## [22c804]: / samples / tapi / squares.cpp  Maximize  Restore  History

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