Learn to generate realistic faces using nVidia StyleGAN2 and Python 3 in this 20-minute video tutorial. Discover how to leverage pretrained weights and a TensorFlow-compatible wrapper to create face-generating GANs without extensive training or compute time. Explore the process of using Google CoLab GPU to run StyleGAN2, and follow along with provided code examples. Gain insights into key concepts such as seed random number generation, latent vectors, and noise variables. Understand how to manipulate images, create video transformations, and work with various Python functions. Perfect for those interested in deep learning and computer vision applications.
Overview
Syllabus
Introduction
Two papers
Fashion sites
GPU required
Tensorflow required
Map to Google Drive
Download StyleGAN2
Seed Random Number Generator
Seed Vector
Random Number Vector
Images
Cars
Python
Python Functions
Noise Variables
Expand Seeds
Latent Vector
Video Transformation
ffmpeg
randomnoise
PSI
Taught by
Jeff Heaton
