I am trying to copy Sebastian Lague's Neural Network project using C++.
I have to assign a color to every pixel on the screen based on a bool variable in a loop. I have a function that works but it works so slow (about 15 fps). I need a faster way to go change pixels.
/* iterates every pixel on the screen and assigns a color to is based
* on the value of net.Classify() method.
*/
void Visualize(sf::RenderWindow& w, sf::Image& im, NeuralNetwork& net, sf::Texture& tx, sf::Sprite& sp)
{
// This variable is used for optimization.
// It allows me to calculate 25 times fewer pixels but the image is grainy
// In optimal, this variable should be euqal to 1
int prescalar = 5;
for (int x = 0; x < w.getSize().x; x += prescalar)
for (int y = 0; y < w.getSize().y; y += prescalar)
{
std::vector<float> f = { (float)x,(float)y };
int result = net.Classify(f); // return true or false
sf::Color c;
if (result)
c = sf::Color(185, 250, 246);
else
c = sf::Color(255, 149, 130);
for(int xx = 0; xx < prescalar; xx++)
for(int yy = 0; yy < prescalar; yy++)
im.setPixel(x + xx, w.getSize().y - y - 1 - yy, c); // y size math used for left bottom corner to be the (0,0)
}
tx.loadFromImage(im);
sp.setTexture(tx, true);
w.draw(sp);
}
My main looks something like this
int main()
{
sf::RenderWindow window(sf::VideoMode::getDesktopMode(), "Window Title", sf::Style::Fullscreen);
sf::Image im;
im.create(window.getSize().x, window.getSize().y, sf::Color::Black);
sf::Texture tx;
sf::Sprite sp;
NeuralNetwork network();
// some stuff
while (window.isOpen())
{
// some stuff
Visualize(window, im, network, tx, sp);
// some other stuff
}
}
I checked the work times of all functions and this one is the by far longest one (60 to 80 milliseconds). What are the faster options to implement this?