#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/imgcodecs.hpp"
#include <iostream>
#include <stdio.h>
#include <stdlib.h>

using namespace cv;
using namespace std;

Mat src; Mat src_gray;
int thresh = 100;
int max_thresh = 255;
RNG rng(12345);

/// Function header
void thresh_callback(int, void* );

/** @function main */
int main( int argc, char** argv )
{
  /// Load source image and convert it to gray
  src = imread( "C:\\Users\\Sky\\Downloads\\photo.jpg", IMREAD_COLOR );

  /// Convert image to gray and blur it
  cvtColor( src, src_gray, COLOR_BGR2GRAY );
  blur( src_gray, src_gray, Size(3,3) );

  /// Create Window
  char* source_window = "Source";
  namedWindow( source_window, WINDOW_AUTOSIZE );
  imshow( source_window, src );

  createTrackbar( " Canny thresh:", "Source", &thresh, max_thresh, thresh_callback );
  thresh_callback( 0, 0 );

  waitKey(0);
  return(0);
}

/** @function thresh_callback */
void thresh_callback(int, void* )
{
  Mat canny_output;
  vector<vector<Point> > contours;
  vector<Vec4i> hierarchy;

  /// Detect edges using canny
  Canny( src_gray, canny_output, thresh, thresh*2, 3 );
  /// Find contours
  findContours( canny_output, contours, hierarchy, RETR_TREE, CHAIN_APPROX_SIMPLE, Point(0, 0) );

  /// Draw contours
  Mat drawing = Mat::zeros( canny_output.size(), CV_8UC3 );
  for( int i = 0; i < contours.size(); i++ )
     {
       Scalar color = Scalar( rng.uniform(0, 255), rng.uniform(0,255), rng.uniform(0,255) );
       drawContours( drawing, contours, i, color, 2, 8, hierarchy, 0, Point() );
     }

  /// Show in a window
  namedWindow( "Contours", WINDOW_AUTOSIZE );
  imshow( "Contours", drawing );
}




















































//#include "opencv2/imgproc.hpp"
//#include "opencv2/imgcodecs.hpp"
//#include "opencv2/highgui.hpp"
//#include <iostream>
//using namespace cv;
//using std::cout;
//int threshold_value = 0;
//int threshold_type = 3;
//int const max_value = 255;
//int const max_type = 4;
//int const max_binary_value = 255;
//Mat src, src_gray, dst;
//const char* window_name = "Threshold Demo";
//const char* trackbar_type = "Type: \n 0: Binary \n 1: Binary Inverted \n 2: Truncate \n 3: To Zero \n 4: To Zero Inverted";
//const char* trackbar_value = "Value";
//static void Threshold_Demo( int, void* )
//{
//    /* 0: Binary
//     1: Binary Inverted
//     2: Threshold Truncated
//     3: Threshold to Zero
//     4: Threshold to Zero Inverted
//    */
//    threshold( src_gray, dst, threshold_value, max_binary_value, threshold_type );
//    imshow( window_name, dst );
//}
//int main( int argc, char** argv )
//{
//    String imageName("C:\\Users\\Sky\\Downloads\\photo.jpg"); // by default
//    if (argc > 1)
//    {
//        imageName = argv[1];
//    }
//    src = imread( samples::findFile( imageName ), IMREAD_COLOR ); // Load an image
//    if (src.empty())
//    {
//        cout << "Cannot read the image: " << imageName << std::endl;
//        return -1;
//    }
//    cvtColor( src, src_gray, COLOR_BGR2GRAY ); // Convert the image to Gray
//    namedWindow( window_name, WINDOW_AUTOSIZE ); // Create a window to display results
//    createTrackbar( trackbar_type,
//                    window_name, &threshold_type,
//                    max_type, Threshold_Demo ); // Create a Trackbar to choose type of Threshold
//    createTrackbar( trackbar_value,
//                    window_name, &threshold_value,
//                    max_value, Threshold_Demo ); // Create a Trackbar to choose Threshold value
//    Threshold_Demo( 0, 0 ); // Call the function to initialize
//    waitKey();
//    return 0;
//}
















































//#include <iostream>
//#include <sstream>
//#include <opencv2/imgcodecs.hpp>
//#include <opencv2/imgproc.hpp>
//#include <opencv2/videoio.hpp>
//#include <opencv2/highgui.hpp>
//#include <opencv2/video.hpp>


//using namespace cv;
//using namespace std;


//const char* params
//    = "{ help h         |           | Print usage }"
//      "{ input          | C:\\Users\\Sky\\Downloads\\Umka video\\Umka video\\1_light.mp4 | Path to a video or a sequence of image }"
//      "{ algo           | MOG2      | Background subtraction method (KNN, MOG2) }";
//int main(int argc, char* argv[])
//{
//    CommandLineParser parser(argc, argv, params);
//    parser.about( "This program shows how to use background subtraction methods provided by "
//                  " OpenCV. You can process both videos and images.\n" );
//    if (parser.has("help"))
//    {
//        //print help information
//        parser.printMessage();
//    }
//    //create Background Subtractor objects
//    Ptr<BackgroundSubtractor> pBackSub;
//    if (parser.get<String>("algo") == "MOG2")
//        pBackSub = createBackgroundSubtractorMOG2();
//    else
//        pBackSub = createBackgroundSubtractorKNN();
//    VideoCapture capture( samples::findFile( parser.get<String>("input") ) );
//    if (!capture.isOpened()){
//        //error in opening the video input
//        cerr << "Unable to open: " << parser.get<String>("input") << endl;
//        return 0;
//    }
//    Mat frame, fgMask;
//    while (true) {
//        capture >> frame;
//        if (frame.empty())
//            break;
//        //update the background model
//        pBackSub->apply(frame, fgMask);
//        //get the frame number and write it on the current frame
//        rectangle(frame, cv::Point(10, 2), cv::Point(100,20),
//                  cv::Scalar(255,255,255), -1);
//        stringstream ss;
//        ss << capture.get(CAP_PROP_POS_FRAMES);
//        string frameNumberString = ss.str();
//        putText(frame, frameNumberString.c_str(), cv::Point(15, 15),
//                FONT_HERSHEY_SIMPLEX, 0.5 , cv::Scalar(0,0,0));
//        //show the current frame and the fg masks
//        imshow("Frame", frame);
//        imshow("FG Mask", fgMask);
//        //get the input from the keyboard
//        int keyboard = waitKey(30);
//        if (keyboard == 'q' || keyboard == 27)
//            break;
//    }
//    return 0;
//}