OpenPose

OpenPose represents a breakthrough in computer vision technology, offering an advanced method for real-time multi-person system identification of human body, hand, facial, and foot keypoints. This tool's integration with generative art models like Stable Diffusion marks a significant step forward in the creation of AI-generated artwork, especially in accurately rendering human figures and their poses.

Understanding OpenPose

Developed as an open-source project, OpenPose has the unique capability to detect human poses by identifying and mapping key points on a person's body, hands, face, and feet. These keypoints serve as critical data points that inform how a human figure is positioned in space, which is essential for replicating or generating images of humans in various poses and actions.

Using OpenPose in Stable Diffusion

OpenPose is used in Stable Diffusion alongside ControlNet to achieve precise control over the generation of human poses within images. This integration allows for the replication of specific poses from reference images, enhancing the realism and fidelity of AI-generated artworks featuring human figures.

To use OpenPose with ControlNet in Stable Diffusion, one typically begins by installing the necessary ControlNet models, focusing on those compatible with OpenPose. Once installed, users can edit and pose stick figures using the OpenPose Editor Extension, adjusting poses as desired. The posed stick figure is then sent to ControlNet, where specific settings are adjusted to enable the generation of images that follow the defined pose closely.

ControlNet and OpenPose together provide a comprehensive suite of tools for controlling the appearance and placement of subjects in generated images. By specifying the ControlNet model and selecting OpenPose as the preprocessor, users can leverage the full capabilities of both tools to create images where the human figures accurately mimic the poses defined by the user. This combination is especially powerful for generating dynamic poses, capturing facial expressions, or focusing on specific details like hands and fingers, thereby expanding the creative possibilities within Stable Diffusion. Various OpenPose preprocessors are available, each tailored to different aspects of pose detection, including basic human key points, facial details, hand positions, or a comprehensive detection of all these elements​