Merging upstream version 1.45.3+dfsg.

Signed-off-by: Daniel Baumann <daniel.baumann@progress-linux.org>

1 files changed, 104 insertions, 0 deletions

diff --git a/src/ml/dlib/examples/image_ex.cpp b/src/ml/dlib/examples/image_ex.cpp
new file mode 100644
index 000000000..148682694
--- /dev/null
+++ b/src/ml/dlib/examples/image_ex.cpp
@@ -0,0 +1,104 @@
+// 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 GUI API as well as some 
+    aspects of image manipulation from the dlib C++ Library.
+
+
+    This is a pretty simple example.  It takes a BMP file on the command line
+    and opens it up, runs a simple edge detection algorithm on it, and 
+    displays the results on the screen.  
+*/
+
+
+
+#include <dlib/gui_widgets.h>
+#include <dlib/image_io.h>
+#include <dlib/image_transforms.h>
+#include <fstream>
+
+
+using namespace std;
+using namespace dlib;
+
+//  ----------------------------------------------------------------------------
+
+int main(int argc, char** argv)
+{
+    try
+    {
+        // make sure the user entered an argument to this program
+        if (argc != 2)
+        {
+            cout << "error, you have to enter a BMP file as an argument to this program" << endl;
+            return 1;
+        }
+
+        // Here we declare an image object that can store rgb_pixels.  Note that in 
+        // dlib there is no explicit image object, just a 2D array and
+        // various pixel types.  
+        array2d<rgb_pixel> img;
+
+        // Now load the image file into our image.  If something is wrong then
+        // load_image() will throw an exception.  Also, if you linked with libpng
+        // and libjpeg then load_image() can load PNG and JPEG files in addition
+        // to BMP files.
+        load_image(img, argv[1]);
+
+
+        // Now let's use some image functions.  First let's blur the image a little.
+        array2d<unsigned char> blurred_img;
+        gaussian_blur(img, blurred_img); 
+
+        // Now find the horizontal and vertical gradient images.
+        array2d<short> horz_gradient, vert_gradient;
+        array2d<unsigned char> edge_image;
+        sobel_edge_detector(blurred_img, horz_gradient, vert_gradient);
+
+        // now we do the non-maximum edge suppression step so that our edges are nice and thin
+        suppress_non_maximum_edges(horz_gradient, vert_gradient, edge_image); 
+
+        // Now we would like to see what our images look like.  So let's use a 
+        // window to display them on the screen.  (Note that you can zoom into 
+        // the window by holding CTRL and scrolling the mouse wheel)
+        image_window my_window(edge_image, "Normal Edge Image");
+
+        // We can also easily display the edge_image as a heatmap or using the jet color
+        // scheme like so.
+        image_window win_hot(heatmap(edge_image));
+        image_window win_jet(jet(edge_image));
+
+        // also make a window to display the original image
+        image_window my_window2(img, "Original Image");
+
+        // Sometimes you want to get input from the user about which pixels are important
+        // for some task.  You can do this easily by trapping user clicks as shown below.
+        // This loop executes every time the user double clicks on some image pixel and it
+        // will terminate once the user closes the window.
+        point p;
+        while (my_window.get_next_double_click(p))
+        {
+            cout << "User double clicked on pixel:         " << p << endl;
+            cout << "edge pixel value at this location is: " << (int)edge_image[p.y()][p.x()] << endl;
+        }
+
+        // wait until the user closes the windows before we let the program 
+        // terminate.
+        win_hot.wait_until_closed();
+        my_window2.wait_until_closed();
+
+
+        // Finally, note that you can access the elements of an image using the normal [row][column]
+        // operator like so:
+        cout << horz_gradient[0][3] << endl;
+        cout << "number of rows in image:    " << horz_gradient.nr() << endl;
+        cout << "number of columns in image: " << horz_gradient.nc() << endl;
+    }
+    catch (exception& e)
+    {
+        cout << "exception thrown: " << e.what() << endl;
+    }
+}
+
+//  ----------------------------------------------------------------------------
+