From c21c3b0befeb46a51b6bf3758ffa30813bea0ff0 Mon Sep 17 00:00:00 2001 From: Daniel Baumann Date: Sat, 9 Mar 2024 14:19:22 +0100 Subject: Adding upstream version 1.44.3. Signed-off-by: Daniel Baumann --- ml/dlib/examples/hough_transform_ex.cpp | 84 +++++++++++++++++++++++++++++++++ 1 file changed, 84 insertions(+) create mode 100644 ml/dlib/examples/hough_transform_ex.cpp (limited to 'ml/dlib/examples/hough_transform_ex.cpp') diff --git a/ml/dlib/examples/hough_transform_ex.cpp b/ml/dlib/examples/hough_transform_ex.cpp new file mode 100644 index 000000000..1c8b9f7bd --- /dev/null +++ b/ml/dlib/examples/hough_transform_ex.cpp @@ -0,0 +1,84 @@ +// 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 +#include + +using namespace dlib; + +int main() +{ + // First let's make a 400x400 image. This will form the input to the Hough transform. + array2d 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 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 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 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. + win.add_overlay(box, rgb_pixel(0,255,0)); + + // We can also display the Hough transform itself using the jet color scheme. + win2.set_image(jet(himg)); + } +} + -- cgit v1.2.3