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CyberHarem/van_gogh_fgo

Dataset of van_gogh/ヴァン・ゴッホ/梵高 (Fate/Grand Order) This is the dataset of van_gogh/ヴァン・ゴッホ/梵高 (Fate/Grand Order), containing 500 images and their tags. The core tags of this character are braid, side_braid, blue_eyes, crown_braid, brown_hair, hat, long_hair, orange_hair, 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… See the full description on the dataset page: https://huggingface.co/datasets/CyberHarem/van_gogh_fgo.

sourceHugging Facemitupdated 3y agoView on Hugging Face
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Dataset Card

Dataset of van_gogh/ヴァン・ゴッホ/梵高 (Fate/Grand Order)

This is the dataset of van_gogh/ヴァン・ゴッホ/梵高 (Fate/Grand Order), containing 500 images and their tags.

The core tags of this character are braid, side_braid, blue_eyes, crown_braid, brown_hair, hat, long_hair, orange_hair, 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

NameImagesSizeDownloadTypeDescription
raw500923.98 MiBDownloadWaifuc-RawRaw data with meta information (min edge aligned to 1400 if larger).
1200500771.81 MiBDownloadIMG+TXTdataset with the shorter side not exceeding 1200 pixels.
stage3-p480-120012061.51 GiBDownloadIMG+TXT3-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

python
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/van_gogh_fgo',
    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

#SamplesImg-1Img-2Img-3Img-4Img-5Tags
08[image][image][image][image][image]1girl, blueoveralls, puffysleeves, solo, sunflower, blush, lookingatviewer, smile, stripedheadwear, upperbody, blacksleeves, openmouth, holdingflower, stripedclothes, belt, buckle, navel
113[image][image][image][image][image]1girl, lookingatviewer, puffysleeves, smallbreasts, smile, solo, sunflower, blueoveralls, belt, openmouth, holding, navel, blush, yellowheadwear, strawhat
210[image][image][image][image][image]1girl, belt, blacksleeves, blueoveralls, blush, lookingatviewer, navelcutout, solo, stripedclothes, stripedheadwear, orangeheadwear, buckle, puffyshortsleeves, openmouth, simplebackground, sweatdrop, upperbody, whitebackground, zipperpulltab, flatchest, fangs, smallbreasts
310[image][image][image][image][image]1girl, blueskin, smile, solo, blackdress, lookingatviewer, see-throughsleeves, bareshoulders, puffysleeves, blackheadwear, long_sleeves, gloves
48[image][image][image][image][image]1girl, bareshoulders, lookingatviewer, smallbreasts, solo, smile, highlegswimsuit, blush, casualone-pieceswimsuit, navelcutout, open_mouth, wet, water

Table Version

#SamplesImg-1Img-2Img-3Img-4Img-51girlblue_overallspuffy_sleevessolosunflowerblushlooking_at_viewersmilestriped_headwearupper_bodyblack_sleevesopen_mouthholding_flowerstriped_clothesbeltbucklenavelsmall_breastsholdingyellow_headwearstraw_hatnavel_cutoutorange_headwearpuffy_short_sleevessimple_backgroundsweatdropwhite_backgroundzipper_pull_tabflat_chestfangsblue_skinblack_dresssee-through_sleevesbare_shouldersblack_headwearlong_sleevesgloveshighleg_swimsuitcasual_one-piece_swimsuitwetwater
08[image][image][image][image][image]XXXXXXXXXXXXXXXXX
113[image][image][image][image][image]XXXXXXXXXXXXXXX
210[image][image][image][image][image]XXXXXXXXXXXXXXXXXXXXXX
310[image][image][image][image][image]XXXXXXXXXXXX
48[image][image][image][image][image]XXXXXXXXXXXXX