How can you implement progressive growing in GANs to improve large-scale image generation

Question

With the help of Python programming, can we implement progressive growth in GANs to improve large-scale image generation?

Answer 1

Progressive growth in GANs involves starting with low-resolution images and incrementally increasing the resolution during training. You can implement progressive growth in GANs to improve large-scale image generation. Here is the code you can refer to:

In the code above, we are using Incremental Training to start with lower resolutions and gradually add layers to the generator and discriminator for higher resolutions. Smooth Transition uses blending techniques (e.g., linear fade-in) for stability during resolution transitions and Dynamic Data to resize training data to match the current resolution.

Hence, by using this approach, you can implement progressive growth in GANs to improve large-scale image generation.