evazion
184 lines
5.1 KiB
Markdown
184 lines
5.1 KiB
Markdown
# Danbooru Autotagger
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A tag prediction system for anime-style images.
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# Demo
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Try it at https://autotagger.donmai.us.
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Or go to https://danbooru.donmai.us/ai_tags to browse predicted tags on all posts on
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Danbooru. Here are some examples of different tags:
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* https://danbooru.donmai.us/ai_tags?search[tag_name]=comic&search[order]=score_desc
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* https://danbooru.donmai.us/ai_tags?search[tag_name]=hatsune_miku&search[order]=score_desc
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* https://danbooru.donmai.us/ai_tags?search[tag_name]=cat&search[order]=score_desc
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See below for how to run your own instance.
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# Quickstart
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## Web
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Start the app server:
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```bash
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# With Docker
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docker run --rm -p 5000:5000 ghcr.io/danbooru/autotagger
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# Without Docker
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python -m poetry run gunicorn
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```
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Then open http://localhost:5000 to use the webapp. Here you can upload images and
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view the list of predicted tags.
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## API
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Start the app server as above, then do:
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```bash
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curl http://localhost:5000/evaluate -X POST -F file=@hatsune_miku.jpg -F format=json
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```
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The output will look like this:
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```json
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[
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{
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"filename": "hatsune_miku.jpg",
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"tags": {
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"1girl": 0.9995526671409607,
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"hatsune_miku": 0.9995216131210327,
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"vocaloid": 0.9981155395507812,
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"solo": 0.9938727617263794,
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"thighhighs": 0.970325767993927,
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"long_hair": 0.9630335569381714,
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"twintails": 0.9352861046791077,
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"very_long_hair": 0.8532902002334595,
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"necktie": 0.8532789945602417,
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"aqua_hair": 0.8266996145248413,
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"detached_sleeves": 0.796751081943512,
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"skirt": 0.7879447340965271,
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"rating:s": 0.7843148112297058,
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"aqua_eyes": 0.6136178374290466,
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"zettai_ryouiki": 0.5611224174499512,
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"thigh_boots": 0.37453025579452515,
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"black_legwear": 0.37255123257637024,
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"full_body": 0.3261113464832306,
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"simple_background": 0.28789788484573364,
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"boots": 0.286143958568573,
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"headset": 0.27902844548225403,
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"white_background": 0.23441512882709503,
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"shirt": 0.21720334887504578,
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"looking_at_viewer": 0.2044636756181717,
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"pleated_skirt": 0.17705336213111877,
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"smile": 0.17575393617153168,
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"bare_shoulders": 0.17370294034481049,
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"headphones": 0.16347116231918335,
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"standing": 0.15511766076087952,
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"rating:g": 0.13711321353912354,
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"aqua_necktie": 0.11798079311847687,
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"black_skirt": 0.11197035759687424,
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"blush": 0.10813453793525696
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}
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}
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]
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```
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## CLI
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Generate tags for a single image:
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```bash
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# With Docker:
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cat image.jpg | docker run --rm ghcr.io/danbooru/autotagger autotag -
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# Without Docker:
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./autotag image.jpg
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```
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Generate tags for multiple images:
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```bash
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# With Docker:
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# `-v $PWD:/host` means mount the current directory as /host inside the Docker container.
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docker run --rm -v $PWD:/host ghcr.io/danbooru/autotagger autotag /host/image1.jpg /host/image2.jpg
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# Without Docker:
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./autotag image1.jpg image2.jpg
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```
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Generate tags for all images inside the `images/` directory:
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```bash
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# With Docker:
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# Change `images` to whatever your image directory is called.
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docker run --rm -v $PWD/images:/images ghcr.io/danbooru/autotagger autotag /images
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# Without Docker:
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./autotag images/
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```
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Generate tags for all files inside a directory matching a pattern:
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```bash
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find images/ -name '*.jpg' | ./autotag -i -
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```
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Generate a list of tags in CSV format, suitable for importing into your own Danbooru instance:
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```bash
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./autotag -c -f -N images/ | gzip > tags.csv.gz
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```
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# Manual Installation
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```
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git clone https://github.com/danbooru/autotagger.git
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# Install system dependencies
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apt-get update
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apt-get install git build-essential gfortran libatlas-base-dev libffi-dev libssl-dev libbz2-dev liblzma-dev
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# Install Python (skip this if Python 3.9.13 is already installed)
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git clone https://github.com/asdf-vm/asdf.git ~/.asdf --branch v0.10.0
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echo ". $HOME/.asdf/asdf.sh" >> ~/.bashrc
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exec bash
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asdf plugin add python
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asdf install python 3.9.13
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asdf shell python 3.9.13
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# Install Python dependencies
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pip install poetry==1.1.13
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python -m poetry env use 3.9
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python -m poetry install --no-dev
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# Download latest model
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wget https://github.com/danbooru/autotagger/releases/download/2022.06.20-233624-utc/model.pth -O models/model.pth
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# Test that it works
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./autotag test/hatsune_miku.jpg
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```
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# Implementation
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The current model is stock Resnet-152, pretrained on Imagenet then finetuned
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on Danbooru for about 10 epochs.
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The model is trained on about 5500 tags. This includes character tags with >750
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posts, copyright tags with >2000 posts, and general tags with >2500 posts, but not artist
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or meta tags. Ratings are also included.
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The model is available at https://github.com/danbooru/autotagger/releases.
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# See also
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* https://github.com/KichangKim/DeepDanbooru
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* https://github.com/SmilingWolf/SW-CV-ModelZoo
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* https://github.com/zyddnys/RegDeepDanbooru
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* https://github.com/rezoo/illustration2vec
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* https://www.gwern.net/Danbooru2021
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* https://console.cloud.google.com/storage/browser/danbooru_public/data?project=danbooru1 (Danbooru data dumps)
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