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regionExtractor.cpp
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regionExtractor.cpp
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#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include <opencv2/opencv.hpp>
#include <opencv2/features2d/features2d.hpp>
#include <opencv2/imgproc/imgproc_c.h>
#include <limits>
#include <iterator>
using namespace cv;
std::vector<vector<Point>> scaleHull(int scale, Point mean, std::vector<Point> specificHull, std::vector<vector<Point>> newcontours )//takes in contour, scales it
{
int scalex, scaley;
std::vector<Point> vector(specificHull.size());
for (size_t i = 0; i < specificHull.size(); i++)
{
int tempx = specificHull[i].x - mean.x;
int tempy = specificHull[i].y - mean.y;
scalex = scale*tempx;
scaley = scale*tempy;
scalex+= mean.x;
scaley+= mean.y;
vector.push_back(Point(scalex,scaley));
}
for (size_t j = 0; j < newcontours.size(); j++)
{
for (size_t k = 0; k < vector.size(); k++)
{
Point p = vector[k];
if (p.x != 0 && p.y != 0 )
{
newcontours[j].push_back(p);
}
}
}
return newcontours;
}
Mat collapseContour(std::vector<Point> specificContour, Point variance, Mat img) //subtract std dev from x and y of contour
{
int stddevx, stddevy;
Size s = img.size(); //obtain image dimensions
int rows = s.height;
int cols = s.width;
Mat temp = Mat::zeros(rows, cols, CV_8UC1 );
stddevx = sqrt(variance.x);
stddevy = sqrt(variance.y);
std::vector<Point> vector(specificContour.size());
std::vector<std::vector<Point>> newcontours(1);
std::vector<std::vector<Point>> oldcontours(1);
for (size_t i = 0; i < specificContour.size(); i++)
{
int tempx, tempy;
tempx = specificContour[i].x - stddevx;
tempy = specificContour[i].y - stddevy;
vector.push_back(Point(tempx,tempy));
}
for (size_t i = 0; i < vector.size(); i++)
{
Point p = vector[i];
Point d = specificContour[i];
if (p.x != 0 && p.y != 0 )
{
newcontours[0].push_back(p);
}
if (d.x != 0 && d.y != 0 )
{
oldcontours[0].push_back(p);
}
}
for (size_t i = 0; i < newcontours.size(); i++)
{
drawContours(temp,newcontours,i,Scalar(255,255,255),2,8, std::vector<Vec4i>(), 0, Point());
//drawContours(temp, oldcontours, i, Scalar(255,255, 0), 2, 8, std::vector<Vec4i>(), 0, Point());
}
/*for (size_t i = 0; i < (size_t)rows; i++)
{
for (size_t j = 0; j < (size_t)cols; j++)
{
if(!(img.at<double>(i,j) == 1))
{
img.at<double>(i,j) = 0;
}
}
}*/
return temp;
}
std::vector<vector<int>> binContours(std::vector<Point> hull, Point mean, size_t numbins, int index, int cols)
{
size_t dimensions = cols/numbins;
std::vector<vector<int>> bins(numbins);
size_t l = 0;
size_t k = 1;
size_t binnumber = 0;
while (binnumber < numbins)
{
double lowerbound = l*dimensions;
double upperbound = k*dimensions;
if ((mean.x >= lowerbound) && (upperbound >= mean.x))
{
//std::cout << counter << "," << mean.x << "," << lowerbound << "," << upperbound << std::endl;
bins[binnumber].push_back(index);
break;
}
l++;
k++;
binnumber++;
}
return bins;
}
int main(int argc, char *argv[])
{
Mat img = imread("/home/jkaikaus/Lab/regionExtractor/Samples/2.jpg");
Mat box;
cvtColor(img, box, COLOR_BGR2GRAY);
Size s = img.size(); //obtain image dimensions
int rows = s.height;
int cols = s.width;
Mat mask = Mat::zeros(rows, cols, CV_8UC1); //make mask based off of image dimensions
Mat temp;
MSER ms(5, 1000, 14400, .25, .2, 200, 1.01, .003, 5);
std::vector<vector<Point>> regions;
std::vector<vector<Point>> contours;
std::vector<Vec4i> hierarchy;
ms(box, regions, Mat());
for (size_t i = 0; i < regions.size(); i++)
{
drawContours(mask,regions,i,Scalar::all(255),1,8, vector<Vec4i>(), 0, Point());
findContours(mask, contours, hierarchy, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_SIMPLE, Point(0, 0));
std::vector<vector<Point>> hull(contours.size());
for (size_t j = 0; j < contours.size(); j++)
{
convexHull(Mat(contours[j]), hull[j], false);
std::vector<Moments> mu(hull.size());
mu[j]= moments(hull[j], false);
std::vector<Point2f> mc(hull.size()); //center of masses (mean)
std::vector<Point2f> mv(hull.size()); //variances
mc[j] = Point2f( mu[j].m10/mu[j].m00 , mu[j].m01/mu[j].m00 );
mv[j] = Point2f( mu[j].m20/mu[j].m00 , mu[j].m02/mu[j].m00 );
std::vector<Point> intmc(mc.size());
intmc[j]= Point((int)mc[j].x,(int)mc[j].y);
std::vector<vector<Point>> newcontours1(contours.size());
std::vector<vector<Point>> newcontours2(contours.size());
std::vector<vector<Point>> newcontours3(contours.size());
newcontours1 = scaleHull(1.5, intmc[j], hull[j], newcontours1);
newcontours2 = scaleHull(2, intmc[j], hull[j], newcontours2);
newcontours3 = scaleHull(3, intmc[j], hull[j], newcontours3);
temp = collapseContour(contours[j], mv[j], img);
std::vector<vector<int>> bins;
bins = binContours(hull[j], mc[j], 10, j, cols);
for (size_t k = 0; k < bins[2].size(); k++)
{
drawContours(img,hull,bins[2][k],Scalar(0,255,255),2,8, vector<Vec4i>(), 0, Point());
}
//drawContours(img,hull,j,Scalar(0,255,255),2,8, vector<Vec4i>(), 0, Point());
//drawContours(img,newcontours1,j,Scalar(0,255,0),2,8, vector<Vec4i>(), 0, Point());
//drawContours(img,newcontours2,j,Scalar(0,0,255),2,8, vector<Vec4i>(), 0, Point());
//drawContours(img,newcontours3,j,Scalar(255,0,0),2,8, vector<Vec4i>(), 0, Point());
//circle( img, mc[j], 4, Scalar::all(255), -1, 8, 0 );
namedWindow("Image Window", WINDOW_NORMAL );
imshow("Image Window", img);
waitKey(0);
}
}
return 0;
}