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@ -16,15 +16,15 @@ using namespace std; |
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void help() |
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{ |
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cout << |
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"\nA program using OCL module pyramid scaling, Canny, dilate functions; cpu contours, contour simpification and\n" |
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"memory storage (it's got it all folks) to find\n" |
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"squares in a list of images pic1-6.png\n" |
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"Returns sequence of squares detected on the image.\n" |
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"the sequence is stored in the specified memory storage\n" |
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"Call:\n" |
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"./squares\n" |
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"Using OpenCV version %s\n" << CV_VERSION << "\n" << endl; |
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cout << |
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"\nA program using OCL module pyramid scaling, Canny, dilate functions, threshold, split; cpu contours, contour simpification and\n" |
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"memory storage (it's got it all folks) to find\n" |
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"squares in a list of images pic1-6.png\n" |
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"Returns sequence of squares detected on the image.\n" |
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"the sequence is stored in the specified memory storage\n" |
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"Call:\n" |
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"./squares\n" |
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"Using OpenCV version %s\n" << CV_VERSION << "\n" << endl; |
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} |
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@ -48,23 +48,21 @@ double angle( Point pt1, Point pt2, Point pt0 ) |
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void findSquares( const Mat& image, vector<vector<Point> >& squares ) |
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{ |
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squares.clear(); |
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Mat pyr, timg, gray0(image.size(), CV_8U), gray; |
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cv::ocl::oclMat pyr_ocl, timg_ocl, gray0_ocl(gray0), gray_ocl; |
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Mat gray; |
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cv::ocl::oclMat pyr_ocl, timg_ocl, gray0_ocl, gray_ocl; |
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// down-scale and upscale the image to filter out the noise
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ocl::pyrDown(ocl::oclMat(image), pyr_ocl); |
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ocl::pyrUp(pyr_ocl, timg_ocl); |
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timg = Mat(timg_ocl); |
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vector<vector<Point> > contours; |
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vector<cv::ocl::oclMat> gray0s; |
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ocl::split(timg_ocl, gray0s); // split 3 channels into a vector of oclMat
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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, 1, &gray0, 1, ch, 1); |
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gray0_ocl = gray0s[c]; |
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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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@ -78,28 +76,29 @@ void findSquares( const Mat& image, vector<vector<Point> >& squares ) |
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cv::ocl::Canny(gray0_ocl, gray_ocl, 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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ocl::dilate(gray0_ocl, gray_ocl, Mat(), Point(-1,-1)); |
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ocl::dilate(gray_ocl, gray_ocl, Mat(), Point(-1,-1)); |
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gray = Mat(gray_ocl); |
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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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gray = gray0 >= (l+1)*255/N; |
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cv::ocl::threshold(gray0_ocl, gray_ocl, (l+1)*255/N, 255, THRESH_BINARY); |
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gray = gray_ocl; |
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} |
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// find contours and store them all as a list
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findContours(gray, contours, CV_RETR_LIST, CV_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(Mat(contours[i]), approx, arcLength(Mat(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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@ -157,7 +156,7 @@ int main(int /*argc*/, char** /*argv*/) |
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help(); |
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namedWindow( wndname, 1 ); |
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vector<vector<Point> > squares; |
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for( int i = 0; names[i] != 0; i++ ) |
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{ |
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Mat image = imread(names[i], 1); |
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@ -166,7 +165,7 @@ int main(int /*argc*/, char** /*argv*/) |
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cout << "Couldn't load " << names[i] << endl; |
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continue; |
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} |
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findSquares(image, squares); |
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drawSquares(image, squares); |
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