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318 lines
9.8 KiB
318 lines
9.8 KiB
/*M/////////////////////////////////////////////////////////////////////////////////////// |
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// |
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. |
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// |
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// By downloading, copying, installing or using the software you agree to this license. |
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// If you do not agree to this license, do not download, install, |
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// copy or use the software. |
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// |
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// |
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// License Agreement |
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// For Open Source Computer Vision Library |
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// |
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// Copyright (C) 2015, Smart Engines Ltd, all rights reserved. |
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// Copyright (C) 2015, Institute for Information Transmission Problems of the Russian Academy of Sciences (Kharkevich Institute), all rights reserved. |
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// Copyright (C) 2015, Dmitry Nikolaev, Simon Karpenko, Michail Aliev, Elena Kuznetsova, all rights reserved. |
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// Third party copyrights are property of their respective owners. |
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// |
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// Redistribution and use in source and binary forms, with or without modification, |
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// are permitted provided that the following conditions are met: |
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// |
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// * Redistribution's of source code must retain the above copyright notice, |
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// this list of conditions and the following disclaimer. |
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// |
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// * Redistribution's in binary form must reproduce the above copyright notice, |
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// this list of conditions and the following disclaimer in the documentation |
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// and/or other materials provided with the distribution. |
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// |
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// * The name of the copyright holders may not be used to endorse or promote products |
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// derived from this software without specific prior written permission. |
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// |
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// This software is provided by the copyright holders and contributors "as is" and |
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// any express or implied warranties, including, but not limited to, the implied |
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// warranties of merchantability and fitness for a particular purpose are disclaimed. |
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// In no event shall the Intel Corporation or contributors be liable for any direct, |
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// indirect, incidental, special, exemplary, or consequential damages |
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// (including, but not limited to, procurement of substitute goods or services; |
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// loss of use, data, or profits; or business interruption) however caused |
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// and on any theory of liability, whether in contract, strict liability, |
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// or tort (including negligence or otherwise) arising in any way out of |
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// the use of this software, even if advised of the possibility of such damage. |
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// |
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//M*/ |
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#include <opencv2/imgproc.hpp> |
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#include <opencv2/highgui.hpp> |
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#include <opencv2/core/utility.hpp> |
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#include <opencv2/ximgproc.hpp> |
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#include <iostream> |
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#include <iomanip> |
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#include <cstdio> |
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#include <ctime> |
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#include <vector> |
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using namespace cv; |
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using namespace cv::ximgproc; |
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using namespace std; |
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static void help() |
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{ |
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cout << "\nThis program demonstrates line finding with the Fast Hough transform.\n" |
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"Usage:\n" |
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"./fasthoughtransform\n" |
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"<image_name>, default is '../../../samples/data/building.jpg'\n" |
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"<fht_image_depth>, default is " << CV_32S << "\n" |
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"<fht_angle_range>, default is " << 6 << " (@see cv::AngleRangeOption)\n" |
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"<fht_operator>, default is " << 2 << " (@see cv::HoughOp)\n" |
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"<fht_makeskew>, default is " << 1 << "(@see cv::HoughDeskewOption)" << endl; |
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} |
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static bool parseArgs(int argc, const char **argv, |
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Mat &img, |
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int &houghDepth, |
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int &houghAngleRange, |
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int &houghOperator, |
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int &houghSkew) |
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{ |
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if (argc > 6) |
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{ |
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cout << "Too many arguments" << endl; |
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return false; |
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} |
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const char *filename = argc >= 2 ? argv[1] |
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: "../../../samples/data/building.jpg"; |
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img = imread(filename, 0); |
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if (img.empty()) |
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{ |
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cout << "Failed to load image from '" << filename << "'" << endl; |
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return false; |
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} |
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houghDepth = argc >= 3 ? atoi(argv[2]) : CV_32S; |
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houghAngleRange = argc >= 4 ? atoi(argv[3]) : 6;//ARO_315_135 |
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houghOperator = argc >= 5 ? atoi(argv[4]) : 2;//FHT_ADD |
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houghSkew = argc >= 6 ? atoi(argv[5]) : 1;//HDO_DESKEW |
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return true; |
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} |
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static bool getEdges(const Mat &src, Mat &dst) |
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{ |
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Mat ucharSingleSrc; |
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src.convertTo(ucharSingleSrc, CV_8UC1); |
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Canny(ucharSingleSrc, dst, 50, 200, 3); |
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return true; |
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} |
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static bool fht(const Mat &src, Mat &dst, |
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int dstDepth, int angleRange, int op, int skew) |
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{ |
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clock_t clocks = clock(); |
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FastHoughTransform(src, dst, dstDepth, angleRange, op, skew); |
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clocks = clock() - clocks; |
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double secs = (double)clocks / CLOCKS_PER_SEC; |
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cout << std::setprecision(2) << "FastHoughTransform finished in " << secs |
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<< " seconds" << endl; |
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return true; |
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} |
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template<typename T> |
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bool rel(pair<T, Point> const &a, pair<T, Point> const &b) |
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{ |
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return a.first > b.first; |
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} |
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template<typename T> |
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bool incIfGreater(const T& a, const T& b, int *value) |
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{ |
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if (!value || a < b) |
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return false; |
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if (a > b) |
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++(*value); |
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return true; |
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} |
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static const int MAX_LEN = 10000; |
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template<typename T> |
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bool getLocalExtr(vector<Vec4i> &lines, |
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const Mat &src, |
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const Mat &fht, |
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float minWeight, |
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int maxCount) |
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{ |
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vector<pair<T, Point> > weightedPoints; |
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for (int y = 0; y < fht.rows; ++y) |
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{ |
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if (weightedPoints.size() > MAX_LEN) |
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break; |
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T const *pLine = (T *)fht.ptr(max(y - 1, 0)); |
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T const *cLine = (T *)fht.ptr(y); |
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T const *nLine = (T *)fht.ptr(min(y + 1, fht.rows - 1)); |
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for (int x = 0; x < fht.cols; ++x) |
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{ |
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if (weightedPoints.size() > MAX_LEN) |
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break; |
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T const value = cLine[x]; |
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if (value >= minWeight) |
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{ |
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int isLocalMax = 0; |
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for (int xx = max(x - 1, 0); |
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xx <= min(x + 1, fht.cols - 1); |
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++xx) |
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{ |
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if (!incIfGreater(value, pLine[xx], &isLocalMax) || |
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!incIfGreater(value, cLine[xx], &isLocalMax) || |
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!incIfGreater(value, nLine[xx], &isLocalMax)) |
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{ |
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isLocalMax = 0; |
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break; |
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} |
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} |
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if (isLocalMax > 0) |
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weightedPoints.push_back(make_pair(value, Point(x, y))); |
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} |
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} |
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} |
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if (weightedPoints.empty()) |
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return true; |
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sort(weightedPoints.begin(), weightedPoints.end(), &rel<T>); |
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weightedPoints.resize(min(static_cast<int>(weightedPoints.size()), |
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maxCount)); |
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for (size_t i = 0; i < weightedPoints.size(); ++i) |
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{ |
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lines.push_back(HoughPoint2Line(weightedPoints[i].second, src)); |
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} |
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return true; |
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} |
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static bool getLocalExtr(vector<Vec4i> &lines, |
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const Mat &src, |
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const Mat &fht, |
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float minWeight, |
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int maxCount) |
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{ |
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int const depth = CV_MAT_DEPTH(fht.type()); |
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switch (depth) |
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{ |
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case 0: |
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return getLocalExtr<uchar>(lines, src, fht, minWeight, maxCount); |
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case 1: |
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return getLocalExtr<schar>(lines, src, fht, minWeight, maxCount); |
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case 2: |
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return getLocalExtr<ushort>(lines, src, fht, minWeight, maxCount); |
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case 3: |
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return getLocalExtr<short>(lines, src, fht, minWeight, maxCount); |
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case 4: |
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return getLocalExtr<int>(lines, src, fht, minWeight, maxCount); |
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case 5: |
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return getLocalExtr<float>(lines, src, fht, minWeight, maxCount); |
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case 6: |
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return getLocalExtr<double>(lines, src, fht, minWeight, maxCount); |
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default: |
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return false; |
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} |
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} |
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static void rescale(Mat const &src, Mat &dst, |
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int const maxHeight=500, |
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int const maxWidth = 1000) |
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{ |
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double scale = min(min(static_cast<double>(maxWidth) / src.cols, |
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static_cast<double>(maxHeight) / src.rows), 1.0); |
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resize(src, dst, Size(), scale, scale, INTER_LINEAR); |
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} |
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static void showHumanReadableImg(string const &name, Mat const &img) |
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{ |
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Mat ucharImg; |
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img.convertTo(ucharImg, CV_MAKETYPE(CV_8U, img.channels())); |
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rescale(ucharImg, ucharImg); |
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imshow(name, ucharImg); |
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} |
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static void showFht(Mat const &fht) |
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{ |
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double minv(0), maxv(0); |
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minMaxLoc(fht, &minv, &maxv); |
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Mat ucharFht; |
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fht.convertTo(ucharFht, CV_MAKETYPE(CV_8U, fht.channels()), |
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255.0 / (maxv + minv), minv / (maxv + minv)); |
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rescale(ucharFht, ucharFht); |
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imshow("fast hough transform", ucharFht); |
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} |
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static void showLines(Mat const &src, vector<Vec4i> const &lines) |
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{ |
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Mat bgrSrc; |
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cvtColor(src, bgrSrc, COLOR_GRAY2BGR); |
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for (size_t i = 0; i < lines.size(); ++i) |
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{ |
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Vec4i const &l = lines[i]; |
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line(bgrSrc, Point(l[0], l[1]), Point(l[2], l[3]), |
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Scalar(0, 0, 255), 1, LINE_AA); |
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} |
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rescale(bgrSrc, bgrSrc); |
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imshow("lines", bgrSrc); |
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} |
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int main(int argc, const char **argv) |
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{ |
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Mat src; |
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int depth(0); |
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int angleRange(0); |
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int op(0); |
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int skew(0); |
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if (!parseArgs(argc, argv, src, depth, angleRange, op, skew)) |
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{ |
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help(); |
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return -1; |
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} |
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showHumanReadableImg("src", src); |
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Mat canny; |
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if (!getEdges(src, canny)) |
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{ |
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cout << "Failed to select canny edges"; |
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return -2; |
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} |
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showHumanReadableImg("canny", canny); |
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Mat hough; |
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if (!fht(canny, hough, depth, angleRange, op, skew)) |
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{ |
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cout << "Failed to compute Fast Hough Transform"; |
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return -2; |
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} |
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showFht(hough); |
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vector<Vec4i> lines; |
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if (!getLocalExtr(lines, canny, hough, |
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static_cast<float>(255 * 0.3 * min(src.rows, src.cols)), |
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50)) |
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{ |
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cout << "Failed to find local maximums on FHT image"; |
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return -2; |
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} |
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showLines(canny, lines); |
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waitKey(); |
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return 0; |
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}
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