CyberHarem/hood_azurlane

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

# Dataset of hood/フッド/胡德 (Azur Lane)

This is the dataset of hood/フッド/胡德 (Azur Lane), containing 347 images and their tags.

The core tags of this character are `blonde_hair, long_hair, blue_eyes, breasts, hair_over_shoulder, large_breasts, earrings`, 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 |
|:-----------------|---------:|:-----------|:---------------------------------------------------------------------------------------------------------------|:-----------|:---------------------------------------------------------------------|
| raw | 347 | 497.76 MiB | [Download](https://huggingface.co/datasets/CyberHarem/hood_azurlane/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). |
| 800 | 347 | 277.68 MiB | [Download](https://huggingface.co/datasets/CyberHarem/hood_azurlane/resolve/main/dataset-800.zip) | IMG+TXT | dataset with the shorter side not exceeding 800 pixels. |
| stage3-p480-800 | 809 | 557.08 MiB | [Download](https://huggingface.co/datasets/CyberHarem/hood_azurlane/resolve/main/dataset-stage3-p480-800.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
| 1200 | 347 | 433.27 MiB | [Download](https://huggingface.co/datasets/CyberHarem/hood_azurlane/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. |
| stage3-p480-1200 | 809 | 787.97 MiB | [Download](https://huggingface.co/datasets/CyberHarem/hood_azurlane/resolve/main/dataset-stage3-p480-1200.zip) | 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](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/hood_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 | 12 |  |  |  |  |  | 1girl, ascot, capelet, solo, hat, union_jack, looking_at_viewer, jewelry, simple_background, white_background, white_gloves, smile, dress, upper_body |
| 1 | 8 |  |  |  |  |  | 1girl, hat, looking_at_viewer, solo, union_jack, white_gloves, blue_sky, cloud, day, machinery, rigging, turret, ascot, blue_dress, holding_cup, jewelry, smile, teacup, white_headwear, cannon, holding_saucer, ocean, outdoors, pantyhose, bangs, blue_capelet, sitting, water |
| 2 | 15 |  |  |  |  |  | 1girl, cleavage, elbow_gloves, solo, white_dress, looking_at_viewer, official_alternate_costume, smile, white_gloves, jewelry, coat_on_shoulders, hat, closed_mouth, white_coat, detached_collar, double-breasted, bangs, holding, standing, white_flower, white_headwear, open_coat, rose, simple_background, white_background |
| 3 | 14 |  |  |  |  |  | 1girl, wedding_dress, bridal_veil, solo, white_dress, cleavage, smile, bride, looking_at_viewer, pearl_necklace, holding_bouquet, rose, blush, petals, white_flower |
| 4 | 27 |  |  |  |  |  | 1girl, cleavage, solo, smile, looking_at_viewer, hair_flower, collarbone, covered_navel, jewelry, sunglasses, eyewear_on_head, bare_shoulders, thighs, choker, official_alternate_costume, blush, thigh_strap, black_one-piece_swimsuit, simple_background |
| 5 | 11 |  |  |  |  |  | 1boy, 1girl, blush, hetero, nipples, penis, sex, completely_nude, open_mouth, vaginal, navel, pussy, spread_legs, solo_focus, on_back, bangs, jewelry, missionary, collarbone, hair_ornament, holding_hands, interlocked_fingers, looking_at_viewer, mosaic_censoring, pubic_hair, smile, sweat, thighs |
| 6 | 6 |  |  |  |  |  | 1girl, blush, hetero, 1boy, beach, day, nipples, ocean, outdoors, bald, big_belly, cloud, heart-shaped_pupils, mosaic_censoring, nude, open_mouth, penis, pregnant, sex, sky, thighband_pantyhose, tongue_out, topless, torn_clothes, lactation, pussy |
| 7 | 6 |  |  |  |  |  | hat, knee_boots, looking_at_viewer, smile, white_gloves, 1girl, black_footwear, jewelry, solo, white_ascot, white_pants, shirt, tilted_headwear, blue_headwear, blue_sky, horseback_riding, long_sleeves |
| 8 | 7 |  |  |  |  |  | 1girl, looking_at_viewer, smile, solo, bra, navel, underwear_only, blush, cleavage, collarbone, jewelry, black_panties, thighs, bangs, bare_shoulders, closed_mouth, lingerie, sitting |
| 9 | 7 |  |  |  |  |  | blue_kimono, hair_flower, obi, smile, wide_sleeves, 1girl, blue_flower, floral_print, holding, solo, looking_at_viewer, architecture, official_alternate_costume, outdoors, tree |

### Table Version

| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1girl | ascot | capelet | solo | hat | union_jack | looking_at_viewer | jewelry | simple_background | white_background | white_gloves | smile | dress | upper_body | blue_sky | cloud | day | machinery | rigging | turret | blue_dress | holding_cup | teacup | white_headwear | cannon | holding_saucer | ocean | outdoors | pantyhose | bangs | blue_capelet | sitting | water | cleavage | elbow_gloves | white_dress | official_alternate_costume | coat_on_shoulders | closed_mouth | white_coat | detached_collar | double-breasted | holding | standing | white_flower | open_coat | rose | wedding_dress | bridal_veil | bride | pearl_necklace | holding_bouquet | blush | petals | hair_flower | collarbone | covered_navel | sunglasses | eyewear_on_head | bare_shoulders | thighs | choker | thigh_strap | black_one-piece_swimsuit | 1boy | hetero | nipples | penis | sex | completely_nude | open_mouth | vaginal | navel | pussy | spread_legs | solo_focus | on_back | missionary | hair_ornament | holding_hands | interlocked_fingers | mosaic_censoring | pubic_hair | sweat | beach | bald | big_belly | heart-shaped_pupils | nude | pregnant | sky | thighband_pantyhose | tongue_out | topless | torn_clothes | lactation | knee_boots | black_footwear | white_ascot | white_pants | shirt | tilted_headwear | blue_headwear | horseback_riding | long_sleeves | bra | underwear_only | black_panties | lingerie | blue_kimono | obi | wide_sleeves | blue_flower | floral_print | architecture | tree |
|----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------|:--------|:----------|:-------|:------|:-------------|:--------------------|:----------|:--------------------|:-------------------|:---------------|:--------|:--------|:-------------|:-----------|:--------|:------|:------------|:----------|:---------|:-------------|:--------------|:---------|:-----------------|:---------|:-----------------|:--------|:-----------|:------------|:--------|:---------------|:----------|:--------|:-----------|:---------------|:--------------|:-----------------------------|:--------------------|:---------------|:-------------|:------------------|:------------------|:----------|:-----------|:---------------|:------------|:-------|:----------------|:--------------|:--------|:-----------------|:------------------|:--------|:---------|:--------------|:-------------|:----------------|:-------------|:------------------|:-----------------|:---------|:---------|:--------------|:---------------------------|:-------|:---------|:----------|:--------|:------|:------------------|:-------------|:----------|:--------|:--------|:--------------|:-------------|:----------|:-------------|:----------------|:----------------|:----------------------|:-------------------|:-------------|:--------|:--------|:-------|:------------|:----------------------|:-------|:-----------|:------|:----------------------|:-------------|:----------|:---------------|:------------|:-------------|:-----------------|:--------------|:--------------|:--------|:------------------|:----------------|:-------------------|:---------------|:------|:-----------------|:----------------|:-----------|:--------------|:------|:---------------|:--------------|:---------------|:---------------|:-------|
| 0 | 12 |  |  |  |  |  | X | X | X | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 1 | 8 |  |  |  |  |  | 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 | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 2 | 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 | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 3 | 14 |  |  |  |  |  | X | | | X | | | X | | | | | X | | | | | | | | | | | | | | | | | | | | | | X | | X | | | | | | | | | X | | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 4 | 27 |  |  |  |  |  | X | | | X | | | X | X | X | | | X | | | | | | | | | | | | | | | | | | | | | | X | | | X | | | | | | | | | | | | | | | | X | | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 5 | 11 |  |  |  |  |  | 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 | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 6 | 6 |  |  |  |  |  | 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 | | | | | | | | | | | | | | | | | | | | |
| 7 | 6 |  |  |  |  |  | X | | | X | X | | X | X | | | X | X | | | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | X | X | X | X | X | X | X | X | X | | | | | | | | | | | |
| 8 | 7 |  |  |  |  |  | X | | | X | | | X | X | | | | X | | | | | | | | | | | | | | | | | | X | | X | | X | | | | | X | | | | | | | | | | | | | | X | | | X | | | | X | X | | | | | | | | | | | | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | X | X | X | X | | | | | | | |
| 9 | 7 |  |  |  |  |  | X | | | X | | | X | | | | | X | | | | | | | | | | | | | | | | X | | | | | | | | | X | | | | | | X | | | | | | | | | | | | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | X | X | X | X | X | X | X |

原始信息汇总

数据集概述

数据集名称

• 名称: Dataset of hood/フッド/胡德 (Azur Lane)

数据集内容

• 描述: 包含347张图像及其标签。
• 核心标签: blonde_hair, long_hair, blue_eyes, breasts, hair_over_shoulder, large_breasts, earrings

数据集来源

• 采集方式: 自动爬虫系统从多个网站（如danbooru, pixiv, zerochan等）爬取。
• 技术支持: DeepGHS Team（通过huggingface organization提供支持）

数据集版本与格式

包名	图像数量	大小	下载链接	类型	描述
raw	347	497.76 MiB	下载	Waifuc-Raw	包含元信息的原始数据（最小边对齐到1400像素如果更大）
800	347	277.68 MiB	下载	IMG+TXT	短边不超过800像素的数据集
stage3-p480-800	809	557.08 MiB	下载	IMG+TXT	三阶段裁剪，区域不小于480x480像素的数据集
1200	347	433.27 MiB	下载	IMG+TXT	短边不超过1200像素的数据集
stage3-p480-1200	809	787.97 MiB	下载	IMG+TXT	三阶段裁剪，区域不小于480x480像素的数据集

数据集使用

• 加载工具: 使用waifuc加载原始数据集。
• 示例代码: 提供Python代码用于下载和加载数据集。

数据集标签集群

• 集群列表: 提供标签集群的结果，可能包含可挖掘的服装信息。
• 集群示例: 展示不同集群的样本图像及其标签。

搜集汇总

背景与挑战

背景概述

该数据集是一个文本到图像生成数据集，专注于艺术内容，但标注为'Not-For-All-Audiences'，可能包含敏感或有害信息，需谨慎使用。数据集规模中等，在1K到10K之间，采用MIT许可证，允许较广泛的应用和分发。