Stable Diffusion Getting Started Guide, Stable Diffusion WebUI Local Deployment Tutorials

Recently took over a project that required the use of Stable Diffusion I've been working on a project that requires me to redeploy an SD environment. This is not quite the same as my previous SD deployment, and I encountered some problems during the deployment process, and summarized a more perfect installation plan, which I'd like to share with you here.

Project address: https://github.com/AUTOMATIC1111/stable-diffusion-webui

environmental preparation

Before I start deploying, I use the following environment:

• Python 3.10.6 (this version is recommended to avoid some compatibility issues)
• NVIDIA RTX 4090 24GB
• Windows 11
• Native CUDA 12.4

deployment process

At first I was installing the dependencies one by one in a step-by-step fashion, but found it tedious to switch directories too many times. Then I wrote a simple script to automate the process.

First, clone the main project:

git clone https://github.com/AUTOMATIC1111/stable-diffusion-webui.git
cd stable-diffusion-webui

condaEnvironmental Creation

conda create -p . \Dlab python=3.10.6 -y

Then create a dependency library directory:

mkdir -p repositories && cd repositories

Here's the auto-install script I wrote to get all the dependencies installed at once:

repos=(
    "Stability-AI/stablediffusion:stable-diffusion-stability-ai"
    "CompVis/taming-transformers:taming-transformers"
    "sczhou/CodeFormer:CodeFormer"
    "salesforce/BLIP:BLIP"
    "Stability-AI/generative-models:generative-models"
)


for repo in "${repos[@]}"; do
    IFS=':' read -r github_path local_path <<< "$repo"
    echo "Cloning and installing $github_path..."
    git clone "https://github.com/$github_path.git" "$local_path"
    cd "$local_path"
    pip install -e .
    cd ...
cd ... done

The next step is to install the other necessary dependencies, these are the versions I've summarized after stepping through the pits and they work perfectly:

# installs the base dependencies
pip install transformers==4.19.2 diffusers invisible-watermark --prefer-binary

# k-diffusion must install the latest version from git
pip install git+https://github.com/crowsonkb/k-diffusion.git --prefer-binary

# Go back to the home directory and install the project dependencies
cd ...
pip install -r requirements.txt --prefer-binary

# These are the versions I've tested over and over again, so I recommend installing them as follows
pip install pytorch_lightning==1.9
pip install -U xformers==0.0.28.post2 torchvision==0.20.0 torchaudio==2.5.0 --index-url https://download.pytorch.org/whl/cu124
pip install pydantic==1.10.11
pip install wandb==0.15.12

Finally start the service:

python launch.py --xformers --no-gradio-queue

Pothole Record

1. Dependency version conflict
   The pitfall is the dependency versioning issue, in particular the versions of PyTorch and xformers have to match. The version combinations I listed above are tested over and over again and work perfectly.
2. network problem
   Scientific Internet access. If you really can't download it, we recommend using a mirror source.

Chinese localization

After entering the interface select Extensions and click Load from to load

Find zh_CN Localization and click Install.

Once installed you can see in the installed plugins screen the

Then you come to the User interface screen

Select zh_CN

Apply settings and restart the UI

After restarting the webui, the interface is now in Chinese.

Generated images for testing and ran successfully!