OpenCV Contour count (learning)

#include <iostream>
#include <opencv2/opencv.hpp>
#include <opencv2/xfeatures2d.hpp>

using namespace Std;
using namespace CV;
using namespace cv::xfeatures2d;

Mat img1, Img2, IMG3, Img4, Img5, Img6, Img_result, Img_gray1, Img_gray2, Img_gray3, Img_canny1, Img_binary1, Img_binary2, Img_dist1, Img_dist2, Kernel_1, kernel_2, Img_laplance, Img_sharp;

Char win1[] = "Window1";
Char win2[] = "Window2";
Char win3[] = "WINDOW3";
Char win4[] = "WINDOW4";
Char win5[] = "WINDOW5";
Char win6[] = "WINDOW6";
Char win7[] = "WINDOW7";

int thread_value = 10;
int max_value = 255;
RNG rng1 (12345);
RNG rng2 (1235);

Double harris_min = 0;
Double Harris_max = 0;

int Demo_surf ();
void Demo_1 (int, void*);
void demo_2 (int, void*);

int Demo_surf ()
{
Namedwindow (Win1, cv_window_autosize);
Namedwindow (win2, cv_window_autosize);
Namedwindow (Win3, cv_window_autosize);

IMG1 = Imread ("D://images//71.png");
IMG1 = Imread ("d://images//77.jpg");
if (Img1.empty ())
{
cout << "Could not load image ..." << Endl;
return 0;
}
Imshow (Win1, IMG1);

Turn grayscale
Cvtcolor (IMG1, Img_gray1, Color_bgr2gray);
Binary Value
Threshold (Img_gray1, img_binary1, 0, 255, thresh_binary | Thresh_triangle);
Imshow (Win2,img_binary1);

Morphological operations
Kernel_1 = Getstructuringelement (Morph_rect, Size (5, 5), point (-1,-1));
Dilate (Img_binary1, Img_binary2, Kernel_1, point (-1,-1), 1);
Imshow (Win3, Img_binary2);

　　
Background transformations
Bitwise_not (Img_binary2,img_binary2);
Distance transform
Distancetransform (Img_binary2, Img2, CV_DIST_L2, 3);
Normalization (0-1)
Normalize (Img2, Img2, 0, 1.0, Norm_minmax);
Imshow (Win4, IMG2);

Threshold two-value segmentation
Threshold (Img2, IMG2, 0.6, 1.0, thresh_binary);
Img2.convertto (IMG3, cv_8u);
Adaptivethreshold (img3,img3,255,adaptive_thresh_gaussian_c,thresh_binary,87,0.0);
kernel_2 = Getstructuringelement (Morph_rect, Size (5, 5), point (-1,-1));
Dilate (IMG3, IMG3, Kernel_2, point (-1,-1), 4);
Normalize (IMG3, IMG3, 0, 255, Norm_minmax);
Imshow (WIN5,IMG3);

Connected areas
Vector<vector<point>> vec_contours;
Findcontours (IMG3, Vec_contours, cv_retr_external, chain_approx_simple);

IMG4 = Mat::zeros (Img1.size (), CV_8UC3);

Drawing outlines
For (size_t k=0;k<vec_contours.size (); k++)
{
Scalar color_1 = scalar (rng1.uniform (0,255), Rng1.uniform (0,255), Rng1.uniform (0,255));
Drawcontours (Img4, Vec_contours, static_cast<int> (k), color_1, 2, 8,mat ());
}
cout << "Size:" <<vec_contours.size () << Endl;
Imshow (WIN6,IMG4);

return 0;
}

void Demo_1 (int, void*)
{
　　
}

void demo_2 (int, void*)
{
　　
}

int main ()
{
Demo_surf ();

Waitkey (0);
return 0;
}

OpenCV Contour count (learning)