README.md

---
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
---

<p align="center"> 
  <img src="https://huggingface.co/datasets/trojblue/danbooru2025-metadata/resolve/main/57931572.png" alt="Danbooru Logo" width="120"/> 
</p> 

<h1 align="center">🎨 Danbooru 2025 Metadata</h1> 

<p align="center">
  <strong>Latest Post ID:</strong> <code>9,158,800</code><br/>
  <em>(as of Apr 16, 2025)</em>
</p>

---

📁 **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:

```python
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:

```python
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](https://danbooru.donmai.us/static/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)