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Graphics / Fastest way to change all pixels in a loop

« on: August 25, 2024, 10:52:29 pm »

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?