用OPENCV视觉解数独
2010-06-29
看到增强视觉网站上介绍老外用视觉解SUDOKU(http://www.cvchina.info/2011/05/29/video-sudoku-solver/)，觉得应该不难，于是用OPENCV和训练好的数字分类器，也试着做一个，纯属娱乐
基本思路如下：
一，定位网格，
1，寻找图像中的矩形，使用OPENCV中经典找矩形（因为速度问题使用C版本）代码就可以，将条件降低（CANNY的对比度和角度是否直角）以便找到更多的矩形。
2，由于不一定能找到所有的矩形，需要根据找到的矩形对网格进行推算，推算出的矩形被称为“虚拟矩形”
3，最后对网格中的虚拟矩形根据上下的矩形进行位置修正
二，数字分析
网格中存在两种可能，有数据和没有数据。我们通过对比度和轮廓大小过滤掉没有数据的网格。
对剩下的网格进行数字分析，使用SVM手写数字分类器，得到该网格的数据
三，求解
剩下的问题就简单了，对得到的SUDOKU题目进行求解就可以啦
效果吗，对网格和数字比较清晰的图像效果不错，从模糊的图片就差一些了，主要是数字和边框不清晰，导致矩形寻找和数字判断错误，可以根据图像的特征进行优化，但如果能做到各种图片通吃就困难多了。
手写数字的图片（蓝色为找到的网格，绿色为推算出的虚拟网格）：
识别结果：
印刷数字的图片（蓝色为找到的网格，绿色为推算出的虚拟网格）：
失败的例子，由于网格不清晰，导致无法找到足够的矩形网格：
主要代码如下（不包括SUDOKU求解部分），
// Sudoku detect #include "stdafx.h" #ifdef _CH_ #pragma package <opencv> #endif #ifndef _EiC #include "opencv2/opencv.hpp" #include <stdio.h> #include <math.h> #include <string.h> #endif #include <vector> #include <list> using namespace cv; #define SHOW_IMG 0 const double MIN_CONTOUR_PROPORTION = 0.02; const int CANNY_LOW_THRESH = 0; const int CANNY_HIGH_THRESH = 30; //int thresh = 50; const double MIN_ANGLE = 0.1; //double MIN_ANGLE = 0.05; IplImage* img = 0; IplImage* img0 = 0; CvMemStorage* storage = 0; CvPoint pt[4]; const char* wndname = "Square Detection Demo"; class FilterRect { public: Rect rc; bool useFlag; FilterRect() { rc = Rect(0, 0, 0, 0); useFlag = false; } }; vector<Rect> allRects; vector<FilterRect> filterRects; const int SUDOKU_GRID_NUM = 9; const unsigned int DIFF_THRESHOLD = 16; class RtTrainData { public: float data[64]; int result; }; class ValidRect { public: Rect rc; int row; int col; bool blankFlag; bool virtualFlag; Rect contourRc; double contrast; double areaProportion; ValidRect() { rc = Rect(0, 0, 0, 0); contourRc = Rect(0, 0, 0, 0); row = 0; col = 0; blankFlag = true; virtualFlag = true; contrast = 0.0; areaProportion = 0.0; } }; ValidRect validRects[81]; typedef struct rectWithArea { CvPoint pt[4]; double area; }RectWithArea; bool compareRects(const Rect& rc1, const Rect& rc2, bool& replaceFirst) { int dx = rc1.x - rc2.x; int dy = rc1.y - rc2.y; int dw = rc1.width - rc2.width; int dh = rc1.height - rc2.height; //if((dx*dx + dy*dy + dw*dw + dh*dh) < DIFF_THRESHOLD) if((dx*dx + dy*dy + dw*dw + dh*dh) < DIFF_THRESHOLD) { if(rc1.area() > rc2.area()) replaceFirst = true; else replaceFirst = false; return true; } else return false; } double getBkInfo(Mat& src, float& highProportion, Scalar& contrast) { Mat temp, high, low; Rect rc(src.cols / 10, src.rows / 10, src.cols * 0.9, src.rows * 0.9); temp = src(rc); double thresh = threshold(temp, high, 0, 0, CV_THRESH_OTSU); //求出分割阈值 threshold(temp, high, thresh, 0, CV_THRESH_TOZERO); //分割高亮部分 threshold(temp, low, thresh, 0, CV_THRESH_TOZERO_INV); //分割低暗部分 int highCount = cv::countNonZero(high); highProportion = (float)highCount / src.total(); //highProportion = (float)highCount / (src.rows * src.cols); Scalar lowValue = mean(low); Scalar highValue = mean(high); contrast = (highValue - lowValue) / lowValue; double ret = abs(contrast.val[0]); return ret; } // helper function: // finds a cosine of angle between vectors // from pt0->pt1 and from pt0->pt2 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); } // returns sequence of squares detected on the image. // the sequence is stored in the specified memory storage CvSeq* findSquares4( IplImage* img, CvMemStorage* storage ) { const int MAX_CONTOUR_SIZE = img->width * img->height / 80; const int MIN_CONTOUR_SIZE = MAX_CONTOUR_SIZE / 16; int contours_num = 0; CvSeq* contours; int i, c, l, N = 1; //11; CvSize sz = cvSize( img->width & -2, img->height & -2 ); IplImage* timg = cvCloneImage( img ); // make a copy of input image //IplImage* timg2 = cvCloneImage( img ); // make a copy of input image 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; // create empty sequence that will contain points - // 4 points per square (the square's vertices) CvSeq* squares = cvCreateSeq( 0, sizeof(CvSeq), sizeof(RectWithArea), storage ); // select the maximum ROI in the image // with the width and height divisible by 2 cvSetImageROI( timg, cvRect( 0, 0, sz.width, sz.height )); //Only care RED //cvSetImageCOI( timg2, 3 ); //cvCopy(timg2, gray, NULL); // down-scale and upscale the image to filter out the noise cvPyrDown( timg, pyr, 7 ); cvPyrUp( pyr, timg, 7 ); tgray = cvCreateImage( sz, 8, 1 ); // find squares in every color plane of the image for( c = 0; c < 3; c++ ) { // extract the c-th color plane cvSetImageCOI( timg, c+1 ); cvCopy( timg, tgray, 0 ); // try several threshold levels for( 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) cvCanny( tgray, gray, CANNY_LOW_THRESH, CANNY_HIGH_THRESH, 5 ); // dilate canny output to remove potential // holes between edge segments cvDilate( gray, gray, 0, 1 ); } else { // apply threshold if l!=0: // tgray(x,y) = gray(x,y) < (l+1)*255/N ? 255 : 0 cvThreshold( tgray, gray, (l+1)*255/N, 255, CV_THRESH_BINARY ); } //imshow("gray", gray); //waitKey(0); // find contours and store them all as a list cvFindContours( gray, storage, &contours, sizeof(CvContour), CV_RETR_LIST, CV_CHAIN_APPROX_SIMPLE, cvPoint(0,0) ); // test each contour while( contours ) { contours_num++; // approximate contour with accuracy proportional // to the contour perimeter result = cvApproxPoly( contours, sizeof(CvContour), storage, CV_POLY_APPROX_DP, cvContourPerimeter(contours)*0.02, 0 ); // 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( result->total == 4 && fabs(cvContourArea(result,CV_WHOLE_SEQ)) > MIN_CONTOUR_SIZE && fabs(cvContourArea(result,CV_WHOLE_SEQ)) < MAX_CONTOUR_SIZE && cvCheckContourConvexity(result) ) { s = 0; for( i = 0; i < 5; i++ ) { // find minimum angle between joint 检查3个角就足够了（对四边形来说如果三个角为直角，则第四个也为直角） // 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 cosines of all angles are small // (all angles are ~90 degree) then write quandrange // vertices to resultant sequence if( s < MIN_ANGLE ) { RectWithArea rwa; for(int i=0; i<4; i++) rwa.pt[i] = *(CvPoint*)cvGetSeqElem( result, i ); rwa.area = fabs(cvContourArea(result,CV_WHOLE_SEQ)); cvSeqPush( squares, &rwa); //Add to all rects Rect rect(rwa.pt[0], rwa.pt[2]); allRects.push_back(rect); } } // take the next contour contours = contours->h_next; } } } // release all the temporary images cvReleaseImage( &gray ); cvReleaseImage( &pyr ); cvReleaseImage( &tgray ); cvReleaseImage( &timg ); return squares; } // the function draws all the squares in the image /* Sort 2d points in top-to-bottom left-to-right order */ static int cmp_func( const void* _a, const void* _b, void* userdata ) { RectWithArea* a = (RectWithArea*)_a; RectWithArea* b = (RectWithArea*)_b; return a->area < b->area ? -1 : a->area > b->area ? 1 : 0; } void drawSquares( IplImage* img, CvSeq* squares ) { cvSeqSort( squares, cmp_func, 0); CvSeqReader reader; IplImage* cpy = cvCloneImage( img ); int i; // initialize reader of the sequence cvStartReadSeq( squares, &reader, 0 ); // read 4 sequence elements at a time (all vertices of a square) for( i = 0; i < squares->total; i ++ ) { RectWithArea rwa; int count = 4; // draw the square as a closed polyline memcpy(&rwa, reader.ptr, squares->elem_size); CvPoint* rect = pt; pt[0] = rwa.pt[0]; pt[1] = rwa.pt[1]; pt[2] = rwa.pt[2]; pt[3] = rwa.pt[3]; cvPolyLine( cpy, &rect, &count, 1, 1, CV_RGB(0,255,0), 3, CV_AA, 0 ); CV_NEXT_SEQ_ELEM( squares->elem_size, reader ); //if(i>10) // break; } // show the resultant image cvShowImage( wndname, cpy ); cvReleaseImage( &cpy ); } void filterDupRect() { for(unsigned int i=0; i<allRects.size(); i++) { bool insertFlag = true; for(unsigned int j=0; j<filterRects.size(); j++) { bool replaceFlag = false; if(compareRects(filterRects[j].rc, allRects[i], replaceFlag)) { if(replaceFlag) filterRects[j].rc = allRects[i]; //Using smaller one insertFlag = false; //Have similiar, not save break; } } if(insertFlag) { FilterRect fr; fr.rc = allRects[i]; filterRects.push_back(fr); } } } int findTopLeftRect(Mat& src) { int min_dist = src.size().width + src.size().height; int index = -1; for(unsigned int j = 0; j < filterRects.size(); j ++ ) { int dist = filterRects[j].rc.x + filterRects[j].rc.y; if(dist < min_dist) { min_dist = dist; index = j; } } return index; } void updateValidRect(int col, int row, Rect rc, bool virtualFlag) { int index = col + row * 9; validRects[index].col = col; validRects[index].row = row; validRects[index].rc = rc; //validRects[index].processFlag = true; validRects[index].virtualFlag = virtualFlag; } int findNearest(Rect& rc, int offsetX, int offsetY) { int min_dist = 1000; int index = -1; for(unsigned int j = 0; j < filterRects.size(); j ++ ) { if(filterRects[j].useFlag == true) continue; int dx = abs(filterRects[j].rc.x -offsetX); int dy = abs(filterRects[j].rc.y -offsetY); int dw = abs(filterRects[j].rc.width - rc.width); int dh = abs(filterRects[j].rc.height - rc.height); int dist = dx+dy+dw+dh; if( dist < min_dist) { index = j; min_dist = dist; } } int maxDiff = rc.width / 4 + rc.height / 4; if(min_dist < maxDiff) return index; else return -1; } bool findValidRects(Mat& src) { int maxW = src.size().width; int maxH = src.size().height; int dx = 10, dy = 10; for(int row = 0; row < 9; row++) { for(int col = 0; col < 9; col++) { if((row == 0) && (col == 0)) { int index = findTopLeftRect(src); if(index>0) { updateValidRect(col, row, filterRects[index].rc, false); filterRects[index].useFlag = true; } else return false; } else if(row == 0) { Rect leftRc = validRects[col -1].rc; //Align to left int offsetX = leftRc.x + leftRc.width + dx; int offsetY = leftRc.y; int index = findNearest(leftRc, offsetX, offsetY); if(index>0) //Find rect { updateValidRect(col, row, filterRects[index].rc, false); filterRects[index].useFlag = true; } else if( (offsetX + leftRc.width) > maxW) //over the scale { return false; } else { leftRc.x = offsetX; leftRc.y = offsetY; updateValidRect(col, row, leftRc, true); } } else if(col == 0) { Rect upRc = validRects[9*(row-1) + col ].rc; //Align to top int offsetX = upRc.x; int offsetY = upRc.y + upRc.height + dy; int index = findNearest(upRc, offsetX, offsetY); if(index>0) { updateValidRect(col, row, filterRects[index].rc, false); filterRects[index].useFlag = true; } else if( (offsetY + upRc.height) > maxH) { return false; } else { upRc.x = offsetX; upRc.y = offsetY; updateValidRect(col, row, upRc, true); } } else { Rect leftRc = validRects[9*row + col -1].rc; //Align to left and top Rect upRc = validRects[9*(row-1) + col ].rc; int offsetX = upRc.x; int offsetY = leftRc.y; int index = findNearest(leftRc, offsetX, offsetY); //Widht and height can use left or top if(index>0) { updateValidRect(col, row, filterRects[index].rc, false); filterRects[index].useFlag = true; } else if( (offsetX + leftRc.width) > maxW) { return false; } else if( (offsetY + upRc.height) > maxH) { return false; } else { leftRc.x = offsetX; leftRc.y = offsetY; leftRc.width = upRc.width; updateValidRect(col, row, leftRc, true); } } } } } int getVirtualRectsCount() { int count = 0; for(int i = 0; i < 81; i++) { if(validRects[i].virtualFlag == true) count++; } return count; } bool modifyValidRect() { for(int row = 0; row < 9; row++) { for(int col = 0; col < 9; col++) { if(validRects[9*row+col].virtualFlag == false) continue; ValidRect leftRc, upRc, rightRc, bottomRc; bool left, up, right, bottom; left = false; up = false; right = false; bottom = false; if(row != 0) { upRc = validRects[9*(row-1) + col ]; up = true; } if(row != 8) { bottomRc = validRects[9*(row + 1) + col]; bottom = true; } if(col != 0) { leftRc = validRects[9*row + col -1]; left = true; } if(col != 8) { rightRc = validRects[9*row + col + 1]; right = true; } if(left && (leftRc.virtualFlag == false)) { validRects[9*row+col].rc.y = leftRc.rc.y; validRects[9*row+col].rc.height = leftRc.rc.height; } else if(right && (rightRc.virtualFlag == false)) { validRects[9*row+col].rc.y = rightRc.rc.y; validRects[9*row+col].rc.height = rightRc.rc.height; } if(up && (upRc.virtualFlag == false)) { validRects[9*row+col].rc.x = upRc.rc.x; validRects[9*row+col].rc.width = upRc.rc.width; } else if(bottom && (bottomRc.virtualFlag == false)) { validRects[9*row+col].rc.x = bottomRc.rc.x; validRects[9*row+col].rc.width = bottomRc.rc.width; } } } return true; } //int findNearest(Mat& src, int offsetX, int offsetY) //{ // int max_dist = src.size().width * src.size().width + src.size().height * src.size().height; // int index = -1; // // for(unsigned int j = 0; j < stardRect.size(); j ++ ) // { // int dx = stardRect[j].x -offsetX; // int dy = stardRect[j].y -offsetY; // // int dist = dx*dx + dy*dy; // if( dist < max_dist) // { // index = j; // max_dist = dist; // } // } // // if(max_dist < 1800) // return index; // else // return -1; //} // void GetROI(Mat& src, Mat& dst) { int left, right, top, bottom; left = src.cols; right = 0; top = src.rows; bottom = 0; for(int i=0; i<src.rows; i++) { for(int j=0; j<src.cols; j++) { if(src.at<uchar>(i, j) > 0) { if(j<left) left = j; if(j>right) right = j; if(i<top) top = i; if(i>bottom) bottom = i; } } } cv::Point center; center.x = (left + right) / 2; center.y = (top + bottom) / 2; int width = right - left; int height = bottom - top; int len = (width < height) ? height : width; dst = Mat::zeros(len, len, CV_8UC1); cv::Rect dstRect((len - width)/2, (len - height)/2, width, height); cv::Rect srcRect(left, top, width, height); Mat dstROI = dst(dstRect); Mat srcROI = src(srcRect); srcROI.copyTo(dstROI); } //bool findValidRects(Mat& src, double stardWidth, double stardHeight) //{ // int minX, minY, maxX = 0, maxY = 0; // minX = src.cols; // minY = src.rows; // // for(unsigned int j = 0; j < stardRect.size(); j ++ ) // { // if(stardRect[j].x < minX) minX = stardRect[j].x; // if(stardRect[j].x > maxX) maxX = stardRect[j].x; // if(stardRect[j].y < minY) minY = stardRect[j].y; // if(stardRect[j].y > maxY) maxY = stardRect[j].y; // } // // int cols = (maxX - minX) / stardWidth + 0.5; // int rows = (maxY - minY) / stardHeight + 0.5; // // // //Not enough valid rect // if( (cols != 9) || (rows != 9) ) // return false; // // int realWidth = (maxX - minX) / 8; // int realHight = (maxY - minY) / 8; // // for(int row = 0; row<rows; row++) // { // for(int col = 0; col<cols; col++) // { // int offsetX = col * realWidth + minX; // int offsetY = row * realHight + minY; // // int index = findNearest(src, offsetX, offsetY); // int vIndex = col + row *9; // // if(index >= 0) // { // validRects[vIndex].rc = stardRect[index]; // validRects[vIndex].flag = true; // } // else // { // validRects[vIndex].rc = Rect( offsetX, offsetY, stardWidth, stardHeight); // validRects[vIndex].flag = false; // } // validRects[vIndex].col = col; // validRects[vIndex].row = row; // // //Only care about 90% rect(ignore edge noise) // //validRects[vIndex].rc.x = validRects[vIndex].rc.x + validRects[vIndex].rc.width / 10; // //validRects[vIndex].rc.y = validRects[vIndex].rc.y + validRects[vIndex].rc.height / 10; // //validRects[vIndex].rc.width = validRects[vIndex].rc.width / 10 * 9; // //validRects[vIndex].rc.height = validRects[vIndex].rc.height / 10 * 9; // // } // } // // return true; //} // //bool findStardardRect(Mat& dst) //{ // int allCount = rects.size(); // // if(allCount < 81) // return false; // // // read 4 sequence elements at a time (all vertices of a square) // int step = 20; // //int step = 8; // int start1 = 0, start2 = step / 2; // // Mat widths = Mat::zeros(2, dst.cols / step + 1, CV_16UC1); // Mat heights = Mat::zeros(2, dst.rows / step + 1, CV_16UC1); // // int col1, col2, row1, row2; // // for(unsigned int i = 0; i < rects.size(); i ++ ) // { // col1 = rects[i].width / step; // col2 = (rects[i].width - start2) / step; // // row1 = rects[i].height / step; // row2 = (rects[i].height - start2) / step; // // widths.at<short>(0, col1) = widths.at<short>(0, col1) + 1; // widths.at<short>(1, col2) = widths.at<short>(1, col2) + 1; // heights.at<short>(0, row1) = heights.at<short>(0, row1) + 1; // heights.at<short>(1, row2) = heights.at<short>(1, row2) + 1; // // //cv::rectangle(dst, rects[i], CV_RGB(0,255,0)); // } // // double maxCol, maxRow; // // Point pt1, pt2; // // cv::minMaxLoc(widths, 0, &maxCol, 0, &pt1, Mat()); // cv::minMaxLoc(heights, 0, &maxRow, 0, &pt2, Mat()); // // double stardWidth = pt1.x * step + step / 2 + pt1.y * start2; // double stardHeight = pt2.x * step + step / 2 + pt2.y * start2; // // for(unsigned int i = 0; i < rects.size(); i ++ ) // { // if( (abs(rects[i].width - stardWidth) < step / 2) && (abs(rects[i].height - stardHeight) < step / 2 ) ) //Sharp check // { // bool flag = true; // for(unsigned int j = 0; j < stardRect.size(); j ++ ) // { // if( (abs(rects[i].x - stardRect[j].x) < (stardWidth - step / 2)) && (abs(rects[i].y - stardRect[j].y) < (stardHeight - step / 2)) ) // { // flag = false; // break; // } // } // // if(flag) // stardRect.push_back(rects[i]); // } // } // // return findValidRects(dst, stardWidth, stardHeight); //} // void drawAllRect(Mat& dst) { //for(unsigned int i = 0; i < stardRect.size(); i ++ ) // { // cv::rectangle(dst, stardRect[i], CV_RGB(0,255,0)); //} for(unsigned int i = 0; i < allRects.size(); i ++ ) { cv::rectangle(dst, allRects[i], CV_RGB(0,255,128), 5); } } void drawFilterRect(Mat& dst) { //for(unsigned int i = 0; i < stardRect.size(); i ++ ) // { // cv::rectangle(dst, stardRect[i], CV_RGB(0,255,0)); //} for(unsigned int i = 0; i < filterRects.size(); i ++ ) { cv::rectangle(dst, filterRects[i].rc, CV_RGB(255,255,0), 5); } } void drawValidRect(Mat& dst) { //for(unsigned int i = 0; i < stardRect.size(); i ++ ) // { // cv::rectangle(dst, stardRect[i], CV_RGB(0,255,0)); //} for(unsigned int i = 0; i < 81; i ++ ) { if(validRects[i].virtualFlag) cv::rectangle(dst, validRects[i].rc, CV_RGB(0,255,0), 5); else cv::rectangle(dst, validRects[i].rc, CV_RGB(0,0,255), 5); } } void newFindSquares4(Mat& src) { storage = cvCreateMemStorage(0); IplImage* img = &IplImage(src); findSquares4(img, storage); } int getMaxContour(vector<vector<Point>> &contours, double& maxArea) { int index = -1; maxArea = -1; for(unsigned int i=0; i<contours.size(); i++) { double area = cv::contourArea(Mat(contours[i])); if(area>maxArea) { index = i; maxArea = area; } } return index; } void removeBlank(Mat& src) { Mat gray, tempGray; cvtColor(src, gray, CV_RGB2GRAY); cv::pyrDown(gray, tempGray); //, 7 ); cv::pyrUp(tempGray, gray ); //, 7 ); //cv::GaussianBlur(gray, tempGray, cvSize(3,3), 3); //cv::GaussianBlur(tempGray, gray, cvSize(3,3), 3); //medianBlur(gray, tempGray, 1); //medianBlur(tempGray, gray, 1); //dilate(dst, temp, Mat(), Point(-1,-1), 3); //dilate(temp, dst, Mat(), Point(-1,-1), 3); //erode(gray, tempGray, Mat(), Point(-1,-1), 1); //dilate(tempGray, gray, Mat(), Point(-1,-1), 1); //cv::subtract(dst, back, dst, Mat()); //equalizeHist(dst, dst); #if(0) Mat gray2; resize(gray, gray2, cvSize(gray.size().width / 2, gray.size().height / 2)); imshow("gray", gray2); if(waitKey(0) == 27) return; #endif for(unsigned int i = 0; i < 81; i ++ ) { validRects[i].blankFlag = true; //Mat dst, back, temp; Mat dst = gray(validRects[i].rc); float proportion; Scalar contrast; validRects[i].contrast = getBkInfo(dst, proportion, contrast); if(validRects[i].contrast<2) // || proportion>0.95) { //stringstream ss; cout << "No number at " << i << ", contrast " << validRects[i].contrast << endl; continue; } //Make inner ellipse to reduce edge noise Point2f centerPt; centerPt.x = dst.size().width / 2; centerPt.y = dst.size().height / 2; cv::RotatedRect rrc(centerPt, cvSize(dst.size().width, dst.size().height), 0); Mat mask = Mat::zeros(dst.size(), CV_8UC1); cv::ellipse(mask, rrc, Scalar(255,255,255), -1); Mat temp, temp2; temp2 = Mat::zeros(dst.size(), CV_8UC1); double thresh = threshold(dst, temp, 0, 0, CV_THRESH_OTSU); //求出分割阈值 threshold(dst, temp, thresh, 255, CV_THRESH_BINARY_INV); //分割 temp.copyTo(temp2, mask & 1); temp2.copyTo(temp); //if(i==60) //{ // imshow("BIN", temp); // if(waitKey(0) == 27) // break; //} //cv::adaptiveThreshold(dst, temp, 255, CV_ADAPTIVE_THRESH_MEAN_C, CV_THRESH_BINARY_INV, 3, 5); vector<vector<Point>> contours; vector<Vec4i> hierarchy; #if(0) imshow("ellipse", temp); if(waitKey(0) == 27) break; #endif //Mat mColor = Mat::zeros(temp.size(), CV_8UC3); findContours(temp, contours, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_SIMPLE); //CV //findContours(temp, contours, hierarchy, CV_RETR_TREE, CV_CHAIN_APPROX_SIMPLE); //CV Scalar color(0, 255, 255 ); double maxArea = -1; int maxContourIndex = getMaxContour(contours, maxArea); validRects[i].areaProportion = maxArea / validRects[i].rc.area(); if(maxContourIndex < 0) { cout << "No number at " << i << ", no contour find " << endl; continue; } else if(validRects[i].areaProportion < MIN_CONTOUR_PROPORTION) //(validRects[i].rc.area() / 50) ) { cout << "No number at " << i << ", contour area too small, proportion is " << validRects[i].areaProportion << endl; continue; } else { validRects[i].blankFlag = false; validRects[i].contourRc = boundingRect(Mat(contours[maxContourIndex])); //if(validRects[i].contrast > 20) //{ // imshow("ellipse", temp); // if(waitKey(0) == 27) // break; //} } } } void Predict(Mat& src) { char result[81]; memset(result, '-', sizeof(result)); //CvRTrees forest; //forest.load( "D:\\SourceCode\\2011\\CV\\CvChessMove\\SvmClassifierForNum\\new_rtrees_10000.xml" ); int featureLen = 64; CvSVM svm; svm.load( "D:\\SourceCode\\2011\\CV\\CvChessMove\\SvmClassifierForNum\\SVM_DATA_60000.xml" ); RtTrainData rtd; memset(rtd.data, 0, sizeof(rtd.data)); Mat m = Mat::zeros(1, featureLen, CV_32FC1); Mat gray, tempGray; cvtColor(src, gray, CV_RGB2GRAY); #if(0) imshow("gray", gray); if(waitKey(0) == 27) return; #endif for(unsigned int i = 0; i < 81; i ++ ) { Mat dst = gray(validRects[i].rc); if(validRects[i].blankFlag == false) { Mat target, temp; double thresh = threshold(dst, target, 0, 0, CV_THRESH_OTSU); //求出分割阈值 threshold(dst, target, thresh, 255, CV_THRESH_BINARY_INV); //分割 GetROI(target(validRects[i].contourRc), temp); #if(0) imshow("NUM", temp); if(waitKey(0) == 27) break; #endif Mat temp2 = Mat::zeros(8, 8, CV_8UC1); resize(temp, temp2, temp2.size()); for(int i = 0; i<8; i++) { for(int j = 0; j<8; j++) { rtd.data[j + i*8] = temp2.at<uchar>(i, j); //注意m.data为UCHAR*类型，因此m的值不能使用下面的表达式 //m.data[j + i*8] = temp3.at<uchar>(i, j); } } memcpy(m.data, rtd.data, featureLen * sizeof(float)); GetRectFeatures(rtd); //memcpy(m.data, rtd.data, featureLen * sizeof(float)); //result[i] = forest.predict(m); normalize(m, m); float svm_ret = svm.predict(m); char svm_char = (char)svm_ret; cout << svm_char << " at " << i << ", contour proportion " << validRects[i].areaProportion << ", contrast " << validRects[i].contrast << endl; result[i] = svm.predict(m); } } cout << endl << "SUDOKU RESULT: "<< endl; for(int i=0; i<9; i++) { for(int j=0; j<9; j++) cout << result[9*i+j] << '\t'; cout << endl; } } int main(int argc, char** argv) { string fileName = "../../res/sudoku/svg_sudoku7.jpg"; Mat src = imread(fileName, 1); Mat dst; // = Mat::zeros(cvSize(src.size().width / 2, src.size().height / 2), CV_8UC3); //Mat org = imread(fileName, 1); //flip(src, src, -1); //Mat src = Mat::zeros(768, 1024, CV_8UC3); //resize(org, src, src.size()); newFindSquares4(src); filterDupRect(); //drawAllRect(src); //drawFilterRect(src); //resize(src, dst, cvSize(src.size().width / 2, src.size().height / 2)); //imshow("all", src); //waitKey(0); if(findValidRects(src)) { int vc = getVirtualRectsCount(); cout << "Virtual rects count is " << vc << endl; if(vc < 30) { modifyValidRect(); removeBlank(src); Predict(src); } else cout << "Too much virtual rects to continue predict" << endl; } else cout << "Find rects error" << endl; drawValidRect(src); resize(src, dst, cvSize(src.size().width / 2, src.size().height / 2)); imshow("IMG", dst); waitKey(0); return 0; }
