Computer Vision: Python Face Swap & Quick Deepfake in Colab

Computer Vision: Python Face Swap & Quick Deepfake in Colab

MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 27 lectures (4 hour, 4 mins) | Size: 2.54 GB
Custom Face Swap using Python and OpenCV & Deepfake Image Animation using 'First Order Motion Model' paper in Colab

What you'll learn
Python based Custom Face Swap Application with Image, Video and Camera. Deepfake Videos based on First Order Motion Model Image Animation Paper
A decent configuration computer (preferably Windows) and an enthusiasm to research with Deepfake Technology
Hello and welcome to my new course 'Python Face Swap & Quick Deepfake using Google Colab'
You know, there is is an old phrase that says 'seeing is believing'. But in the world of 'Deepfake' what we see is not always true. Let's define deep fake with the help of an example video. Here is it.
I used only a single stamp size photos of these people to create these videos. Yes, you heard it right. With only a single face image and few minutes of time with a normal computer, you can create deepfake of anyone. You an even make dead people talk or even sing for you.
Yes! Be prepared to be amazed. Before we proceed any further, let me explain the list of contents that are included in this course. This course is divided exactly into two halves.
In the first half, we will be creating a basic python based face swap application. Before we proceed, we will have an introduction to the deep fake technique, its applications, advantages and disadvantages. Then we have to prepare our computer with all the dependencies installed. We will be installing Anaconda, the platform and IDE for our python programming. Later there are few optional sessions for those who want to learn the basics of python programming language basics.
Later we will install the rest of dependences required to built our custom python face swap application. After that we will writing the python code line by line to complete the whole program with more than 300 lines. Alternatively you may also download the complete code from the google drive link provided in the last session of this course. At first we will be doing the face swap using two static images. One as the source image and other as the target image. Later we will try it for realtime video from our computer's web camera. And then we will modify it to make it work with a pre-saved video saved in our computer.
From the examples, you can see that this was just a basic face swap program and is not at all perfect. We were doing it just to learn how things works behind the scenes.
Later we will proceed with implementing deepfake based on a paper called

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