The ControlNet Union SDXL 1.0 is a cutting-edge model designed to enhance image generation and editing capabilities within the Stable Diffusion framework. With support for various control mechanisms and advanced editing features, it offers unparalleled flexibility for both creative and technical applications.
Key Features of ControlNet Union SDXL 1.0
Multi-Control Support
Integrates Canny, Depth, Openpose, Scribble, Lineart, and more for detailed image customization.
Advanced Editing
Includes tile deblurring, variation, super resolution, inpainting, and outpainting.
Efficiency and Flexibility
Optimized for various resolutions and fast performance with different control models.
Community and Development
Ongoing updates and community support to enhance functionality and add new features.
Download and Install ControlNet Union SDXL 1.0
Step 1: Install the Package
Run the following command to install the necessary packages:
pip install diffusers transformersStep 2: Download the Model
Use the following code to download the model files from Hugging Face:
from huggingface_hub import snapshot_download
from pathlib import Path
model_path = Path.home().joinpath('controlnet_models', 'union_sdxl')
model_path.mkdir(parents=True, exist_ok=True)
snapshot_download(repo_id="xinsir/controlnet-union-sdxl-1.0", local_dir=model_path)
How to Use ControlNet Union SDXL 1.0?
Using the Model
Initialize the model and tokenizer with:
from diffusers import StableDiffusionPipeline
import torch
model_id = "xinsir/controlnet-union-sdxl-1.0"
pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16).to("cuda")
prompt = "A beautiful landscape painting"
image = pipe(prompt).images[0]
image.save("generated_image.png")
Example prompt:
"Generate an image of a futuristic cityscape with vibrant lights and towering skyscrapers."
Advanced Features
Use advanced features like inpainting with the following code:
from diffusers import StableDiffusionInpaintPipeline
inpaint_pipe = StableDiffusionInpaintPipeline.from_pretrained(model_id, torch_dtype=torch.float16).to("cuda")
mask_image = Image.open("mask.png")
inpaint_image = inpaint_pipe(prompt=prompt, mask_image=mask_image).images[0]
inpaint_image.save("inpainted_image.png")
Additional Tips for ControlNet Union SDXL 1.0
Optimizing Performance
- Use a control weight setting between 0.75 to 1.0 for optimal effects.
- Ensure your hardware meets the requirements for running large models efficiently.
Function Calling
Example function call implementation:
from transformers import AutoTokenizer, AutoModel
tokenizer = AutoTokenizer.from_pretrained("xinsir/controlnet-union-sdxl-1.0")
model = AutoModel.from_pretrained("xinsir/controlnet-union-sdxl-1.0")
inputs = tokenizer("Describe the current weather in Paris.", return_tensors="pt")
outputs = model(**inputs)
ControlNet Union SDXL 1.0 is designed to be a robust and flexible model suitable for a wide range of applications. Whether you need advanced control mechanisms, efficient image editing, or community support, this model provides a comprehensive solution. By following the installation and usage guidelines, you can harness the full potential of ControlNet Union SDXL 1.0 for your projects.
