---
license: cc0-1.0
task_categories:
- visual-question-answering
- image-to-text
tags:
- comics
- metadata
- book-level
- tiny-dataset
- testing
size_categories:
- n<1K
---

# Comic Books Tiny Dataset v0 - Books (Testing)

**Small test dataset of book-level metadata for rapid development and testing.**

⚠️ **This is a TINY dataset** for testing only. For production, use `comix_v0_books`.

## Dataset Description

- **Total Books**: Unknown
- **Format**: WebDataset (tar files)
- **Content**: Metadata only (NO images)
- **License**: Public Domain (CC0-1.0)
- **Purpose**: Fast testing and development

## What's Included

Each book has:
- `{book_id}.json` - Book metadata with page references

## Purpose

This dataset provides book-level metadata to group pages from **comix_v0_tiny_pages**.

**Workflow**:
1. Download `comix_v0_tiny_pages` (with images)
2. Download `comix_v0_tiny_books` (metadata only)
3. Use WebDataset pipeline to group pages by book

## Quick Start

```python
from datasets import load_dataset
import json

# Load tiny books dataset
books = load_dataset(
    "emanuelevivoli/comix_v0_tiny_books",
    split="train",
    streaming=True
)

# Iterate through books
for book in books:
    book_data = json.loads(book["json"])
    
    book_id = book_data["book_id"]
    total_pages = book_data["book_metadata"]["total_pages"]
    
    # Get page references
    for page_ref in book_data["pages"]:
        page_id = page_ref["page_id"]
        dataset = page_ref["dataset"]  # "comix_v0_tiny_pages"
        tar_file = page_ref["tar_file"]
        files = page_ref["files"]  # json, jpg, seg.npz (if available)
    
    print(f"Book {book_id}: {total_pages} pages")
```

## Dataset Structure

### Book JSON Schema (v0)

```json
{
  "book_id": "c00004",
  "split": "train",
  "book_metadata": {
    "series_title": null,
    "issue_number": null,
    "publication_date": null,
    "publisher": null,
    "total_pages": 68,
    "license_status": "Public Domain",
    "digital_source": "Digital Comic Museum"
  },
  "pages": [
    {
      "page_number": 0,
      "page_id": "c00004_p000",
      "dataset": "comix_v0_tiny_pages",
      "tar_file": "comix-v0-tiny-pages-00000.tar",
      "files": {
        "json": "c00004_p000.json",
        "jpg": "c00004_p000.jpg",
        "seg.npz": "c00004_p000.seg.npz"
      }
    },
    ...
  ],
  "segments": [],     // v1: story segments (to be added)
  "characters": []    // v1: character bank (to be added)
}
```

## Data Splits

| Split | Books |
|-------|-------|
| Train | Unknown |
| Validation | Unknown |
| Test | Unknown |
| **Total** | **Unknown** |

## Use Cases

✅ **Testing**: Rapid iteration on book-level structure
✅ **Development**: Quick validation of page grouping
✅ **Debugging**: Small dataset for troubleshooting
✅ **Prototyping**: Fast experimentation

❌ **NOT for**: Training production models

## Version 0 (Primordial)

This is a **primordial v0** with:
- ✅ Basic structure
- ✅ Page references
- ⏳ Empty `book_metadata` fields (to be populated in v1)
- ⏳ Empty `segments` (to be added in v1)
- ⏳ Empty `characters` (to be added in v1)

**Future (v1+)** will include:
- Bibliographic information (series, issue, publisher)
- Story segments with summaries
- Character banks with appearances

## Companion Dataset

**comix_v0_tiny_pages**: Individual pages with images

## Full Dataset

For production use: **comix_v0_books** (~19K books)

## Example: Group Pages by Book

```python
# Load both datasets
pages = load_dataset("emanuelevivoli/comix_v0_tiny_pages", split="train")
books = load_dataset("emanuelevivoli/comix_v0_tiny_books", split="train")

# Create page index
page_index = {p["json"]["page_id"]: p for p in pages}

# Get a book and its pages
book = books[0]
book_data = json.loads(book["json"])

book_pages = []
for page_ref in book_data['pages']:
    page_id = page_ref['page_id']
    if page_id in page_index:
        book_pages.append(page_index[page_id])

print(f"Book {book_data['book_id']}: {len(book_pages)} pages loaded")
```

## Citation

```bibtex
@dataset{comix_v0_tiny_books_2025,
  title={Comic Books Tiny Dataset v0 - Books},
  author={Emanuele Vivoli},
  year={2025},
  publisher={Hugging Face},
  note={Testing dataset - metadata only},
  url={https://huggingface.co/datasets/emanuelevivoli/comix_v0_tiny_books}
}
```

## License

Public Domain (CC0-1.0) - Digital Comic Museum

## Updates

- **v0 (2025-11-18)**: Initial release
  - Unknown books
  - Primordial version with placeholder fields
  - For testing only