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Open Source Computer Vision Library
https://opencv.org/
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200 lines
6.2 KiB
200 lines
6.2 KiB
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#include "opencv2/core.hpp" |
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#include "opencv2/core/ocl.hpp" |
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#include "opencv2/core/utility.hpp" |
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#include "opencv2/imgproc.hpp" |
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#include "opencv2/imgcodecs.hpp" |
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#include "opencv2/highgui.hpp" |
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#include <iostream> |
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using namespace cv; |
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using namespace std; |
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int thresh = 50, N = 11; |
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const char* wndname = "Square Detection Demo"; |
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// helper function: |
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// finds a cosine of angle between vectors |
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// from pt0->pt1 and from pt0->pt2 |
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static double angle( Point pt1, Point pt2, Point pt0 ) |
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{ |
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double dx1 = pt1.x - pt0.x; |
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double dy1 = pt1.y - pt0.y; |
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double dx2 = pt2.x - pt0.x; |
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double dy2 = pt2.y - pt0.y; |
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return (dx1*dx2 + dy1*dy2)/sqrt((dx1*dx1 + dy1*dy1)*(dx2*dx2 + dy2*dy2) + 1e-10); |
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} |
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// returns sequence of squares detected on the image. |
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static void findSquares( const UMat& image, vector<vector<Point> >& squares ) |
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{ |
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squares.clear(); |
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UMat pyr, timg, gray0(image.size(), CV_8U), gray; |
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// down-scale and upscale the image to filter out the noise |
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pyrDown(image, pyr, Size(image.cols/2, image.rows/2)); |
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pyrUp(pyr, timg, image.size()); |
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vector<vector<Point> > contours; |
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// find squares in every color plane of the image |
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for( int c = 0; c < 3; c++ ) |
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{ |
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int ch[] = {c, 0}; |
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mixChannels(timg, gray0, ch, 1); |
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// try several threshold levels |
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for( int l = 0; l < N; l++ ) |
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{ |
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// hack: use Canny instead of zero threshold level. |
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// Canny helps to catch squares with gradient shading |
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if( l == 0 ) |
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{ |
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// apply Canny. Take the upper threshold from slider |
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// and set the lower to 0 (which forces edges merging) |
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Canny(gray0, gray, 0, thresh, 5); |
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// dilate canny output to remove potential |
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// holes between edge segments |
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dilate(gray, gray, UMat(), Point(-1,-1)); |
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} |
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else |
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{ |
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// apply threshold if l!=0: |
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// tgray(x,y) = gray(x,y) < (l+1)*255/N ? 255 : 0 |
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threshold(gray0, gray, (l+1)*255/N, 255, THRESH_BINARY); |
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} |
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// find contours and store them all as a list |
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findContours(gray, contours, RETR_LIST, CHAIN_APPROX_SIMPLE); |
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vector<Point> approx; |
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// test each contour |
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for( size_t i = 0; i < contours.size(); i++ ) |
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{ |
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// approximate contour with accuracy proportional |
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// to the contour perimeter |
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approxPolyDP(contours[i], approx, arcLength(contours[i], true)*0.02, true); |
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// square contours should have 4 vertices after approximation |
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// relatively large area (to filter out noisy contours) |
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// and be convex. |
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// Note: absolute value of an area is used because |
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// area may be positive or negative - in accordance with the |
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// contour orientation |
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if( approx.size() == 4 && |
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fabs(contourArea(approx)) > 1000 && |
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isContourConvex(approx) ) |
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{ |
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double maxCosine = 0; |
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for( int j = 2; j < 5; j++ ) |
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{ |
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// find the maximum cosine of the angle between joint edges |
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double cosine = fabs(angle(approx[j%4], approx[j-2], approx[j-1])); |
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maxCosine = MAX(maxCosine, cosine); |
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} |
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// if cosines of all angles are small |
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// (all angles are ~90 degree) then write quandrange |
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// vertices to resultant sequence |
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if( maxCosine < 0.3 ) |
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squares.push_back(approx); |
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} |
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} |
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} |
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} |
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} |
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// the function draws all the squares in the image |
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static void drawSquares( UMat& _image, const vector<vector<Point> >& squares ) |
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{ |
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Mat image = _image.getMat(ACCESS_WRITE); |
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for( size_t i = 0; i < squares.size(); i++ ) |
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{ |
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const Point* p = &squares[i][0]; |
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int n = (int)squares[i].size(); |
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polylines(image, &p, &n, 1, true, Scalar(0,255,0), 3, LINE_AA); |
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} |
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} |
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// draw both pure-C++ and ocl square results onto a single image |
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static UMat drawSquaresBoth( const UMat& image, |
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const vector<vector<Point> >& sqs) |
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{ |
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UMat imgToShow(Size(image.cols, image.rows), image.type()); |
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image.copyTo(imgToShow); |
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drawSquares(imgToShow, sqs); |
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return imgToShow; |
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} |
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int main(int argc, char** argv) |
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{ |
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const char* keys = |
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"{ i input | ../data/pic1.png | specify input image }" |
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"{ o output | squares_output.jpg | specify output save path}" |
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"{ h help | | print help message }" |
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"{ m cpu_mode | | run without OpenCL }"; |
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CommandLineParser cmd(argc, argv, keys); |
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if(cmd.has("help")) |
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{ |
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cout << "Usage : " << argv[0] << " [options]" << endl; |
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cout << "Available options:" << endl; |
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cmd.printMessage(); |
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return EXIT_SUCCESS; |
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} |
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if (cmd.has("cpu_mode")) |
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{ |
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ocl::setUseOpenCL(false); |
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cout << "OpenCL was disabled" << endl; |
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} |
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string inputName = cmd.get<string>("i"); |
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string outfile = cmd.get<string>("o"); |
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int iterations = 10; |
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namedWindow( wndname, WINDOW_AUTOSIZE ); |
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vector<vector<Point> > squares; |
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UMat image; |
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imread(inputName, 1).copyTo(image); |
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if( image.empty() ) |
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{ |
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cout << "Couldn't load " << inputName << endl; |
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cmd.printMessage(); |
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return EXIT_FAILURE; |
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} |
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int j = iterations; |
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int64 t_cpp = 0; |
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//warm-ups |
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cout << "warming up ..." << endl; |
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findSquares(image, squares); |
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do |
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{ |
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int64 t_start = getTickCount(); |
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findSquares(image, squares); |
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t_cpp += cv::getTickCount() - t_start; |
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t_start = getTickCount(); |
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cout << "run loop: " << j << endl; |
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} |
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while(--j); |
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cout << "average time: " << 1000.0f * (double)t_cpp / getTickFrequency() / iterations << "ms" << endl; |
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UMat result = drawSquaresBoth(image, squares); |
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imshow(wndname, result); |
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imwrite(outfile, result); |
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waitKey(0); |
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return EXIT_SUCCESS; |
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}
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