An infinite number of monkeys randomly throwing paint at a canvas
Using randomly generated token id's this app can generate a huge diverse set of images very rapidly. I've created 1000 images in 34.6 seconds on a 4090. That is not a typo. 4 step LCM, 512x512, batchsize=8, using torch.compile. With 1024x1024 batchsize=2 sdxl you can get great images in under .46 seconds per image
Tongue in cheek: In ancient granite Wikipedia carvings dated near the end of August 2022 Stable Diffusion was inscribed and human artists were no more. They were replaced by AI Artists typing words, getting the spelling right 2 out of 3 times and usually finding the "Generate" button. Now, eons later, we are at a point where AI Artists will soon be replaced. The dawn of ArtSpew is at hand. Harnessing the magic of a random number generator you can excrete 1000 random images very quickly.
TODO: Add the 150 images per second speed demo'd by maxperf to artspew.
# Get the code
git clone https://github.com/aifartist/ArtSpew
cd ArtSpew
# Create a virtual environment in the current directory
python3 -m venv ./venv
# Activate the virtual environment
source venv/bin/activate
# Install the required dependencies
pip3 install -r requirements.txt
Try the following for a first run:
python3 sdxl.py -l -t -g 0 -c 8 -b 2 -n 5 -s 12
l: use lcm
t: use tiny vae
g: CFG/Guidance. Use 0 if using -l for LCM
c: count of batches
b: batch size
n: number of random tokens to use
s: Number of inference steps
Use: python3 sdxl.py -h to get the full usage.
Also, try sd15.py which is supper fast with LCM. 16 to 29 images per second on a 4090 depending on the number of steps and other options.
The new images with appear in the directory named spew/. Even at nSteps=4 there'll be some good ones. The idea is to see the space of possibilities and generate ideas. Set nSteps to 12 or 16 and you'll get better images. Then perhaps set "-c" to 100 and look at the diversity of images you get.
Then try to pick a subject like "Mutant kitty monsters with glowing eyes, H.R.Giger style" and gen random versions of it. THe command below is doing 10 inference steps and appending 5 random tokens to the prompt.
python3 sdxl.py -p "Mutant kitty monsters with glowing eyes, H.R.Giger style" -c 32 -b 2 -s 10 -n 5 -l -t -g 0
