CyberHarem/shiryuu_chou_un_ikkitousen

---
license: mit
task_categories:
- text-to-image
tags:
- art
- not-for-all-audiences
size_categories:
- n<1K
---

# Dataset of Shiryuu Chou'un/趙雲子龍 (Ikkitousen)

This is the dataset of Shiryuu Chou'un/趙雲子龍 (Ikkitousen), containing 505 images and their tags.

The core tags of this character are `long_hair, grey_hair, breasts, bow, large_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](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)).

## List of Packages

| Name | Images | Size | Download | Type | Description | Images-others | Images-head |
|:-----------------|---------:|:-----------|:----------------------------------------------------------------------------------------------------------------------------|:-----------|:---------------------------------------------------------------------|:----------------|:--------------|
| raw | 505 | 338.88 MiB | [Download](https://huggingface.co/datasets/CyberHarem/shiryuu_chou_un_ikkitousen/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). | -- | -- |
| stage3-p480-1200 | 935 | 553.58 MiB | [Download](https://huggingface.co/datasets/CyberHarem/shiryuu_chou_un_ikkitousen/resolve/main/dataset-stage3-p480-1200.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. | 521 | 414 |

### Load Raw Dataset with Waifuc

We provide raw dataset (including tagged images) for [waifuc](https://deepghs.github.io/waifuc/main/tutorials/installation/index.html) 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/shiryuu_chou_un_ikkitousen',
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 | 16 |  |  |  |  |  | 1girl, closed_eyes, solo, close-up, closed_mouth, parody, portrait, anime_coloring |
| 1 | 11 |  |  |  |  |  | 1girl, closed_eyes, school_uniform, solo, parody, anime_coloring, sweat |
| 2 | 5 |  |  |  |  |  | 1girl, closed_eyes, school_uniform, solo, torn_clothes, underboob, navel, no_bra, medium_breasts |
| 3 | 8 |  |  |  |  |  | 1girl, closed_eyes, school_uniform, solo, torn_clothes, nipple_slip, open_mouth |
| 4 | 6 |  |  |  |  |  | 1girl, closed_eyes, school_uniform, shirt, short_sleeves, solo, upper_body, red_bowtie, indoors, vest |
| 5 | 7 |  |  |  |  |  | 1girl, closed_eyes, katana, school_uniform, short_sleeves, solo, white_gloves, holding_sword, sheath, shirt, bamboo_forest, red_bow, upper_body, vest, fingerless_gloves, white_hair |
| 6 | 6 |  |  |  |  |  | 1girl, closed_eyes, holding_sword, katana, outdoors, pleated_skirt, red_bowtie, school_uniform, shirt, short_sleeves, vest, white_gloves, brown_skirt, sheath, solo, tree, thighs, torn_clothes |
| 7 | 6 |  |  |  |  |  | 1girl, pleated_skirt, school_uniform, solo, white_gloves, closed_eyes, open_mouth, holding_sword, katana, short_sleeves, shirt, very_long_hair |
| 8 | 15 |  |  |  |  |  | 1girl, school_uniform, skirt, solo, closed_eyes, katana, night, fingerless_gloves, sky |
| 9 | 21 |  |  |  |  |  | 1girl, school_uniform, solo, kneehighs, gloves, closed_eyes, shoes, black_socks, pleated_skirt, katana |
| 10 | 5 |  |  |  |  |  | 1girl, alcohol, japanese_clothes, katana, sakazuki, solo, closed_eyes, drinking, holding_cup, sheathed |
| 11 | 7 |  |  |  |  |  | 1girl, nude, solo, nipples, sword, closed_eyes |
| 12 | 6 |  |  |  |  |  | 1girl, closed_eyes, serafuku, solo, very_long_hair, yellow_neckerchief, crop_top, katana, midriff, white_shirt, holding_sword, short_sleeves, from_side, indoors, sheathed |
| 13 | 6 |  |  |  |  |  | 2girls, closed_eyes, closed_mouth, pleated_skirt, red_bowtie, school_uniform, short_sleeves, white_shirt, brown_vest, collared_shirt, fingerless_gloves, hands_on_lap, indoors, sitting, solo_focus, white_gloves, hair_bobbles, sleeping, wing_collar, black_skirt, black_socks, kneehighs |
| 14 | 14 |  |  |  |  |  | closed_eyes, nipples, nude, brown_hair, 2girls, 3girls, medium_breasts, smile, navel, chinese_text |
| 15 | 10 |  |  |  |  |  | 1girl, nipples, solo, closed_eyes, sakazuki, smile, collarbone, completely_nude, onsen, outdoors, closed_mouth, holding_cup, alcohol, partially_submerged, water |
| 16 | 5 |  |  |  |  |  | 1girl, bandages, closed_eyes, futon, on_back, pillow, sleeping, solo, blanket, collarbone, injury |

### Table Version

| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1girl | closed_eyes | solo | close-up | closed_mouth | parody | portrait | anime_coloring | school_uniform | sweat | torn_clothes | underboob | navel | no_bra | medium_breasts | nipple_slip | open_mouth | shirt | short_sleeves | upper_body | red_bowtie | indoors | vest | katana | white_gloves | holding_sword | sheath | bamboo_forest | red_bow | fingerless_gloves | white_hair | outdoors | pleated_skirt | brown_skirt | tree | thighs | very_long_hair | skirt | night | sky | kneehighs | gloves | shoes | black_socks | alcohol | japanese_clothes | sakazuki | drinking | holding_cup | sheathed | nude | nipples | sword | serafuku | yellow_neckerchief | crop_top | midriff | white_shirt | from_side | 2girls | brown_vest | collared_shirt | hands_on_lap | sitting | solo_focus | hair_bobbles | sleeping | wing_collar | black_skirt | brown_hair | 3girls | smile | chinese_text | collarbone | completely_nude | onsen | partially_submerged | water | bandages | futon | on_back | pillow | blanket | injury |
|----:|----------:|:---------------------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------------------------------------------|:--------|:--------------|:-------|:-----------|:---------------|:---------|:-----------|:-----------------|:-----------------|:--------|:---------------|:------------|:--------|:---------|:-----------------|:--------------|:-------------|:--------|:----------------|:-------------|:-------------|:----------|:-------|:---------|:---------------|:----------------|:---------|:----------------|:----------|:--------------------|:-------------|:-----------|:----------------|:--------------|:-------|:---------|:-----------------|:--------|:--------|:------|:------------|:---------|:--------|:--------------|:----------|:-------------------|:-----------|:-----------|:--------------|:-----------|:-------|:----------|:--------|:-----------|:---------------------|:-----------|:----------|:--------------|:------------|:---------|:-------------|:-----------------|:---------------|:----------|:-------------|:---------------|:-----------|:--------------|:--------------|:-------------|:---------|:--------|:---------------|:-------------|:------------------|:--------|:----------------------|:--------|:-----------|:--------|:----------|:---------|:----------|:---------|
| 0 | 16 |  |  |  |  |  | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 1 | 11 |  |  |  |  |  | X | X | X | | | X | | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 2 | 5 |  |  |  |  |  | X | X | X | | | | | | X | | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 3 | 8 |  |  |  |  |  | X | X | X | | | | | | X | | X | | | | | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 4 | 6 |  |  |  |  |  | X | X | X | | | | | | X | | | | | | | | | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 5 | 7 |  |  |  |  |  | X | X | X | | | | | | X | | | | | | | | | X | X | X | | | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 6 | 6 |  |  |  |  |  | X | X | X | | | | | | X | | X | | | | | | | X | X | | X | | X | X | X | X | X | | | | | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 7 | 6 |  |  |  |  |  | X | X | X | | | | | | X | | | | | | | | X | X | X | | | | | X | X | X | | | | | | | X | | | | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 8 | 15 |  |  |  |  |  | X | X | X | | | | | | X | | | | | | | | | | | | | | | X | | | | | | X | | | | | | | | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 9 | 21 |  |  |  |  |  | X | X | X | | | | | | X | | | | | | | | | | | | | | | X | | | | | | | | | X | | | | | | | | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 10 | 5 |  |  |  |  |  | X | X | X | | | | | | | | | | | | | | | | | | | | | X | | | | | | | | | | | | | | | | | | | | | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 11 | 7 |  |  |  |  |  | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 12 | 6 |  |  |  |  |  | X | X | X | | | | | | | | | | | | | | | | X | | | X | | X | | X | | | | | | | | | | | X | | | | | | | | | | | | | X | | | | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | |
| 13 | 6 |  |  |  |  |  | | X | | | X | | | | X | | | | | | | | | | X | | X | X | | | X | | | | | X | | | X | | | | | | | | X | | | X | | | | | | | | | | | | | | X | | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | |
| 14 | 14 |  |  |  |  |  | | X | | | | | | | | | | | X | | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | X | X | | | | | | | | X | | | | | | | | | | X | X | X | X | | | | | | | | | | | |
| 15 | 10 |  |  |  |  |  | X | X | X | | X | | | | | | | | | | | | | | | | | | | | | | | | | | | X | | | | | | | | | | | | | X | | X | | X | | | X | | | | | | | | | | | | | | | | | | | | X | | X | X | X | X | X | | | | | | |
| 16 | 5 |  |  |  |  |  | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | X | | | | | | | X | | | | | X | X | X | X | X | X |

原始信息汇总

数据集概述：Shiryuu Chouun/趙雲子龍 (Ikkitousen)

基本信息

• 数据集名称：Shiryuu Chouun/趙雲子龍 (Ikkitousen)
• 包含内容：505张图像及其标签
• 主要标签：long_hair, grey_hair, breasts, bow, large_breasts
• 许可：MIT
• 任务类别：text-to-image
• 标签：art, not-for-all-audiences
• 大小类别：n<1K

数据来源

• 图像来源：danbooru, pixiv, zerochan等网站
• 自动爬虫系统：由DeepGHS Team提供技术支持

数据集包

原始数据包

• 名称：raw
• 图像数量：505
• 大小：338.88 MiB
• 下载链接：Download
• 类型：Waifuc-Raw
• 描述：包含元信息的原始数据，最小边对齐至1400像素（如果更大）

处理后数据包

• 名称：stage3-p480-1200
• 图像数量：935
• 大小：553.58 MiB
• 下载链接：Download
• 类型：IMG+TXT
• 描述：三阶段裁剪数据集，区域不小于480x480像素

数据集加载

• 加载工具：waifuc
• 加载代码示例： python import os import zipfile from huggingface_hub import hf_hub_download from waifuc.source import LocalSource

下载原始档案文件

zip_file = hf_hub_download( repo_id=CyberHarem/shiryuu_chou_un_ikkitousen, repo_type=dataset, filename=dataset-raw.zip )

提取文件至目录

dataset_dir = dataset_dir os.makedirs(dataset_dir, exist_ok=True) with zipfile.ZipFile(zip_file, r) as zf: zf.extractall(dataset_dir)

使用waifuc加载数据集

source = LocalSource(dataset_dir) for item in source: print(item.image, item.meta[filename], item.meta[tags])

集群列表

• 集群列表：提供标签聚类结果，可能包含可挖掘的服装信息。
• 示例集群：
  • 集群0：16个样本，包含标签如1girl, closed_eyes, solo, close-up等。
  • 集群1：11个样本，包含标签如1girl, closed_eyes, school_uniform, solo等。
  • 集群2：5个样本，包含标签如1girl, closed_eyes, school_uniform, solo, torn_clothes等。
  • 集群3：8个样本，包含标签如1girl, closed_eyes, school_uniform, solo, torn_clothes等。
  • 集群4：6个样本，包含标签如1girl, closed_eyes, school_uniform, shirt, short_sleeves等。
  • 集群5：7个样本，包含标签如1girl, closed_eyes, katana, school_uniform, short_sleeves等。
  • 集群6：6个样本，包含标签如1girl, closed_eyes, holding_sword, katana, outdoors等。
  • 集群7：6个样本，包含标签如1girl, pleated_skirt, school_uniform, solo, white_gloves等。
  • 集群8：15个样本，包含标签如1girl, school_uniform, skirt, solo, closed_eyes等。
  • 集群9：21个样本，包含标签如1girl, school_uniform, solo, kneehighs, gloves等。
  • 集群10：5个样本，包含标签如1girl, alcohol, japanese_clothes, katana, sakazuki等。
  • 集群11：7个样本，包含标签如1girl, nude, solo, nipples, sword等。
  • 集群12：6个样本，包含标签如1girl, closed_eyes, serafuku, solo, very_long_hair等。
  • 集群13：6个样本，包含标签如2girls, closed_eyes, closed_mouth, pleated_skirt等。
  • 集群14：14个样本，包含标签如closed_eyes, nipples, nude, brown_hair等。
  • 集群15：10个样本，包含标签如1girl, nipples, solo, closed_eyes, sakazuki等。
  • 集群16：5个样本，包含标签如1girl, bandages, closed_eyes, futon, on_back等。