Hands-On Image Generation with TensorFlow: A pragmatic guide to generating images and videos using deep learning

Hands-On Image Generation with TensorFlow: A pragmatic guide to generating images and videos using deep learning

English | 2021 | ISBN: 978-1838826789 | 267 Pages | PDF, EPUB, MOBI | 232 MB

Implement various state-of-the-art architectures, such as GANs and autoencoders, for image generation using TensorFlow 2.x from scratch The emerging field of generative adversarial networks (GANs) has made it possible to generate indistinguishable images from existing datasets. With this hands-on book, you’ll not only develop image generation skills but also gain a solid understanding of the underlying principles. Starting with an introduction to the fundamentals of image generation using TensorFlow, this book covers variational autoencoders and GANs. You’ll discover how to build models for different applications as you get to grips with performing face swap using deepfakes, neural style transfer, image-to-image translation, turning simple images into photorealistic images, and much more. You’ll also understand how and why to construct state-of-the-art deep neural networks using advanced techniques such as spectral normalization and self-attention layer. before working with advanced models for photo restoration, face generation and editing, text-to-image synthesis, video retargeting, and neural rendering. Throughout the book, you’ll learn to implement models from scratch in TensorFlow 2.x, including PixelCNN, VAE, DCGAN, WGAN, pix2pix, and Progressive GAN. By the end of this book, you’ll be well-versed in TensorFlow and be able to implement image generative technologies confidently. What you will learn
  • Train on face datasets and use them to explore latent spaces for editing new faces
  • Get to grips with swapping faces with deepfakes
  • Perform style transfer to convert a photo into a painting
  • Build and train pix2pix, CycleGAN, and BicycleGAN for image-to-image translation
  • Use iGAN to understand manifold interpolation and GauGAN to turn simple images into photorealistic images
  • Become well-versed with attention generative models such as SAGAN and BigGAN
  • Generate high-resolution photos with Progressive GAN and StyleGAN