1// The "Square Detector" program. 2// It loads several images sequentially and tries to find squares in 3// each image 4 5#include "opencv2/core.hpp" 6#include "opencv2/core/ocl.hpp" 7#include "opencv2/core/utility.hpp" 8#include "opencv2/imgproc/imgproc.hpp" 9#include "opencv2/imgcodecs.hpp" 10#include "opencv2/highgui/highgui.hpp" 11#include <iostream> 12#include <string.h> 13 14using namespace cv; 15using namespace std; 16 17int thresh = 50, N = 11; 18const char* wndname = "Square Detection Demo"; 19 20// helper function: 21// finds a cosine of angle between vectors 22// from pt0->pt1 and from pt0->pt2 23static double angle( Point pt1, Point pt2, Point pt0 ) 24{ 25 double dx1 = pt1.x - pt0.x; 26 double dy1 = pt1.y - pt0.y; 27 double dx2 = pt2.x - pt0.x; 28 double dy2 = pt2.y - pt0.y; 29 return (dx1*dx2 + dy1*dy2)/sqrt((dx1*dx1 + dy1*dy1)*(dx2*dx2 + dy2*dy2) + 1e-10); 30} 31 32 33// returns sequence of squares detected on the image. 34// the sequence is stored in the specified memory storage 35static void findSquares( const UMat& image, vector<vector<Point> >& squares ) 36{ 37 squares.clear(); 38 UMat pyr, timg, gray0(image.size(), CV_8U), gray; 39 40 // down-scale and upscale the image to filter out the noise 41 pyrDown(image, pyr, Size(image.cols/2, image.rows/2)); 42 pyrUp(pyr, timg, image.size()); 43 vector<vector<Point> > contours; 44 45 // find squares in every color plane of the image 46 for( int c = 0; c < 3; c++ ) 47 { 48 int ch[] = {c, 0}; 49 mixChannels(timg, gray0, ch, 1); 50 51 // try several threshold levels 52 for( int l = 0; l < N; l++ ) 53 { 54 // hack: use Canny instead of zero threshold level. 55 // Canny helps to catch squares with gradient shading 56 if( l == 0 ) 57 { 58 // apply Canny. Take the upper threshold from slider 59 // and set the lower to 0 (which forces edges merging) 60 Canny(gray0, gray, 0, thresh, 5); 61 // dilate canny output to remove potential 62 // holes between edge segments 63 dilate(gray, gray, UMat(), Point(-1,-1)); 64 } 65 else 66 { 67 // apply threshold if l!=0: 68 // tgray(x,y) = gray(x,y) < (l+1)*255/N ? 255 : 0 69 cv::threshold(gray0, gray, (l+1)*255/N, 255, THRESH_BINARY); 70 } 71 72 // find contours and store them all as a list 73 findContours(gray, contours, RETR_LIST, CHAIN_APPROX_SIMPLE); 74 75 vector<Point> approx; 76 77 // test each contour 78 for( size_t i = 0; i < contours.size(); i++ ) 79 { 80 // approximate contour with accuracy proportional 81 // to the contour perimeter 82 83 approxPolyDP(Mat(contours[i]), approx, arcLength(Mat(contours[i]), true)*0.02, true); 84 85 // square contours should have 4 vertices after approximation 86 // relatively large area (to filter out noisy contours) 87 // and be convex. 88 // Note: absolute value of an area is used because 89 // area may be positive or negative - in accordance with the 90 // contour orientation 91 if( approx.size() == 4 && 92 fabs(contourArea(Mat(approx))) > 1000 && 93 isContourConvex(Mat(approx)) ) 94 { 95 double maxCosine = 0; 96 97 for( int j = 2; j < 5; j++ ) 98 { 99 // find the maximum cosine of the angle between joint edges 100 double cosine = fabs(angle(approx[j%4], approx[j-2], approx[j-1])); 101 maxCosine = MAX(maxCosine, cosine); 102 } 103 104 // if cosines of all angles are small 105 // (all angles are ~90 degree) then write quandrange 106 // vertices to resultant sequence 107 if( maxCosine < 0.3 ) 108 squares.push_back(approx); 109 } 110 } 111 } 112 } 113} 114 115// the function draws all the squares in the image 116static void drawSquares( UMat& _image, const vector<vector<Point> >& squares ) 117{ 118 Mat image = _image.getMat(ACCESS_WRITE); 119 for( size_t i = 0; i < squares.size(); i++ ) 120 { 121 const Point* p = &squares[i][0]; 122 int n = (int)squares[i].size(); 123 polylines(image, &p, &n, 1, true, Scalar(0,255,0), 3, LINE_AA); 124 } 125} 126 127 128// draw both pure-C++ and ocl square results onto a single image 129static UMat drawSquaresBoth( const UMat& image, 130 const vector<vector<Point> >& sqs) 131{ 132 UMat imgToShow(Size(image.cols, image.rows), image.type()); 133 image.copyTo(imgToShow); 134 135 drawSquares(imgToShow, sqs); 136 137 return imgToShow; 138} 139 140 141int main(int argc, char** argv) 142{ 143 const char* keys = 144 "{ i input | ../data/pic1.png | specify input image }" 145 "{ o output | squares_output.jpg | specify output save path}" 146 "{ h help | false | print help message }" 147 "{ m cpu_mode | false | run without OpenCL }"; 148 149 CommandLineParser cmd(argc, argv, keys); 150 151 if(cmd.has("help")) 152 { 153 cout << "Usage : squares [options]" << endl; 154 cout << "Available options:" << endl; 155 cmd.printMessage(); 156 return EXIT_SUCCESS; 157 } 158 if (cmd.has("cpu_mode")) 159 { 160 ocl::setUseOpenCL(false); 161 std::cout << "OpenCL was disabled" << std::endl; 162 } 163 164 string inputName = cmd.get<string>("i"); 165 string outfile = cmd.get<string>("o"); 166 167 int iterations = 10; 168 namedWindow( wndname, WINDOW_AUTOSIZE ); 169 vector<vector<Point> > squares; 170 171 UMat image; 172 imread(inputName, 1).copyTo(image); 173 if( image.empty() ) 174 { 175 cout << "Couldn't load " << inputName << endl; 176 cmd.printMessage(); 177 return EXIT_FAILURE; 178 } 179 180 int j = iterations; 181 int64 t_cpp = 0; 182 //warm-ups 183 cout << "warming up ..." << endl; 184 findSquares(image, squares); 185 186 do 187 { 188 int64 t_start = cv::getTickCount(); 189 findSquares(image, squares); 190 t_cpp += cv::getTickCount() - t_start; 191 192 t_start = cv::getTickCount(); 193 194 cout << "run loop: " << j << endl; 195 } 196 while(--j); 197 cout << "average time: " << 1000.0f * (double)t_cpp / getTickFrequency() / iterations << "ms" << endl; 198 199 UMat result = drawSquaresBoth(image, squares); 200 imshow(wndname, result); 201 imwrite(outfile, result); 202 waitKey(0); 203 204 return EXIT_SUCCESS; 205} 206