Cross-platform desktop application for quickly adding and editing image tags and captions, aimed towards creators of image datasets for generative AI models like Stable Diffusion.
- Keyboard-friendly interface for fast tagging
- Tag autocomplete based on your own most-used tags
- Integrated Stable Diffusion token counter
- Automatic caption and tag generation with models including CogVLM, LLaVA, WD Tagger, and many more
- Batch tag operations for renaming, deleting, and sorting tags
- Advanced image list filtering
The easiest way to use the application is to download the latest release from the releases page. Choose the appropriate file for your operating system, extract it wherever you want, and run the executable file inside. You may have to install 7-Zip to extract the files if you don't have it on your system.
- macOS users: There is no macOS release because it requires a device running the OS, and I do not have one. You can still install and run the program manually (see below).
- Linux users: You may need to install
libxcb-cursor0. (See this Stack Overflow answer.) You may also have to installpython3.11-devorpython3.10-dev(depending on your Python version) if you get an error while trying to use a CogVLM2 model. (See this issue.)
Alternatively, you can install manually by cloning this repository and
installing the dependencies in requirements.txt.
Run taggui/run_gui.py to start the program.
Python 3.11 is recommended, but Python 3.10 should also work.
Load the directory containing your images by clicking the Load Directory
button in the center of the window (or File -> Load Directory).
Tags are loaded from .txt files in the directory with the same names as the
images.
Any changes you make to the tags are also automatically saved to these .txt
files.
In addition to manual tagging, you can automatically generate captions or tags for your images inside TagGUI. GPU generation requires a compatible NVIDIA GPU, and CPU generation is also supported.
To use the feature, select the images you want to caption in the image list,
then select the captioning model you want to use in the Auto-Captioner pane.
If you have a local directory containing previously downloaded models, you can
set it in File -> Settings to include the models in the model list.
Click the Start Auto-Captioning button to start captioning.
You can select multiple images to batch generate captions for all of them.
It can take up to several minutes to download and load a model when you first
use it, but subsequent generations will be much faster.
Prompt: Instructions given to the captioning model.
Prompt formats are handled automatically based on the selected model.
You can use the following template variables to dynamically insert information
about each image into the prompt:
{tags}: The tags of the image, separated by commas.{name}: The file name of the image without the extension.{directory}or{folder}: The name of the directory containing the image.
An example prompt using a template variable could be
Describe the image using the following tags as context: {tags}.
With this prompt, {tags} would be replaced with the existing tags of each
image before the prompt is sent to the model.
Start caption with: Generated captions will start with this text.
Remove tag separators in caption: If checked, tag separators (commas by
default) will be removed from the generated captions.
Discourage from caption: Words or phrases that should not be present in the
generated captions.
You can separate multiple words or phrases with commas (,).
For example, you can put appears,seems,possibly to prevent the model from
using an uncertain tone in the captions.
The words may still be generated due to limitations related to tokenization.
Include in caption: Words or phrases that should be present somewhere in the
generated captions.
You can separate multiple words or phrases with commas (,).
You can also allow the captioning model to choose from a group of words or
phrases by separating them with |.
For example, if you put cat,orange|white|black, the model will attempt to
generate captions that contain the word cat and either orange, white,
or black.
It is not guaranteed that all of your specifications will be met.
Tags to exclude (WD Tagger models): Tags that should not be generated,
separated by commas.
Many of the other generation parameters are described in the Hugging Face documentation.
The basic functionality of filtering for images that contain a certain tag is
available by clicking on the tag in the All Tags pane.
In addition to this, you can construct more complex filters in
the Filter Images box at the top of the Images pane.
Click here to see the full documentation for the filter syntax.
These are the prefixes you can use to specify the filter criteria you want to apply:
tag:: Images that have the filter term as a tagtag:catwill match images with the tagcat.
caption: Images that contain the filter term in the caption- The caption is the list of tags as a single string, as it appears in the
.txtfile. caption:catwill match images that havecatanywhere in the caption. For example, images with the tagorange cator the tagcatastrophe.
- The caption is the list of tags as a single string, as it appears in the
name: Images that contain the filter term in the file namename:catwill match images such ascat-1.jpgorlarge_cat.png.
path: Images that contain the filter term in the full file pathpath:catwill match images such asC:\Users\cats\dog.jpgor/home/dogs/cat.jpg.
- You can also use a filter term with no prefix to filter for images that
contain the term in either the caption or the file path.
catwill match images containingcatin the caption or file path.
The following are prefixes for numeric filters. The operators = (== also
works), !=, <, >, <=, and >= are used to specify the type of
comparison.
tags: Images that have the specified number of tagstags:=13will match images that have exactly 13 tags.tags:!=7will match images that do not have exactly 7 tags (images with less than 7 tags or more than 7 tags).
chars: Images that have the specified number of characters in the captionchars:<100will match images that have less than 100 characters in the caption.chars:>=30will match images that have 30 or more characters in the caption.
tokens: Images that have the specified number of tokens in the captiontokens:>75will match images that have more than 75 tokens in the caption.tokens:<=50will match images that have 50 or fewer tokens in the caption.
If the filter term contains spaces, you must enclose it in quotes (either
single or double quotes).
For example, to find images with the tag orange cat, you must
use tag:"orange cat" or tag:'orange cat'.
If you have both spaces and quotes in the filter term, you can escape the
quotes with backslashes.
For example, you can use tag:"orange \"cat\"" for the tag orange "cat".
An alternative is to use different types of quotes for the outer and inner
quotes, like so: tag:'orange "cat"'.
You can use the * character as a wildcard to match any number of any
characters, and the ? character to match any single character.
For example, tag:*cat will match images with tags like orange cat,
large cat, and cat.
Logical operators can be used to combine multiple filters:
NOT: Images that do not match the filterNOT tag:catwill match images that do not have the tagcat.
AND: Images that match both filters before and after the operatortag:cat AND tag:orangewill match images that have both the tagcatand the tagorange.
OR: Images that match either filter before or after the operatortag:cat OR tag:dogwill match images that have either the tagcator the tagdog, or both.
The lowercase versions of these operators will also work: not, and,
and or.
The operator precedence is NOT > AND > OR, so by default, NOT will be
evaluated first, then AND, then OR.
You can use parentheses to change this order.
For example, in tag:cat AND (tag:orange OR tag:white), the OR will be
evaluated first, matching images that have the tag cat and either the
tag orange or the tag white.
You can nest parentheses and operators to create arbitrarily complex filters.
- ⭐ Previous / next image:
CtrlUp/Down(justUp/Downalso works in some cases) - Jump to the first untagged image:
CtrlJ - Focus the
Filter Imagesbox:AltF - Focus the
Add Tagbox:AltA - Focus the
Image Tagslist:AltI - Focus the
Search Tagsbox:AltS - Focus the
Start Auto-Captioningbutton:AltC
- First / last image:
Home/End - Select multiple images: Hold
CtrlorShiftand click the images - Select all images:
CtrlA - Invert selection:
CtrlI - Right-clicking on an image will bring up the context menu, which includes actions such as copying and pasting tags and moving or copying selected images to another directory.
- Add a tag: Type the tag into the
Add Tagbox and pressEnter - ⭐ Add the first tag suggested by autocomplete:
CtrlEnter - Add a tag to multiple images: Select the images in the image list add the tag
- Delete a tag: Select the tag and press
Delete - Rename a tag: Double-click the tag, or select the tag and press
F2 - Reorder tags: Drag and drop the tags
- Select multiple tags: Hold
CtrlorShiftand click the tags
- Show all images containing a tag: Select the tag (When
Tag click actionis set toFilter images for tag) - Add a tag to selected images: Click the tag (When
Tag click actionis set toAdd tag to selected images) - Delete all instances of a tag: Select the tag and press
Delete - Rename all instances of a tag: Double-click the tag, or select the tag and
press
F2
The Edit menu contains additional features for batch tag operations, such as
Find and Replace (Ctrl R) and Batch Reorder Tags (Ctrl B).