|
---
|
|
language:
|
|
- en
|
|
pretty_name: "PD12M"
|
|
license: "cdla-permissive-2.0"
|
|
tags:
|
|
- image
|
|
|
|
---
|
|
|
|
# PD12M
|
|
|
|
|
|
|
|
# Summary
|
|
At 12.4 million image-caption pairs, PD12M is the largest public domain image-text dataset to date, with sufficient size to train foundation models while minimizing copyright concerns. Through the Source.Plus platform, we also introduce novel, community-driven dataset governance mechanisms that reduce harm and support reproducibility over time.
|
|
|
|
[Jordan Meyer](https://linkedin.com/in/jordanmeyer) [Nicholas Padgett](https://www.linkedin.com/in/nicholas-padgett-36a921a0/) [Cullen Miller](https://www.linkedin.com/in/cullen-miller-312941290/) [Laura Exline](https://www.linkedin.com/in/lauraexline/)
|
|
|
|
[Paper](https://arxiv.org/abs/2410.23144) [Datasheet](https://huggingface.co/datasets/Spawning/PD12M/blob/main/Datasheet.pdf) [Project](https://source.plus/pd12m)
|
|
|
|
# About
|
|
PD12M was built and curated with [Source.Plus](https://source.plus) with the aim of resolving many of the data quality issues that arise in web-scraped training data: the presence of copyrighted material, low quality images and captions, violent or nsfw content, PII, decaying dataset quality via broken links, etc.
|
|
|
|
PD12M consists of entirely public domain and CC0 licensed images, with automated recaptioning of image data, and quality and safety filtering. Images in PD12M are also hosted on dedicated cloud storage, separate from the original image hosts, to avoid placing an undue burden on those hosts or impacting services for regular users. This also ensures the dataset remains wholly intact over its lifetime.
|
|
|
|
# Overview
|
|
This dataset has two components. The first is the `metadata`, which contains the image urls, captions, image dimensions, etc. The second component are the `images`.
|
|
|
|
## Metadata
|
|
The metadata is made available through a series of parquet files with the following schema:
|
|
- `id`: A unique identifier for the image.
|
|
- `url`: The URL of the image.
|
|
- `caption`: A caption for the image.
|
|
- `width`: The width of the image in pixels.
|
|
- `height`: The height of the image in pixels.
|
|
- `mime_type`: The MIME type of the image file.
|
|
- `hash`: The MD5 hash of the image file.
|
|
- `license`: The URL of the image license.
|
|
- `source` : The source organization of the image.
|
|
|
|
Additionally, CLIP Vit-L/14 embeddings are provided in the `embeddings` directory.
|
|
|
|
## Images
|
|
The image files are all hosted in the AWS S3 bucket `pd12m`. The URLs to the images files are all maintained in the metadata files.
|
|
|
|
# Tutorials
|
|
|
|
[Working with the Metadata](./tutorials/metadata.md)
|
|
|
|
[Downloading Images](./tutorials/images.md)
|
|
|
|
[Working with the Embeddings](./tutorials/embeddings.md)
|
|
|
|
# License
|
|
The dataset is licensed under the [CDLA-Permissive-2.0](https://cdla.dev/permissive-2-0/).
|
|
|
|
# Reporting Issues
|
|
We've gone through great lengths to ensure the dataset is free from objectionable and infringing content. If you find any issues or have any concerns, please flag the item in [Source.Plus](https://source.plus/collection/pd12m-mxenifxs), where our review process will remove the infringing material, and find a suitable replacement.
|
|
|
|
# Citation
|
|
@misc{meyer2024publicdomain12mhighly,
|
|
title={Public Domain 12M: A Highly Aesthetic Image-Text Dataset with Novel Governance Mechanisms},
|
|
author={Jordan Meyer and Nick Padgett and Cullen Miller and Laura Exline},
|
|
year={2024},
|
|
eprint={2410.23144},
|
|
archivePrefix={arXiv},
|
|
primaryClass={cs.AI},
|
|
url={https://arxiv.org/abs/2410.23144},
|
|
}
|
|
|
