Detecting and extracting human body parts such as hair, arms, and legs is made efficient with this custom node utilizing the DeepLabV3+ ResNet50 model from Keras-io. Designed for low memory usage, it allows users to seamlessly incorporate human part segmentation into their ComfyUI workflows.
- Utilizes the DeepLabV3+ model for accurate detection of human body parts.
- Converts Keras model to ONNX format for compatibility and ease of use.
- Offers a community-shared model repository for enhanced accessibility.
Context
This tool serves as a custom node within ComfyUI specifically designed for the segmentation of human body parts using the DeepLabV3+ ResNet50 model. Its primary purpose is to facilitate the extraction of various human features, making it easier for users to incorporate detailed human segmentation into their AI art projects.
Key Features & Benefits
The tool leverages the DeepLabV3+ model, known for its precision in identifying human components. By converting the model to ONNX format, it ensures broader compatibility and allows users to benefit from a lightweight solution that does not compromise on performance.
Advanced Functionalities
One of the standout aspects of this node is its ability to accurately detect and segment human parts, a capability that is often lacking in other models that focus primarily on general object detection. This specialization allows for detailed manipulation and artistic expression in AI-generated imagery.
Practical Benefits
Integrating this node into ComfyUI significantly enhances workflow efficiency by providing a straightforward method for segmenting human features. This results in improved control over the final output quality, enabling artists to achieve more refined and realistic representations in their work.
Credits/Acknowledgments
The original DeepLabV3+ model is developed by Keras-io and is available under a CC1.0 license, allowing for unrestricted use. The conversion to ONNX format and the creation of the associated Hugging Face repository were carried out by the tool's author, who has made it accessible to the community for further development and use.