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The installer file updated for the latest version to work with GPU blazing fast
Ignore this message at the end of install : ERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.
tensorflow 2.14.0 requires keras<2.15,>=2.14.0, but you have keras 3.1.1 which is incompatible.
Now supports Fast Stable Diffusion template and Roop updated to the latest version with new features. Please read this post carefully. Don't forget to execute very bottom commands after turn off and turn on pod.
Tutorial : How To Use Roop DeepFake On RunPod Step By Step Tutorial With Custom Made Auto Installer Script
Readme file of this tutorial click here
Select template
RunPod Fast Stable Diffusion (runpod/stable-diffusion:fast-stable-diffusion)
or
RunPod Stable Diffusion (runpod/stable-diffusion:web-automatic)
Make runtime container disk size at least 20 GB
With my way you will be able to use Stable Diffusion auto1111 and Roop at the same time so you can use codeformer to improve faces as I have shown in this video : Mind-Blowing Deepfake Tutorial: Turn Anyone into Your Favorite Movie Star! PC & Google Colab - roop
Upload the attached auto_install.sh into your workspace folder
Open a new terminal (cmd)
Execute below commands with order
chmod +x auto_install.sh
./auto_install.sh
This will install everything fully automatically
You don't have to do above steps anymore once you done them
Then whenever you want to use Roop deepfake
Open a new terminal inside the main Roop folder in your workspace as shown in tutorial video
Execute below commands
cd /workspace/roop
source ./venv/bin/activate
Then modify your file names in the given below command and hit enter on the opened cmd window
First option will not enhance face
Second option will enhance face automatically
Quality 1 is best quality 100 is worst
python run.py -s "face2.png" -t "video3.mp4" -o "face_changed_video.mp4" --keep-frames --keep-fps --temp-frame-quality 1 --output-video-quality 1 --execution-provider cuda
python run.py -s "face2.png" -t "video3.mp4" -o "face_restored_video.mp4" --keep-frames --keep-fps --temp-frame-quality 1 --output-video-quality 1 --execution-provider cuda --frame-processor face_swapper face_enhancer
It will generate face_changed_video.mp4 or the file name you give in the main Roop folder. Also you will see frames folder in main Roop folder named as video3 or whatever the video name you have given
For uploading files you can use jupyterlab interface or runpodctl which would be much faster
For runpodctl watch this tutorial : Ultimate RunPod Tutorial For Stable Diffusion - Automatic1111 - Data Transfers, Extensions, CivitAI
You can also use
To get example images and videos into your runpod quickly
Then unzip them with
7z x example_roop_dataset.zip
Copy all and paste and hit enter at once
apt update
yes | apt-get install -y python3.10-tk
yes | apt-get install ffmpeg
yes | apt-get install p7zip-full
yes | apt install -y libcudnn8=8.7.0.84-1+cuda11.8 libcudnn8-dev=8.7.0.84-1+cuda11.8 --allow-change-held-packages
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