Instructions to use InstantX/SD3-Controlnet-Pose with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use InstantX/SD3-Controlnet-Pose with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("InstantX/SD3-Controlnet-Pose", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
Does this model's control image align with the original ControlNet-Openpose
#3
by citrinegui - opened
Hi,
Can I use the following code to generate pose as the control image input of this model?
from controlnet_aux import OpenposeDetector
processor = OpenposeDetector.from_pretrained('lllyasviel/ControlNet')
control_image = processor(image, hand_and_face=True)
control_image.save("./images/control.png")
Just make sure the output could be optimal.
Thank you!