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答题卡改卷_vc 答题卡改卷代码

作者：知新_RL | 2024-06-29 04:33:41

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vc 答题卡改卷代码

 当初用C++写的， 高考答题卡 大概原理是先进行模板匹配  得到四个顶点，然后分割出下图这两根线

 

 

读取端点，然后判断目标点上有没有涂黑。

  1. #include <opencv2/opencv.hpp>
  2. #include <iostream>
  3. #include <stdio.h>
  4. #include <conio.h>
  5. #include <stack>
  6. using namespace std;
  7. using namespace cv;
  8.  
  9. vector<char*>  listFiles(const char * dir);
  10. void cuttingX();
  11. void cuttingY();
  12. void HSVthreshold ();//HSV阈值分割
  13. int linex[16]={0};
  14. int liney[22]={0};
  15. //for循环 用%10求余来得到余值加2便可以
  16. /**************请在此处输入正确答案*************************/
  17. int a[60]={15,15,14,14,16,//1-5
  18.            15,14,14,16,15,//6-10
  19.            16,15,16,14,16,//11-15
  20.            15,16,14,15,14,//16-20
  21.            13,11,12,10,12,//21-25
  22.            12,11,10,12,13,//26-30
  23.            11,13,12,10,11,//31-35
  24.            12,10,11,8,7,//36-40
  25.            5,3,6,4,6,//41-45
  26.            6,4,5,4,3,//46-50
  27.            6,5,4,5,3,//51-55
  28.            5,6,6,3,4 //56-60
  29.             };
  30. int main()
  31. {
  32.     /***************拍照***************/
  33.     VideoCapture capture(0);
  34.     waitKey(50);
  35.     capture.set(CV_CAP_PROP_FRAME_WIDTH, 1920);
  36. 	capture.set(CV_CAP_PROP_FRAME_HEIGHT, 1080);
  37. 	while(1)
  38.     {
  39.     Mat src;
  40.     while (1)
  41.     {
  42.     capture >> src;
  43.     Mat src1=src.clone();
  44.  
  45.     int x0 = src1.cols / 4;
  46.     int x1 = src1.cols * 9/10;
  47.     int y0 = src1.rows / 4-140;
  48.     int y1 = src1.rows * 9/10;
  49.     //画线的坐标，起始坐标和终止坐标
  50.  
  51.     cv::Point p0 = cv::Point(x0,y0);
  52.     cv::Point p1 = cv::Point(x1, y0);
  53.     cv::Point p2 = cv::Point(x1, y1);
  54.     cv::line(src1, p0, p1, cv::Scalar(0, 0, 255), 3, 4);
  55.     cv::line(src1, p1, p2, cv::Scalar(0, 0, 255), 3, 4);
  56.     cv::namedWindow("对齐", CV_WINDOW_NORMAL);
  57.     cv::imshow("对齐", src1);
  58.     waitKey(10);
  59.     if(kbhit( ))
  60.     {
  61.         int k1=getch();
  62.         break;
  63.     }}
  64.     imwrite("保存的图像.jpg", src);
  65.     /***************模板匹配***************/
  66.     //Mat src= imread("±£´æ.jpg",1);
  67.     Mat mattmp= imread("3.jpg", 1);
  68.     Mat imagematch;
  69.     Point minLoc;
  70.     Point maxLoc01,maxLoc02,maxLoc03,maxLoc04,judje0;
  71.     Point anchor01,anchor02,anchor03,anchor04;
  72.     double minVal;
  73.     double maxVal2;
  74.     //Mat src = imread("C:/answercard/1.jpg",0);//¶ÁÈëºÚ°×ԭʼͼÏñ
  75.     int srcRows = src.rows;
  76.     int srcCols = src.cols;
  77.     Mat src01 = src(Rect(0,0,srcCols/2,srcRows/2));
  78.     Mat src02 = src(Rect(srcCols/2,0,srcCols/2,srcRows/2));
  79.     Mat src03 = src(Rect(0,srcRows/2,srcCols/2,srcRows/2));
  80.     Mat src04 = src(Rect(srcCols/2,srcRows/2,srcCols/2,srcRows/2));
  81.     //imshow("src01",src01);imshow("src02",src02);imshow("src03",src03);imshow("src04",src04);
  82.  
  83.     matchTemplate( mattmp, src01, imagematch, 5 );
  84.     normalize( imagematch, imagematch, 0, 1, NORM_MINMAX, -1, Mat() );
  85.     minMaxLoc( imagematch, &minVal, &maxVal2, &minLoc, &maxLoc01, Mat() );
  86.     anchor01 = maxLoc01;
  87.     maxLoc01.x=maxLoc01.x+28;
  88.     maxLoc01.y=maxLoc01.y+25;
  89.     circle(src,maxLoc01,3,Scalar(0,255,0),3);
  90.  
  91.     matchTemplate( mattmp, src02, imagematch, 5 );
  92.     normalize( imagematch, imagematch, 0, 1, NORM_MINMAX, -1, Mat() );
  93.     minMaxLoc( imagematch, &minVal, &maxVal2, &minLoc, &maxLoc02, Mat() );
  94.     anchor02 = Point(maxLoc02.x+srcCols/2,maxLoc02.y);
  95.     anchor02.x=anchor02.x+28;
  96.     anchor02.y=anchor02.y+25;
  97.     circle(src,anchor02,3,Scalar(0,255,0),3);
  98.  
  99.     matchTemplate( mattmp, src03, imagematch, 5 );
  100.     normalize( imagematch, imagematch, 0, 1, NORM_MINMAX, -1, Mat() );
  101.     minMaxLoc( imagematch, &minVal, &maxVal2, &minLoc, &maxLoc03, Mat() );
  102.     anchor03 = Point(maxLoc03.x,maxLoc03.y+srcRows/2);
  103.     anchor03.x=anchor03.x+28;
  104.     anchor03.y=anchor03.y+27;
  105.     circle(src,anchor03,3,Scalar(0,255,0),3);
  106.  
  107.     matchTemplate( mattmp, src04, imagematch, 5 );
  108.     normalize( imagematch, imagematch, 0, 1, NORM_MINMAX, -1, Mat() );
  109.     minMaxLoc( imagematch, &minVal, &maxVal2, &minLoc, &maxLoc04, Mat() );
  110.     anchor04 = Point(maxLoc04.x+srcCols/2,maxLoc04.y+srcRows/2);
  111.     anchor04.x=anchor04.x+28;
  112.     anchor04.y=anchor04.y+27;
  113.     circle(src,anchor04,3,Scalar(0,255,0),3);
  114.  
  115.     //cv::namedWindow("原图", CV_WINDOW_NORMAL);
  116.     //cv::imshow("原图", src);
  117.     imwrite("保存图像.jpg", src);
  118.     HSVthreshold ();//HSV阈值分割
  119.     src = imread("img.jpg", 0);
  120.  
  121.  
  122.     /***************区域切割***************/
  123.     threshold(src, src, 16, 255, THRESH_BINARY);
  124. //    imshow("二值图",src);
  125.     GaussianBlur(src, src, Size(9,9), 0);
  126.     Mat element = getStructuringElement(MORPH_RECT, Size(3,4));
  127.     dilate(src, src, element);
  128.     //element = getStructuringElement(MORPH_RECT, Size(5,4));
  129.     erode(src, src, element);
  130.     GaussianBlur(src, src, Size(7,7), 0);
  131.     GaussianBlur(src, src, Size(7,7), 0);
  132. 	//morphologyEx(img, img, MORPH_OPEN, element);
  133. 	//morphologyEx(img, img, MORPH_CLOSE, element);
  134. 	//morphologyEx(img, img, MORPH_OPEN, element);
  135. 	threshold(src, src, 150, 255, THRESH_BINARY);
  136.  //   cv::namedWindow("camera", CV_WINDOW_NORMAL);//CV_WINDOW_NORMAL¾ÍÊÇ0
  137. //    cv::imshow("camera", src);
  138.     IplImage imgTmp = src;
  139.     IplImage* image =  cvCloneImage(&imgTmp);//以上两行为深拷贝
  140.     cvSetImageROI(image,cvRect(maxLoc01.x,anchor02.y-10,anchor02.x-maxLoc01.x,20));//x、y、长、宽
  141.     //cvShowImage("imageROIX",image);//X轴
  142.     cvSaveImage("imageROIX.jpg",image);
  143.     image =  cvCloneImage(&imgTmp);
  144.     cvSetImageROI(image,cvRect(anchor02.x-10,anchor02.y,20,anchor04.y-anchor02.y));//x、y、长、宽
  145.     //cvShowImage("imageROIY",image);//Y轴
  146.     cvSaveImage("imageROIY.jpg",image);
  147.     cuttingX();
  148.     cuttingY();
  149.     /****************答案获取************************/
  150.     //选择题20道 1.5分 1-20
  151.     //21-35       2    36-40是2分一道 7个选项
  152.     //41-60       2
  153.     //用for循环对于某一点的右下角区域进行考察15*15
  154.     //若白色区域大于50 则认为进行了填涂，且为对。且用绿色标注
  155.     //否则为错，并用红色对该点进行标注
  156.     //用for循环开始判断 x位置为linex【a【题号】】 y的位置为题号%liney【10+2】
  157.     cvSetImageROI(image,cvRect(maxLoc01.x,anchor02.y,anchor02.x-maxLoc01.x,anchor04.y-maxLoc02.y));//x、y、长、宽
  158.     cvSaveImage("imageROI.jpg",image);
  159.     Mat srcXY = imread("imageROI.jpg", 1);
  160.     float sum1=0,sum2=0,sum3=0;
  161.     for (int tihao=0;tihao<60;tihao++)//判断每一题的正确与错误
  162.     {
  163.         int whitesum=0;
  164.  
  165.         for (int x=0;x<16;x++)
  166.         {
  167.             for (int y=0;y<16;y++)
  168.             {
  169.                 Vec3b &p = srcXY.at<Vec3b>(liney[tihao%20+2]+y , (linex[a[tihao]-1]+x) );
  170.                 //printf(" （%d,%d）处的颜色为(b=%d, g=%d, r=%d) \n",linex[a[tihao]]+x, liney[tihao%10+2]+y,p[0], p[1], p[2]);
  171.                 //printf("第%d个的答案是%d\r\n",x+y,a[x+y]);
  172.                 if (p[0]>128)
  173.                 {
  174.                     whitesum++;
  175.                 }
  176. //           p[0] = 255;//p1蓝色 用于判断
  177. //			 p[1] = 255; //P2 绿色
  178. //			 p[2] = 255; //P3 红色
  179.             }
  180.         }
  181.         judje0.x=linex[a[tihao]-1];
  182.         judje0.y=liney[tihao%20+2];
  183.         //printf("第%d道题目位置是(%d，%d)\r\n",tihao,judje0.x,judje0.y);
  184.         if (whitesum>20)
  185.         {
  186.             circle(srcXY,judje0,3,Scalar(0,255,0),3);
  187.             if (0<=tihao&tihao<=19) sum1++;
  188.             if (40<=tihao&tihao<=59) sum3++;
  189.             if (20<=tihao&tihao<=39) sum2++;
  190.  
  191.         }
  192.         else
  193.         {
  194.             circle(srcXY,judje0,3,Scalar(0,0,255),3);
  195.         }
  196.  
  197.            // printf("一共有%d个白色像素\n",whitesum);
  198.     }
  199.             imshow("指定点",srcXY);
  200.             imwrite("指定点.jpg",srcXY);
  201.             //cvSaveImage("imageROI.jpg",srcXY);
  202.             printf("该同学1-20得分%.1f\n",(1.5*sum1));
  203.             printf("21-40得分%.1f\n",(sum2*2));
  204.             printf("41-60得分%.1f\n",sum3*1.5);
  205.             printf("总分为%.1f\n",(1.5*sum1+2*sum2+1.5*sum3));
  206.  
  207.     }
  208.     }
  209.  
  210.  
  211.  
  212. void HSVthreshold ()//HSV阈值分割
  213. {
  214. Mat img;
  215. Mat bgr;
  216. Mat hsv;
  217. Mat dst;
  218. 	//输入图像
  219. 	img = imread("保存图像.jpg", IMREAD_COLOR);
  220.  
  221. 	//imshow("原图", img);
  222. 	//彩色图像的灰度值归一化
  223. 	img.convertTo(bgr, CV_32FC3, 1.0 / 255, 0);
  224. 	//颜色空间转换
  225. 	cvtColor(bgr, hsv, COLOR_BGR2HSV);
  226.  
  227.    dst = Mat::zeros(img.size(), CV_32FC3);
  228. 	//掩码
  229. 	Mat mask;
  230. 	inRange(hsv, Scalar(0, 0 / float(255)    ,     0 / float(255))    , Scalar(360 , 255  / float(255)     , 142  / float(255)), mask);
  231. 	//               hmin,smin/float(smin_Max), vmin / float(vmin_Max)), Scalar(hmax, smax / float(smax_Max), vmax / float(vmax_Max)
  232. 	//只保留
  233. 	for (int r = 0; r < bgr.rows; r++)
  234. 	{
  235. 		for (int c = 0; c < bgr.cols; c++)
  236. 		{
  237. 			if (mask.at<uchar>(r, c) == 255)
  238. 			{
  239. 				dst.at<Vec3f>(r, c) = bgr.at<Vec3f>(r, c);
  240. 			}
  241. 		}
  242. 	}
  243. 	//输出图像
  244. 	//imshow("3HSV阈值计算", dst);
  245. 	//保存图像
  246.     dst.convertTo(dst, CV_8UC3, 255.0, 0);
  247. 	imwrite("img.jpg", dst);
  248.     dst.release();//释放内存
  249. 	//waitKey(0);
  250.  
  251. }
  252.  
  253. void cuttingX( )
  254. {
  255.  
  256.     //一共有15个点 后期进行位置排序 并且去掉第一个和最后一个
  257.     Mat matSrc = imread("imageROIX.jpg", 0);
  258.     //threshold(matSrc, matSrc, 135, 254, THRESH_BINARY_INV);
  259.  
  260. 	GaussianBlur(matSrc, matSrc, Size(7,7), 0);
  261. 	vector<vector<Point> > contours;//contours的类型，双重的vector
  262. 	vector<Vec4i> hierarchy;//Vec4i是指每一个vector元素中有四个int型数据。
  263. 	//阈值
  264. 	threshold(matSrc, matSrc, 70, 255, THRESH_BINARY);
  265. 	//imshow("阈值",matSrc);
  266. 	//寻找轮廓，这里注意，findContours的输入参数要求是二值图像，二值图像的来源大致有两种，第一种用threshold，第二种用canny
  267. 	findContours(matSrc.clone(), contours, hierarchy,CV_RETR_EXTERNAL, CHAIN_APPROX_SIMPLE, Point(0, 0));
  268. 	/// 计算矩
  269. 	vector<Moments> mu(contours.size());
  270. 	for (int i = 0; i < contours.size(); i++)
  271. 	{
  272. 		mu[i] = moments(contours[i], false);
  273. 	}
  274. 	///  计算中心矩:
  275. 	vector<Point2f> mc(contours.size());
  276. 	for (int i = 0; i < contours.size(); i++)
  277. 	{
  278. 		mc[i] = Point2f(mu[i].m10 / mu[i].m00, mu[i].m01 / mu[i].m00);
  279. 		linex[i]=int (mu[i].m10 / mu[i].m00);
  280. 		//printf("第 %d 个的位置是 %d\r\n",i,linex[i]);
  281. 	}
  282. 	/// 绘制轮廓
  283. 	Mat drawing = Mat::zeros(matSrc.size(), CV_8UC1);
  284. 	for (int i = 0; i < contours.size(); i++)
  285. 	{
  286. 		Scalar color = Scalar(255);
  287. 		//drawContours(drawing, contours, i, color, 2, 8, hierarchy, 0, Point());
  288. 		circle(drawing, mc[i], 4, color, -1, 8, 0);
  289. 	}
  290. 	int i,j,temp;
  291.     for(j=0;j<=17;j++)//外围循环 循环10次
  292.     {
  293.         for (i=0;i<16-j;i++)//内层循环 循环 10减去外围的循环的第几次
  294.         if (linex[i]>linex[i+1])//比较 比较 a[i]是不是大于a[i+1]是的话
  295.     {
  296.         temp=linex[i]; //就吧a[i]和a[i+1]互相交换了 这样 大的数就 随着循环
  297.         linex[i]=linex[i+1]; //排到 后面了
  298.         linex[i+1]=temp;}
  299.     }
  300.     //for(i=0;i<16;i++)
  301.  //   printf("%d=%d,",i,linex[i] );//去掉前后两个
  302. //    printf("\r\n");
  303. //	imshow("outImageX",drawing);
  304.  
  305. }
  306. void cuttingY( )
  307. {
  308.     Mat matSrc = imread("imageROIY.jpg", 0);
  309.     //threshold(matSrc, matSrc, 120, 254, THRESH_BINARY_INV);
  310.  
  311. 	GaussianBlur(matSrc, matSrc, Size(7, 7), 0);
  312. 	vector<vector<Point> > contours;//contours的类型，双重的vector
  313. 	vector<Vec4i> hierarchy;//Vec4i是指每一个vector元素中有四个int型数据。
  314. 	//阈值
  315. 	threshold(matSrc, matSrc, 70, 255, THRESH_BINARY);
  316. 	//寻找轮廓，这里注意，findContours的输入参数要求是二值图像，二值图像的来源大致有两种，第一种用threshold，第二种用canny
  317. 	findContours(matSrc.clone(), contours, hierarchy,CV_RETR_EXTERNAL, CHAIN_APPROX_SIMPLE, Point(0, 0));
  318. 	/// 计算矩
  319. 	vector<Moments> mu(contours.size());
  320. 	for (int i = 0; i < contours.size(); i++)
  321. 	{
  322. 		mu[i] = moments(contours[i], false);
  323. 	}
  324. 	///  计算中心矩:
  325. 	vector<Point2f> mc(contours.size());
  326. 	for (int i = 0; i < contours.size(); i++)
  327. 	{
  328. 		mc[i] = Point2f(mu[i].m10 / mu[i].m00, mu[i].m01 / mu[i].m00);
  329. 		liney[i]=int (mu[i].m01 / mu[i].m00);
  330. 		//printf("第%d个的位置是%d\r\n",i,liney[i]);
  331. 	}
  332. 	/// 绘制轮廓
  333. 	Mat drawing = Mat::zeros(matSrc.size(), CV_8UC1);
  334. 	for (int i = 0; i < contours.size(); i++)
  335. 	{
  336. 		Scalar color = Scalar(255);
  337. 		//drawContours(drawing, contours, i, color, 2, 8, hierarchy, 0, Point());
  338. 		circle(drawing, mc[i], 4, color, -1, 8, 0);
  339. 	}
  340. 	int i,j,temp;
  341.     for(j=0;j<=23;j++)//外围循环 循环10次
  342.     { for (i=0;i<22-j;i++)//内层循环 循环 10减去外围的循环的第几次
  343.     if (liney[i]>liney[i+1])//比较 比较 a[i]是不是大于a[i+1]是的话
  344.     { temp=liney[i]; //就吧a[i]和a[i+1]互相交换了 这样 大的数就 随着循环
  345.     liney[i]=liney[i+1]; //排到 后面了
  346.     liney[i+1]=temp;}
  347.     }
  348.  //   for(i=0;i<22;i++)
  349.  //   printf("%d=%d,",i,liney[i] );//去掉前后两个
  350. //    printf("\r\n");
  351. //	imshow("outImageY",drawing);
  352.  
  353. }
  354.

 

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