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brid_nikke / README.md
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Publish character 'brid_nikke' to repository, on 2024-01-24 05:45:46 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 brid/ブリッド/布丽德/브리드 (Nikke: Goddess of Victory)

This is the dataset of brid/ブリッド/布丽德/브리드 (Nikke: Goddess of Victory), containing 184 images and their tags.

The core tags of this character are breasts, blue_eyes, hair_over_one_eye, bangs, large_breasts, grey_hair, earrings, hat, blue_headwear, mole, long_hair, mole_on_breast, short_hair, garrison_cap, dangle_earrings, sidelocks, 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 184 306.66 MiB Download Waifuc-Raw Raw data with meta information (min edge aligned to 1400 if larger).
800 184 147.38 MiB Download IMG+TXT dataset with the shorter side not exceeding 800 pixels.
stage3-p480-800 442 315.42 MiB Download IMG+TXT 3-stage cropped dataset with the area not less than 480x480 pixels.
1200 184 259.58 MiB Download IMG+TXT dataset with the shorter side not exceeding 1200 pixels.
stage3-p480-1200 442 501.92 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/brid_nikke',
    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 14 1girl, blue_necktie, blue_skirt, high-waist_skirt, sideboob, solo, white_shirt, armpits, bare_shoulders, collared_shirt, looking_at_viewer, striped_necktie, jewelry, arms_up, blush, arms_behind_head, belt_pouch, sleeveless_shirt, simple_background, white_background, closed_mouth, huge_breasts, gloves, sweat, upper_body
1 15 1girl, bare_shoulders, blue_skirt, collared_shirt, high-waist_skirt, jewelry, sideboob, solo, white_shirt, blue_necktie, sleeveless_shirt, bridal_gauntlets, holding, long_skirt, striped_necktie, white_background, looking_at_viewer, tablet_pc, collarbone, shoulder_tattoo, pouch, simple_background, sitting, closed_mouth, low_ponytail, parted_lips
2 5 1girl, armpits, blue_necktie, erection, futanari, huge_penis, jewelry, large_penis, looking_at_viewer, smile, solo, testicles, uncensored, white_hair, arms_behind_head, arms_up, belt, veiny_penis, blue_skirt, blush, outdoors, parted_lips, sky, striped_necktie, sweat, thighs, black_thighhighs, collared_shirt, elbow_gloves, no_panties, sideboob, sitting, uniform, white_shirt

Table Version

# Samples Img-1 Img-2 Img-3 Img-4 Img-5 1girl blue_necktie blue_skirt high-waist_skirt sideboob solo white_shirt armpits bare_shoulders collared_shirt looking_at_viewer striped_necktie jewelry arms_up blush arms_behind_head belt_pouch sleeveless_shirt simple_background white_background closed_mouth huge_breasts gloves sweat upper_body bridal_gauntlets holding long_skirt tablet_pc collarbone shoulder_tattoo pouch sitting low_ponytail parted_lips erection futanari huge_penis large_penis smile testicles uncensored white_hair belt veiny_penis outdoors sky thighs black_thighhighs elbow_gloves no_panties uniform
0 14 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
1 15 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 X
2 5 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 X X X X X X X X X