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---
license: mit
task_categories:
- text-to-image
tags:
- art
- not-for-all-audiences
size_categories:
- n<1K
---
# Dataset of tam_lin_lancelot/妖精騎士ランスロット/妖精骑士兰斯洛特 (Fate/Grand Order)
This is the dataset of tam_lin_lancelot/妖精騎士ランスロット/妖精骑士兰斯洛特 (Fate/Grand Order), containing 500 images and their tags.
The core tags of this character are `long_hair, white_hair, sidelocks, breasts, forked_eyebrows, small_breasts, yellow_eyes, brown_eyes`, 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 | 500 | 892.76 MiB | [Download](https://huggingface.co/datasets/CyberHarem/tam_lin_lancelot_fgo/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). |
| 1200 | 500 | 758.09 MiB | [Download](https://huggingface.co/datasets/CyberHarem/tam_lin_lancelot_fgo/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. |
| stage3-p480-1200 | 1303 | 1.48 GiB | [Download](https://huggingface.co/datasets/CyberHarem/tam_lin_lancelot_fgo/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/tam_lin_lancelot_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
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | Tags |
|----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| 0 | 14 |  |  |  |  |  | 1girl, long_sleeves, looking_at_viewer, solo, wide_sleeves, obi, blue_kimono, layered_kimono, purple_kimono, smile, flower, open_mouth |
| 1 | 22 |  |  |  |  |  | 1girl, bare_shoulders, dragon_wings, horns, solo, thighs, looking_at_viewer, white_one-piece_swimsuit, thighlet, covered_navel, dragon_tail, dragon_girl, smile, ahoge |
| 2 | 6 |  |  |  |  |  | 1girl, bare_shoulders, dragon_wings, horns, looking_at_viewer, smile, solo, thighs, dragon_tail, open_mouth, white_bikini, navel, thighlet, elbow_gloves, thighhighs |
| 3 | 22 |  |  |  |  |  | 1girl, black_bikini, cropped_jacket, dragon_wings, high_ponytail, long_sleeves, looking_at_viewer, shrug_(clothing), solo, smile, thighlet, thighs, black_jacket, navel, mouth_mask, pubic_tattoo, tongue_out, mask_pull |
| 4 | 15 |  |  |  |  |  | 1girl, solo, thighs, looking_at_viewer, bare_shoulders, revealing_clothes, body_markings, dragon_wings, weapon, black_panties, horns |
| 5 | 17 |  |  |  |  |  | 1girl, blue_dress, solo, frills, long_sleeves, looking_at_viewer, blue_cape, white_thighhighs, smile, white_rose |
| 6 | 10 |  |  |  |  |  | 1girl, blue_dress, breastplate, faulds, looking_at_viewer, pauldrons, solo, armored_dress, blue_armor, short_dress, thighs, weapon |
| 7 | 9 |  |  |  |  |  | 1boy, 1girl, hetero, nipples, penis, sex, thighs, vaginal, blush, navel, open_mouth, spread_legs, sweat, collarbone, cum_in_pussy, completely_nude, mosaic_censoring, girl_on_top, looking_at_viewer, smile, straddling |
| 8 | 5 |  |  |  |  |  | 1girl, bare_shoulders, fake_animal_ears, playboy_bunny, rabbit_ears, solo, highleg_leotard, looking_at_viewer, open_mouth, strapless_leotard, thighs, wrist_cuffs, blue_leotard, blush, smile, bare_legs, black_leotard, collarbone, covered_navel, fake_tail, heart, pantyhose, rabbit_tail |
### Table Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1girl | long_sleeves | looking_at_viewer | solo | wide_sleeves | obi | blue_kimono | layered_kimono | purple_kimono | smile | flower | open_mouth | bare_shoulders | dragon_wings | horns | thighs | white_one-piece_swimsuit | thighlet | covered_navel | dragon_tail | dragon_girl | ahoge | white_bikini | navel | elbow_gloves | thighhighs | black_bikini | cropped_jacket | high_ponytail | shrug_(clothing) | black_jacket | mouth_mask | pubic_tattoo | tongue_out | mask_pull | revealing_clothes | body_markings | weapon | black_panties | blue_dress | frills | blue_cape | white_thighhighs | white_rose | breastplate | faulds | pauldrons | armored_dress | blue_armor | short_dress | 1boy | hetero | nipples | penis | sex | vaginal | blush | spread_legs | sweat | collarbone | cum_in_pussy | completely_nude | mosaic_censoring | girl_on_top | straddling | fake_animal_ears | playboy_bunny | rabbit_ears | highleg_leotard | strapless_leotard | wrist_cuffs | blue_leotard | bare_legs | black_leotard | fake_tail | heart | pantyhose | rabbit_tail |
|----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------|:---------------|:--------------------|:-------|:---------------|:------|:--------------|:-----------------|:----------------|:--------|:---------|:-------------|:-----------------|:---------------|:--------|:---------|:---------------------------|:-----------|:----------------|:--------------|:--------------|:--------|:---------------|:--------|:---------------|:-------------|:---------------|:-----------------|:----------------|:-------------------|:---------------|:-------------|:---------------|:-------------|:------------|:--------------------|:----------------|:---------|:----------------|:-------------|:---------|:------------|:-------------------|:-------------|:--------------|:---------|:------------|:----------------|:-------------|:--------------|:-------|:---------|:----------|:--------|:------|:----------|:--------|:--------------|:--------|:-------------|:---------------|:------------------|:-------------------|:--------------|:-------------|:-------------------|:----------------|:--------------|:------------------|:--------------------|:--------------|:---------------|:------------|:----------------|:------------|:--------|:------------|:--------------|
| 0 | 14 |  |  |  |  |  | X | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 1 | 22 |  |  |  |  |  | X | | X | X | | | | | | X | | | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 2 | 6 |  |  |  |  |  | X | | X | X | | | | | | X | | X | X | X | X | X | | X | | X | | | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 3 | 22 |  |  |  |  |  | X | X | X | X | | | | | | X | | | | X | | X | | X | | | | | | X | | | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 4 | 15 |  |  |  |  |  | X | | X | X | | | | | | | | | X | X | X | X | | | | | | | | | | | | | | | | | | | | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 5 | 17 |  |  |  |  |  | X | X | X | X | | | | | | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 6 | 10 |  |  |  |  |  | X | | X | X | | | | | | | | | | | | X | | | | | | | | | | | | | | | | | | | | | | X | | X | | | | | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 7 | 9 |  |  |  |  |  | X | | X | | | | | | | X | | X | | | | X | | | | | | | | X | | | | | | | | | | | | | | | | | | | | | | | | | | | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | |
| 8 | 5 |  |  |  |  |  | X | | X | X | | | | | | X | | X | X | | | X | | | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | X | | | X | | | | | | X | X | X | X | X | X | X | X | X | X | X | X | X |
|