opencv2實現多張圖片路線路牌(直線和圓）檢測並將處理後的圖片合成視頻_電腦視覺大作業2

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linefinder.h

#if !defined LINEF#define LINEF#include<cmath>#include <opencv2/core/core.hpp>#include <opencv2/imgproc/imgproc.hpp>#define PI 3.1415926using namespace cv;using namespace std;class LineFinder {  private:  // original image  Mat img;  // vector containing the end points   // of the detected lines  vector<Vec4i> lines;  // accumulator resolution parameters  double deltaRho;  double deltaTheta;  // minimum number of votes that a line   // must receive before being considered  int minVote;  // min length for a line  double minLength;  // max allowed gap along the line  double maxGap;  public:  // Default accumulator resolution is 1 pixel by 1 degree  // no gap, no mimimum length  LineFinder() : deltaRho(1), deltaTheta(PI/180), minVote(10), minLength(0.), maxGap(0.) {}  // Set the resolution of the accumulator  void setAccResolution(double dRho, double dTheta) {  deltaRho= dRho;  deltaTheta= dTheta;  }  // Set the minimum number of votes  void setMinVote(int minv) {  minVote= minv;  }  // Set line length and gap  void setLineLengthAndGap(double length, double gap) {  minLength= length;  maxGap= gap;  }  // Apply probabilistic Hough Transform  vector<Vec4i> findLines(Mat& binary) {  lines.clear();  HoughLinesP(binary,lines,deltaRho,deltaTheta,minVote, minLength, maxGap);  return lines;  }  // Draw the detected lines on an image  void drawDetectedLines(Mat &image, Scalar color=Scalar(255,0,0)) {  // Draw the lines  vector<Vec4i>::const_iterator it2= lines.begin();  while (it2!=lines.end()) {  Point pt1((*it2)[0],(*it2)[1]);          Point pt2((*it2)[2],(*it2)[3]);  double slope = fabs(double((*it2)[1]-(*it2)[3])/((*it2)[0]-(*it2)[2]));   // double slope = fabs (((double)(lines[1].y-lines[0].y))/((double)(lines[1].x-lines[0].x)));//求直線在座標系中的斜率//double length=sqrt((line[1].y-line[0].y)*(line[1].y-line[0].y)+(line[1].x-line[0].x)*(line[1].x-line[0].x));////線段的長度//if((slope>0.3)&&(slope<1000)&&(length>50)&&(length<500))//{//line[0].y= line[0].y+ROI_rect_src.y;//line[1].y =line[1].y+ROI_rect_src.y;//cvLine(frame, line[0], line[1], CV_RGB(255,0,0), 3, CV_AA, 0 );//}if((slope>0.52)&&(slope<2)){  line( image, pt1, pt2, color,3,8,0);}  ++it2;  }  } };#endif

main.cpp

#include<stdio.h>#include <iostream>#include <vector>#include <opencv2/core/core.hpp>//#include <opencv2/imageproc/imageproc.hpp>#include <opencv2/highgui/highgui.hpp>#include<string>  #include <sstream>#include "linefinder.h"//#include "edgedetector.h"#include <opencv2\opencv.hpp> using namespace cv;using namespace std;//#define PI 3.1415926int main(){stringstream ss;  string str; stringstream sss;  string strs; for(int i=1;i<=80;i++)  {  str="C:\\Users\\hsn\\Desktop\\直線檢測\\直線檢測\\作業2\\";//選擇F:\\圖片\\中的5張圖片  ss.clear();  ss<<str;  ss<<i;  ss<<".jpg";  ss>>str;  Mat image=imread(str,1);  // Read input image//Mat image= imread("1.jpg",1);if (!image.data)return 0; /*namedWindow("Original Image");imshow("Original Image",image);*/Mat img=image(Rect(0.4*image.cols,0.58*image.rows,0.4*image.cols,0.3*image.rows));Mat contours;Canny(img,contours,80,100);Mat contoursInv;threshold(contours,contoursInv,128,255,THRESH_BINARY_INV);// Display the image of contours/*namedWindow("Canny Contours");imshow("Canny Contours",contoursInv);*/// Create LineFinder instanceLineFinder ld;// Set probabilistic Hough parametersld.setLineLengthAndGap(60,40);ld.setMinVote(30);vector<Vec4i> li= ld.findLines(contours);ld.drawDetectedLines(img);/*namedWindow(" HoughP");imshow(" HoughP",img);*//*namedWindow("Detected Lines with HoughP");imshow("Detected Lines with HoughP",image);*/Mat imgGry;cvtColor(image,imgGry,CV_BGR2GRAY);GaussianBlur(imgGry,imgGry,Size(5,5),1.5);vector<Vec3f> circles;HoughCircles(imgGry, circles, CV_HOUGH_GRADIENT, 2,   // accumulator resolution (size of the image / 2) 150,  // minimum distance between two circles200, // Canny high threshold 100, // minimum number of votes 25, 50); // min and max radiuscout << "Circles: " << circles.size() << endl;// Draw the circlesvector<Vec3f>::const_iterator itc= circles.begin();while (itc!=circles.end()) {circle(image, Point((*itc)[0], (*itc)[1]), // circle centre(*itc)[2], // circle radiusScalar(255), // color 2); // thickness++itc;}/*namedWindow(str);imshow(str,image);*/strs="C:\\Users\\hsn\\Desktop\\直線檢測\\直線檢測\\處理後\\";//選擇F:\\圖片\\中的5張圖片  sss.clear();  sss<<strs;  sss<<i;  sss<<".jpg";  sss>>strs;  imwrite(strs,image);}int num = 1;  CvSize size = cvSize(1024,960);  //視訊框架格式的大小  double fps = 3;// <span style="white-space:pre">      </span>//每秒鐘的幀率  CvVideoWriter *writer = cvCreateVideoWriter("C:\\Users\\hsn\\Desktop\\直線檢測\\直線檢測\\1.avi",-1,fps,size); //建立視頻檔案  char cname[100];  sprintf(cname,"C:\\Users\\hsn\\Desktop\\直線檢測\\直線檢測\\處理後\\%d.jpg",num); //載入圖片的檔案夾，圖片的名稱編號是1開始1，2,3,4,5.。。。  IplImage *src = cvLoadImage(cname);  if (!src)  {  return 0;  }  IplImage *src_resize = cvCreateImage(size,8,3); //建立視頻檔案格式大小的圖片  cvNamedWindow("avi");  while (src)  {  cvShowImage("avi",src_resize);  cvWaitKey(1); cvResize(src,src_resize); //<span style="white-space:pre">    </span>//將讀取的圖片設定為視頻格式大小相同  cvWriteFrame(writer,src_resize); //儲存圖片為視頻流格式  cvReleaseImage(&src);// <span style="white-space:pre">        </span> //釋放空間  num++;  sprintf(cname,"C:\\Users\\hsn\\Desktop\\直線檢測\\直線檢測\\處理後\\%d.jpg",num);  src = cvLoadImage(cname);       //迴圈讀取資料  }  cvReleaseVideoWriter(&writer);   cvReleaseImage(&src_resize);  waitKey();return 0;}

opencv2實現多張圖片路線路牌(直線和圓）檢測並將處理後的圖片合成視頻_電腦視覺大作業2