This online course provides a theoretical and practical guide to the use of face-swap technology. In the past few months, deep neural networks have been wildly used to digital insert actor Nicolas Cage into several movie scenes. These so-called deepfakes have generated a lot of discussion on the ethics of Machine Learning. This second lesson will focus on the potential applications that face-swap technology can offer, and on how to use it properly.
If you are interested in understanding not only how deekfakes are generated, but also to create your own, this is the tutorial you have been looking for. And if you have been using face-swap technology already, I hope this first post will help you become more aware of why and how this technology should (and shouldn’t) be used.
This tutorial will cover the theory and practice of creating deepfakes: videos in which faces have been swapped using Machine Learning and Deep Neural Networks. If you are interested in learning more about this novel technique, this is the course for you.
After a theoretical introduction, this course will focus on how to make the most out of the popular applications FakeApp and faceswap; most of the deepfakes you will find online (such as the ones featuring Nicolas Cage) have been created using them.
The previous post in this series, Understanding Deep Dreams, explained what deep dreams are, and what they can be used for. In this second post you’ll learn how to create them, with a step by step guide.
This series of tutorial is about evolutionary computation: what it is, how it works and how to implement it in your projects and games. At the end of this series you’ll be able to harness the power of evolution to find the solution to problems you have no idea how to solve. As a toy example, this tutorial will show how evolutionary computation can be used to teach a simple creature to walk. If you want to try the power of evolutionary computation directly in your browser, try Genetic Algorithm Walkers.
In a previous post, I explained how I grabbed all the screenshots from #ScreenshotSaturday. If that was something relatively easy to implement, ordering them by colour is slightly trickier. The problem here is that there is no standard way to find the main colours in an image. Quite the opposite, different techniques will produce very different results. Long story short: this is not really a problem for programmers, and that’s why it may be more interesting to discuss about it.
Let’s say that we already have our screenshot. Now, we want to find its main colours. If you are familiar with Photoshop, a starting point is accessing the histogram which represents the distribution of colours. Peaks in the colour histograms can be associated with the main colours. Conrad Chavez wrote a very detailed post about it, if you are interested in this. The image below shows a level in 0RBITALIS which is predominantly blue and green; this can be seen directly from the colour histogram.