ControlNet

ControlNet is an open-source neural network architecture designed to enhance Stable Diffusion by providing fine-grained control over image generation. It allows users to guide diffusion models using various input conditions such as edges, depth maps, poses, or segmentation masks, enabling more precise and creative AI-generated images.

Features of ControlNet:

• Provides fine control over image generation using conditioning inputs like Canny edges, depth maps, and human poses.
• Compatible with Stable Diffusion and Hugging Face Diffusers pipelines.
• Supports multiple ControlNet models for specific tasks (e.g., Canny, Depth, Scribble, OpenPose, etc.).
• Allows users to combine multiple ControlNet models simultaneously for complex control.
• Integrated with PyTorch for efficient computation and GPU acceleration.
• Open-source and actively maintained by the community with frequent model updates.
• Available via the diffusers library, making it easy to implement in Python projects.
• Pretrained ControlNet models available on Hugging Face for immediate use.

To Check the Version of ControlNet:
$ sudo su
$ sudo apt update
$ cd /opt/controlnet
$ source /opt/controlnet-env/bin/activate
$ pip show diffusers | grep Version
$ python3 -c "from diffusers import ControlNetModel; print(ControlNetModel.__name__)"

Disclaimer: ControlNet is an open-source project developed by the AI research community. It is distributed under open-source licenses (such as Apache 2.0) and is not affiliated with, endorsed by, or sponsored by any single company. ControlNet is provided "as is," without any warranty, express or implied. Users are responsible for complying with all licensing terms and using the software responsibly in accordance with applicable regulations.