MasterArbeit/libuvosunwrap
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split into many files

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add better outlier rejection
add normalization
add background removal
This commit is contained in:
uvos
2020-10-22 11:21:12 +02:00
parent a5440ed857
commit 6defcad11b
12 changed files with 904 additions and 446 deletions
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4
CMakeLists.txt
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@ -2,14 +2,14 @@ cmake_minimum_required(VERSION 2.4)
project(unwap)
set(SRC_FILES main.cpp )
set(SRC_FILES main.cpp unwrap.cpp drawing.cpp matutils.cpp bgremoval.cpp)
set(LIBS -lX11 -lrt)
find_package( OpenCV REQUIRED )
add_executable(${PROJECT_NAME} ${SRC_FILES})
target_link_libraries( ${PROJECT_NAME} ${LIBS} -lopencv_core -lopencv_imgcodecs -lopencv_highgui -lopencv_features2d -lopencv_imgcodecs -lopencv_imgproc )
target_link_libraries( ${PROJECT_NAME} ${LIBS} -lopencv_core -lopencv_imgcodecs -lopencv_highgui -lopencv_features2d -lopencv_imgcodecs -lopencv_imgproc -lopencv_video)
target_include_directories(${PROJECT_NAME} PRIVATE "/usr/include/opencv4")
add_definitions(" -std=c++17 -Wall -O2 -flto -fno-strict-aliasing")
set(CMAKE_CXX_FLAGS_RELEASE "${CMAKE_CXX_FLAGS_RELEASE} -s")

21
argpopt.h
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@ -24,7 +24,9 @@
struct Config
{
char** inFileNames = NULL;
std::string outputFileName = "out.png";
std::string norm = "";
std::string maps = "";
std::string bg = "";
bool verbose = false;
};
@ -36,7 +38,9 @@ static char args_doc[] = "";
static struct argp_option options[] =
{
{"verbose", 'v', 0, 0, "Enable verbose logging" },
{"output", 'o', "File Name", 0, "Output image file name" },
{"map", 'm', "File Name", 0, "remap maps file" },
{"bg", 'b', "File Name", 0, "background image file" },
{"normalize", 'n', "File Name", 0, "image to use as a normalization source" },
{ 0 }
};
@ -47,10 +51,16 @@ error_t parse_opt (int key, char *arg, struct argp_state *state)
switch (key)
{
case 'v':
config->verbose = false;
config->verbose = true;
break;
case 'o':
config->outputFileName.assign(arg);
case 'm':
config->maps.assign(arg);
break;
case 'b':
config->bg.assign(arg);
break;
case 'n':
config->norm.assign(arg);
break;
case ARGP_KEY_NO_ARGS:
argp_usage(state);
@ -66,3 +76,4 @@ error_t parse_opt (int key, char *arg, struct argp_state *state)
static struct argp argp = { options, parse_opt, args_doc, doc };

21
bgremoval.cpp Normal file
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@ -0,0 +1,21 @@
#include "bgremoval.h"
#include <iostream>
#include <opencv2/highgui.hpp>
#include <opencv2/imgproc.hpp>
#include <opencv2/bgsegm.hpp>
bool createMask(const cv::Mat& in, cv::Mat& mask, const cv::Mat& bg)
{
if(in.size != bg.size || in.type() != bg.type())
{
std::cerr<<"input image and backgournd image size and type needs to be the same\n";
return false;
}
cv::Ptr<cv::BackgroundSubtractorMOG2> bgremv = cv::createBackgroundSubtractorMOG2(2,10,false);
bgremv->apply(bg, mask, 1);
bgremv->apply(in, mask, 0);
cv::GaussianBlur(mask,mask,cv::Size(49,49), 15);
cv::threshold(mask, mask, 70, 255, cv::THRESH_BINARY);
return true;
}

5
bgremoval.h Normal file
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@ -0,0 +1,5 @@
#pragma once
#include <opencv2/core/ocl.hpp>
bool createMask(const cv::Mat& in, cv::Mat& mask, const cv::Mat& bg);

19
drawing.cpp Normal file
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@ -0,0 +1,19 @@
#include "drawing.h"
#include <opencv2/viz/types.hpp>
#include <opencv2/imgproc.hpp>
void drawRows(cv::Mat& image, const std::vector< std::vector<cv::Point2f > >& rows)
{
for(size_t i = 0; i < rows.size(); ++i)
{
for(size_t y = 0; y < rows[i].size(); ++y)
{
cv::circle(image, rows[i][y], 5, cv::viz::Color(128 * (i%3), 128 * ((i+1)%3), 128 * ((i+2)%3)));
}
}
}
void drawEllipses(cv::Mat& image, const std::vector<cv::RotatedRect>& ellipses )
{
for(const auto& ellipse : ellipses)cv::ellipse(image, ellipse, cv::viz::Color(128,128,128));
}

6
drawing.h Normal file
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@ -0,0 +1,6 @@
#pragma once
#include <opencv2/core/ocl.hpp>
void drawRows(cv::Mat& image, const std::vector< std::vector<cv::Point2f > >& rows);
void drawEllipses(cv::Mat& image, const std::vector<cv::RotatedRect>& ellipses );

502
main.cpp
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@ -1,19 +1,13 @@
#include <iostream>
#include <opencv2/highgui.hpp>
#include <opencv2/imgproc.hpp>
#include <opencv2/core/ocl.hpp>
#include <opencv2/features2d.hpp>
#include <opencv2/viz/types.hpp>
#include <math.h>
#include <unistd.h>
#include <vector>
#include <string>
#include <sstream>
#include <algorithm>
#include "argpopt.h"
bool verbose = false;
#include "unwrap.h"
#include "bgremoval.h"
#include "normalize.h"
void cd_to_exe_dir( char *argv[] )
{
@ -39,403 +33,6 @@ std::vector<cv::Mat> loadImages(char** fileNames)
return images;
}
std::vector< std::vector<cv::Point2f > > sortPointsIntoRows(std::vector<cv::Point2f>& points)
{
if(points.size() < 6) return std::vector< std::vector<cv::Point2f> >();
struct
{
bool operator()(const cv::Point2f& a, const cv::Point2f& b) const
{
return sqrt(a.y*a.y+a.x*a.x) < sqrt(b.y*b.y+b.x*b.x);
}
} lessDist;
std::vector<cv::Point2f>::iterator topLeftIt = std::min_element(points.begin(), points.end(), lessDist);
std::vector<cv::Point2f>::iterator bottomRightIt = std::max_element(points.begin(), points.end(), lessDist);
cv::Point2f topLeft(topLeftIt[0]);
cv::Point2f bottomRight(bottomRightIt[0]);
std::cout<<"topLeft "<<topLeft.x<<' '<<topLeft.y<<'\n';
std::cout<<"bottomRight "<<bottomRight.x<<' '<<bottomRight.y<<'\n';
float fuzz = (bottomRight.x-topLeft.x)*0.01f;
for(size_t i = 0; i < points.size(); ++i)
{
if(points[i].x < topLeft.x-fuzz || points[i].y < topLeft.y-fuzz ||
points[i].x > bottomRight.x+fuzz || points[i].y > bottomRight.y+fuzz)
points.erase(points.begin()+i);
}
std::sort(points.begin(), points.end(), [](const cv::Point2f& a, const cv::Point2f& b){return a.y < b.y;});
double accumulator = points[0].y+points[1].y;
size_t accuCount = 2;
float sigDist = (bottomRight.y-topLeft.y) / 20;
std::vector< std::vector<cv::Point2f> > result(1);
result.back().push_back(points[0]);
result.back().push_back(points[1]);
for(size_t i = 2; i < points.size(); ++i)
{
if( points[i].y - accumulator/accuCount > sigDist )
{
if(points.size() - i - 3 < 0) break;
else
{
accumulator = points[i+1].y+points[i+2].y;
accuCount = 2;
}
result.push_back(std::vector<cv::Point2f>());
}
result.back().push_back(points[i]);
accumulator += points[i].y;
++accuCount;
}
for(auto& row : result) std::sort(row.begin(), row.end(), [](const cv::Point2f& a, const cv::Point2f& b){return a.x < b.x;});
return result;
}
void drawRows(cv::Mat& image, const std::vector< std::vector<cv::Point2f > >& rows)
{
for(size_t i = 0; i < rows.size(); ++i)
{
for(size_t y = 0; y < rows[i].size(); ++y)
{
cv::circle(image, rows[i][y], 5, cv::viz::Color(128 * (i%3), 128 * ((i+1)%3), 128 * ((i+2)%3)));
}
}
}
std::vector<cv::RotatedRect> fitEllipses(std::vector< std::vector<cv::Point2f > >& rows, bool remove = true)
{
if(rows.empty()) return std::vector<cv::RotatedRect>();
std::vector<cv::RotatedRect> ellipses;
ellipses.reserve(rows.size());
for(size_t i = 0; i < rows.size(); ++i)
{
if(rows[i].size() > 4) ellipses.push_back(cv::fitEllipse(rows[i]));
else rows.erase(rows.begin()+i);
}
return ellipses;
}
void drawEllipses(cv::Mat& image, const std::vector<cv::RotatedRect>& ellipses )
{
for(const auto& ellipse : ellipses)cv::ellipse(image, ellipse, cv::viz::Color(128,128,128));
}
struct DisplacmentMap
{
std::vector< std::vector<cv::Point2f> > destination;
std::vector< std::vector<cv::Point2f> > source;
};
DisplacmentMap calcDisplacementMap(const std::vector< std::vector<cv::Point2f > >& rows,
const std::vector<cv::RotatedRect>& elipses)
{
if(rows.size() < 2 || rows.size() != elipses.size()) {
std::cerr<<__func__<<": rows < 2 or rows != elipses\n";
return DisplacmentMap();
}
DisplacmentMap displacmentmap;
displacmentmap.destination.assign(rows.size(), std::vector<cv::Point2f>());
displacmentmap.source = rows;
for(int i = 0; i < displacmentmap.destination.size(); ++i)
displacmentmap.source[i].reserve(rows[i].size());
std::cout<<__func__<<": "<<elipses[1].center.y-elipses[0].center.y<<'\n';
float meanYdist = 0;
size_t j = 0;
while(j < elipses.size()-1)
{
meanYdist += elipses[j+1].center.y-elipses[j].center.y;
++j;
}
meanYdist = meanYdist/elipses.size();
std::cout<<__func__<<": meanYdist "<<meanYdist<<'\n';
for(int rowCnt = 0; rowCnt < rows.size(); ++rowCnt)
{
const std::vector<cv::Point2f>& row = rows[rowCnt];
const cv::RotatedRect& elipse = elipses[rowCnt];
cv::Rect_<float> boundingRect = elipse.boundingRect2f();
std::cout<<__func__<<": Proc row "<<rowCnt<<'\n';
for(size_t i = 0; i < row.size(); ++i)
{
float yDest = rowCnt*meanYdist;
double normDist = ((row[i].x - boundingRect.x)/boundingRect.width-0.5)*2;
double tau = asin(normDist);
float xDest = (((2*tau)/M_PI)*500)+500;
std::cout<<__func__<<": normDist "<<normDist<<" tau "<<tau<<" xDest "<<xDest<<'\n';
displacmentmap.destination[rowCnt].push_back(cv::Point2f(xDest,yDest));
}
}
return displacmentmap;
}
float detimineXPitch(const std::vector<cv::Point2f>& row, float fuzz = 1.3f)
{
std::vector<float> xRowDists;
for(size_t i = 0; i < row.size()-1; ++i)
xRowDists.push_back(abs(row[i+1].x-row[i].x));
float xMinDist = *std::min(xRowDists.begin(), xRowDists.end());
std::cout<<__func__<<": xMinDist "<<xMinDist<<'\n';
float meanXDistAccum = 0;
size_t validCount = 0;
for(size_t i = 0; i < xRowDists.size(); ++i)
{
if(xRowDists[i] < xMinDist*fuzz)
{
++validCount;
meanXDistAccum+=xRowDists[i];
}
}
return meanXDistAccum/validCount;
}
double distance(const cv::Point2f& a, const cv::Point2f& b)
{
return sqrt((a.y-b.y)*(a.y-b.y)+(a.x-b.x)*(a.x-b.x));
}
bool findClosest(size_t& xIndex, size_t& yIndex,
cv::Point2f point, const std::vector< std::vector<cv::Point2f> >& array,
float xTolerance, float yTolerance)
{
size_t rowBelow = 0;
while(rowBelow < array.size() && array[rowBelow][0].y < point.y) ++rowBelow;
if(rowBelow == array.size()) rowBelow = array.size()-1;
int rightAbove = -1;
int rightBelow = 0;
while(rightBelow < array[rowBelow].size() && array[rowBelow][rightBelow].x < point.x ) ++rightBelow;
float distRB = distance(point, array[rowBelow][rightBelow]);
float distLB = rightBelow > 0 ? distance(point, array[rowBelow][rightBelow-1]) : std::numeric_limits<float>::max();
float distRA = std::numeric_limits<float>::max();
float distLA = std::numeric_limits<float>::max();
if(rowBelow > 0)
{
while(rightAbove < array[rowBelow].size() && array[rowBelow-1][rightAbove].x < point.x ) ++rightAbove;
distRA = distance(point, array[rowBelow-1][rightAbove]);
if(rightAbove > 0) distLA = distance(point, array[rowBelow-1][rightAbove-1]);
}
float* min = &distRB;
if(distLB < *min) min = &distLB;
if(distRA < *min) min = &distRA;
if(distLA < *min) min = &distLA;
if(min == &distRB)
{
yIndex = rowBelow;
xIndex = rightBelow;
}
else if(min == &distLB)
{
yIndex = rowBelow;
xIndex = rightBelow-1;
}
else if(min == &distRA)
{
yIndex = rowBelow-1;
xIndex = rightBelow;
}
else if(min == &distLA)
{
yIndex = rowBelow-1;
xIndex = rightBelow-1;
}
return abs(array[yIndex][xIndex].x - point.x) < xTolerance && abs(array[yIndex][xIndex].y - point.y) < yTolerance;
}
void interpolateMissing(cv::Mat& mat)
{
for(size_t y = 0; y < mat.rows; y++)
{
float* col = mat.ptr<float>(y);
for(int x = 0; x < mat.cols; ++x)
{
if(col[x] < 0)
{
int closestA = -1;
int closestB = -1;
int dist = std::numeric_limits<int>::max();
for(int i = 0; i < mat.cols; ++i)
{
if(col[i] >= 0 && abs(i-x) <= dist)
{
closestB = closestA;
closestA = i;
dist = abs(i-x);
}
}
float slope = (col[closestB] - col[closestA])/(closestB-closestA);
col[x] = col[closestA] - (closestA-x)*slope;
}
}
}
}
void fillMissing(cv::Mat& mat)
{
for(size_t y = 0; y < mat.rows; y++)
{
float* col = mat.ptr<float>(y);
for(int x = 0; x < mat.cols; ++x)
{
if(col[x] < 0)
{
if(y > 0 && mat.at<float>(x,y-1) >= 0)
col[x] = mat.at<float>(x,y-1);
else if(y < mat.rows && mat.at<float>(x,y+1) >= 0)
col[x] = mat.at<float>(x,y+1);
if((x+1 < mat.cols && col[x] > col[x+1]) || (x > 0 && col[x] < col[x-1]))
col[x] = -1;
}
}
}
}
void sanityCheckMap(cv::Mat& mat, const float min, const float max)
{
for(size_t y = 0; y < mat.rows; y++)
{
float* col = mat.ptr<float>(y);
for(int x = 0; x < mat.cols; ++x)
{
if(col[x] < min)
col[x] = min;
else if(col[x] > max)
col[x] = max;
}
}
}
//dst(x,y) = src(map_x(x,y),map_y(x,y))
void generateRemapMaps(const DisplacmentMap& map, cv::Mat& xMat, cv::Mat& yMat, const cv::Size& size, float fuzz = 1.3f)
{
if(map.destination.size() < 2)
{
std::cerr<<__func__<<": at least 2 rows are needed"<<std::endl;
return;
}
float yMeanDist = map.destination[1][0].y-map.destination[0][0].y;
float xMeanDist = 0;
for(size_t i = 0; i < map.destination.size(); ++i)
{
xMeanDist+=detimineXPitch(map.destination[i]);
}
xMeanDist/=map.destination.size();
std::cout<<__func__<<": xMeanDist "<<xMeanDist<<'\n';
float xMin = std::numeric_limits<float>::max();
float xMax = std::numeric_limits<float>::min();
for(auto& row: map.destination )
{
if(xMin > row.front().x )
xMin = row.front().x;
if(xMax < row.back().x)
xMax = row.back().x;
}
std::cout<<__func__<<": Grid: xMin "<<xMin<<'\n';
std::cout<<__func__<<": Grid: grid xMax "<<xMax<<'\n';
size_t xGridSize = static_cast<size_t>(std::lround(abs((xMax-xMin)/xMeanDist))+1);
xMat = cv::Mat::zeros(cv::Size(xGridSize, map.destination.size()), CV_32FC1);
yMat = cv::Mat::zeros(cv::Size(xGridSize, map.destination.size()), CV_32FC1);
std::cout<<"Grid: "<<xGridSize<<'x'<<map.destination.size()<<'\n';
for(size_t y = 0; y < xMat.rows; y++)
{
float* colx = xMat.ptr<float>(y);
float* coly = yMat.ptr<float>(y);
for(int x = 0; x < xMat.cols; x++)
{
size_t xIndex;
size_t yIndex;
bool found = findClosest(xIndex, yIndex,
cv::Point2f((x+1)*xMeanDist, (y)*yMeanDist),
map.destination, xMeanDist/2, yMeanDist/2);
std::cout<<__func__<<": found: "<<found<<' '<<xIndex<<"x"<<yIndex<<'\n';
colx[x] = found ? map.source[yIndex][xIndex].x : -1;
coly[x] = found ? map.source[yIndex][xIndex].y : -1;
}
}
fillMissing(xMat);
interpolateMissing(xMat);
interpolateMissing(yMat);
std::cout<<__func__<<": xMat \n"<<xMat<<'\n';
std::cout<<__func__<<": yMat \n"<<yMat<<'\n';
resize(xMat, xMat, size);
resize(yMat, yMat, size);
}
std::vector<cv::Point2f> detectPoints(cv::Mat& image)
{
cv::Mat gray;
cv::cvtColor(image, gray, cv::COLOR_BGR2GRAY);
//detect corners
cv::Mat corners;
cv::cornerHarris(gray, corners, 5, 5, 0.01);
cv::normalize(corners, corners, 0, 255, cv::NORM_MINMAX, CV_32FC1, cv::Mat());
cv::convertScaleAbs( corners, corners );
cv::threshold(corners, corners, 40, 255, cv::THRESH_BINARY);
cv::waitKey(0);
cv::imshow( "Viewer", corners );
//get middle of corners
cv::SimpleBlobDetector::Params blobParams;
blobParams.filterByArea = true;
blobParams.minArea = 4;
blobParams.maxArea = 50;
blobParams.filterByColor = false;
blobParams.blobColor = 255;
blobParams.filterByInertia = false;
blobParams.filterByConvexity = false;
cv::Ptr<cv::SimpleBlobDetector> blobDetector = cv::SimpleBlobDetector::create(blobParams);
std::vector<cv::KeyPoint> keypoints;
blobDetector->detect(corners, keypoints);
std::vector<cv::Point2f> points;
cv::KeyPoint::convert(keypoints, points);
return points;
}
int main(int argc, char* argv[])
{
cv::ocl::setUseOpenCL(false);
@ -453,47 +50,90 @@ int main(int argc, char* argv[])
return -1;
}
for(auto& image : inImages)
if(config.verbose)
{
cv::namedWindow( "Viewer", cv::WINDOW_NORMAL );
cv::resizeWindow("Viewer", 960, 500);
cv::imshow( "Viewer", image );
std::vector<cv::Point2f > points = detectPoints(image);
std::vector< std::vector<cv::Point2f > > rows = sortPointsIntoRows(points);
std::vector< cv::RotatedRect > ellipses = fitEllipses(rows);
cv::Mat pointsMat = cv::Mat::zeros(image.size(), CV_8UC3);
drawEllipses(pointsMat, ellipses);
std::cout<<"rows: "<<rows.size()<<'\n';
}
DisplacmentMap dispMap = calcDisplacementMap(rows, ellipses);
drawRows(pointsMat, dispMap.source);
if(config.maps.empty())
{
cv::Mat mask;
if(config.verbose)
{
cv::imshow( "Viewer", inImages[0] );
cv::waitKey(0);
cv::imshow( "Viewer", pointsMat );
cv::Mat dispPointsDest = cv::Mat::zeros(cv::Size(cv::Size(1000,1000)), CV_8UC3);
drawRows(dispPointsDest, dispMap.destination);
}
if(!config.bg.empty())
{
cv::Mat bg = cv::imread(config.bg);
if(bg.data)
{
createMask(inImages[0], mask, bg);
if(config.verbose)
{
cv::Mat masked;
inImages[0].copyTo(masked, mask);
cv::imshow( "Viewer", masked );
cv::waitKey(0);
cv::imshow( "Viewer", dispPointsDest );
}
}
else std::cout<<"can not read background image from "<<config.bg<<'\n';
}
createRemapMap(inImages[0], config.inFileNames[0], mask, config.verbose);
}
else
{
cv::FileStorage fs(config.maps, cv::FileStorage::READ);
if (!fs.isOpened())
{
std::cerr<<"could not open maps file " <<config.maps<<'\n';
return -1;
}
cv::Mat xMat;
cv::Mat yMat;
generateRemapMaps(dispMap, xMat, yMat, cv::Size(1000,1000));
fs["xmat"]>>xMat;
fs["ymat"]>>yMat;
cv::Mat remaped;
cv::remap(image, remaped, xMat, yMat, cv::INTER_LINEAR);
cv::Mat norm;
if(!config.norm.empty())
{
cv::Mat tmp = cv::imread(config.norm);
if(!tmp.data)
{
std::cerr<<"could not open normalize file " <<config.norm<<'\n';
}
applyRemap(tmp, norm, xMat, yMat, cv::Size(900,1000));
if(config.verbose)
{
cv::imshow("Viewer", norm );
cv::waitKey(0);
}
}
for(auto& image : inImages)
{
if(config.verbose)
{
cv::imshow( "Viewer", image );
cv::waitKey(0);
}
cv::Mat remaped;
applyRemap(image, remaped, xMat, yMat, cv::Size(900,1000));
if(norm.data) normalize(remaped, norm);
cv::imshow( "Viewer", remaped );
cv::waitKey(0);
}
}
if(config.verbose)
{
cv::destroyWindow("Viewer");
cv::waitKey(0);
}
return 0;
}

166
matutils.cpp Normal file
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@ -0,0 +1,166 @@
#include "matutils.h"
#include <opencv2/core/ocl.hpp>
#include <iostream>
void sanityCheckMap(cv::Mat& mat, const float min, const float max, float minValue, float maxValue)
{
for(int y = 0; y < mat.rows; y++)
{
float* col = mat.ptr<float>(y);
for(int x = 0; x < mat.cols; ++x)
{
if(col[x] < min)
col[x] = minValue;
else if(col[x] > max)
col[x] = maxValue;
}
}
}
std::vector<cv::Point2f>::iterator getTopLeft(std::vector<cv::Point2f>& points)
{
return std::min_element(points.begin(), points.end(), [](const cv::Point2f& a, const cv::Point2f& b){
return sqrt(a.y*a.y+a.x*a.x) < sqrt(b.y*b.y+b.x*b.x);
});
}
std::vector<cv::Point2f>::iterator getBottomRight(std::vector<cv::Point2f>& points)
{
return std::max_element(points.begin(), points.end(), [](const cv::Point2f& a, const cv::Point2f& b){
return sqrt(a.y*a.y+a.x*a.x) < sqrt(b.y*b.y+b.x*b.x);
});
}
double distance(const cv::Point2f& a, const cv::Point2f& b)
{
return sqrt((a.y-b.y)*(a.y-b.y)+(a.x-b.x)*(a.x-b.x));
}
bool findClosest(size_t& xIndex, size_t& yIndex,
cv::Point2f point, const std::vector< std::vector<cv::Point2f> >& array,
float xTolerance, float yTolerance)
{
size_t rowBelow = 0;
while(rowBelow < array.size() && !array[rowBelow].empty() && array[rowBelow][0].y < point.y) ++rowBelow;
if(rowBelow == array.size()) rowBelow = array.size()-1;
size_t rightAbove = 0;
size_t rightBelow = 0;
while(rightBelow < array[rowBelow].size() && array[rowBelow][rightBelow].x < point.x ) ++rightBelow;
float distRB = distance(point, array[rowBelow][rightBelow]);
float distLB = rightBelow > 0 ? distance(point, array[rowBelow][rightBelow-1]) : std::numeric_limits<float>::max();
float distRA = std::numeric_limits<float>::max();
float distLA = std::numeric_limits<float>::max();
if(rowBelow > 0)
{
while(rightAbove < array[rowBelow-1].size() && array[rowBelow-1][rightAbove].x < point.x ) ++rightAbove;
distRA = distance(point, array[rowBelow-1][rightAbove]);
if(rightAbove > 0) distLA = distance(point, array[rowBelow-1][rightAbove-1]);
}
float* min = &distRB;
if(distLB < *min) min = &distLB;
if(distRA < *min) min = &distRA;
if(distLA < *min) min = &distLA;
if(min == &distRB)
{
yIndex = rowBelow;
xIndex = rightBelow;
}
else if(min == &distLB)
{
yIndex = rowBelow;
xIndex = rightBelow-1;
}
else if(min == &distRA)
{
yIndex = rowBelow-1;
xIndex = rightBelow;
}
else if(min == &distLA)
{
yIndex = rowBelow-1;
xIndex = rightBelow-1;
}
else return false;
return abs(array[yIndex][xIndex].x - point.x) < xTolerance && abs(array[yIndex][xIndex].y - point.y) < yTolerance;
}
void interpolateMissing(cv::Mat& mat)
{
for(int y = 0; y < mat.rows; y++)
{
float* col = mat.ptr<float>(y);
for(int x = 0; x < mat.cols; ++x)
{
if(col[x] < 0)
{
int closestA = -1;
int closestB = -1;
int dist = std::numeric_limits<int>::max();
for(int i = 0; i < mat.cols; ++i)
{
if(i != closestA && col[i] >= 0 && abs(i-x) <= dist)
{
closestB = closestA;
closestA = i;
dist = abs(i-x);
}
}
if(closestA < 0 || closestB < 0)
{
closestA = -1;
closestB = -1;
dist = std::numeric_limits<int>::max();
for(int i = mat.cols-1; i >= 0; --i)
{
if(i != closestA && col[i] >= 0 && abs(i-x) <= dist)
{
closestB = closestA;
closestA = i;
dist = abs(i-x);
}
}
}
float slope = (col[closestB] - col[closestA])/(closestB-closestA);
col[x] = col[closestA] - (closestA-x)*slope;
}
}
}
}
void fillMissing(cv::Mat& mat)
{
bool finished = true;
for(int y = 0; y < mat.rows; y++)
{
float* col = mat.ptr<float>(y);
for(int x = 0; x < mat.cols; ++x)
{
if(col[x] < 0 && col[x] > -2)
{
if(y > 0 && mat.at<float>(y-1,x) >= 0)
{
col[x] = mat.at<float>(y-1,x);
finished = false;
}
else if(y < mat.rows-1 && mat.at<float>(y+1,x) >= 0)
{
col[x] = mat.at<float>(y+1,x);
finished = false;
}
if(col[x] > 0 && ((x+1 < mat.cols && col[x] > col[x+1]) || (x > 0 && col[x] < col[x-1])))
col[x] = -2;
}
}
}
if(!finished) fillMissing(mat);
}

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#pragma once
#include <opencv2/core/ocl.hpp>
#include <vector>
void sanityCheckMap(cv::Mat& mat, const float min, const float max, const float minValue, const float maxValue);
std::vector<cv::Point2f>::iterator getTopLeft(std::vector<cv::Point2f>& points);
std::vector<cv::Point2f>::iterator getBottomRight(std::vector<cv::Point2f>& points);
double distance(const cv::Point2f& a, const cv::Point2f& b);
bool findClosest(size_t& xIndex, size_t& yIndex,
cv::Point2f point, const std::vector< std::vector<cv::Point2f> >& array,
float xTolerance, float yTolerance);
void interpolateMissing(cv::Mat& mat);
void fillMissing(cv::Mat& mat);

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#pragma once
#include <opencv2/core/ocl.hpp>
#include <opencv2/imgproc.hpp>
#include <stdint.h>
inline bool normalize(cv::Mat& image, const cv::Mat& referance)
{
cv::Mat labReferance;
cv::cvtColor(referance, labReferance, cv::COLOR_BGR2Lab);
std::vector<cv::Mat> labPlanesRef(3);
cv::split(labReferance, labPlanesRef);
cv::Scalar mean = cv::mean(labPlanesRef[0]);
labPlanesRef[0].convertTo(labPlanesRef[0], CV_16SC1);
labPlanesRef[0] = labPlanesRef[0] - cv::Scalar(mean);
cv::Mat labImage;
cv::cvtColor(image, labImage, cv::COLOR_BGR2Lab);
std::vector<cv::Mat> labPlanes(3);
cv::split(labImage, labPlanes);
cv::add(labPlanes[0], labPlanesRef[0], labPlanes[0], cv::noArray(), CV_8UC1);
cv::merge(labPlanes, labImage);
cv::cvtColor(labImage, image, cv::COLOR_Lab2BGR);
return true;
}

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

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#pragma once
#include <opencv2/core/ocl.hpp>
#include <string>
bool createRemapMap(cv::Mat& image, const std::string& fileName, const cv::Mat& mask, bool verbose = false);
void applyRemap(cv::Mat& image, cv::Mat& out, const cv::Mat& xmap, const cv::Mat& ymap, cv::Size size);