I’ve modified the code a bit, but I’m still having some problems.
I’ve taken the pixels in generated_images and multiplied them by 0.5, and then added +0.5, so they all would be in range [0,1], now I’m able to get colored images…but they’re all interference images:

Figure_11536×753 104 KB

This is the result after 100 epochs. It isn’t that much epochs, but I think that the result should be slightly better, right?
I’ve modified my dataset so my images would be 64x64, then I copy+pasted the generator and discriminator from the tutorial. Kept the training loop AND the Dropout layers in the Discriminator, though. And the result is the same.
I’ve searched a bit and learned that this could mean that the model failed to converge, but how could this happens if now I’m using literally the same parameters from the tutorial? Same parameters for the structure, same for the optimizers…