dataset_info:
features:
- name: file_url
dtype: string
- name: approver_id
dtype: float64
- name: bit_flags
dtype: int64
- name: created_at
dtype: string
- name: down_score
dtype: int64
- name: fav_count
dtype: int64
- name: file_ext
dtype: string
- name: file_size
dtype: int64
- name: has_active_children
dtype: bool
- name: has_children
dtype: bool
- name: has_large
dtype: bool
- name: has_visible_children
dtype: bool
- name: image_height
dtype: int64
- name: image_width
dtype: int64
- name: is_banned
dtype: bool
- name: is_deleted
dtype: bool
- name: is_flagged
dtype: bool
- name: is_pending
dtype: bool
- name: large_file_url
dtype: string
- name: last_comment_bumped_at
dtype: string
- name: last_commented_at
dtype: string
- name: last_noted_at
dtype: string
- name: md5
dtype: string
- name: media_asset_created_at
dtype: string
- name: media_asset_duration
dtype: float64
- name: media_asset_file_ext
dtype: string
- name: media_asset_file_key
dtype: string
- name: media_asset_file_size
dtype: int64
- name: media_asset_id
dtype: int64
- name: media_asset_image_height
dtype: int64
- name: media_asset_image_width
dtype: int64
- name: media_asset_is_public
dtype: bool
- name: media_asset_md5
dtype: string
- name: media_asset_pixel_hash
dtype: string
- name: media_asset_status
dtype: string
- name: media_asset_updated_at
dtype: string
- name: media_asset_variants
dtype: string
- name: parent_id
dtype: float64
- name: pixiv_id
dtype: float64
- name: preview_file_url
dtype: string
- name: rating
dtype: string
- name: score
dtype: int64
- name: source
dtype: string
- name: tag_count
dtype: int64
- name: tag_count_artist
dtype: int64
- name: tag_count_character
dtype: int64
- name: tag_count_copyright
dtype: int64
- name: tag_count_general
dtype: int64
- name: tag_count_meta
dtype: int64
- name: tag_string
dtype: string
- name: tag_string_artist
dtype: string
- name: tag_string_character
dtype: string
- name: tag_string_copyright
dtype: string
- name: tag_string_general
dtype: string
- name: tag_string_meta
dtype: string
- name: up_score
dtype: int64
- name: updated_at
dtype: string
- name: uploader_id
dtype: int64
- name: id
dtype: int64
splits:
- name: train
num_bytes: 21271155853
num_examples: 9113285
download_size: 7601577894
dataset_size: 21271155853
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
license: mit
task_categories:
- text-to-image
- image-classification
language:
- en
- ja
pretty_name: Danbooru 2025 Metadata
size_categories:
- 1M<n<10M
🎨 Danbooru 2025 Metadata
Latest Post ID: 9,158,800
(as of Apr 16, 2025)
📁 About the Dataset
This dataset provides structured metadata for user-submitted images on Danbooru, a large-scale imageboard focused on anime-style artwork.
Scraping began on January 2, 2025, and the data are stored in Parquet format for efficient programmatic access.
Compared to earlier versions, this snapshot includes:
- More consistent tag history tracking
- Better coverage of older or previously skipped posts
- Reduced presence of unlabeled AI-generated entries
Dataset Overview
Each row corresponds to a Danbooru post, with fields including:
- Tag list (both general and system-specific)
- Upload timestamp
- File details (size, extension, resolution)
- User stats (favorites, score, etc.)
The schema follows Danbooru’s public API structure, and should be familiar to anyone who has worked with their JSON output.
File Format
The metadata are stored in a flat table. Nested dictionaries have been flattened using a consistent naming scheme (parentkey_childkey) to aid downstream use in ML pipelines or indexing tools.
Access & Usage
You can load the dataset via the Hugging Face datasets library:
from datasets import load_dataset
danbooru_metadata = load_dataset("trojblue/danbooru2025-metadata", split="train")
df = danbooru_metadata.to_pandas()
Potential use cases include:
- Image retrieval systems
- Text-to-image alignment tasks
- Dataset curation or filtering
- Historical or cultural analysis of trends in tagging
Be cautious if working in public settings. The dataset contains adult content.
Notable Characteristics
- Single-Snapshot Coverage: All posts up to the stated ID are included. No need to merge partial scrapes.
- Reduced Tag Drift: Many historic tag renames and merges are reflected correctly.
- Filtered AI-Generated Posts: Some attempts were made to identify and exclude unlabeled AI-generated entries, though the process is imperfect.
Restricted tags (e.g., certain content filters) are inaccessible without privileged API keys and are therefore missing here.
If you need metadata with those tags, you’ll need to integrate previous datasets (such as Danbooru2021) and resolve inconsistencies manually.
Code: Flattening the JSON
Included below is a simplified example showing how the raw JSON was transformed:
import pandas as pd
from pandarallel import pandarallel
# Initialize multiprocessing
pandarallel.initialize(nb_workers=4, progress_bar=True)
def flatten_dict(d, parent_key='', sep='_'):
items = []
for k, v in d.items():
new_key = f"{parent_key}{sep}{k}" if parent_key else k
if isinstance(v, dict):
items.extend(flatten_dict(v, new_key, sep=sep).items())
elif isinstance(v, list):
items.append((new_key, ', '.join(map(str, v))))
else:
items.append((new_key, v))
return dict(items)
def extract_all_illust_info(json_content):
return pd.Series(flatten_dict(json_content))
def dicts_to_dataframe_parallel(dicts):
df = pd.DataFrame(dicts)
return df.parallel_apply(lambda row:
extract_all_illust_info(row.to_dict()), axis=1)
Warnings & Considerations
- NSFW Material: Includes sexually explicit tags or content. Do not deploy without clear filtering and compliance checks.
- Community Bias: Tags are user-generated and reflect collective subjectivity. Representation may skew or omit.
- Data Licensing: Image rights remain with original uploaders. This dataset includes metadata only, not media. Review Danbooru’s Terms of Service for reuse constraints.
- Missing Content: Posts with restricted tags or deleted content may appear with incomplete fields or be absent entirely.
Column Summaries (Sample — Apr 16, 2025)
Full schema and additional statistics are viewable on the Hugging Face Dataset Viewer.
File Information
- file_url: 8.8 million unique file links
- file_ext: 9 file types
'jpg': 73.3%'png': 25.4%- Other types (
mp4,gif,zip, etc.): <1.5% combined
- file_size and media_asset_file_size (bytes):
- Min: 49
- Max: ~106MB
- Avg: ~1.5MB
Image Dimensions
- image_width:
- Min: 1 px
- Max: 35,102 px
- Mean: 1,471 px
- image_height:
- Min: 1 px
- Max: 54,250 px
- Mean: 1,760 px
(Note: extremely small dimensions may indicate deleted or broken images.)
Scoring and Engagement
- score (net = up − down):
- Min: −167
- Max: 2,693
- Mean: 26.15
- up_score:
- Max: 2,700
- Mean: 25.87
- down_score:
- Min: −179
- Mean: −0.24
- fav_count:
- Max: 4,458
- Mean: 32.49
Rating and Moderation
- rating:
'g'(general, safe): 29.4%'s'(suggestive): 49.5%'q'(questionable): 11.2%'e'(explicit): 9.8%
- is_banned: 1.13% true
- is_deleted: 5.34% true
- is_flagged / is_pending: <0.01% true (rare moderation edge-cases)
Children & Variations
- has_children: 10.7%
- has_active_children: 10.0%
- has_visible_children: 10.3%
- has_large: 70.6% of posts are linked to full-res versions
Tag Breakdown
(Tag counts are per post; some posts may have hundreds.)
- tag_count (total tags):
- Avg: 36.3
- tag_count_artist: 0.99 avg
- tag_count_character: 1.62 avg
- tag_count_copyright: 1.39 avg
- tag_count_general: 30.0 avg
- tag_count_meta: 2.3 avg
Some outliers contain hundreds of tags—up to 1,250 in total on rare posts.
Other Fields
- uploader_id (anonymized integer ID)
- updated_at (timestamp) — nearly every post has a unique update time
(last updated: 2025-04-16 12:15:29.262308)