19野狼队任务3

任务要求：识别图片上的方向信息并打印在终端上

以上为示例图片
任务思路：对图片进行滤波等几步预处理之后，在图片中寻找轮廓，将其轮廓包围获得一个包围图形，使用角点检测将其识别。

#include<opencv2/opencv.hpp>
#include<opencv2/highgui/highgui.hpp>
#include<opencv2/imgproc/imgproc.hpp>
#include<iostream>  
using namespace cv;
using namespace std;
void on_CornerHarris(int, void*);
int main(){
    Mat src,ROI1,graysrc,dst,dst1,img;
    src=imread("/home/ma/图片/mmexport1601205165349.jpg");
    imshow("原圖",src);
    ROI1=src(Rect(100,100,320,300));
    imshow("roi1",ROI1);
     blur(ROI1,graysrc,Size(3,6));
    cvtColor(graysrc,dst,COLOR_BGR2GRAY);
    Canny(graysrc,dst,100,200,3,false);
    cvtColor(dst,dst1,COLOR_GRAY2BGR);
     threshold(dst1,img,60,100,THRESH_BINARY);
    vector<Vec4f>lines;
            HoughLinesP(dst,lines,1,CV_PI/180,10,0,0);
            Scalar color=Scalar(0,0,255);
            for (size_t i = 0; i < lines.size(); i++)
                {
                    Vec4f plines=lines[i];
                    line(img,Point(plines[0],plines[1]),Point(plines[2],plines[3]),color,3,LINE_AA);
                }
             putText(img,"Straight",Point(100,280),FONT_HERSHEY_COMPLEX, 1, Scalar(255,23,0),4,8);
            imshow("output",img);
    Mat src1,ROI2,src2,dst2,dst3,dst4,dst5;
    src1=imread("/home/ma/图片/mmexport1601200552742.jpg");
    imshow("原圖1",src1);
    ROI2=src1(Rect(100,100,320,300));
    blur(ROI2,src2,Size(3,3));
    cvtColor(src2,dst2,COLOR_BGR2GRAY);
    Canny(dst2,dst3,100,200,3,false);
    cvtColor(dst3,dst4,COLOR_GRAY2BGR);
        threshold(dst4,dst5,60,100,THRESH_BINARY);
    vector<Vec4f>lines1;
            HoughLinesP(dst3,lines1,1,CV_PI/180,10,0,0);
            Scalar color1=Scalar(0,0,255);
            for(size_t j=0; j < lines1.size(); j++)
            {
                Vec4f plines=lines1[j];
                line(dst5,Point(plines[0],plines[1]),Point(plines[2],plines[3]),color1,3,LINE_AA);
            }
         putText(dst5,"leftturn",Point(80,50),FONT_HERSHEY_COMPLEX,1,Scalar(255,23,0),4,8);
         imshow("output1",dst5);
    Mat src3,ROI3,dst6,dst7,dst8,dst9,dst10;
    src3=imread("/home/ma/下载/mmexport1601200550450.jpg");
    imshow("原圖2",src3);
    ROI3=src3(Rect(150,100,320,300));
    blur(ROI3,dst6,Size(2,4));
    cvtColor(dst6,dst7,COLOR_BGR2GRAY);
    Canny(dst7,dst8,100,200,3,false);
    cvtColor(dst8,dst9,COLOR_GRAY2BGR);
        threshold(dst9,dst10,60,100,THRESH_BINARY);
        vector<Vec4f>lines2;
                HoughLinesP(dst8,lines2,1,CV_PI/180,10,0,0);
                Scalar color2=Scalar(0,0,255);
                for(size_t k=0; k< lines2.size(); k++){
                    Vec4f plines=lines2[k];
                    line(dst10,Point(plines[0],plines[1]),Point(plines[2],plines[3]),color2,3,LINE_AA);
                }
            putText(dst10,"rightturn",Point(100,260),FONT_HERSHEY_COMPLEX,1,Scalar(255,23,0),4,8);
            imshow("output2",dst10);
    Mat src4,ROI4,dsta,dstb,dstc,dstd,dste;
    src4=imread("/home/ma/下载/mmexport1601200545676.jpg");
    imshow("原圖3",src4);
    ROI4=src4(Rect(150,20,380,330));
    blur(ROI4,dsta,Size(3,3));
    cvtColor(dsta,dstb,COLOR_BGR2GRAY);
    Canny(dstb,dstc,100,200,3,false);
    cvtColor(dstc,dstd,COLOR_GRAY2BGR);
        threshold(dstd,dste,60,100,THRESH_BINARY);
        vector<Vec4f>lines3;
        HoughLinesP(dstc,lines3,1,CV_PI/180,10,0,0);
            Scalar color3=Scalar(0,0,255);
            for(size_t z=0; z < lines3.size();z++){
            Vec4f plines=lines3[z];
            line(dste,Point(plines[0],plines[1]),Point(plines[2],plines[3]),color3,3,LINE_AA);
        }
         putText(dste,"crossing",Point(205,100),FONT_HERSHEY_COMPLEX,1,Scalar(255,23,0),4,8);
         imshow("output3",dste);
            waitKey(0);
            return 0;
}

以上为第一版代码，因为二值化的阈值调的太大导致代码效率很低。

#include<opencv2/opencv.hpp>
#include<opencv2/highgui/highgui.hpp>
#include<opencv2/imgproc/imgproc.hpp>
#include<iostream>
using namespace cv;
using namespace std;
int main(){
    Mat src,ROI1,graysrc,dst,dst1,img;
    src=imread("/home/ma/图片/mmexport1601205165349.jpg");
    imshow("原圖",src);
    ROI1=src(Rect(100,100,320,300));
     blur(ROI1,graysrc,Size(3,3));
    cvtColor(ROI1,graysrc,COLOR_BGR2GRAY);
    Canny(graysrc,dst,100,200,3,false);
    cvtColor(dst,dst1,COLOR_GRAY2BGR);
     threshold(dst1,img,60,100,THRESH_BINARY);
    vector<Vec4f>lines;
            HoughLinesP(dst,lines,1,CV_PI/90,10,10,10);
            Scalar color=Scalar(0,0,255);
            for (size_t i = 0; i < lines.size(); i++)
                {
                    Vec4f plines=lines[i];
                    line(img,Point(plines[0],plines[1]),Point(plines[2],plines[3]),color,3,LINE_AA);
                }
            vector<Point2f>getlines1(vector<Vec4f>lines);
                float k1;
                vector<Point2f>linesk1;
                for(unsigned int a=0;a<lines.size();a++){
                    k1=(double)(lines[a][3]-lines[a][1])/(double)(lines[a][3]-lines[a][1]);
            }
                cout<<k1<<endl;
                if(k1==1){
                    putText(img,"Straight",Point(100,280),FONT_HERSHEY_COMPLEX, 1, Scalar(255,23,0),4,8);
                }
            imshow("output",img);
    Mat src1,ROI2,src2,dst2,dst3,dst4,dst5;
    src1=imread("/home/ma/图片/mmexport1601200552742.jpg");
    imshow("原圖1",src1);
    ROI2=src1(Rect(100,100,320,300));
    blur(ROI2,src2,Size(3,3));
    cvtColor(src2,dst2,COLOR_BGR2GRAY);
    Canny(dst2,dst3,100,200,3,false);
    cvtColor(dst3,dst4,COLOR_GRAY2BGR);
        threshold(dst4,dst5,60,100,THRESH_BINARY);
    vector<Vec4f>lines1;
            HoughLinesP(dst3,lines1,1,CV_PI/180,10,0,10);
            Scalar color1=Scalar(0,0,255);
            for(size_t j=0; j < lines1.size(); j++)
            {
                Vec4f plines=lines1[j];
                line(dst5,Point(plines[0],plines[1]),Point(plines[2],plines[3]),color1,3,LINE_AA);
            }
            vector<Point2f>getlines2(vector<Vec4f>lines1);
            float k2;
            vector<Point2f>linesk2;
            for(unsigned int b=0;b<lines1.size();b++){
                 k2=(double)(lines1[b][3]-lines1[b][1])/(double)(lines1[b][3]-lines1[b][1]);
            }
            if(k2==1){
                putText(dst5,"leftturn",Point(80,50),FONT_HERSHEY_COMPLEX,1,Scalar(255,23,0),4,8);
            }
         imshow("output1",dst5);
    Mat src3,ROI3,dst6,dst7,dst8,dst9,dst10;
    src3=imread("/home/ma/下载/mmexport1601200550450.jpg");
    imshow("原圖2",src3);
    ROI3=src3(Rect(150,100,320,300));
    blur(ROI3,dst6,Size(3,4));
    cvtColor(dst6,dst7,COLOR_BGR2GRAY);
    Canny(dst7,dst8,100,200,3,false);
    cvtColor(dst8,dst9,COLOR_GRAY2BGR);
        threshold(dst9,dst10,60,100,THRESH_BINARY);
        vector<Vec4f>lines2;
                HoughLinesP(dst8,lines2,1,CV_PI/180,10,0,15);
                Scalar color2=Scalar(0,0,255);
                for(size_t k=0; k< lines2.size(); k++){
                    Vec4f plines=lines2[k];
                    line(dst10,Point(plines[0],plines[1]),Point(plines[2],plines[3]),color2,3,LINE_AA);
                }
            vector<Point2f>getlines2(vector<Vec4f>lines2);
            float k3;
            vector<Point2f>linesk3;
            for(unsigned int c=0;c<lines2.size();c++){
                 k3=(double)(lines1[c][3]-lines1[c][1])/(double)(lines1[c][3]-lines1[c][1]);
            }
            if(k3==1){
                putText(dst10,"rightturn",Point(100,260),FONT_HERSHEY_COMPLEX,1,Scalar(255,23,0),4,8);
            }
            imshow("output2",dst10);
    Mat src4,ROI4,dsta,dstb,dstc,dstd,dste;
    src4=imread("/home/ma/下载/mmexport1601200545676.jpg");
    imshow("原圖3",src4);
    ROI4=src4(Rect(150,20,380,330));
    blur(ROI4,dsta,Size(3,3));
    cvtColor(dsta,dstb,COLOR_BGR2GRAY);
    Canny(dstb,dstc,100,200,3,false);
    cvtColor(dstc,dstd,COLOR_GRAY2BGR);
        threshold(dstd,dste,60,100,THRESH_BINARY);
        vector<Vec4f>lines3;
        HoughLinesP(dstc,lines3,1,CV_PI/180,10,0,15);
            Scalar color3=Scalar(0,0,255);
            for(size_t z=0; z < lines3.size();z++){
            Vec4f plines=lines3[z];
            line(dste,Point(plines[0],plines[1]),Point(plines[2],plines[3]),color3,3,LINE_AA);
        }
            vector<Point2f>getlines2(vector<Vec4f>lines3);
            float k4;
            vector<Point2f>linesk4;
            for(unsigned int d=0;d<lines3.size();d++){
                 k4=(double)(lines3[d][3]-lines3[d][1])/(double)(lines3[d][3]-lines3[d][1]);
            }
            if(k4==1){
            }
            putText(dste,"crossing",Point(205,100),FONT_HERSHEY_COMPLEX,1,Scalar(255,23,0),4,8);
         imshow("output3",dste);
            waitKey(0);
            return 0;
}

第二版代码使用了ROI,使得阈值不需要太大从而大大的提升了代码效率。