```// 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 Hough transform tool in the
dlib C++ Library.

In this example we are going to draw a line on an image and then use the
Hough transform to detect the location of the line.  Moreover, we do this in
a loop that changes the line's position slightly each iteration, which gives
a pretty animation of the Hough transform in action.
*/

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

using namespace dlib;

int main()
{
// First let's make a 400x400 image.  This will form the input to the Hough transform.
array2d<unsigned char> img(400,400);
// Now we make a hough_transform object.  The 300 here means that the Hough transform
// will operate on a 300x300 subwindow of its input image.
hough_transform ht(300);

image_window win, win2;
double angle1 = 0;
double angle2 = 0;
while(true)
{
// Generate a line segment that is rotating around inside the image.  The line is
// generated based on the values in angle1 and angle2. So each iteration creates a
// slightly different line.
angle1 += pi/130;
angle2 += pi/400;
const point cent = center(get_rect(img));
// A point 90 pixels away from the center of the image but rotated by angle1.
const point arc = rotate_point(cent, cent + point(90,0), angle1);
// Now make a line that goes though arc but rotate it by angle2.
const point l = rotate_point(arc, arc + point(500,0), angle2);
const point r = rotate_point(arc, arc - point(500,0), angle2);

// Next, blank out the input image and then draw our line on it.
assign_all_pixels(img, 0);
draw_line(img, l, r, 255);

const point offset(50,50);
array2d<int> himg;
// pick the window inside img on which we will run the Hough transform.
const rectangle box = translate_rect(get_rect(ht),offset);
// Now let's compute the hough transform for a subwindow in the image.  In
// particular, we run it on the 300x300 subwindow with an upper left corner at the
// pixel point(50,50).  The output is stored in himg.
ht(img, box, himg);
// Now that we have the transformed image, the Hough image pixel with the largest
// value should indicate where the line is.  So we find the coordinates of the
// largest pixel:
point p = max_point(mat(himg));
// And then ask the ht object for the line segment in the original image that
// corresponds to this point in Hough transform space.
std::pair<point,point> line = ht.get_line(p);

// Finally, let's display all these things on the screen.  We copy the original
// input image into a color image and then draw the detected line on top in red.
array2d<rgb_pixel> temp;
assign_image(temp, img);
// Note that we must offset the output line to account for our offset subwindow.
// We do this by just adding in the offset to the line endpoints.
draw_line(temp, line.first+offset, line.second+offset, rgb_pixel(255,0,0));
win.clear_overlay();
win.set_image(temp);
// Also show the subwindow we ran the Hough transform on as a green box.  You will
// see that the detected line is exactly contained within this box and also
// overlaps the original line.