dustynv/stable-diffusion

By dustynv

•Updated almost 3 years ago

https://github.com/dusty-nv/jetson-containers/packages/diffusion/stable-diffusion

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dustynv/stable-diffusion repository overview

⁠stable-diffusion

CONTAINERS⁠ IMAGES⁠ RUN⁠ BUILD⁠

Generate images from text (txt2img) or from other images (img2img)

stable-diffusion: https://github.com/CompVis/stable-diffusion⁠ (/opt/stable-diffusion)
with memory optimizations: https://github.com/basujindal/stable-diffusion⁠ (/opt/stable-diffusion/optimizedSD)
tested on stable-diffusion-1.4 model: https://huggingface.co/CompVis/stable-diffusion-v-1-4-original⁠

See the stable-diffusion-webui⁠ container for a faster implementation with a web interface.

⁠txt2img

Download the stable-diffusion-1.4⁠ model (sd-v1-4.ckpt)

wget https://huggingface.co/CompVis/stable-diffusion-v-1-4-original/resolve/main/sd-v1-4.ckpt -O /data/models/stable-diffusion/sd-v1-4.ckpt

Then run this in the container to generate images (by default, six 512x512 images with 50 refinement steps)

cd /opt/stable-diffusion && python3 scripts/txt2img.py --plms \
  --ckpt /data/models/stable-diffusion/sd-v1-4.ckpt \
  --outdir /data/images/stable-diffusion \
  --prompt "a photograph of an astronaut riding a horse"

See here for options: https://github.com/CompVis/stable-diffusion#reference-sampling-script⁠

For just one 512x512 image with 25 steps:

cd /opt/stable-diffusion && python3 scripts/txt2img.py --plms \
  --n_samples 1 --n_iter 1 --ddim_steps 25 \
  --ckpt /data/models/stable-diffusion/sd-v1-4.ckpt \
  --outdir /data/images/stable-diffusion \
  --prompt "two robots walking in the woods"

Change the image resolution with --W and --H (the default is 512x512)
Change the --seed to have the images be different (the default seed is 42)

For Jetson Orin Nano and reduced memory usage:

cd /opt/stable-diffusion && python3 optimizedSD/optimized_txt2img.py \
  --sampler plms --seed 42 \
  --n_samples 1 --n_iter 1 --ddim_steps 25 \
  --ckpt /data/models/stable-diffusion/sd-v1-4.ckpt \
  --outdir /data/images/stable-diffusion \
  --prompt "a photograph of an astronaut riding a horse"

To run all these steps from a script, see stable-diffusion/test.sh⁠

CONTAINERS⁠

`stable-diffusion`
Builds
Requires	`L4T ['>=34.1.0']`
Dependencies	`build-essential`⁠ `cuda`⁠ `cudnn`⁠ `python`⁠ `numpy`⁠ `cmake`⁠ `onnx`⁠ `pytorch:2.2`⁠ `torchvision`⁠ `huggingface_hub`⁠ `rust`⁠ `transformers`⁠
Dependants	`l4t-diffusion`⁠
Dockerfile	`Dockerfile`⁠
Images	`dustynv/stable-diffusion:r35.2.1`⁠ `(2023-12-14, 6.1GB)` `dustynv/stable-diffusion:r35.3.1`⁠ `(2023-12-12, 6.1GB)` `dustynv/stable-diffusion:r35.4.1`⁠ `(2023-12-15, 6.1GB)`
Notes	disabled on JetPack 4

CONTAINER IMAGES⁠

Repository/Tag	Date	Arch	Size
`dustynv/stable-diffusion:r35.2.1`⁠	`2023-12-14`	`arm64`	`6.1GB`
`dustynv/stable-diffusion:r35.3.1`⁠	`2023-12-12`	`arm64`	`6.1GB`
`dustynv/stable-diffusion:r35.4.1`⁠	`2023-12-15`	`arm64`	`6.1GB`

_{Container images are compatible with other minor versions of JetPack/L4T:}
_{• L4T R32.7 containers can run on other versions of L4T R32.7 (JetPack 4.6+)}
_{• L4T R35.x containers can run on other versions of L4T R35.x (JetPack 5.1+)}

RUN CONTAINER⁠

To start the container, you can use jetson-containers run⁠ and autotag⁠, or manually put together a docker run⁠ command:

# automatically pull or build a compatible container image
jetson-containers run $(autotag stable-diffusion)

# or explicitly specify one of the container images above
jetson-containers run dustynv/stable-diffusion:r35.4.1

# or if using 'docker run' (specify image and mounts/ect)
sudo docker run --runtime nvidia -it --rm --network=host dustynv/stable-diffusion:r35.4.1

^{jetson-containers run⁠ forwards arguments to docker run⁠ with some defaults added (like --runtime nvidia, mounts a /data cache, and detects devices)}
^{autotag⁠ finds a container image that's compatible with your version of JetPack/L4T - either locally, pulled from a registry, or by building it.}

To mount your own directories into the container, use the -v⁠ or --volume⁠ flags:

jetson-containers run -v /path/on/host:/path/in/container $(autotag stable-diffusion)

To launch the container running a command, as opposed to an interactive shell:

jetson-containers run $(autotag stable-diffusion) my_app --abc xyz

You can pass any options to it that you would to docker run⁠, and it'll print out the full command that it constructs before executing it.

BUILD CONTAINER⁠

⁠

If you use ⁠autotag⁠ as shown above, it'll ask to build the container for you if needed. To manually build it, first do the system setup⁠, then run:

jetson-containers build stable-diffusion

The dependencies from above will be built into the container, and it'll be tested during. Run it with --help⁠ for build options.

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sha256:30ca8b407…

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6.1 GB

Last updated

almost 3 years ago

docker pull dustynv/stable-diffusion:r35.4.1