- Where can I download the software?
- If you are on Windows you can use the Windows Installer, which will set everything up for you. Similarly on Linux you can use the Linux Installer.
For other platforms check the installation instructions which have fairly detailed instructions for installing in most circumstances.
- Is there a usage guide?
- Yes! At least for the main components of Faceswap. Unfortunately the code changes often and documentation takes time. However, a knowledge base is building up in the forums, and the main guides are updated regularly.
support forums for more specific guides and tips.
Also check the USAGE.md page of github. The search function in this forum and our Discord server is also useful.
We welcome contributions to the repo/fourm to expand documentation.
- But seriously. I've installed and I don't know what I'm doing!
- First and foremost: Read the guides! Once you've done that, then read them again, then go over them once more for good measure.
Machine Learning techniques are complex, and whilst we are working hard to demystify the process as much as possible, there will still be some work required on your part to get the basics down.
For a very high level overview of the process you can read USEAGE.md on our github repo.
Also read through the remainder of the FAQs on this page as it will help you familiarize yourself with some of the challenges you may face.
At a high level, the process is fairly simple:
- Run extract on source face (A)
- Run extract on target face (B)
- Train on generated faces from A + B
- Convert from your source frames (A) Specifying the model you used
- Why does Windows say my GPU is hardly being used?
- By default, the Windows GPU usage reporting is highly inaccurate, and is tailored towards gaming rather than Machine Learning. If you want accurate usage statistics use nvidia-smi or modify the GPU setting in Task Manager to "CUDA usage". In addition, your CPU is used to prepare the data for the GPU. This includes getting the images into a format that the GPU can work with easily and quickly as well as any augmentation that you have selected. Depending on the options and the details of your system it's quite possible that your CPU may be in more use than your GPU. This is normal.
- How do I update Faceswap to the latest version?
- To update faceswap to the latest version, look under Tools button in the GUI, and select "Check for updates." The latest commit and any new dependencies will be installed. You may be prompted to re-start faceswap after the update.
- Can faceswap work on Mobile phones/Game consoles?
- Unfortunately, faceswap uses the speed that only a GPU can sustain to train the AI used for swapping. Portable and low end devices cannot train or use faceswap. They're simply not powerful or fast enough.
- Can I use Faceswap to swap a single photograph?
- This is a loaded question. The answer is 'yes', but with severe caveats. Machine Learning requires many thousands of different images to train a model. This is true regardless of how many images you finally intend to convert (a video is just a series of still images after all). The process to convert a single photograph would be the same as to convert a video. You would still need to collect thousands of faces to train the model. It is not as simple as just feeding in a single image.
- Why does faceswap make my computer shut down?
- Faceswap uses your GPU and CPU quite heavily. When Faceswap starts up, it causes a spike of power usage that on some Power Supplies cause a voltage drop that leads to a shutdown. This is NOT limited to insufficient wattage, but can happen even with power supplies that should provide enough wattage or that run fine in other usages.
- What graphics card do I need?
- Faceswap runs on both AMD and Nvidia graphics cards, but you will get a far better experience with Nvidia GPUs due to their propriety Cuda library for machine learning. You may be able to run the smallest model on a 2GB GPU, under Linux, but you really want a graphics card with 4GB or more. 8GB is the minimum to run the larger models.