV 3.1/opencv/sources/samples/data/pic2.png",
		"D:/OpenCV 3.1/opencv/sources/samples/data/pic3.png",
		"D:/OpenCV 3.1/opencv/sources/samples/data/pic4.png", 
		"D:/OpenCV 3.1/opencv/sources/samples/data/pic5.png", 
		"D:/OpenCV 3.1/opencv/sources/samples/data/pic6.png", 0 };
	help();
	namedWindow(wndname, 1);
	vector<vector<Point> > squares;

	for (int i = 0; names[i] != 0; i++)
	{
		Mat image = imread(names[i], 1);
		if (image.empty())
		{
			cout << "Couldn't load " << names[i] << endl;
			continue;
		}

		findSquares(image, squares);
		drawSquares(image, squares);

		int c = waitKey();
		if ((char)c == 27)
			break;
	}

	return 0;
}

Absolute Path:It's the path starting from the disk,like——D:OpenCV 3.1opencvsourcessamplesdatapic1.png
Relative Path:It's the path starting from the current path,if the current path is "E:VS2015ConsoleApplication1ConsoleApplication1"
If you want to describe the path(E:VS2015ConsoleApplication1ConsoleApplication1pic1.png),just input the relative path"pic1.png".In fact,the strict relative path writing should be ".pic1.png".
"./"(It means that the current path can be omitted under normal)

//The "Square Detector" program

//It loads several images sequentially and tries to find squares in

//each image

static const char* names[] = { 
		"D:/OpenCV 3.1/opencv/sources/samples/data/pic1.png",
		"D:/OpenCV 3.1/opencv/sources/samples/data/pic2.png",
		"D:/OpenCV 3.1/opencv/sources/samples/data/pic3.png",
		"D:/OpenCV 3.1/opencv/sources/samples/data/pic4.png", 
		"D:/OpenCV 3.1/opencv/sources/samples/data/pic5.png", 
		"D:/OpenCV 3.1/opencv/sources/samples/data/pic6.png", 0 };

Warning:"ConsoleApplication1.exe"(Win32):loaded,"C:WindowsSystem32 tdll.dll".Unable to find or open the pdb file.

pdb file(be used to help the debugging of the software)