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---
license: mit
task_categories:
- text-to-image
tags:
- art
- not-for-all-audiences
size_categories:
- n<1K
---
# Dataset of purestream/セイリュウ/清流 (Arknights)
This is the dataset of purestream/セイリュウ/清流 (Arknights), containing 50 images and their tags.
The core tags of this character are `long_hair, twintails, blue_eyes, low_twintails, visor_cap, bow, breasts, brown_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](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)).
## List of Packages
| Name | Images | Size | Download | Type | Description |
|:-----------------|---------:|:-----------|:----------------------------------------------------------------------------------------------------------------------|:-----------|:---------------------------------------------------------------------|
| raw | 50 | 83.05 MiB | [Download](https://huggingface.co/datasets/CyberHarem/purestream_arknights/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). |
| 1200 | 50 | 71.00 MiB | [Download](https://huggingface.co/datasets/CyberHarem/purestream_arknights/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. |
| stage3-p480-1200 | 137 | 140.29 MiB | [Download](https://huggingface.co/datasets/CyberHarem/purestream_arknights/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/purestream_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 | 16 |  |  |  |  |  | 1girl, solo, looking_at_viewer, sleeveless_dress, white_dress, smile, white_background, bare_shoulders, blush, shoulder_bag, water, hat, holding, open_mouth, hair_between_eyes, purple_hair, simple_background, bracelet, small_breasts, staff, white_footwear |
| 1 | 11 |  |  |  |  |  | 1girl, sleeveless_dress, solo, looking_at_viewer, smile, white_dress, closed_mouth, water, cloud, day, outdoors, blue_sky, blush, ocean, bare_shoulders, blue_bow, collarbone, hair_between_eyes, open_mouth, small_breasts |
### Table Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1girl | solo | looking_at_viewer | sleeveless_dress | white_dress | smile | white_background | bare_shoulders | blush | shoulder_bag | water | hat | holding | open_mouth | hair_between_eyes | purple_hair | simple_background | bracelet | small_breasts | staff | white_footwear | closed_mouth | cloud | day | outdoors | blue_sky | ocean | blue_bow | collarbone |
|----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------|:-------|:--------------------|:-------------------|:--------------|:--------|:-------------------|:-----------------|:--------|:---------------|:--------|:------|:----------|:-------------|:--------------------|:--------------|:--------------------|:-----------|:----------------|:--------|:-----------------|:---------------|:--------|:------|:-----------|:-----------|:--------|:-----------|:-------------|
| 0 | 16 |  |  |  |  |  | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | |
| 1 | 11 |  |  |  |  |  | X | X | X | X | X | X | | X | X | | X | | | X | X | | | | X | | | X | X | X | X | X | X | X | X |
|