    // The contents of this file are in the public domain. See LICENSE_FOR_EXAMPLE_PROGRAMS.txt
    /*

        This is an example illustrating the use of the GUI API as well as some
        aspects of image manipulation from the dlib C++ Library.

        This is a pretty simple example.  It takes a BMP file on the command line
        and opens it up, runs a simple edge detection algorithm on it, and
        displays the results on the screen.
    */

    #include <dlib/gui_widgets.h>
    #include <dlib/image_io.h>
    #include <dlib/image_transforms.h>
    #include <fstream>

    using namespace std;
    using namespace dlib;

    //  ----------------------------------------------------------------------------

    int main(int argc, char** argv)
    {
        try
        {
            // make sure the user entered an argument to this program
            if (argc != 2)
            {
                cout << "error, you have to enter a BMP file as an argument to this program" << endl;
                return 1;
            }

            // Here we declare an image object that can store rgb_pixels.  Note that in
            // dlib there is no explicit image object, just a 2D array and
            // various pixel types.
            array2d<rgb_pixel> img;

            // Now load the image file into our image.  If something is wrong then
            // load_image() will throw an exception.  Also, if you linked with libpng
            // and libjpeg then load_image() can load PNG and JPEG files in addition
            // to BMP files.
            load_image(img, argv[1]);

            // Now let's use some image functions.  First let's blur the image a little.
            array2d<unsigned char> blurred_img;
            gaussian_blur(img, blurred_img);

            // Now find the horizontal and vertical gradient images.
            array2d<short> horz_gradient, vert_gradient;
            array2d<unsigned char> edge_image;
            sobel_edge_detector(blurred_img, horz_gradient, vert_gradient);

            // now we do the non-maximum edge suppression step so that our edges are nice and thin
            suppress_non_maximum_edges(horz_gradient, vert_gradient, edge_image);

            // Now we would like to see what our images look like.  So let's use a
            // window to display them on the screen.  (Note that you can zoom into
            // the window by holding CTRL and scrolling the mouse wheel)
            image_window my_window(edge_image, "Normal Edge Image");

            // We can also easily display the edge_image as a heatmap or using the jet color
            // scheme like so.
            image_window win_hot(heatmap(edge_image));
            image_window win_jet(jet(edge_image));

            // also make a window to display the original image
            image_window my_window2(img, "Original Image");

            // Sometimes you want to get input from the user about which pixels are important
            // for some task.  You can do this easily by trapping user clicks as shown below.
            // This loop executes every time the user double clicks on some image pixel and it
            // will terminate once the user closes the window.
            point p;
            while (my_window.get_next_double_click(p))
            {
                cout << "User double clicked on pixel:         " << p << endl;
                cout << "edge pixel value at this location is: " << (int)edge_image[p.y()][p.x()] << endl;
            }

            // wait until the user closes the windows before we let the program
            // terminate.
            win_hot.wait_until_closed();
            my_window2.wait_until_closed();
        }
        catch (exception& e)
        {
            cout << "exception thrown: " << e.what() << endl;
        }
    }

    //  ----------------------------------------------------------------------------