mirror of https://github.com/davisking/dlib.git
98 lines
3.6 KiB
C++
98 lines
3.6 KiB
C++
// 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 GUI API as well as some
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aspects of image manipulation from the dlib C++ Library.
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This is a pretty simple example. It takes a BMP file on the command line
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and opens it up, runs a simple edge detection algorithm on it, and
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displays the results on the screen.
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*/
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#include <dlib/gui_widgets.h>
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#include <dlib/image_io.h>
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#include <dlib/image_transforms.h>
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#include <fstream>
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using namespace std;
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using namespace dlib;
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// ----------------------------------------------------------------------------
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int main(int argc, char** argv)
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{
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try
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{
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// make sure the user entered an argument to this program
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if (argc != 2)
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{
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cout << "error, you have to enter a BMP file as an argument to this program" << endl;
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return 1;
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}
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// Here we declare an image object that can store rgb_pixels. Note that in
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// dlib there is no explicit image object, just a 2D array and
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// various pixel types.
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array2d<rgb_pixel> img;
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// Now load the image file into our image. If something is wrong then
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// load_image() will throw an exception. Also, if you linked with libpng
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// and libjpeg then load_image() can load PNG and JPEG files in addition
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// to BMP files.
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load_image(img, argv[1]);
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// Now lets use some image functions. First lets blur the image a little.
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array2d<unsigned char> blurred_img;
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gaussian_blur(img, blurred_img);
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// Now find the horizontal and vertical gradient images.
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array2d<short> horz_gradient, vert_gradient;
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array2d<unsigned char> edge_image;
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sobel_edge_detector(blurred_img, horz_gradient, vert_gradient);
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// now we do the non-maximum edge suppression step so that our edges are nice and thin
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suppress_non_maximum_edges(horz_gradient, vert_gradient, edge_image);
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// Now we would like to see what our images look like. So lets use a
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// window to display them on the screen. (Note that you can zoom into
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// the window by holding CTRL and scrolling the mouse wheel)
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image_window my_window(edge_image, "Normal Edge Image");
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// We can also easily display the edge_image as a heatmap or using the jet color
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// scheme like so.
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image_window win_hot(heatmap(edge_image));
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image_window win_jet(jet(edge_image));
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// also make a window to display the original image
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image_window my_window2(img, "Original Image");
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// Sometimes you want to get input from the user about which pixels are important
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// for some task. You can do this easily by trapping user clicks as shown below.
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// This loop executes every time the user double clicks on some image pixel and it
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// will terminate once the user closes the window.
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point p;
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while (my_window.get_next_double_click(p))
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{
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cout << "User double clicked on pixel: " << p << endl;
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cout << "edge pixel value at this location is: " << (int)edge_image[p.y()][p.x()] << endl;
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}
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// wait until the user closes the windows before we let the program
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// terminate.
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win_hot.wait_until_closed();
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my_window2.wait_until_closed();
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}
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catch (exception& e)
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{
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cout << "exception thrown: " << e.what() << endl;
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}
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}
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// ----------------------------------------------------------------------------
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