Stable Diffusion Setup¶

Stable Diffusion <add info here>

Prerequisites¶

Hardware¶

• Modern Linux computer with 20 GB disk space
• NVidia GPU with >= 4 GB VRAM

CUDA¶

Installation of NVidia Driver and CUDA is not covered here.

Docker¶

1. Ensure Docker prereqs are all installed:
   

   $ sudo apt update
   $ sudo apt install ca-certificates curl gnupg lsb-release
   

2. Install GPG key:
   

   $ sudo mkdir -m 0755 -p /etc/apt/keyrings
   $ curl -fsSL https://download.docker.com/linux/ubuntu/gpg | sudo gpg --dearmor -o /etc/apt/keyrings/docker.gpg
   

3. Add Docker APT repository configuration:
   

   echo "deb [arch=$(dpkg --print-architecture) signed-by=/etc/apt/keyrings/docker.gpg] https://download.docker.com/linux/ubuntu  $(lsb_release -cs) stable" | sudo tee /etc/apt/sources.list.d/docker.list > /dev/null
   

4. Install packages:
   

   $ sudo apt install docker-ce docker-ce-cli containerd.io docker-buildx-plugin docker-compose-plugin
   

NVidia Container Toolkit¶

1. Install GPG key:
   

   $ curl -s -L https://nvidia.github.io/nvidia-docker/gpgkey | apt-key add -
   

2. Setup APT repo:
   

   $ sudo bash -c "curl -s -L https://nvidia.github.io/nvidia-docker/ubuntu22.04/nvidia-docker.list > /etc/apt/sources.list.d/nvidia-docker.list" 
   

3. Install package:
   

   $ sudo apt update
   $ sudo apt -y install nvidia-container-toolkit
   

4. Restart docker:
   

   $ sudo systemctl restart docker
   

Stable Diffusion Docker Container of WebUI¶

1. Go to https://github.com/AbdBarho/stable-diffusion-webui-docker/releases, download the latest source code release (ZIP) under Assets. Unzip it somewhere.
2. Go to the directory where you unzipped the archive, and run
   

   sudo docker compose --profile download up --build
   

   
   this will download 12GB of pretrained models. Wait until it is finished, then
   

   docker compose --profile auto up --build
   

   
   More details are available on the project's wiki: https://github.com/AbdBarho/stable-diffusion-webui-docker/wiki/Setup
3. Wait until you see
   

    Running on local URL:  http://0.0.0.0:7860
    To create a public link, set `share=True` in `launch()`.
   

   
   Then go to http://localhost:7860/ in any browser.

Naughty Stuff¶

1. Download one of the better 'Nudifying' models,
   • Go to https://civitai.com/models/2661/uber-realistic-porn-merge-urpm (account required) and under Versions, click on 'URPMv1.2-inpainting', then at the right, download
     • "Pruned Model SafeTensor (1.99 GB)"
   • "Config"
   • Save them to the data/StableDiffusion folder in the Webui docker project you unzipped earlier. The model file should be called uberRealisticPornMerge_urpmv12-inpainting.safetensors and the config file should be named uberRealisticPornMerge_urpmv12-inpainting.yaml
2. Embeddings​
   • Add the following files in the data/embeddings: https://gofile.io/d/az0mmz
   • These allow you to add breasts, small_tits and Style-Unshaved in your prompt, and provide better quality breasts / vaginas. The first one is more generalized, the latter is well.. yes.
   • Check the Discord link in the 'Additional Tips', ppl post additional embeddings on there.
3. Loading Model​
   • In the webui, at the top left, "Stable Diffusion checkpoint", hit the 'Refresh' icon.
   • Now you should see the uberRealisticPornMerge_urpmv12 model in the list, select it.
4. Model Parameters​
   • Go to the 'img2img' tab, and then the 'Inpaint' tab.
   • In the first textarea (positive prompt), enter

     • RAW photo of a nude woman, naked​

   • In the second textarea (negative prompt), enter

     • ((clothing), (monochrome:1.3), (deformed, distorted, disfigured:1.3), (hair), jeans, tattoo, wet, water, clothing, shadow, 3d render, cartoon, ((blurry)), duplicate, ((duplicate body parts)), (disfigured), (poorly drawn), ((missing limbs)), logo, signature, text, words, low res, boring, artifacts, bad art, gross, ugly, poor quality, low quality, poorly drawn, bad anatomy, wrong anatomy​

   • If not otherwise mentioned, leave default,
     • Masked content: fill (will just fill in the area without taking in to consideration the original masked 'content', but play around with others too)​
       ​* Inpaint area: Only masked​
     • Sampling method: DPM++ SDE Karras (one of the better methods that takes care of using similar skin colors for masked area, etc)​
       ​*** Sampling steps: start with 20, then increase to 50 for better quality/results when needed. But the higher, the longer it takes. I have mostly good results with 20, but it all depends on the complexity of the source image and the masked area.​
       ​*** CFG Scale: 7 - 12 (mostly 7)​
       ​*** Denoise Strength: 0.75 (default, the lower you set this, the more it will look like the original masked area)​
       ​

Miscellaneous¶

• Convert PNG files to JPG en masse:
  

  ls -1 *.png | parallel --eta convert -quality 85 '{}' '{.}.jpg'