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art
Not-For-All-Audiences
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owari_azurlane / README.md
narugo's picture
Publish character 'owari (Azur Lane)' to repository, on 2024-01-13 03:18:23 UTC
8435434 verified
metadata
license: mit
task_categories:
  - text-to-image
tags:
  - art
  - not-for-all-audiences
size_categories:
  - n<1K

Dataset of owari/尾張/尾张 (Azur Lane)

This is the dataset of owari/尾張/尾张 (Azur Lane), containing 297 images and their tags.

The core tags of this character are breasts, long_hair, braid, hair_over_one_eye, horns, large_breasts, yellow_eyes, blonde_hair, mole, twin_braids, dark_skin, bangs, earrings, hair_ornament, very_long_hair, dark-skinned_female, mole_under_mouth, hairclip, huge_breasts, which are pruned in this dataset.

Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by DeepGHS Team(huggingface organization).

List of Packages

Name Images Size Download Type Description
raw 297 568.49 MiB Download Waifuc-Raw Raw data with meta information (min edge aligned to 1400 if larger).
800 297 274.64 MiB Download IMG+TXT dataset with the shorter side not exceeding 800 pixels.
stage3-p480-800 795 624.78 MiB Download IMG+TXT 3-stage cropped dataset with the area not less than 480x480 pixels.
1200 297 478.26 MiB Download IMG+TXT dataset with the shorter side not exceeding 1200 pixels.
stage3-p480-1200 795 952.89 MiB Download IMG+TXT 3-stage cropped dataset with the area not less than 480x480 pixels.

Load Raw Dataset with Waifuc

We provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code

import os
import zipfile

from huggingface_hub import hf_hub_download
from waifuc.source import LocalSource

# download raw archive file
zip_file = hf_hub_download(
    repo_id='CyberHarem/owari_azurlane',
    repo_type='dataset',
    filename='dataset-raw.zip',
)

# extract files to your directory
dataset_dir = 'dataset_dir'
os.makedirs(dataset_dir, exist_ok=True)
with zipfile.ZipFile(zip_file, 'r') as zf:
    zf.extractall(dataset_dir)

# load the dataset with waifuc
source = LocalSource(dataset_dir)
for item in source:
    print(item.image, item.meta['filename'], item.meta['tags'])

List of Clusters

List of tag clustering result, maybe some outfits can be mined here.

Raw Text Version

# Samples Img-1 Img-2 Img-3 Img-4 Img-5 Tags
0 5 1girl, black_horns, blush, cleavage, collarbone, grin, jewelry, looking_at_viewer, solo, thighs, bare_shoulders, indoors, nurse_cap, white_dress, black_choker, demon_horns, sitting, teeth, armband, bed, cross, panties
1 11 1girl, grin, looking_at_viewer, solo, black_gloves, jewelry, cleavage, blush, choker, upper_body, fishnets, virtual_youtuber, white_background, white_hair, bare_shoulders, simple_background
2 26 1girl, looking_at_viewer, solo, cleavage, bare_shoulders, black_skirt, grin, pleated_skirt, jewelry, black_gloves, white_background, fishnet_thighhighs, thighs, blush, simple_background, choker, black_thighhighs, elbow_gloves, wide_sleeves
3 8 1girl, cleavage, looking_at_viewer, solo, thighs, water, white_one-piece_swimsuit, blush, bracelet, grin, necklace, sitting, white_hair
4 7 1boy, 1girl, hetero, jewelry, nipples, penis, solo_focus, blush, mosaic_censoring, smile, navel, spread_legs, sweat, looking_at_viewer, nude, open_mouth, pussy, sex, vaginal, collarbone, missionary, on_back, pillow, teeth, white_hair

Table Version

# Samples Img-1 Img-2 Img-3 Img-4 Img-5 1girl black_horns blush cleavage collarbone grin jewelry looking_at_viewer solo thighs bare_shoulders indoors nurse_cap white_dress black_choker demon_horns sitting teeth armband bed cross panties black_gloves choker upper_body fishnets virtual_youtuber white_background white_hair simple_background black_skirt pleated_skirt fishnet_thighhighs black_thighhighs elbow_gloves wide_sleeves water white_one-piece_swimsuit bracelet necklace 1boy hetero nipples penis solo_focus mosaic_censoring smile navel spread_legs sweat nude open_mouth pussy sex vaginal missionary on_back pillow
0 5 X X X X X X X X X X X X X X X X X X X X X X
1 11 X X X X X X X X X X X X X X X X
2 26 X X X X X X X X X X X X X X X X X X X
3 8 X X X X X X X X X X X X X
4 7 X X X X X X X X X X X X X X X X X X X X X X X X X