private static void Main(string[] args)
{
try
{
// Make sure the user entered an argument to this program. It should be the
// filename for an image.
if (args.Length != 1)
{
Console.WriteLine("error, you have to enter a BMP file as an argument to this program.");
return;
}
// Here we declare an image object that can store color rgb_pixels.
// 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.
using (var img = Dlib.LoadImage <RgbPixel>(args[0]))
{
// Now convert the image into a FHOG feature image. The output, hog, is a 2D array
// of 31 dimensional vectors.
using (var hog = Dlib.ExtracFHogFeatures <float>(img))
{
Console.WriteLine($"hog image has {hog.Rows} rows and {hog.Columns} columns.");
// Let's see what the image and FHOG features look like.
using (var win = new ImageWindow(img))
using (var drawhog = Dlib.DrawFHog(hog))
using (var winhog = new ImageWindow(drawhog))
{
// Another thing you might want to do is map between the pixels in img and the
// cells in the hog image. dlib provides the image_to_fhog() and fhog_to_image()
// routines for this. Their use is demonstrated in the following loop which
// responds to the user clicking on pixels in the image img.
Point p; // A 2D point, used to represent pixel locations.
while (win.GetNextDoubleClick(out p))
{
var hp = Dlib.ImgaeToFHog(p);
Console.WriteLine($"The point {p} in the input image corresponds to {hp} in hog space.");
var row = hog[hp.Y];
var column = row[hp.X];
var t = Dlib.Trans(column);
// Console.WriteLine($"FHOG features at this point: {t}");
}
// Finally, sometimes you want to get a planar representation of the HOG features
// rather than the explicit vector (i.e. interlaced) representation used above.
var planar_hog = Dlib.ExtracFHogFeaturesArray <float>(img);
// Now we have an array of 31 float valued image planes, each representing one of
// the dimensions of the HOG feature vector.
}
}
}
}
catch (Exception e)
{
Console.WriteLine($"exception thrown: {e}");
}
}