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Open Source Computer Vision Library
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240 lines
8.5 KiB
240 lines
8.5 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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// Intel License Agreement |
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// For Open Source Computer Vision Library |
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// |
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// Copyright (C) 2000, Intel Corporation, 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 Intel Corporation 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 "precomp.hpp" |
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#include <limits> |
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#include <utility> |
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#include <algorithm> |
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#include <math.h> |
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namespace cv { |
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inline bool is_smaller(const std::pair<int, float>& p1, const std::pair<int, float>& p2) |
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{ |
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return p1.second < p2.second; |
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} |
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static void orderContours(const std::vector<std::vector<Point> >& contours, Point2f point, std::vector<std::pair<int, float> >& order) |
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{ |
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order.clear(); |
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size_t i, j, n = contours.size(); |
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for(i = 0; i < n; i++) |
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{ |
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size_t ni = contours[i].size(); |
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float min_dist = std::numeric_limits<float>::max(); |
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for(j = 0; j < ni; j++) |
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{ |
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double dist = norm(Point2f((float)contours[i][j].x, (float)contours[i][j].y) - point); |
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min_dist = (float)MIN((double)min_dist, dist); |
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} |
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order.push_back(std::pair<int, float>((int)i, min_dist)); |
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} |
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std::sort(order.begin(), order.end(), is_smaller); |
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} |
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// fit second order curve to a set of 2D points |
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inline void fitCurve2Order(const std::vector<Point2f>& /*points*/, std::vector<float>& /*curve*/) |
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{ |
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// TBD |
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} |
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inline void findCurvesCross(const std::vector<float>& /*curve1*/, const std::vector<float>& /*curve2*/, Point2f& /*cross_point*/) |
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{ |
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} |
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static void findLinesCrossPoint(Point2f origin1, Point2f dir1, Point2f origin2, Point2f dir2, Point2f& cross_point) |
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{ |
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float det = dir2.x*dir1.y - dir2.y*dir1.x; |
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Point2f offset = origin2 - origin1; |
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float alpha = (dir2.x*offset.y - dir2.y*offset.x)/det; |
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cross_point = origin1 + dir1*alpha; |
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} |
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static void findCorner(const std::vector<Point2f>& contour, Point2f point, Point2f& corner) |
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{ |
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// find the nearest point |
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double min_dist = std::numeric_limits<double>::max(); |
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int min_idx = -1; |
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// find corner idx |
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for(size_t i = 0; i < contour.size(); i++) |
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{ |
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double dist = norm(contour[i] - point); |
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if(dist < min_dist) |
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{ |
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min_dist = dist; |
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min_idx = (int)i; |
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} |
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} |
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CV_Assert(min_idx >= 0); |
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// temporary solution, have to make something more precise |
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corner = contour[min_idx]; |
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return; |
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} |
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static int segment_hist_max(const Mat& hist, int& low_thresh, int& high_thresh) |
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{ |
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Mat bw; |
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double total_sum = sum(hist).val[0]; |
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double quantile_sum = 0.0; |
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//double min_quantile = 0.2; |
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double low_sum = 0; |
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double max_segment_length = 0; |
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int max_start_x = -1; |
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int max_end_x = -1; |
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int start_x = 0; |
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const double out_of_bells_fraction = 0.1; |
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for(int x = 0; x < hist.size[0]; x++) |
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{ |
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quantile_sum += hist.at<float>(x); |
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if(quantile_sum < 0.2*total_sum) continue; |
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if(quantile_sum - low_sum > out_of_bells_fraction*total_sum) |
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{ |
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if(max_segment_length < x - start_x) |
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{ |
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max_segment_length = x - start_x; |
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max_start_x = start_x; |
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max_end_x = x; |
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} |
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low_sum = quantile_sum; |
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start_x = x; |
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} |
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} |
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if(start_x == -1) |
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{ |
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return 0; |
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} |
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else |
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{ |
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low_thresh = cvRound(max_start_x + 0.25*(max_end_x - max_start_x)); |
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high_thresh = cvRound(max_start_x + 0.75*(max_end_x - max_start_x)); |
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return 1; |
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} |
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} |
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} |
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bool cv::find4QuadCornerSubpix(InputArray _img, InputOutputArray _corners, Size region_size) |
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{ |
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CV_INSTRUMENT_REGION(); |
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Mat img = _img.getMat(), cornersM = _corners.getMat(); |
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int ncorners = cornersM.checkVector(2, CV_32F); |
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CV_Assert( ncorners >= 0 ); |
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Point2f* corners = cornersM.ptr<Point2f>(); |
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const int nbins = 256; |
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float ranges[] = {0, 256}; |
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const float* _ranges = ranges; |
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Mat hist; |
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Mat black_comp, white_comp; |
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for(int i = 0; i < ncorners; i++) |
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{ |
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int channels = 0; |
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Rect roi(cvRound(corners[i].x - region_size.width), cvRound(corners[i].y - region_size.height), |
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region_size.width*2 + 1, region_size.height*2 + 1); |
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Mat img_roi = img(roi); |
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calcHist(&img_roi, 1, &channels, Mat(), hist, 1, &nbins, &_ranges); |
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int black_thresh = 0, white_thresh = 0; |
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segment_hist_max(hist, black_thresh, white_thresh); |
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threshold(img, black_comp, black_thresh, 255.0, THRESH_BINARY_INV); |
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threshold(img, white_comp, white_thresh, 255.0, THRESH_BINARY); |
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const int erode_count = 1; |
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erode(black_comp, black_comp, Mat(), Point(-1, -1), erode_count); |
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erode(white_comp, white_comp, Mat(), Point(-1, -1), erode_count); |
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std::vector<std::vector<Point> > white_contours, black_contours; |
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findContours(black_comp, black_contours, RETR_LIST, CHAIN_APPROX_SIMPLE); |
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findContours(white_comp, white_contours, RETR_LIST, CHAIN_APPROX_SIMPLE); |
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if(black_contours.size() < 5 || white_contours.size() < 5) continue; |
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// find two white and black blobs that are close to the input point |
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std::vector<std::pair<int, float> > white_order, black_order; |
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orderContours(black_contours, corners[i], black_order); |
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orderContours(white_contours, corners[i], white_order); |
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const float max_dist = 10.0f; |
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if(black_order[0].second > max_dist || black_order[1].second > max_dist || |
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white_order[0].second > max_dist || white_order[1].second > max_dist) |
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{ |
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continue; // there will be no improvement in this corner position |
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} |
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const std::vector<Point>* quads[4] = {&black_contours[black_order[0].first], &black_contours[black_order[1].first], |
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&white_contours[white_order[0].first], &white_contours[white_order[1].first]}; |
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std::vector<Point2f> quads_approx[4]; |
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Point2f quad_corners[4]; |
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for(int k = 0; k < 4; k++) |
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{ |
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std::vector<Point2f> temp; |
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for(size_t j = 0; j < quads[k]->size(); j++) temp.push_back((*quads[k])[j]); |
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approxPolyDP(Mat(temp), quads_approx[k], 0.5, true); |
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findCorner(quads_approx[k], corners[i], quad_corners[k]); |
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quad_corners[k] += Point2f(0.5f, 0.5f); |
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} |
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// cross two lines |
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Point2f origin1 = quad_corners[0]; |
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Point2f dir1 = quad_corners[1] - quad_corners[0]; |
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Point2f origin2 = quad_corners[2]; |
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Point2f dir2 = quad_corners[3] - quad_corners[2]; |
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double angle = acos(dir1.dot(dir2)/(norm(dir1)*norm(dir2))); |
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if(cvIsNaN(angle) || cvIsInf(angle) || angle < 0.5 || angle > CV_PI - 0.5) continue; |
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findLinesCrossPoint(origin1, dir1, origin2, dir2, corners[i]); |
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} |
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return true; |
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}
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