python opencv检测虚线框 opencv检测图中矩形框

本文参考了网上对于opencv矩形识别的程序，并对其适当修改，使之可以在自己电脑上运行为自己想要的结果。主要做的修改是读取图像的方式，调整识别图中矩形的大小。转载原文的链接和修改后的程序如下。

#include "cv.h"

#include "highgui.h"

#include <stdio.h>

#include <math.h>

#include <string.h>

#include <iostream>

int thresh = 50;

IplImage* img =NULL;

IplImage* img0 = NULL;

CvMemStorage* storage =NULL;

const char * wndname = "正方形检测 demo";

//angle函数用来返回（两个向量之间找到角度的余弦值）

double angle( CvPoint* pt1, CvPoint* pt2, CvPoint* 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);

}

// 返回图像中找到的所有轮廓序列，并且序列存储在内存存储器中

CvSeq* findSquares4( IplImage* img, CvMemStorage* storage )

{

 CvSeq* contours;

 int i, c, l, N = 11;

 CvSize sz = cvSize( img->width & -2, img->height & -2 ); 

 

 IplImage* timg = cvCloneImage( img );

 IplImage* gray = cvCreateImage( sz, 8, 1 );

 IplImage* pyr = cvCreateImage( cvSize(sz.width/2, sz.height/2), 8, 3 );

 IplImage* tgray;

 CvSeq* result;

 double s, t;

 // 创建一个空序列用于存储轮廓角点

 CvSeq* squares = cvCreateSeq( 0, sizeof(CvSeq), sizeof(CvPoint), storage );

 cvSetImageROI( timg, cvRect( 0, 0, sz.width, sz.height ));

 // 过滤噪音

 cvPyrDown( timg, pyr, 7 );

 cvPyrUp( pyr, timg, 7 );

 tgray = cvCreateImage( sz, 8, 1 );

 // 红绿蓝3色分别尝试提取

 for( c = 0; c < 3; c++ )

 {

  // 提取 the c-th color plane

  cvSetImageCOI( timg, c+1 );

  cvCopy( timg, tgray, 0 );

  // 尝试各种阈值提取得到的（N=11）

  for( l = 0; l < N; l++ )

  {

   // apply Canny. Take the upper threshold from slider

   // Canny helps to catch squares with gradient shading  

   if( l == 0 )

   {

    cvCanny( tgray, gray, 0, thresh, 5 );

    //使用任意结构元素膨胀图像

    cvDilate( gray, gray, 0, 1 );

   }

   else

   {

    // apply threshold if l!=0:

    cvThreshold( tgray, gray, (l+1)*255/N, 255, CV_THRESH_BINARY );

   }

   // 找到所有轮廓并且存储在序列中

   cvFindContours( gray, storage, &contours, sizeof(CvContour),

    CV_RETR_LIST, CV_CHAIN_APPROX_SIMPLE, cvPoint(0,0) );

   // 遍历找到的每个轮廓contours

   while( contours )

   {

     //用指定精度逼近多边形曲线

    result = cvApproxPoly( contours, sizeof(CvContour), storage,

     CV_POLY_APPROX_DP, cvContourPerimeter(contours)*0.02, 0 );

                  

    if( result->total == 4 &&

     fabs(cvContourArea(result,CV_WHOLE_SEQ)) > 500 &&

     fabs(cvContourArea(result,CV_WHOLE_SEQ)) < 100000 &&

     cvCheckContourConvexity(result) )

    {

     s = 0;

     for( i = 0; i < 5; i++ )

     {

      // find minimum angle between joint edges (maximum of cosine)

      if( i >= 2 )

      {

       t = fabs(angle(

        (CvPoint*)cvGetSeqElem( result, i ),

        (CvPoint*)cvGetSeqElem( result, i-2 ),

        (CvPoint*)cvGetSeqElem( result, i-1 )));

       s = s > t ? s : t;

      }

     }

     // if 余弦值 足够小，可以认定角度为90度直角

     //cos0.1=83度，能较好的趋近直角

     if( s < 0.1 )  

      for( i = 0; i < 4; i++ )

       cvSeqPush( squares,

       (CvPoint*)cvGetSeqElem( result, i ));

    }

    // 继续查找下一个轮廓

    contours = contours->h_next;

   }

  }

 }

 cvReleaseImage( &gray );

 cvReleaseImage( &pyr );

 cvReleaseImage( &tgray );

 cvReleaseImage( &timg );

 return squares;

}

//drawSquares函数用来画出在图像中找到的所有正方形轮廓

void drawSquares( IplImage* img, CvSeq* squares )

{

 CvSeqReader reader;

 IplImage* cpy = cvCloneImage( img );

 int i;

 cvStartReadSeq( squares, &reader, 0 );

 // read 4 sequence elements at a time (all vertices of a square)

 for( i = 0; i < squares->total; i += 4 )

 {

  CvPoint pt[4], *rect = pt;

  int count = 4;

  // read 4 vertices

  CV_READ_SEQ_ELEM( pt[0], reader );

  CV_READ_SEQ_ELEM( pt[1], reader );

  CV_READ_SEQ_ELEM( pt[2], reader );

  CV_READ_SEQ_ELEM( pt[3], reader );

  // draw the square as a closed polyline

  cvPolyLine( cpy, &rect, &count, 1, 1, CV_RGB(0,255,0), 2, CV_AA, 0 );

 }

 cvShowImage( wndname, cpy );

 cvReleaseImage( &cpy );

}

 

char* names[] = { "pic1.png", "pic2.png", "pic3.png",

     "pic4.png", "pic5.png", "pic6.png","pic7.png","pic8.png",

     "pic9.png","pic10.png","pic11.png","pic12.png", 0 };

int main(int argc, char** argv)

{

 int i, c;

 storage = cvCreateMemStorage(0);

 for( i = 0; names[i] != 0; i++ )

 {

  img0 = cvLoadImage( names[i], 1 );

  if( !img0 )

  {

   cout<<"不能载入"<<names[i]<<"继续下一张图片"<<endl;

   continue;

  }

  img = cvCloneImage( img0 );

  cvNamedWindow( wndname, 1 );

  // find and draw the squares

  drawSquares( img, findSquares4( img, storage ) );

  c = cvWaitKey(0);

  

  cvReleaseImage( &img );

  cvReleaseImage( &img0 );

  cvClearMemStorage( storage );

  if( (char)c == 27 )

   break;

 }

 cvDestroyWindow( wndname );

 return 0;

}

#include "opencv/cv.h"

#include "opencv2/highgui/highgui_c.h"
#include "opencv2/imgproc.hpp"
#include <stdio.h>

#include <math.h>

#include <string.h>

#include <iostream>
#include<opencv2/opencv.hpp>
using namespace cv;
using namespace std;
int thresh = 100;

IplImage* img = NULL;

CvMemStorage* storage = NULL;

const char * wndname = "正方形检测 demo";

//angle函数用来返回（两个向量之间找到角度的余弦值）

double angle(CvPoint* pt1, CvPoint* pt2, CvPoint* 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);

}

// 返回图像中找到的所有轮廓序列，并且序列存储在内存存储器中

CvSeq* findSquares4(IplImage* img, CvMemStorage* storage)

{

	CvSeq* contours;

	int i, c, l, N = 11;

	CvSize sz = cvSize(img->width & -2, img->height & -2);



	IplImage* timg = cvCloneImage(img);

	IplImage* gray = cvCreateImage(sz, 8, 1);

	IplImage* pyr = cvCreateImage(cvSize(sz.width / 2, sz.height / 2), 8, 3);

	IplImage* tgray;

	CvSeq* result;

	double s, t;

	// 创建一个空序列用于存储轮廓角点

	CvSeq* squares = cvCreateSeq(0, sizeof(CvSeq), sizeof(CvPoint), storage);

	cvSetImageROI(timg, cvRect(0, 0, sz.width, sz.height));

	// 过滤噪音

	cvPyrDown(timg, pyr, 7);//gaussian金字塔分解对输入图像下采样。（输入图像，输出图像，滤波器类型）

	cvPyrUp(pyr, timg, 7);

	tgray = cvCreateImage(sz, 8, 1);

	// 红绿蓝3色分别尝试提取

	for (c = 0; c < 3; c++)

	{

		// 提取 the c-th color plane

		cvSetImageCOI(timg, c + 1);

		cvCopy(timg, tgray, 0);//（输入，输出）

		// 尝试各种阈值提取得到的（N=11）

		for (l = 0; l < N; l++)

		{

			// apply Canny. Take the upper threshold from slider

			// Canny helps to catch squares with gradient shading  

			if (l == 0)

			{

				cvCanny(tgray, gray, 0, thresh, 5);

				//使用任意结构元素膨胀图像

				cvDilate(gray, gray, 0, 1);

			}

			else

			{

				// apply threshold if l!=0:

				cvThreshold(tgray, gray, (l + 1) * 255 / N, 255, CV_THRESH_BINARY);

			}

			// 找到所有轮廓并且存储在序列中

			cvFindContours(gray, storage, &contours, sizeof(CvContour),

				CV_RETR_LIST, CV_CHAIN_APPROX_SIMPLE, cvPoint(0, 0));

			// 遍历找到的每个轮廓contours

			while (contours)

			{

				//用指定精度逼近多边形曲线

				result = cvApproxPoly(contours, sizeof(CvContour), storage,

					CV_POLY_APPROX_DP, cvContourPerimeter(contours)*0.02, 0);



				if (result->total == 4 &&

					fabs(cvContourArea(result, CV_WHOLE_SEQ)) > 500 &&

					fabs(cvContourArea(result, CV_WHOLE_SEQ)) < 100000 &&

					cvCheckContourConvexity(result))

				{

					s = 0;

					for (i = 0; i < 5; i++)

					{

						// find minimum angle between joint edges (maximum of cosine)

						if (i >= 2)

						{

							t = fabs(angle(

								(CvPoint*)cvGetSeqElem(result, i),

								(CvPoint*)cvGetSeqElem(result, i - 2),

								(CvPoint*)cvGetSeqElem(result, i - 1)));

							s = s > t ? s : t;

						}

					}

					// if 余弦值 足够小，可以认定角度为90度直角

					//cos0.1=83度，能较好的趋近直角

					if (s < 0.1)

						for (i = 0; i < 4; i++)

							cvSeqPush(squares,

							(CvPoint*)cvGetSeqElem(result, i));

				}

				// 继续查找下一个轮廓

				contours = contours->h_next;

			}

		}

	}

	cvReleaseImage(&gray);

	cvReleaseImage(&pyr);

	cvReleaseImage(&tgray);

	cvReleaseImage(&timg);

	return squares;

}

//drawSquares函数用来画出在图像中找到的所有正方形轮廓

void drawSquares(IplImage* img, CvSeq* squares)

{

	CvSeqReader reader;

	IplImage* cpy = cvCloneImage(img);

	int i;

	cvStartReadSeq(squares, &reader, 0);

	// read 4 sequence elements at a time (all vertices of a square)

	for (i = 0; i < squares->total; i += 4)

	{

		CvPoint pt[4], *rect = pt;

		int count = 4;

		// read 4 vertices

		CV_READ_SEQ_ELEM(pt[0], reader);

		CV_READ_SEQ_ELEM(pt[1], reader);

		CV_READ_SEQ_ELEM(pt[2], reader);

		CV_READ_SEQ_ELEM(pt[3], reader);

		// draw the square as a closed polyline

		cvPolyLine(cpy, &rect, &count, 1, 1, CV_RGB(0, 255, 0), 2, CV_AA, 0);

	}

	cvShowImage(wndname, cpy);

	cvReleaseImage(&cpy);

}


int main(int argc, char** argv)

{

	int i, c;

	storage = cvCreateMemStorage(0);
	
	img = cvLoadImage("E:\\work\\1原始大图.jpg", 1);
	
	cvNamedWindow(wndname, 1);//设置显示图片的窗口，窗口名字为wndname，标志位为1即窗口可以根据图像大小自动调整

	// find and draw the squares

	drawSquares(img, findSquares4(img, storage));

	c = cvWaitKey(0);

	cvReleaseImage(&img);

	cvClearMemStorage(storage);

	cvDestroyWindow(wndname);

	return 0;

}