My code is working just fine in debug mode and here is the Output. Once I tried it in release mode I got this error :
Unhandled exception at 0x5E3ADF2C (msvcp120d.dll) in Project4.exe: 0xC0000005: Access violation reading location 0x00000000.
From what I read on the internet, I think it is something that has to do with uninitialized Pointer or some other variable. my bet is on : vector< vector< Point > > contours;in the findSquares function. I tried to intitialize it with everything I could think of but no luck so far.
I am using Visual Studio 2013 with OpenCV.3.0.0 the X86 version.Here is the complet code :
#include <stdio.h>
#include <iostream>
#include "opencv2/core/core.hpp"
#include "opencv2/features2d/features2d.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/calib3d/calib3d.hpp"
#include <sstream>
#include "opencv2/imgproc/imgproc.hpp"
#include <math.h>
#include <string.h>
#ifndef NOMINMAX
#define NOMINMAX
#endif
#include <windows.h>
#include <algorithm>
using namespace cv;
using namespace std;
// helper function:
// finds a cosine of angle between vectors
// from pt0->pt1 and from pt0->pt2
static double angle(Point pt1, Point pt2, Point pt0)
{
double dx1 = pt1.x - pt0.x;
double dy1 = pt1.y - pt0.y;
double dx2 = pt2.x - pt0.x;
double dy2 = pt2.y - pt0.y;
return (dx1*dx2 + dy1*dy2) / sqrt((dx1*dx1 + dy1*dy1)*(dx2*dx2 + dy2*dy2) +
1e-10);
}
// returns sequence of squares detected on the image.
// the sequence is stored in the specified memory storage
static void findSquares(const Mat& image, vector<vector<Point> >& squares)
{
squares.clear();
vector<vector<Point>> contours;
// find white and yellow patch
Mat grayscal, grayscal1;
cvtColor(image, grayscal, CV_BGR2GRAY);
// try several threshold levels
for (int l = 0; l < 1; l++)
{
Mat imgThresholded, imgThresholded1, imgThresholded2;
cv::adaptiveThreshold(grayscal, grayscal1, 255,
cv::ADAPTIVE_THRESH_MEAN_C, cv::THRESH_BINARY, 11, 0);
inRange(grayscal, Scalar(100, 100, 100), Scalar(255, 255, 255),
imgThresholded1);
//morphological closing (fill small holes in the foreground)
//dilate(imgThresholded1, imgThresholded1,
getStructuringElement(MORPH_RECT, Size(7, 7)));
erode(imgThresholded1, imgThresholded1,
getStructuringElement(MORPH_RECT, Size(7, 7)));
// find contours and store them all as a list
findContours(imgThresholded1, contours, RETR_LIST, CHAIN_APPROX_SIMPLE);
vector<Point> approx;
// test each contour
for (size_t i = 0; i < contours.size(); i++)
{
// approximate contour with accuracy proportional
// to the contour perimeter
approxPolyDP(Mat(contours[i]), approx, arcLength(Mat(contours[i]),
true)*0.02, true);
// square contours should have 4 vertices after approximation
// relatively large area (to filter out noisy contours)
// and be convex.
// Note: absolute value of an area is used because
// area may be positive or negative - in accordance with the
// contour orientation
if (approx.size() == 4 &&
fabs(contourArea(Mat(approx))) > 4000 &&
fabs(contourArea(Mat(approx))) < 400000 &&
isContourConvex(Mat(approx)))
{
double maxCosine = 0;
for (int j = 2; j < 5; j++)
{
// find the maximum cosine of the angle between joint edges
double cosine = fabs(angle(approx[j % 4], approx[j - 2],
approx[j - 1]));
maxCosine = MAX(maxCosine, cosine);
}
// if cosines of all angles are small
// (all angles are ~90 degree) then write quandrange
// vertices to resultant sequence
if (maxCosine < 0.07)
squares.push_back(approx);
}
}
cout << "size of squares:" << squares.size() << endl;
}
}
// the function draws all the squares in the image
cv::Mat drawSquares(Mat& image, const vector<vector<Point> >& squares)
{
std::vector<cv::Mat> listOfMatrices, listOfMatrices2;
vector<Point> centers;
int m = listOfMatrices.size();
int n = listOfMatrices2.size();
int q = centers.size();
for (size_t i = 0; i < squares.size(); i++)
{
const Point* p = &squares[i][0];
int n = (int)squares[i].size();
Rect r = boundingRect(Mat(squares[i]));
cv::Size inflationSize(2, 2);
r -= inflationSize;
r.x = r.x + r.width / 4;
r.y = r.y + r.height / 4;
r.width = r.width / 2;
r.height = r.height / 2;
//dont detect the border
//Mat roi = image(r);
cv::Mat Image(image);
cv::Mat croppedImage = Image(Rect(r.x, r.y, r.width - 4, r.height - 4));
Point center(r.x + r.width / 2, r.y + r.height / 2);
centers.push_back(center);
q++;
listOfMatrices.push_back(croppedImage);
m++;
}
int maxbleu = 0;
Scalar tempVal0 = mean(listOfMatrices[0]);
double myMAtMeanB0 = tempVal0.val[0];
for (int j = 1; j < q; j++)
{
Scalar tempVal = mean(listOfMatrices[j]);
double myMAtMeanB = tempVal.val[0];
if (myMAtMeanB > myMAtMeanB0)
{
myMAtMeanB0 = myMAtMeanB;
maxbleu = j;
}
}
int maxdistance = 0, indicemax = 0, resmax = 0;
for (int i = 0; i < q; i++)
{
//listOfMatrices[i].release();
double xDiff = abs(centers[maxbleu].x - centers[i].x);
double yDiff = abs(centers[maxbleu].y - centers[i].y);
resmax = sqrt((xDiff * xDiff) + (yDiff * yDiff));
if (i == maxbleu)
{
continue;
}
else if (resmax>maxdistance)
{
maxdistance = resmax;
indicemax = i;
}
}
int mindistance = 1000, indicemin = 0, resmin = 0;
for (int i = 0; i < q; i++)
{
//listOfMatrices[i].release();
double xDiff = abs(centers[maxbleu].x - centers[i].x);
double yDiff = abs(centers[maxbleu].y - centers[i].y);
resmin = sqrt((xDiff * xDiff) + (yDiff * yDiff));
if (i == maxbleu)
{
continue;
}
else if (resmin<mindistance)
{
mindistance = resmin;
indicemin = i;
}
}
cout << "cyan" << centers[indicemax] << endl;
cout << "white" << centers[maxbleu] << endl;
cout << "gray" << centers[indicemin] << endl;
vector<Point> centersV2;
for (int j = 0; j < 4; j++)
{
for (int i = 0; i < 6; i++)
{
if (abs(centers[maxbleu].x - centers[indicemax].x) <
abs(centers[maxbleu].y - centers[indicemax].y))
{
if (centers[maxbleu].y - centers[indicemax].y > 0)
{
if (5 * abs(centers[maxbleu].x - centers[indicemin].x) > 30)
{
Point tmpV2(centers[maxbleu].x - i*(centers[maxbleu].x -
centers[indicemin].x) - j*(centers[maxbleu].x - centers[indicemax].x) / 3.3,
centers[maxbleu].y - i*(abs(centers[maxbleu].y - centers[indicemax].y)) /
5);
centersV2.push_back(tmpV2);
}
else {
Point tmpV2(centers[maxbleu].x - i*(centers[maxbleu].x -
centers[indicemin].x) - j*(centers[maxbleu].x - centers[indicemax].x) / 3,
centers[maxbleu].y - i*(abs(centers[maxbleu].y - centers[indicemax].y)) /
5);
centersV2.push_back(tmpV2);
}
}
else {
if (5 * abs(centers[maxbleu].x - centers[indicemin].x) > 30)
{
Point tmpV2(centers[maxbleu].x - i*
(abs(centers[maxbleu].x - centers[indicemin].x)) - j*(abs(centers[maxbleu].x
- centers[indicemax].x)) / 3.3, centers[maxbleu].y + i*
(abs(centers[maxbleu].y - centers[indicemax].y) / 5));
centersV2.push_back(tmpV2);
}
else {
Point tmpV2(centers[maxbleu].x - i*
(abs(centers[maxbleu].x - centers[indicemin].x)) - j*
(abs(centers[maxbleu].x - centers[indicemax].x)) / 3, centers[maxbleu].y
+ i*(abs(centers[maxbleu].y - centers[indicemax].y) / 5));
centersV2.push_back(tmpV2);
}
}
}
else {
if (centers[maxbleu].x - centers[indicemin].x > 0)
{
if (5 * abs(centers[maxbleu].y - centers[indicemin].y) > 30)
{
Point tmpV2(centers[maxbleu].x - i*
(abs(centers[maxbleu].x - centers[indicemax].x) / 5) + i,
centers[indicemin].y - i*(centers[maxbleu].y - centers[indicemin].y) - j*
(centers[maxbleu].y - centers[indicemax].y) / 3.3);
centersV2.push_back(tmpV2);
}
else {
Point tmpV2(centers[maxbleu].x - i*
(abs(centers[maxbleu].x - centers[indicemax].x) / 5) + i,
centers[indicemin].y - i*(centers[maxbleu].y - centers[indicemin].y) - j*
(centers[maxbleu].y - centers[indicemax].y) / 3);
centersV2.push_back(tmpV2);
}
}
else {
if (5 * abs(centers[maxbleu].y - centers[indicemin].y) > 30)
{
Point tmpV2(centers[maxbleu].x + i*
(abs(centers[maxbleu].x - centers[indicemax].x) / 5) + i,
centers[maxbleu].y - i*((centers[maxbleu].y - centers[indicemin].y)) - j*
(centers[maxbleu].y - centers[indicemax].y) / 3.3);
centersV2.push_back(tmpV2);
}
else
{
Point tmpV2(centers[maxbleu].x + i*
(abs(centers[maxbleu].x - centers[indicemax].x) / 5) + i,
centers[maxbleu].y - i*((centers[maxbleu].y - centers[indicemin].y)) - j*
(centers[maxbleu].y - centers[indicemax].y) / 3);
centersV2.push_back(tmpV2);
}
}
}
}
}
for (int i = 0; i < centersV2.size(); i++)
{
cv::Mat IImage;
image.copyTo(IImage);
cv::Mat roi = IImage(Rect(centersV2[i].x -
0.66*listOfMatrices[maxbleu].size().width / 2, centersV2[i].y -
0.66*listOfMatrices[maxbleu].size().height / 2,
0.66*listOfMatrices[maxbleu].size().width,
0.66*listOfMatrices[maxbleu].size().height));
listOfMatrices2.push_back(roi);
n++;
cout << "centre de patchs :" << i + 1 << " :est:" << centersV2[i] << "
colour :" << mean(listOfMatrices2[i]) << endl;
rectangle(image, Point(centersV2[i].x -
0.66*listOfMatrices[maxbleu].size().width, centersV2[i].y -
0.66*listOfMatrices[maxbleu].size().height), Point(centersV2[i].x +
0.66*listOfMatrices[maxbleu].size().width, centersV2[i].y +
0.66*listOfMatrices[maxbleu].size().height), Scalar(0, 255, 0), 4, 8,
0);
//ellipse(image, centersV2[i],
Size(0.66*listOfMatrices[maxbleu].size().width,
0.66*listOfMatrices[maxbleu].size().height), 0, 0, 360, Scalar(0, 255,
0), 2, LINE_AA);
stringstream numero;
numero << i + 1;
putText(image, numero.str(), Point(centersV2[i].x - 15, centersV2[i].y +
5), 5, 2, Scalar(0, 0, 255), 4, 8, false);
}
}
int main(int /*argc*/, char** /*argv*/)
{
static const char* filename[] = { "E:/Zouhair Jimmouh-Colorimetrie/Example
Etudes/Exemple2/AS1606001A-008-R045-HP-01.jpg", 0};
vector<vector<Point> > Squares;
for (int i = 0; filename[i] != 0; i++)
{
Mat Image = imread(filename[i], 1);
if (Image.empty())
{
cout << "Couldn't load " << endl;
//continue;
}
Mat blackTOwhite;
findSquares(Image, Squares);
(drawSquares(Image, Squares)).copyTo(blackTOwhite);
//show image with detected patches
namedWindow("RECT", CV_WINDOW_NORMAL);
imshow("RECT", Image);
int c = waitKey();
if ((char)c == 27)
break;
}
return 0;
}
Any help guys is appreciated ! i've been struggling with this for days now.
