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saileach_arknights / README.md
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Publish character 'saileach (Arknights)' to repository, on 2024-01-10 16:32:20 UTC
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metadata
license: mit
task_categories:
  - text-to-image
tags:
  - art
  - not-for-all-audiences
size_categories:
  - n<1K

Dataset of saileach/サイラッハ/琴柳 (Arknights)

This is the dataset of saileach/サイラッハ/琴柳 (Arknights), containing 320 images and their tags.

The core tags of this character are long_hair, blonde_hair, bangs, horns, pointy_ears, blue_eyes, breasts, very_long_hair, hairband, large_breasts, blue_hairband, braid, hair_between_eyes, dragon_horns, twin_braids, 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 320 713.34 MiB Download Waifuc-Raw Raw data with meta information (min edge aligned to 1400 if larger).
800 320 310.74 MiB Download IMG+TXT dataset with the shorter side not exceeding 800 pixels.
stage3-p480-800 818 683.07 MiB Download IMG+TXT 3-stage cropped dataset with the area not less than 480x480 pixels.
1200 320 577.61 MiB Download IMG+TXT dataset with the shorter side not exceeding 1200 pixels.
stage3-p480-1200 818 1.06 GiB 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/saileach_arknights',
    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, bare_shoulders, black_skirt, blue_necktie, cowboy_shot, elbow_gloves, fingerless_gloves, looking_at_viewer, miniskirt, solo, standing, white_shirt, white_thighhighs, zettai_ryouiki, flag, holding, black_gloves, smile, thighs, belt, grey_thighhighs
1 7 1girl, blue_necktie, elbow_gloves, holding_sword, looking_at_viewer, smile, solo, standing, white_shirt, bare_shoulders, black_skirt, cowboy_shot, arm_strap, miniskirt, thighs, black_gloves, flag, white_thighhighs, zettai_ryouiki
2 11 1girl, solo, upper_body, looking_at_viewer, white_background, bare_shoulders, blue_necktie, simple_background, smile, white_shirt, closed_mouth, blush, cleavage
3 37 1girl, solo, white_dress, bare_shoulders, official_alternate_costume, off-shoulder_dress, looking_at_viewer, white_gloves, flower, smile, choker, holding_umbrella, standing
4 7 1girl, bare_shoulders, cleavage, looking_at_viewer, solo, thigh_strap, sitting, thighs, blush, flower, hair_ornament, official_alternate_costume, smile, swimsuit, blue_sky, closed_mouth, feet_out_of_frame, nail_polish, navel, white_dress

Table Version

# Samples Img-1 Img-2 Img-3 Img-4 Img-5 1girl bare_shoulders black_skirt blue_necktie cowboy_shot elbow_gloves fingerless_gloves looking_at_viewer miniskirt solo standing white_shirt white_thighhighs zettai_ryouiki flag holding black_gloves smile thighs belt grey_thighhighs holding_sword arm_strap upper_body white_background simple_background closed_mouth blush cleavage white_dress official_alternate_costume off-shoulder_dress white_gloves flower choker holding_umbrella thigh_strap sitting hair_ornament swimsuit blue_sky feet_out_of_frame nail_polish navel
0 5 X X X X X X X X X X X X X X X X X X X X X
1 7 X X X X X X X X X X X X X X X X X X X
2 11 X X X X X X X X X X X X X
3 37 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