Machine learning essentially involves a ton of trial and error. You're letting a program try millions of different settings to land on an algorithm that sort of does what you want it to do. This process is really really slow unless you have the hardware required to speed this up.
The type of computations that the process does are well suited for graphics cards, rather than regular processors. **It is pretty much required that you run the training process on a desktop or server capable GPU.** Running this on your CPU means it can take weeks to train your model, compared to several hours on a GPU.
## Hardware Requirements
**TL;DR: you need at least one of the following:**
- **A powerful CPU**
- Laptop CPUs can often run the software, but will not be fast enough to train at reasonable speeds
Windows 7 and 8 might work. Your mileage may vary. Windows has an installer which will set up everything you need. See: https://github.com/deepfakes/faceswap/releases
**In its current iteration, the project relies heavily on the use of the command line, although a gui is available. if you are unfamiliar with command line tools, you may have difficulty setting up the environment and should perhaps not attempt any of the steps described in this guide.** This guide assumes you have intermediate knowledge of the command line.
Windows now has an installer which installs everything for you and creates a desktop shortcut to launch straight into the GUI. You can download the installer from https://github.com/deepfakes/faceswap/releases.
If you have issues with the installer then read on for the more manual way to install Faceswap on Windows.
## Manual Install
Setting up Faceswap can seem a little intimidating to new users, but it isn't that complicated, although a little time consuming. It is recommended to use Linux where possible as Windows will hog about 20% of your GPU Memory, making Faceswap run a little slower, however using Windows is perfectly fine and 100% supported.
## Prerequisites
### Anaconda
Download and install the latest Python 3 Anaconda from: https://www.anaconda.com/download/. Unless you know what you are doing, you can leave all the options at default.
### Git
Download and install Git for Windows: https://git-scm.com/download/win. Unless you know what you are doing, you can leave all the options at default.
## Setup
Reboot your PC, so that everything you have just installed gets registered.
### Anaconda
#### Set up a virtual environment
- Open up Anaconda Navigator
- Select "Environments" on the left hand side
- Select "Create" at the bottom
- In the pop up:
- Give it the name: faceswap
- **IMPORTANT**: Select python version 3.6
- Hit "Create" (NB: This may take a while as it will need to download Python 3.6)
- If using the GUI you can go to the Tools Menu and select "Check for Updates...". This will update Faceswap to the latest code and update your dependencies.
- [virtualenv](https://github.com/pypa/virtualenv) and [virtualenvwrapper](https://virtualenvwrapper.readthedocs.io) may help when you are not using docker.
- If you are using an Nvidia graphics card You should install CUDA (https://developer.nvidia.com/cuda-zone) and CUDNN (https://developer.nvidia.com/cudnn). If you do not plan to build Tensorflow yourself, make sure you install no higher than version 10.0 of CUDA and 7.4.x of CUDNN
Simply download the code from http://github.com/deepfakes/faceswap - For development, it is recommended to use git instead of downloading the code and extracting it.
For now, extract the code to a directory where you're comfortable working with it. Navigate to it with the command line. For our example, we will use `~/faceswap/` as our project directory.
If you are experiencing issues, please raise them in the [faceswap-playground](https://github.com/deepfakes/faceswap-playground) repository instead of the main repo.
