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Hello everyone. I have tried this tutorial, and unfortunately I didn't really get it. Can anyone tell/explain me how can I filter also the other rectangles from the ZebraCrossing, not only the middle one. (Result attached).

Many thanks !

Here is the 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 "opencv2/nonfree/nonfree.hpp"

using namespace cv;

/** @function main */
#include "opencv2/core/core.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/highgui/highgui.hpp"

#include <iostream>
#include <math.h>
#include <string.h>

using namespace cv;
using namespace std;


int thresh = 50, N = 5;
const char* wndname = "Square Detection Demo";

// 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();

    //s    Mat pyr, timg, gray0(image.size(), CV_8U), gray;

    // down-scale and upscale the image to filter out the noise
    //pyrDown(image, pyr, Size(image.cols/2, image.rows/2));
    //pyrUp(pyr, timg, image.size());


    // blur will enhance edge detection
    Mat timg(image);
    cv::medianBlur(image, timg, 9);
    Mat gray0(timg.size(), CV_8U), gray;

    vector<vector<Point> > contours;

    // find squares in every color plane of the image
    for (int c = 0; c < 3; c++)
    {
        int ch[] = { c, 0 };
        mixChannels(&timg, 1, &gray0, 1, ch, 1);

        // try several threshold levels
        for (int l = 0; l < N; l++)
        {
            // hack: use Canny instead of zero threshold level.
            // Canny helps to catch squares with gradient shading
            if (l == 0)
            {
                // apply Canny. Take the upper threshold from slider
                // and set the lower to 0 (which forces edges merging)
                Canny(gray0, gray, 5, thresh, 5);
                // dilate canny output to remove potential
                // holes between edge segments
                dilate(gray, gray, Mat(), Point(-1, -1));
            }
            else
            {
                // apply threshold if l!=0:
                //     tgray(x,y) = gray(x,y) < (l+1)*255/N ? 255 : 0
                gray = gray0 >= (l + 1) * 255 / N;
            }

            // find contours and store them all as a list
            findContours(gray, 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))) > 1000 &&
                    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 < 0.3)
                        squares.push_back(approx);
                }
            }
        }
    }
}


// the function draws all the squares in the image
static void drawSquares(Mat& image, const vector<vector<Point> >& squares)
{
    for (size_t i = 0; i < squares.size(); i++)
    {
        const Point* p = &squares[i][0];

        int n = (int)squares[i].size();
        //dont detect the border
        if (p->x > 3 && p->y > 3)
            polylines(image, &p, &n, 1, true, Scalar(0, 255, 0), 3, CV_AA);
    }

    imshow(wndname, image);
}


int main(int /*argc*/, char** /*argv*/)
{
    static const char* names[] = { "a001285-1.bmp", "a001281-1.bmp", 0 };
    namedWindow(wndname, 1);
    vector<vector<Point> > squares;

    for (int i = 0; names[i] != 0; i++)
    {
        Mat image = imread(names[i], 1);
        if (image.empty())
        {
            cout << "Couldn't load " << names[i] << endl;
            continue;
        }

        findSquares(image, squares);
        drawSquares(image, squares);
        //imwrite( "out", image );
        int c = waitKey();
        if ((char)c == 27)
            break;
    }

    return 0;
}