This software is meant to be a productive contribution to the rapidly growing AI-generated media industry. It will help artists with tasks such as animating a custom character or using the character as a model for clothing etc.
The developers of this software are aware of its possible unethical applications and are committed to take preventative measures against them. It has a built-in check which prevents the program from working on inappropriate media including but not limited to nudity, graphic content, sensitive material such as war footage etc. We will continue to develop this project in the positive direction while adhering to law and ethics. This project may be shut down or include watermarks on the output if requested by law.
Users of this software are expected to use this software responsibly while abiding by local laws. If the face of a real person is being used, users are required to get consent from the concerned person and clearly mention that it is a deepfake when posting content online. Developers of this software will not be responsible for actions of end-users.
### Basic: It is more likely to work on your computer but it will also be very slow. You can follow instructions for the basic install (This usually runs via **CPU**)
2. [inswapper_128_fp16.onnx](https://huggingface.co/hacksider/deep-live-cam/resolve/main/inswapper_128_fp16.onnx) *(Note: Use this [replacement version](https://github.com/facefusion/facefusion-assets/releases/download/models/inswapper_128_fp16.onnx) if an issue occurs on your computer)*
##### DONE!!! If you don't have any GPU, You should be able to run roop using `python run.py` command. Keep in mind that while running the program for first time, it will download some models which can take time depending on your network connection.
#### 5. Proceed if you want to use GPU acceleration (optional)
Choose a face (image with desired face) and the target image/video (image/video in which you want to replace the face) and click on `Start`. Open file explorer and navigate to the directory you select your output to be in. You will find a directory named `<video_title>` where you can see the frames being swapped in realtime. Once the processing is done, it will create the output file. That's it.
Just use your favorite screencapture to stream like OBS
> Note: In case you want to change your face, just select another picture, the preview mode will then restart (so just wait a bit).
Additional command line arguments are given below. To learn out what they do, check [this guide](https://github.com/s0md3v/roop/wiki/Advanced-Options).
If you want to use WSL2 on Windows 11 you will notice, that Ubuntu WSL2 doesn't come with USB-Webcam support in the Kernel. You need to do two things: Compile the Kernel with the right modules integrated and forward your USB Webcam from Windows to Ubuntu with the usbipd app. Here are detailed Steps:
This tutorial will guide you through the process of setting up WSL2 Ubuntu with USB webcam support, rebuilding the kernel, and preparing the environment for the Deep-Live-Cam project.
#### 1. Install WSL2 Ubuntu
Install WSL2 Ubuntu from the Microsoft Store or using PowerShell:
2. In Windows PowerShell (as Administrator), connect your webcam to WSL:
```powershell
usbipd list
usbipd bind --busid x-x # Replace x-x with your webcam's bus ID
usbipd attach --wsl --busid x-x # Replace x-x with your webcam's bus ID
```
You need to redo the above every time you reboot wsl or re-connect your webcam/usb device.
#### 3. Rebuild WSL2 Ubuntu Kernel with USB and Webcam Modules
Follow these steps to rebuild the kernel:
1. Start with this guide: [https://github.com/PINTO0309/wsl2_linux_kernel_usbcam_enable_conf](https://github.com/PINTO0309/wsl2_linux_kernel_usbcam_enable_conf)
2. When you reach the `sudo wget [github.com](http://github.com/)...PINTO0309` step, which won't work for newer kernel versions, follow this video instead or alternatively follow the video tutorial from the beginning:
2. If modules are loadable (m), not built-in (y), check if the file exists:
```bash
ls /lib/modules/$(uname -r)/kernel/drivers/media/usb/uvc/
```
3. Load the module and check for errors (optional if built-in):
```bash
sudo modprobe uvcvideo
dmesg | tail
```
4. Verify video devices:
```bash
sudo ls -al /dev/video*
```
#### 6. Set Up Permissions
1. Add user to video group and set permissions:
```bash
sudo usermod -a -G video $USER
sudo chgrp video /dev/video0 /dev/video1
sudo chmod 660 /dev/video0 /dev/video1
```
2. Create a udev rule for permanent permissions:
```bash
sudo nano /etc/udev/rules.d/81-webcam.rules
```
Add this content:
```
KERNEL=="video[0-9]*", GROUP="video", MODE="0660"
```
3. Reload udev rules:
```bash
sudo udevadm control --reload-rules && sudo udevadm trigger
```
4. Log out and log back into your WSL session.
5. Start Deep-Live-Cam with `python run.py --execution-provider cuda --max-memory 8` where 8 can be changed to the number of GB VRAM of your GPU has, minus 1-2GB. If you have a RTX3080 with 10GB I suggest adding 8GB. Leave some left for Windows.
#### Final Notes
- Steps 6 and 7 may be optional if the modules are built into the kernel and permissions are already set correctly.
- Always ensure you're using compatible versions of CUDA, ONNX, and other dependencies.
- If issues persist, consider checking the Deep-Live-Cam project's specific requirements and troubleshooting steps.
By following these steps, you should have a WSL2 Ubuntu environment with USB webcam support ready for the Deep-Live-Cam project. If you encounter any issues, refer back to the specific error messages and troubleshooting steps provided.
#### Troubleshooting CUDA Issues
If you encounter this error:
```
[ONNXRuntimeError] : 1 : FAIL : Failed to load library [libonnxruntime_providers_cuda.so](http://libonnxruntime_providers_cuda.so/) with error: libcufft.so.10: cannot open shared object file: No such file or directory
```
Follow these steps:
1. Install CUDA Toolkit 11.8 (ONNX 1.16.3 requires CUDA 11.x, not 12.x):
4. Install CUDA Toolkit 11.8 again [https://developer.nvidia.com/cuda-11-8-0-download-archive](https://developer.nvidia.com/cuda-11-8-0-download-archive), select: Linux, x86_64, WSL-Ubuntu, 2.0, deb (local)
If you want the latest and greatest build, or want to see some new great features, go to our [experimental branch](https://github.com/hacksider/Deep-Live-Cam/tree/experimental) and experience what the contributors have given.
*Note: This is an open-source project, and we’re working on it in our free time. Therefore, features, replies, bug fixes, etc., might be delayed. We hope you understand. Thanks.*
- [deepinsight](https://github.com/deepinsight): for their [insightface](https://github.com/deepinsight/insightface) project which provided a well-made library and models. Please be reminded that the [use of the model is for non-commercial use only as per license details](https://github.com/deepinsight/insightface?tab=readme-ov-file#license).
- Foot Note: [This is originally roop-cam, see the full history of the code here.](https://github.com/hacksider/roop-cam) Please be informed that the base author of the code is [s0md3v](https://github.com/s0md3v/roop)
