Awesome
ComfyUI WD 1.4 Tagger
A ComfyUI extension allowing the interrogation of booru tags from images.
Based on SmilingWolf/wd-v1-4-tags and toriato/stable-diffusion-webui-wd14-tagger
All models created by SmilingWolf
Installation
git clone https://github.com/pythongosssss/ComfyUI-WD14-Tagger
into thecustom_nodes
folder- e.g.
custom_nodes\ComfyUI-WD14-Tagger
- e.g.
- Open a Command Prompt/Terminal/etc
- Change to the
custom_nodes\ComfyUI-WD14-Tagger
folder you just created- e.g.
cd C:\ComfyUI_windows_portable\ComfyUI\custom_nodes\ComfyUI-WD14-Tagger
or wherever you have it installed
- e.g.
- Install python packages
- Windows Standalone installation (embedded python):
../../../python_embeded/python.exe -s -m pip install -r requirements.txt
- Manual/non-Windows installation
pip install -r requirements.txt
- Windows Standalone installation (embedded python):
Usage
Add the node via image
-> WD14Tagger|pysssss
Models are automatically downloaded at runtime if missing.
Supports tagging and outputting multiple batched inputs.
- model: The interrogation model to use. You can try them out here WaifuDiffusion v1.4 Tags. The newest model (as of writing) is
MOAT
and the most popular isConvNextV2
. - threshold: The score for the tag to be considered valid
- character_threshold: The score for the character tag to be considered valid
- exclude_tags A comma separated list of tags that should not be included in the results
Quick interrogation of images is also available on any node that is displaying an image, e.g. a LoadImage
, SaveImage
, PreviewImage
node.
Simply right click on the node (or if displaying multiple images, on the image you want to interrogate) and select WD14 Tagger
from the menu
Settings used for this are in the settings
section of pysssss.json
.
Offline Use
Simplest way is to use it online, interrogate an image, and the model will be downloaded and cached, however if you want to manually download the models:
- Create a
models
folder (in same folder as thewd14tagger.py
) - Use URLs for models from the list in
pysssss.json
- Download
model.onnx
and name it with the model name e.g.wd-v1-4-convnext-tagger-v2.onnx
- Download
selected_tags.csv
and name it with the model name e.g.wd-v1-4-convnext-tagger-v2.csv
Requirements
onnxruntime
(recommended, interrogation is still fast on CPU, included in requirements.txt)
or onnxruntime-gpu
(allows use of GPU, many people have issues with this, if you try I can't provide support for this)
Changelog
- 2023-05-14 - Moved to own repo, add downloading models, support multiple inputs