split into many files
add better outlier rejection add normalization add background removal
This commit is contained in:
532
unwrap.cpp
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532
unwrap.cpp
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#include "unwrap.h"
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#include <opencv2/highgui.hpp>
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#include <opencv2/imgproc.hpp>
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#include <math.h>
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#include <vector>
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#include <algorithm>
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#include <opencv2/features2d.hpp>
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#include <iostream>
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#include "matutils.h"
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#include "drawing.h"
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struct DisplacmentMap
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{
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std::vector< std::vector<cv::Point2f> > destination;
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std::vector< std::vector<cv::Point2f> > source;
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};
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static std::vector< std::vector<cv::Point2f > > sortPointsIntoRows(std::vector<cv::Point2f>& points)
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{
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if(points.size() < 6) return std::vector< std::vector<cv::Point2f> >();
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cv::Point2f topLeft(*getTopLeft(points));
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cv::Point2f bottomRight(*getBottomRight(points));
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std::cout<<"topLeft "<<topLeft.x<<' '<<topLeft.y<<'\n';
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std::cout<<"bottomRight "<<bottomRight.x<<' '<<bottomRight.y<<'\n';
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float fuzz = (bottomRight.x-topLeft.x)*0.01f;
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for(size_t i = 0; i < points.size(); ++i)
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{
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if(points[i].x < topLeft.x-fuzz || points[i].y < topLeft.y-fuzz ||
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points[i].x > bottomRight.x+fuzz || points[i].y > bottomRight.y+fuzz)
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points.erase(points.begin()+i);
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}
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std::sort(points.begin(), points.end(), [](const cv::Point2f& a, const cv::Point2f& b){return a.y < b.y;});
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double accumulator = points[0].y+points[1].y;
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size_t accuCount = 2;
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float sigDist = (bottomRight.y-topLeft.y) / 20;
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std::vector< std::vector<cv::Point2f> > result(1);
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result.back().push_back(points[0]);
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result.back().push_back(points[1]);
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for(size_t i = 2; i < points.size(); ++i)
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{
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if( points[i].y - accumulator/accuCount > sigDist )
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{
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if(points.size() - i - 3 < 0) break;
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else
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{
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accumulator = points[i+1].y+points[i+2].y;
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accuCount = 2;
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}
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result.push_back(std::vector<cv::Point2f>());
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}
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result.back().push_back(points[i]);
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accumulator += points[i].y;
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++accuCount;
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}
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for(auto& row : result) std::sort(row.begin(), row.end(), [](const cv::Point2f& a, const cv::Point2f& b){return a.x < b.x;});
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return result;
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}
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static float detimineXPitch(const std::vector<cv::Point2f>& row, float fuzz = 1.3f)
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{
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std::vector<float> xRowDists;
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for(size_t i = 0; i < row.size()-1; ++i)
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xRowDists.push_back(abs(row[i+1].x-row[i].x));
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float xMinDist = *std::min(xRowDists.begin(), xRowDists.end());
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std::cout<<__func__<<": xMinDist "<<xMinDist<<'\n';
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float meanXDistAccum = 0;
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size_t validCount = 0;
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for(size_t i = 0; i < xRowDists.size(); ++i)
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{
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if(xRowDists[i] < xMinDist*fuzz)
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{
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++validCount;
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meanXDistAccum+=xRowDists[i];
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}
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}
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return meanXDistAccum/validCount;
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}
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static std::vector<cv::RotatedRect> fitEllipses(std::vector< std::vector<cv::Point2f > >& rows, bool remove = true)
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{
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if(rows.empty()) return std::vector<cv::RotatedRect>();
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std::vector<cv::RotatedRect> ellipses;
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ellipses.reserve(rows.size());
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for(size_t i = 0; i < rows.size(); ++i)
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{
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if(rows[i].size() > 4) ellipses.push_back(cv::fitEllipse(rows[i]));
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else
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{
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rows.erase(rows.begin()+i);
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i--;
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}
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}
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return ellipses;
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}
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static void thompsonTauTest(const std::vector<float>& in, std::vector<size_t>& outliers, float criticalValue)
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{
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float mean = 0;
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size_t n = 0;
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for(size_t i = 0; i < in.size(); ++i)
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{
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bool found = false;
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for(size_t j = 0; j < outliers.size() && !found; ++j)
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if(outliers[j]==i) found = true;
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if(!found)
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{
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mean+=in[i];
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++n;
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}
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}
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mean/=n;
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float sd = 0;
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for(size_t i = 0; i < in.size(); ++i)
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{
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bool found = false;
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for(size_t j = 0; j < outliers.size() && !found; ++j)
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if(outliers[j]==i) found = true;
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if(!found) sd+=pow(in[i]-mean,2);
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}
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sd = sqrt(sd/(n-1));
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float rej = (criticalValue*(n-1))/(sqrt(n)*sqrt(n-2+criticalValue));
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bool removed = false;
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for(size_t i = 0; i < in.size() && !removed; ++i)
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{
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bool found = false;
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for(size_t j = 0; j < outliers.size() && !found; ++j)
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if(outliers[j]==i) found = true;
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if(!found)
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{
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if(abs((in[i]-mean)/sd) > rej)
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{
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std::cout<<__func__<<": "<<i<<" is outlier mean: "<<mean<<" sd: "<<sd<<" n: "<<n<<'\n';
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outliers.push_back(i);
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removed = true;
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}
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}
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}
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if(removed) thompsonTauTest(in, outliers, criticalValue);
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}
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static bool sanityCheckElipses(std::vector< std::vector<cv::Point2f > >& rows, std::vector<cv::RotatedRect>& elipses)
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{
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if(rows.size() != elipses.size() && elipses.size() > 1) return false;
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for(size_t i = 0; i < elipses.size(); ++i)
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{
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float angDiff = fmod(elipses[i].angle,90);
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if(angDiff < 90-5 && angDiff > 5)
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{
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elipses.erase(elipses.begin()+i);
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rows.erase(rows.begin()+i);
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--i;
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}
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}
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std::vector<float> widths;
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std::vector<float> heights;
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for(auto& elipse : elipses)
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{
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widths.push_back(elipse.size.width);
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heights.push_back(elipse.size.height);
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}
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std::vector<size_t> outliersW;
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std::vector<size_t> outliersH;
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thompsonTauTest(widths, outliersW, 2);
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thompsonTauTest(heights, outliersH, 2);
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std::vector< std::vector<cv::Point2f > > rowsReduced;
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std::vector<cv::RotatedRect> elipsesReduced;
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for(size_t i = 0; i < elipses.size(); ++i)
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{
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bool found = false;
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for(size_t j = 0; j < outliersW.size() && !found; ++j)
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if(outliersW[j]==i) found = true;
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for(size_t j = 0; j < outliersH.size() && !found; ++j)
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if(outliersH[j]==i) found = true;
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if(!found)
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{
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rowsReduced.push_back(rows[i]);
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elipsesReduced.push_back(elipses[i]);
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}
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}
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elipses = elipsesReduced;
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rows = rowsReduced;
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return true;
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}
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static DisplacmentMap calcDisplacementMap(const std::vector< std::vector<cv::Point2f > >& rows,
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const std::vector<cv::RotatedRect>& elipses)
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{
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if(rows.size() < 2 || rows.size() != elipses.size()) {
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std::cerr<<__func__<<": rows < 2 or rows != elipses\n";
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return DisplacmentMap();
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}
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DisplacmentMap displacmentmap;
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displacmentmap.destination.assign(rows.size(), std::vector<cv::Point2f>());
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displacmentmap.source = rows;
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for(size_t i = 0; i < displacmentmap.destination.size(); ++i)
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{
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displacmentmap.destination[i].reserve(rows[i].size());
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}
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float meanYdist = 0;
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size_t j = 0;
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while(j < elipses.size()-1)
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{
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meanYdist += elipses[j+1].center.y-elipses[j].center.y;
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++j;
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}
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meanYdist = meanYdist/elipses.size();
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std::cout<<__func__<<": meanYdist "<<meanYdist<<'\n';
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for(size_t rowCnt = 0; rowCnt < rows.size(); ++rowCnt)
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{
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const std::vector<cv::Point2f>& row = rows[rowCnt];
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const cv::RotatedRect& elipse = elipses[rowCnt];
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cv::Rect_<float> boundingRect = elipse.boundingRect2f();
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std::cout<<__func__<<": Proc row "<<rowCnt<<'\n';
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for(size_t i = 0; i < row.size(); ++i)
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{
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float yDest = rowCnt*meanYdist;
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double normDist = ((row[i].x - boundingRect.x)/boundingRect.width-0.5)*2;
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double tau = asin(normDist);
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float xDest = (((2*tau)/M_PI)*500)+500;
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std::cout<<__func__<<": normDist "<<normDist<<" tau "<<tau<<" xDest "<<xDest<<'\n';
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displacmentmap.destination[rowCnt].push_back(cv::Point2f(xDest,yDest));
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}
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}
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return displacmentmap;
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}
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static void removeSparseCollums(cv::Mat& mat)
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{
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int front = 0;
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int back = 0;
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for(int y = 0; y < mat.rows; ++y)
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{
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if(mat.at<float>(y,0) >= 0) ++front;
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if(mat.at<float>(y,mat.cols-1) >= 0) ++back;
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}
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std::cout<<__func__<<" front: "<<front<<" back "<<back<<'\n';
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cv::Rect roi;
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bool frontRej = (front < mat.rows/2);
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bool backRej = (back < mat.rows/2);
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roi.x=frontRej;
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roi.y=0;
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roi.width = mat.cols - backRej - frontRej;
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roi.height = mat.rows;
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mat = mat(roi);
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if(frontRej || backRej) removeSparseCollums(mat);
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}
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static void generateRemapMaps(const DisplacmentMap& map, cv::Mat& xMat, cv::Mat& yMat, float fuzz = 1.3f)
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{
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if(map.destination.size() < 2)
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{
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std::cerr<<__func__<<": at least 2 rows are needed"<<std::endl;
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return;
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}
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float yMeanDist = map.destination[1][0].y-map.destination[0][0].y;
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float xMeanDist = 0;
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for(size_t i = 0; i < map.destination.size(); ++i)
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{
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xMeanDist+=detimineXPitch(map.destination[i]);
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}
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xMeanDist/=map.destination.size();
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std::cout<<__func__<<": xMeanDist "<<xMeanDist<<'\n';
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float xMin = std::numeric_limits<float>::max();
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float xMeanMin = 0;
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float xMax = std::numeric_limits<float>::min();
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for(auto& row: map.destination )
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{
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xMeanMin+=row.front().x;
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if(xMin > row.front().x )
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xMin = row.front().x;
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if(xMax < row.back().x)
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xMax = row.back().x;
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}
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xMeanMin = xMeanMin / map.destination.size();
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std::cout<<__func__<<": Grid: xMin "<<xMin<<'\n';
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std::cout<<__func__<<": Grid: grid xMax "<<xMax<<'\n';
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std::cout<<__func__<<": Grid: grid xMeanMin "<<xMeanMin<<'\n';
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/*if(abs(xMeanMin-xMin) > (xMeanDist)/2)
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{
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std::cout<<__func__<<": Grid: xMin is outlier\n";
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xMin = xMeanMin;
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}*/
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size_t xGridSize = static_cast<size_t>(std::lround(abs((xMax-xMin)/xMeanDist))+1);
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xMat = cv::Mat::zeros(cv::Size(xGridSize, map.destination.size()), CV_32FC1);
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yMat = cv::Mat::zeros(cv::Size(xGridSize, map.destination.size()), CV_32FC1);
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std::cout<<"Grid: "<<xGridSize<<'x'<<map.destination.size()<<'\n';
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for(int y = 0; y < xMat.rows; y++)
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{
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float* colx = xMat.ptr<float>(y);
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float* coly = yMat.ptr<float>(y);
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for(int x = 0; x < xMat.cols; x++)
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{
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size_t xIndex = 0;
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size_t yIndex = 0;
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bool found = findClosest(xIndex, yIndex,
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cv::Point2f((x)*xMeanDist+xMin, (y)*yMeanDist),
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map.destination, (2*xMeanDist)/5, (2*yMeanDist)/5);
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std::cout<<__func__<<": found: "<<found<<' '<<xIndex<<'x'<<yIndex<<" at: "<<(x)*xMeanDist+xMin<<'x'<<(y)*yMeanDist<<'\n';
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colx[x] = found ? map.source[yIndex][xIndex].x : -1;
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coly[x] = found ? map.source[yIndex][xIndex].y : -1;
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}
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}
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std::cout<<__func__<<": xMat raw\n"<<xMat<<'\n';
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removeSparseCollums(xMat);
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removeSparseCollums(yMat);
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std::cout<<__func__<<": xMat rejcted\n"<<xMat<<'\n';
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fillMissing(xMat);
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std::cout<<__func__<<": xMat filled\n"<<xMat<<'\n';
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interpolateMissing(xMat);
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std::cout<<__func__<<": yMat raw \n"<<yMat<<'\n';
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interpolateMissing(yMat);
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std::cout<<__func__<<": xMat \n"<<xMat<<'\n';
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std::cout<<__func__<<": yMat \n"<<yMat<<'\n';
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}
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static std::vector<cv::Point2f> detectPoints(cv::Mat& image, const cv::Mat& mask, bool verbose = false)
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{
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cv::Mat gray;
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cv::cvtColor(image, gray, cv::COLOR_BGR2GRAY);
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//detect corners
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cv::Mat corners;
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cv::cornerHarris(gray, corners, 5, 5, 0.01);
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cv::normalize(corners, corners, 0, 255, cv::NORM_MINMAX, CV_32FC1, cv::Mat());
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cv::convertScaleAbs( corners, corners );
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cv::threshold(corners, corners, 50, 255, cv::THRESH_BINARY);
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cv::Mat cornersMasked;
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if(mask.size == corners.size) corners.copyTo(cornersMasked, mask);
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else corners.copyTo(cornersMasked);
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if(verbose)
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{
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cv::imshow( "Viewer", cornersMasked );
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cv::waitKey(0);
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}
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//get middle of corners
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cv::SimpleBlobDetector::Params blobParams;
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blobParams.filterByArea = true;
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blobParams.minArea = 7;
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blobParams.maxArea = 500;
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blobParams.filterByColor = false;
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blobParams.blobColor = 255;
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blobParams.filterByInertia = false;
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blobParams.filterByConvexity = false;
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cv::Ptr<cv::SimpleBlobDetector> blobDetector = cv::SimpleBlobDetector::create(blobParams);
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std::vector<cv::KeyPoint> keypoints;
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blobDetector->detect(cornersMasked, keypoints);
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std::vector<cv::Point2f> points;
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cv::KeyPoint::convert(keypoints, points);
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return points;
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}
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bool createRemapMap(cv::Mat& image, const std::string& fileName, const cv::Mat& mask, bool verbose)
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{
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std::vector<cv::Point2f > points = detectPoints(image, mask, verbose);
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if(verbose) std::cout<<"Found "<<points.size()<<" points\n";
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if(points.size() < 8)
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{
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std::cout<<"Error creating map, insufficant points detected\n";
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return false;
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}
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std::vector< std::vector<cv::Point2f > > rows = sortPointsIntoRows(points);
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if(verbose) std::cout<<"Found "<<rows.size()<<" rows\n";
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if(rows.size() < 2)
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{
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std::cout<<"Error creating map, insufficant rows detected\n";
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return false;
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}
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std::vector< cv::RotatedRect > ellipses = fitEllipses(rows);
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if(verbose) std::cout<<"Found "<<ellipses.size()<<" ellipses. rows reduced to "<<rows.size()<<'\n';
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if(ellipses.size() < 3)
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{
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std::cout<<"Error creating map, insufficant ellipses detected\n";
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return false;
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}
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if(verbose)
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{
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cv::Mat pointsMat = cv::Mat::zeros(image.size(), CV_8UC3);
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drawRows(pointsMat, rows);
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drawEllipses(pointsMat, ellipses);
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cv::imshow( "Viewer", pointsMat );
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cv::waitKey(0);
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}
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||||
sanityCheckElipses(rows, ellipses);
|
||||
|
||||
if(verbose)
|
||||
{
|
||||
cv::Mat pointsMat = cv::Mat::zeros(image.size(), CV_8UC3);
|
||||
drawRows(pointsMat, rows);
|
||||
drawEllipses(pointsMat, ellipses);
|
||||
cv::imshow( "Viewer", pointsMat );
|
||||
cv::waitKey(0);
|
||||
}
|
||||
|
||||
DisplacmentMap dispMap = calcDisplacementMap(rows, ellipses);
|
||||
if(dispMap.destination.size() < 2)
|
||||
{
|
||||
std::cout<<"Error creating map, unable to calculate destination points";
|
||||
return false;
|
||||
}
|
||||
|
||||
cv::Mat dispPointsDest = cv::Mat::zeros(cv::Size(cv::Size(1000,1000)), CV_8UC3);
|
||||
drawRows(dispPointsDest, dispMap.destination);
|
||||
|
||||
if(verbose)
|
||||
{
|
||||
cv::imshow( "Viewer", dispPointsDest );
|
||||
cv::waitKey(0);
|
||||
}
|
||||
|
||||
cv::Mat xMat;
|
||||
cv::Mat yMat;
|
||||
generateRemapMaps(dispMap, xMat, yMat);
|
||||
sanityCheckMap(xMat, 0, image.cols-1, -1, -1);
|
||||
sanityCheckMap(yMat, 0, image.rows-1, -1, -1);
|
||||
fillMissing(xMat);
|
||||
interpolateMissing(xMat);
|
||||
interpolateMissing(yMat);
|
||||
sanityCheckMap(xMat, 0, image.cols-1, 0, image.cols-1);
|
||||
sanityCheckMap(yMat, 0, image.rows-1, 0, image.rows-1);
|
||||
|
||||
cv::FileStorage matf(fileName+".mat", cv::FileStorage::WRITE );
|
||||
matf<<"xmat"<<xMat<<"ymat"<<yMat;
|
||||
matf.release();
|
||||
|
||||
if(verbose)
|
||||
{
|
||||
cv::Mat remaped;
|
||||
applyRemap(image, remaped, xMat, yMat, cv::Size(900,1000));
|
||||
cv::imshow( "Viewer", remaped );
|
||||
cv::waitKey(0);
|
||||
}
|
||||
return true;
|
||||
}
|
||||
|
||||
bool findDeadSpace(const cv::Mat& mat, cv::Rect& roi)
|
||||
{
|
||||
if(mat.cols < 2 || mat.rows < 2) return false;
|
||||
|
||||
float centerTop = mat.at<float>(0,mat.cols/2);
|
||||
float centerLeft = mat.at<float>(mat.rows/2,0);
|
||||
float centerBottom = mat.at<float>(mat.rows-1,mat.cols/2);
|
||||
float centerRight = mat.at<float>(mat.rows/2,mat.cols-1);
|
||||
|
||||
int left = 0;
|
||||
int right = mat.cols-1;
|
||||
int top = 0;
|
||||
int bottom = mat.rows-1;
|
||||
for(; left < mat.cols && mat.at<float>(mat.rows/2,left) == centerLeft; ++left);
|
||||
for(; top < mat.rows && mat.at<float>(top,mat.cols/2) == centerTop; ++top);
|
||||
for(; right > left && mat.at<float>(mat.rows/2,right) == centerRight; --right);
|
||||
for(; bottom > top && mat.at<float>(bottom,mat.cols/2) == centerBottom; --bottom);
|
||||
|
||||
roi.x=left;
|
||||
roi.y=top;
|
||||
roi.width = right-left;
|
||||
roi.height = bottom-top;
|
||||
return true;
|
||||
}
|
||||
|
||||
void applyRemap(cv::Mat& image, cv::Mat& out, const cv::Mat& xmap, const cv::Mat& ymap, cv::Size size)
|
||||
{
|
||||
cv::Mat xMapResized;
|
||||
cv::Mat yMapResized;
|
||||
cv::resize(xmap, xMapResized, cv::Size(800,900), cv::INTER_CUBIC);
|
||||
cv::resize(ymap, yMapResized, cv::Size(800,900), cv::INTER_CUBIC);
|
||||
cv::Rect roi;
|
||||
cv::Mat xMapRed;
|
||||
cv::Mat yMapRed;
|
||||
if(findDeadSpace(xMapResized, roi))
|
||||
{
|
||||
xMapRed = xMapResized(roi);
|
||||
yMapRed = yMapResized(roi);
|
||||
}
|
||||
else
|
||||
{
|
||||
xMapRed = xMapResized;
|
||||
yMapRed = yMapResized;
|
||||
}
|
||||
cv::remap(image, out, xMapRed, yMapRed, cv::INTER_LINEAR);
|
||||
}
|
||||
Reference in New Issue
Block a user