Easily and quickly run stable-diffsion-webui with ControlNet in Docker.
- Docker
- Docker Compose
$ cp .env.example .envEdit your environment,
$ cat .env
TZ=Etc/UTC # timezone
PORT=7861 # port mapping
VOLUME=data # docker volume storage mount point, eg. ./data to /dataIf you modified the value of VOLUME, for example from VOLUME=data to VOLUME=volume, please follow these steps as well,
$ cat .env
...
VOLUME=volume # docker volume storage mount point, eg. ./data to /data$ mv data volumeHere are some models for reference,
$ cat data/enhancing.sh
#!/usr/bin/env bash
declare -A arr
# models
arr["https://huggingface.co/prompthero/openjourney/resolve/main/mdjrny-v4.safetensors"]="models/Stable-diffusion"
arr+=(["https://huggingface.co/prompthero/openjourney-v2/resolve/main/openjourney-v2.ckpt"]="models/Stable-diffusion")
arr+=(["https://huggingface.co/ckpt/anything-v4.5-vae-swapped/resolve/main/anything-v4.5-vae-swapped.safetensors"]="models/Stable-diffusion")
arr+=(["https://huggingface.co/dreamlike-art/dreamlike-photoreal-2.0/resolve/main/dreamlike-photoreal-2.0.safetensors"]="models/Stable-diffusion")
arr+=(["https://huggingface.co/nuigurumi/basil_mix/resolve/main/Basil_mix_fixed.safetensors"]="models/Stable-diffusion")
arr+=(["https://huggingface.co/Alsebay/Chilloutmix-Ni-fix/resolve/main/Chilloutmix-Ni-fix/Chilloutmix-Ni-prune-fp32-fix.safetensors"]="models/Stable-diffusion")
# vae
arr+=(["https://huggingface.co/stabilityai/sd-vae-ft-mse-original/resolve/main/vae-ft-mse-840000-ema-pruned.safetensors"]="models/VAE")
# embeddings
arr+=(["https://huggingface.co/datasets/gsdf/EasyNegative/resolve/main/EasyNegative.safetensors"]="embeddings")
...Downloading ...
$ cd data ; bash enhancing.shThese models, and others. will be linked in Docker once the container is successfully running.
$ docker compose --profile cpu up -d # for CPU
$ docker compose --profile gpu up -d # for GPUPlease wait while the process completes.
If you want to track the progress,
$ docker compose --profile cpu logs -f # for CPU
$ docker compose --profile gpu logs -f # for GPU- Open your browser and navigate to http://127.0.0.1:7861. The default port specified in the .env file is 7861.
- The saved images will be located in the data/outputs directory.
- Examples of prompts can be found in data/prompts.
$ docker compose --profile cpu restart # for restart
$ docker compose --profile cpu stop # for stop
$ docker compose --profile cpu down # for deinstallation
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