mirror of https://github.com/davisking/dlib.git
129 lines
3.7 KiB
C++
129 lines
3.7 KiB
C++
/*
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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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class win : public drawable_window
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{
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/*
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Here we are making a GUI window that will be capable of displaying
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an image.
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*/
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public:
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template <typename image_type>
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win(
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const image_type& img
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) :
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gui_img(*this)
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{
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// set the size of this window to match the size of the input image
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set_size(img.nc(),img.nr());
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// Now load the image into the image widget so it has something to display.
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gui_img.set_image(img);
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set_title("image example");
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// show this window on the screen
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show();
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}
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~win(
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)
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{
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// You should always call close_window() in the destructor of window
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// objects to ensure that no events will be sent to this window while
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// it is being destructed.
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close_window();
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}
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private:
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image_widget gui_img;
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};
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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 open the image file. Note that when you open a binary file with
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// the C++ ifstream you must supply the ios::binary flag.
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ifstream fin(argv[1],ios::binary);
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if (!fin)
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{
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cout << "error, can't find " << argv[1] << 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>::kernel_1a img;
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// now load the bmp file into our image. If the file isn't really a BMP
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// or is corrupted then load_bmp() will throw an exception.
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load_bmp(img, fin);
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// Now lets use some image functions. This example is going to perform
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// simple edge detection on the image. First lets find the horizontal and
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// vertical gradient images.
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array2d<short>::kernel_1a horz_gradient, vert_gradient;
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array2d<unsigned char>::kernel_1a edge_image;
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sobel_edge_detector(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 our
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// window to display them on the screen.
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// create a window to display the edge image
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win my_window(edge_image);
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// also make a window to display the original image
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win my_window2(img);
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// wait until the user closes both windows before we let the program
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// terminate.
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my_window.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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