Hands On Image Generation with TensorFlow-P2P
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.

Hands On Image Generation with TensorFlow-P2P
English | ePUB | 267 pages | 10 MB
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