In this chapter, we have learned about generating images from a given contour using the Pix2Pix GAN. Further, we learned about the various loss functions in CycleGAN to convert images of one class to another. Next, we learned about how StyleGAN helps in generating realistic faces and also copying the style from one image to another based on the way in which the generator is trained. Finally, we learned about leveraging the pre-trained SRGAN model to generate high-resolution images.
In the next chapter, we will switch to learning about training an image classification model based on very few (typically less than 20) images.
