floyo logobeta logo
Powered by
ThinkDiffusion
floyo logobeta logo
Powered by
ThinkDiffusion

ComfyUI WD 1.4 Tagger

899

Last updated
2025-05-04

ComfyUI WD 1.4 Tagger is an extension designed for ComfyUI that enables users to extract booru tags from images efficiently. It leverages advanced models for image interrogation, making it a valuable tool for users needing to categorize and label visual content.

  • Supports multiple tagging models, allowing users to select the best fit for their needs.
  • Enables quick interrogation of images directly from various nodes in the ComfyUI workflow.
  • Offers customizable thresholds for tag validity, enhancing the precision of the tagging process.

Context

This tool serves as a specialized extension within ComfyUI, focusing on the interrogation of images to retrieve booru tags. Its primary goal is to streamline the process of tagging images, which is particularly useful for artists and developers working with large datasets.

Key Features & Benefits

The extension provides the ability to utilize multiple models for image interrogation, including popular options like MOAT and ConvNextV2. Users can adjust parameters such as tag and character thresholds, allowing for tailored results based on specific project requirements.

Advanced Functionalities

In addition to basic tagging, the tool allows for batch processing of images, making it efficient for users dealing with multiple files simultaneously. The right-click functionality on image nodes to initiate tagging further enhances usability, ensuring that users can quickly access the tool without navigating away from their workflow.

Practical Benefits

By integrating this tagging extension into ComfyUI, users can significantly enhance their workflow efficiency, achieving faster and more accurate tagging of images. This leads to improved organization and categorization of visual assets, ultimately saving time and effort in content management.

Credits/Acknowledgments

The extension is based on contributions from various developers, including original models by SmilingWolf and adaptations from other repositories. It is available under an open-source license, promoting community collaboration and further development.