README.md

metadata

configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
dataset_info:
  features:
    - name: url
      dtype: string
    - name: caption
      dtype: string
    - name: similarity
      dtype: float64
    - name: page_title
      dtype: string
    - name: page_url
      dtype: string
    - name: punsafe
      dtype: float64
    - name: width
      dtype: float64
    - name: height
      dtype: float64
    - name: original_width
      dtype: float64
    - name: original_height
      dtype: float64
    - name: sha256
      dtype: string
    - name: phash
      dtype: string
  splits:
    - name: train
      num_bytes: 72405439283
      num_examples: 153942892
  download_size: 46743814850
  dataset_size: 72405439283
license: apache-2.0
language:
  - ja
size_categories:
  - 100M<n<1B

WAON: Large-Scale and High-Quality Japanese Image-Text Pair Dataset for Vision-Language Models

| 🤗 HuggingFace  | 📄 Paper  | 🧑‍💻 Code  |

Introduction

WAON is a Japanese (image, text) pair dataset containing approximately 155M examples, crawled from Common Crawl. It is built from snapshots taken in 2025-18, 2025-08, 2024-51, 2024-42, 2024-33, and 2024-26. The dataset is high-quality and diverse, constructed through a sophisticated data processing pipeline. We apply filtering based on image size and SigLIP scores, and perform deduplication using URLs, captions, and perceptual hashes (pHash).

How to Use

Clone the repository:

git clone https://gitlab.llm-jp.nii.ac.jp/datasets/waon.git
cd waon

Load the dataset using the datasets library:

from datasets import load_dataset

ds = load_dataset("parquet", data_dir="data")

Format

• url: URL of the image
• caption: Caption associated with the image
• page_title: Title of the page containing the image
• page_url: URL of the page
• punsafe: Probability that the image is unsafe
• quality: The quality of the text in the text column
• width: Width (in pixels) of the resized image used for computing pHash
• height: Height (in pixels) of the resized image used for computing pHash
• original_width: Original width of the image
• original_height: Original height of the image
• sha256: SHA-256 hash of the original image file
• phash: Perceptual hash (pHash) computed from the resized image

Dataset Construction Pipeline

We construct WAON dataset through the following steps (The numbers in parentheses indicate the remaining data count after each processing step (based on the 2025-18 snapshot):

LICENSE

This dataset (not including images themselves) is licensed under the Apache License 2.0 and governed by Japanese law. Its use is limited to “information analysis” as defined in Article 30-4 of the Japanese Copyright Act.

Citation

@misc{sugiura2025waonlargescalehighqualityjapanese,
      title={WAON: Large-Scale and High-Quality Japanese Image-Text Pair Dataset for Vision-Language Models},
      author={Issa Sugiura and Shuhei Kurita and Yusuke Oda and Daisuke Kawahara and Yasuo Okabe and Naoaki Okazaki},
      year={2025},
      eprint={2510.22276},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2510.22276},
}