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85 lines
3.6 KiB
85 lines
3.6 KiB
// The contents of this file are in the public domain. See LICENSE_FOR_EXAMPLE_PROGRAMS.txt
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/*
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This is an example illustrating the use of the Hough transform tool in the
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dlib C++ Library.
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In this example we are going to draw a line on an image and then use the
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Hough transform to detect the location of the line. Moreover, we do this in
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a loop that changes the line's position slightly each iteration, which gives
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a pretty animation of the Hough transform in action.
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*/
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#include <dlib/gui_widgets.h>
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#include <dlib/image_transforms.h>
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using namespace dlib;
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int main()
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{
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// First let's make a 400x400 image. This will form the input to the Hough transform.
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array2d<unsigned char> img(400,400);
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// Now we make a hough_transform object. The 300 here means that the Hough transform
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// will operate on a 300x300 subwindow of its input image.
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hough_transform ht(300);
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image_window win, win2;
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double angle1 = 0;
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double angle2 = 0;
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while(true)
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{
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// Generate a line segment that is rotating around inside the image. The line is
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// generated based on the values in angle1 and angle2. So each iteration creates a
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// slightly different line.
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angle1 += pi/130;
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angle2 += pi/400;
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const point cent = center(get_rect(img));
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// A point 90 pixels away from the center of the image but rotated by angle1.
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const point arc = rotate_point(cent, cent + point(90,0), angle1);
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// Now make a line that goes though arc but rotate it by angle2.
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const point l = rotate_point(arc, arc + point(500,0), angle2);
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const point r = rotate_point(arc, arc - point(500,0), angle2);
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// Next, blank out the input image and then draw our line on it.
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assign_all_pixels(img, 0);
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draw_line(img, l, r, 255);
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const point offset(50,50);
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array2d<int> himg;
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// pick the window inside img on which we will run the Hough transform.
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const rectangle box = translate_rect(get_rect(ht),offset);
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// Now let's compute the hough transform for a subwindow in the image. In
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// particular, we run it on the 300x300 subwindow with an upper left corner at the
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// pixel point(50,50). The output is stored in himg.
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ht(img, box, himg);
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// Now that we have the transformed image, the Hough image pixel with the largest
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// value should indicate where the line is. So we find the coordinates of the
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// largest pixel:
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point p = max_point(mat(himg));
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// And then ask the ht object for the line segment in the original image that
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// corresponds to this point in Hough transform space.
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std::pair<point,point> line = ht.get_line(p);
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// Finally, let's display all these things on the screen. We copy the original
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// input image into a color image and then draw the detected line on top in red.
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array2d<rgb_pixel> temp;
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assign_image(temp, img);
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// Note that we must offset the output line to account for our offset subwindow.
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// We do this by just adding in the offset to the line endpoints.
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draw_line(temp, line.first+offset, line.second+offset, rgb_pixel(255,0,0));
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win.clear_overlay();
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win.set_image(temp);
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// Also show the subwindow we ran the Hough transform on as a green box. You will
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// see that the detected line is exactly contained within this box and also
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// overlaps the original line.
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win.add_overlay(box, rgb_pixel(0,255,0));
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// We can also display the Hough transform itself using the jet color scheme.
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win2.set_image(jet(himg));
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}
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}
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