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---
license: mit
task_categories:
- text-to-image
tags:
- art
- not-for-all-audiences
size_categories:
- n<1K
---
# Dataset of Sonetto/十四行诗/ソネット(リバース:1999) (Reverse:1999)
This is the dataset of Sonetto/十四行诗/ソネット(リバース:1999) (Reverse:1999), containing 282 images and their tags.
The core tags of this character are `orange_hair, long_hair, two_side_up, green_eyes, braid, side_braid`, 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-head | Images-others |
|:-----------------|---------:|:-----------|:---------------------------------------------------------------------------------------------------------------------|:-----------|:---------------------------------------------------------------------|:--------------|:----------------|
| raw | 282 | 556.39 MiB | [Download](https://huggingface.co/datasets/CyberHarem/sonetto_reverse1999/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). | -- | -- |
| stage3-p480-1200 | 685 | 881.15 MiB | [Download](https://huggingface.co/datasets/CyberHarem/sonetto_reverse1999/resolve/main/dataset-stage3-p480-1200.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. | 246 | 439 |
### 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/sonetto_reverse1999',
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 | 11 |  |  |  |  |  | 2girls, simple_background, white_background, blush, long_sleeves, open_mouth, upper_body, solo_focus, yuri, grey_hair, smile, white_dress, closed_eyes, coat, collared_shirt, jacket, white_shirt |
| 1 | 10 |  |  |  |  |  | 2girls, closed_mouth, long_sleeves, simple_background, white_background, white_dress, blush, coat, grey_hair, yuri, solo_focus, white_shirt, upper_body, white_gloves, white_pants |
| 2 | 8 |  |  |  |  |  | simple_background, 1girl, looking_at_viewer, portrait, solo, closed_mouth, white_background, upper_body, white_shirt, :o, parted_lips |
| 3 | 11 |  |  |  |  |  | aged_down, white_dress, white_hairband, 1girl, closed_mouth, solo_focus, 2girls, full_body, puffy_long_sleeves, white_socks, black_footwear, holding, shoes, standing, child, collared_dress |
| 4 | 6 |  |  |  |  |  | 1girl, high_collar, long_sleeves, solo, upper_body, white_dress, holding_pen, looking_at_viewer, white_gloves, grey_sleeves, magic, closed_mouth, dark_background, floating_hair, hand_up, holding_wand |
| 5 | 5 |  |  |  |  |  | 1girl, high_collar, solo, white_dress, white_gloves, grey_sleeves, holding_pen, looking_at_viewer, black_background, capelet, closed_mouth, cowboy_shot, floating_hair, parted_lips, thigh_strap, white_pants, feet_out_of_frame, hand_up, puffy_long_sleeves, short_dress, thigh_belt |
| 6 | 6 |  |  |  |  |  | solo_focus, white_dress, white_gloves, grey_sleeves, holding, outdoors, puffy_long_sleeves, white_pants, 2girls, building, hand_up, high_collar, looking_at_viewer, parted_lips, standing, 1girl, full_body, hat, rain |
| 7 | 14 |  |  |  |  |  | 1girl, solo, long_sleeves, looking_at_viewer, glasses, hairband, round_eyewear, closed_mouth, black_footwear, blue_dress, bowtie, full_body, hand_up, socks, white_background, black_bow, checkered_clothes, hair_bow, holding_book, shirt, simple_background, upper_body |
| 8 | 7 |  |  |  |  |  | 1girl, white_background, white_shirt, full_body, long_sleeves, simple_background, solo, hairband, looking_at_viewer, long_skirt, blue_skirt, boots, holding, open_mouth, smile, standing, very_long_hair |
| 9 | 7 |  |  |  |  |  | solo_focus, 2girls, white_dress, upper_body, 1girl, closed_mouth, high_collar, long_sleeves, sitting |
| 10 | 16 |  |  |  |  |  | 1girl, solo, white_dress, white_gloves, sleeveless_dress, white_headwear, elbow_gloves, hand_up, shoulder_sash, bird, floating_hair, high_collar, yellow_sash, looking_at_viewer, outdoors, parted_lips, upper_body, beret, blue_sky, closed_mouth, day, holding |
### Table Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 2girls | simple_background | white_background | blush | long_sleeves | open_mouth | upper_body | solo_focus | yuri | grey_hair | smile | white_dress | closed_eyes | coat | collared_shirt | jacket | white_shirt | closed_mouth | white_gloves | white_pants | 1girl | looking_at_viewer | portrait | solo | :o | parted_lips | aged_down | white_hairband | full_body | puffy_long_sleeves | white_socks | black_footwear | holding | shoes | standing | child | collared_dress | high_collar | holding_pen | grey_sleeves | magic | dark_background | floating_hair | hand_up | holding_wand | black_background | capelet | cowboy_shot | thigh_strap | feet_out_of_frame | short_dress | thigh_belt | outdoors | building | hat | rain | glasses | hairband | round_eyewear | blue_dress | bowtie | socks | black_bow | checkered_clothes | hair_bow | holding_book | shirt | long_skirt | blue_skirt | boots | very_long_hair | sitting | sleeveless_dress | white_headwear | elbow_gloves | shoulder_sash | bird | yellow_sash | beret | blue_sky | day |
|----:|----------:|:--------------------------------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------------------------------|:---------|:--------------------|:-------------------|:--------|:---------------|:-------------|:-------------|:-------------|:-------|:------------|:--------|:--------------|:--------------|:-------|:-----------------|:---------|:--------------|:---------------|:---------------|:--------------|:--------|:--------------------|:-----------|:-------|:-----|:--------------|:------------|:-----------------|:------------|:---------------------|:--------------|:-----------------|:----------|:--------|:-----------|:--------|:-----------------|:--------------|:--------------|:---------------|:--------|:------------------|:----------------|:----------|:---------------|:-------------------|:----------|:--------------|:--------------|:--------------------|:--------------|:-------------|:-----------|:-----------|:------|:-------|:----------|:-----------|:----------------|:-------------|:---------|:--------|:------------|:--------------------|:-----------|:---------------|:--------|:-------------|:-------------|:--------|:-----------------|:----------|:-------------------|:-----------------|:---------------|:----------------|:-------|:--------------|:--------|:-----------|:------|
| 0 | 11 |  |  |  |  |  | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 1 | 10 |  |  |  |  |  | X | X | X | X | X | | X | X | X | X | | X | | X | | | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 2 | 8 |  |  |  |  |  | | X | X | | | | X | | | | | | | | | | X | X | | | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 3 | 11 |  |  |  |  |  | X | | | | | | | X | | | | X | | | | | | X | | | X | | | | | | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 4 | 6 |  |  |  |  |  | | | | | X | | X | | | | | X | | | | | | X | X | | X | X | | X | | | | | | | | | | | | | | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 5 | 5 |  |  |  |  |  | | | | | | | | | | | | 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 | | | | | | | | | | | | | | | | | | | | | | | | | |
| 7 | 14 |  |  |  |  |  | | X | X | | X | | X | | | | | | | | | | | X | | | 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 | | | | | | | | | | |
| 9 | 7 |  |  |  |  |  | X | | | | X | | X | X | | | | X | | | | | | X | | | X | | | | | | | | | | | | | | | | | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | X | | | | | | | | | |
| 10 | 16 |  |  |  |  |  | | | | | | | X | | | | | X | | | | | | X | X | | X | X | | X | | X | | | | | | | X | | | | | X | | | | | X | X | | | | | | | | | X | | | | | | | | | | | | | | | | | | | | X | X | X | X | X | X | X | X | X |
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