Non nude models forums12/17/2023 ![]() ![]() The NN needs to know how well it is doing encoding and decoding faces. Some models are constructed slightly differently, but the basic premise remains the same. Decoder - This has the job of taking the vectors created by the encoder and attempting to turn this representation back into faces, as closely matching the input images as possible.It is important to note that it is not learning an exact representation of every face you feed into it, rather, it is trying to create an algorithm that can be used to later reconstruct faces as closely as possible to the input images. Encoder - This has the job of taking a load of faces as an input and "encoding" them into a representation in the form of a "vector".Most of the models are largely made up of 2 parts: I will be using the GUI for this guide, but the premise is exactly the same for the cli (all the options present in the GUI are available in the cli).Īt a high level, training is teaching our Neural Network (NN) how to recreate a face. Having a basic understanding about how the Neural Network works, and the kind of data it benefits from seeing will vastly improve your chances of achieving a successful swap. Machine Learning is a complicated concept, but I have tried to break it down to be as simple to understand as possible. I advise that you familiarize yourself with it all. There is quite a lot of background information in this guide. If you have not already generated your face sets for training, then stop right now and head over to the Extract Guide to generate them now. I won't cover everything off, but hopefully this will give you enough to make informed decisions of your own. There are several models with many options. In this post I will detail how we train a model. It's how we learn, but it can sometimes help to have a bit of an understanding of the processes involved before diving in. I will try to keep it updated.Ī lot of people get overwhelmed when they start out Faceswapping, and many mistakes are made. NB: This guide was correct at time of writing, but things do change. ![]()
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