ComfyUI-WD-Timm-Tagger

ComfyUI custom node for image tagging using WD v3 models, based on timm.

<img width="1655" height="673" alt="image" src="https://github.com/user-attachments/assets/ded512b3-0272-4e14-bf76-eb2719c0ad2a" />

Installation

1. Clone this repo into ComfyUI/custom_nodes/
2. Install dependencies:

   pip install -r requirements.txt
   

Performance

Tested on 291 images with RTX 5090, wd-eva02-large-tagger-v3 model.

| Node | Time | |---|---| | ComfyUI-WD14-Tagger | 226.99s | | ComfyUI-WD-Timm-Tagger | 9.34s |

Models

Models are automatically downloaded to models/wd_taggers/ on first use.

| Model | Original Repo | | ---------------------------------------------------------- | --------------------------------------------------------------------------------------------------- | | eva02 | SmilingWolf/wd-eva02-large-tagger-v3 | | vit-large | SmilingWolf/wd-vit-large-tagger-v3 | | vit | SmilingWolf/wd-vit-tagger-v3 | | swinv2 | SmilingWolf/wd-swinv2-tagger-v3 | | convnext | SmilingWolf/wd-convnext-tagger-v3 | | pixai-tagger-v0.9 | pixai-labs/pixai-tagger-v0.9 | | OppaiOracle-V1.1 | Grio43/OppaiOracle |

You can also place your own model folders under models/wd_taggers/ and they will appear in the model list automatically.

Inputs

| Name | Type | Description | |------|------|-------------| | image | IMAGE | Input image(s) | | model_name | COMBO | Model to use | | dtype | COMBO | Model precision (auto / bf16 / fp16) | | general_threshold | FLOAT | Confidence threshold for general tags (default: 0.35) | | character_threshold | FLOAT | Confidence threshold for character tags (default: 0.75) | | add_rating | BOOLEAN | Prepend rating tag to output | | exclude_tags | STRING | Comma-separated tags to exclude | | batch_size | INT | Number of images per inference batch |

batch_size only takes effect when multiple images are passed as a batch.

Outputs

• STRING — Formatted tag string per image
• RAW — Dict with ratings, character, general scores per image

Credits

Based on wdv3-timm by neggles.