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autotagger

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1.0.0

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Danbooru Autotagger

A tag prediction system for anime-style images.

Demo

Try it at https://autotagger.donmai.us.

Or go to https://danbooru.donmai.us/ai_tags to browse predicted tags on all posts on Danbooru. Here are some examples of different tags:

https://danbooru.donmai.us/ai_tags?search[tag_name]=comic&search[order]=score_desc
https://danbooru.donmai.us/ai_tags?search[tag_name]=hatsune_miku&search[order]=score_desc
https://danbooru.donmai.us/ai_tags?search[tag_name]=cat&search[order]=score_desc

Quickstart

# Get tags for a single image
cat image.jpg | docker run --rm -i ghcr.io/danbooru/autotagger autotag -

# Run the web server. Open http://localhost:5000.
docker run --rm -p 5000:5000 ghcr.io/danbooru/autotagger

# Get tags from the web server.
curl http://localhost:5000/evaluate -X POST -F file=@hatsune_miku.jpg -F format=json

Web

Start the app server:

# With Dockerdocker run --rm -p 5000:5000 ghcr.io/danbooru/autotagger# Without Dockerpython -m poetry run gunicorn

Then open http://localhost:5000 to use the webapp. Here you can upload images and view the list of predicted tags.

API

Start the app server as above, then do:

curl http://localhost:5000/evaluate -X POST -F file=@hatsune_miku.jpg -F format=json

The output will look like this:

[
  {"filename": "hatsune_miku.jpg","tags": {      "1girl": 0.9995526671409607,      "hatsune_miku": 0.9995216131210327,      "vocaloid": 0.9981155395507812,      "solo": 0.9938727617263794,      "thighhighs": 0.970325767993927,      "long_hair": 0.9630335569381714,      "twintails": 0.9352861046791077,      "very_long_hair": 0.8532902002334595,      "necktie": 0.8532789945602417,      "aqua_hair": 0.8266996145248413,      "detached_sleeves": 0.796751081943512,      "skirt": 0.7879447340965271,      "rating:s": 0.7843148112297058,      "aqua_eyes": 0.6136178374290466,      "zettai_ryouiki": 0.5611224174499512,      "thigh_boots": 0.37453025579452515,      "black_legwear": 0.37255123257637024,      "full_body": 0.3261113464832306,      "simple_background": 0.28789788484573364,      "boots": 0.286143958568573,      "headset": 0.27902844548225403,      "white_background": 0.23441512882709503,      "shirt": 0.21720334887504578,      "looking_at_viewer": 0.2044636756181717,      "pleated_skirt": 0.17705336213111877,      "smile": 0.17575393617153168,      "bare_shoulders": 0.17370294034481049,      "headphones": 0.16347116231918335,      "standing": 0.15511766076087952,      "rating:g": 0.13711321353912354,      "aqua_necktie": 0.11798079311847687,      "black_skirt": 0.11197035759687424,      "blush": 0.10813453793525696}
  }
]

CLI

Generate tags for a single image:

# With Docker:cat image.jpg | docker run --rm ghcr.io/danbooru/autotagger autotag -# Without Docker:./autotag image.jpg

Generate tags for multiple images:

# With Docker:# `-v $PWD:/host` means mount the current directory as /host inside the Docker container.docker run --rm -v $PWD:/host ghcr.io/danbooru/autotagger autotag /host/image1.jpg /host/image2.jpg# Without Docker:./autotag image1.jpg image2.jpg

Generate tags for all images inside the images/ directory:

# With Docker:# Change `images` to whatever your image directory is called.docker run --rm -v $PWD/images:/images ghcr.io/danbooru/autotagger autotag /images# Without Docker:./autotag images/

Generate tags for all files inside a directory matching a pattern:

find images/ -name '*.jpg' | ./autotag -i -

Generate a list of tags in CSV format, suitable for importing into your own Danbooru instance:

./autotag -c -f -N images/ | gzip > tags.csv.gz

Manual Installation

# Install system dependencies
apt-get update
apt-get install git build-essential gfortran libatlas-base-dev libffi-dev libssl-dev libbz2-dev liblzma-dev

# Get code
git clone https://github.com/danbooru/autotagger.git
cd autotagger

# Install Python (skip this if Python 3.9.13 is already installed)
git clone https://github.com/asdf-vm/asdf.git ~/.asdf --branch v0.10.0
echo ". $HOME/.asdf/asdf.sh" >> ~/.bashrc
exec bash
asdf plugin add python
asdf install python 3.9.13
asdf shell python 3.9.13

# Install Python dependencies
pip install poetry==1.1.13
python -m poetry env use 3.9
python -m poetry install --no-dev

# Download latest model
wget https://github.com/danbooru/autotagger/releases/download/2022.06.20-233624-utc/model.pth -O models/model.pth

# Test that it works
./autotag test/hatsune_miku.jpg

Implementation

The current model is stock Resnet-152, pretrained on Imagenet then finetuned on Danbooru for about 10 epochs.

The model is trained on about 5500 tags. This includes character tags with >750 posts, copyright tags with >2000 posts, and general tags with >2500 posts, but not artist or meta tags. Ratings are also included.

The model is available at https://github.com/danbooru/autotagger/releases.