2a6fb2867e
Made all STL usages explicit to be able automatically find all usages of particular class or function.
367 lines
12 KiB
C++
367 lines
12 KiB
C++
/*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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//#define _SUBPIX_VERBOSE
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#undef max
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namespace cv {
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// static void drawCircles(Mat& img, const std::vector<Point2f>& corners, const std::vector<float>& radius)
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// {
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// for(size_t i = 0; i < corners.size(); i++)
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// {
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// circle(img, corners[i], cvRound(radius[i]), CV_RGB(255, 0, 0));
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// }
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// }
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// static int histQuantile(const Mat& hist, float quantile)
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// {
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// if(hist.dims > 1) return -1; // works for 1D histograms only
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// float cur_sum = 0;
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// float total_sum = (float)sum(hist).val[0];
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// float quantile_sum = total_sum*quantile;
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// for(int j = 0; j < hist.size[0]; j++)
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// {
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// cur_sum += (float)hist.at<float>(j);
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// if(cur_sum > quantile_sum)
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// {
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// return j;
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// }
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// }
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// return hist.size[0] - 1;
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// }
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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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double min_dist = std::numeric_limits<double>::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 = MIN(min_dist, dist);
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}
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order.push_back(std::pair<int, float>((int)i, (float)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<Point>& 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(Point2f((float)contour[i].x, (float)contour[i].y) - 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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// 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 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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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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//const double max_bell_width = 20; // we expect two bells with width bounded above
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//const double min_bell_width = 5; // and below
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double total_sum = sum(hist).val[0];
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//double thresh = total_sum/(2*max_bell_width)*0.25f; // quarter of a bar inside a bell
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// threshold(hist, bw, thresh, 255.0, CV_THRESH_BINARY);
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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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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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#if defined(_SUBPIX_VERBOSE)
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std::vector<float> radius;
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radius.assign(corners.size(), 0.0f);
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#endif //_SUBPIX_VERBOSE
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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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#if 0
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int black_thresh = histQuantile(hist, 0.45f);
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int white_thresh = histQuantile(hist, 0.55f);
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#else
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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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#endif
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threshold(img, black_comp, black_thresh, 255.0, CV_THRESH_BINARY_INV);
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threshold(img, white_comp, white_thresh, 255.0, CV_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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#if defined(_SUBPIX_VERBOSE)
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namedWindow("roi", 1);
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imshow("roi", img_roi);
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imwrite("test.jpg", img);
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namedWindow("black", 1);
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imshow("black", black_comp);
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namedWindow("white", 1);
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imshow("white", white_comp);
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cvWaitKey(0);
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imwrite("black.jpg", black_comp);
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imwrite("white.jpg", white_comp);
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#endif
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std::vector<std::vector<Point> > white_contours, black_contours;
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std::vector<Vec4i> white_hierarchy, black_hierarchy;
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findContours(black_comp, black_contours, black_hierarchy, CV_RETR_LIST, CV_CHAIN_APPROX_SIMPLE);
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findContours(white_comp, white_contours, white_hierarchy, CV_RETR_LIST, CV_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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#if 1
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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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#else
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findCorner(*quads[k], corners[i], quad_corners[k]);
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#endif
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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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#if defined(_SUBPIX_VERBOSE)
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radius[i] = norm(corners[i] - ground_truth_corners[ground_truth_idx])*6;
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#if 1
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Mat test(img.size(), CV_32FC3);
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cvtColor(img, test, CV_GRAY2RGB);
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// line(test, quad_corners[0] - corners[i] + Point2f(30, 30), quad_corners[1] - corners[i] + Point2f(30, 30), cvScalar(0, 255, 0));
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// line(test, quad_corners[2] - corners[i] + Point2f(30, 30), quad_corners[3] - corners[i] + Point2f(30, 30), cvScalar(0, 255, 0));
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std::vector<std::vector<Point> > contrs;
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contrs.resize(1);
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for(int k = 0; k < 4; k++)
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{
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//contrs[0] = quads_approx[k];
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contrs[0].clear();
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for(size_t j = 0; j < quads_approx[k].size(); j++) contrs[0].push_back(quads_approx[k][j]);
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drawContours(test, contrs, 0, CV_RGB(0, 0, 255), 1, 1, std::vector<Vec4i>(), 2);
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circle(test, quad_corners[k], 0.5, CV_RGB(255, 0, 0));
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}
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Mat test1 = test(Rect(corners[i].x - 30, corners[i].y - 30, 60, 60));
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namedWindow("1", 1);
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imshow("1", test1);
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imwrite("test.jpg", test);
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waitKey(0);
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#endif
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#endif //_SUBPIX_VERBOSE
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}
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#if defined(_SUBPIX_VERBOSE)
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Mat test(img.size(), CV_32FC3);
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cvtColor(img, test, CV_GRAY2RGB);
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drawCircles(test, corners, radius);
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namedWindow("corners", 1);
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imshow("corners", test);
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waitKey();
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#endif //_SUBPIX_VERBOSE
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return true;
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}
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