from diffusers import ControlNetModel, StableDiffusionControlNetPipeline
controlnet = ControlNetModel.from_pretrained("karoldobiczek/sam-controlnet")
pipe = StableDiffusionControlNetPipeline.from_pretrained(
"runwayml/stable-diffusion-v1-5", controlnet=controlnet
)controlnet-karoldobiczek/sam-controlnet
These are controlnet weights trained on runwayml/stable-diffusion-v1-5 with new type of conditioning.
You can find some example images below.
prompt: Horses graze in front of a large building amid snow.
prompt: some horses grazing in front of a church
prompt: A dog watches an animal on the television.
prompt: A four engine jet transport airplane flying low.
prompt: The snow covered mountain looks over the small city.
prompt: Close up of a traffic light with three lights, the top illuminated red with a person image, the second down not illuminated, and the bottom on hanging down.
prompt: several men on a street corner repairing a street sign
prompt: An arrow on the sign points the way to the Oil City Restaurant drive thru window.
prompt: A tall two story gray house sitting in front of a street sign that readsd Nirvana Dr.
prompt: several women on a street corner repairing a street sign
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Model tree for karoldobiczek/sam-controlnet
Base model
runwayml/stable-diffusion-v1-5