pixparse/cc3m-wds

Dataset Card for Conceptual Captions (CC3M)

Dataset Summary

Conceptual Captions is a dataset consisting of ~3.3M images annotated with captions. In contrast with the curated style of other image caption annotations, Conceptual Caption images and their raw descriptions are harvested from the web, and therefore represent a wider variety of styles. More precisely, the raw descriptions are harvested from the Alt-text HTML attribute associated with web images. To arrive at the current version of the captions, we have developed an automatic pipeline that extracts, filters, and transforms candidate image/caption pairs, with the goal of achieving a balance of cleanliness, informativeness, fluency, and learnability of the resulting captions.

Usage

This instance of Conceptual Captions is in webdataset .tar format. It can be used with webdataset library or upcoming releases of Hugging Face datasets.

...More Detail TBD

Data Splits

This dataset was downloaded using img2dataset. Images resized on download if shortest edge > 512 to shortest edge = 512.

Train

• cc3m-train-*.tar
• Downloaded on 2021/12/22
• 576 shards, 2905954 (of 3318333) samples

Validation

• cc3m-validation-*.tar
• Downloaded on 2023/12/13 (original validation set download in 2021 was corrupted)
• 16 shards, 13443 (of 15840) samples

Additional Information

Dataset Curators

Piyush Sharma, Nan Ding, Sebastian Goodman and Radu Soricut.

Licensing Information

The dataset may be freely used for any purpose, although acknowledgement of Google LLC ("Google") as the data source would be appreciated. The dataset is provided "AS IS" without any warranty, express or implied. Google disclaims all liability for any damages, direct or indirect, resulting from the use of the dataset.

Citation Information

@inproceedings{sharma2018conceptual,
  title = {Conceptual Captions: A Cleaned, Hypernymed, Image Alt-text Dataset For Automatic Image Captioning},
  author = {Sharma, Piyush and Ding, Nan and Goodman, Sebastian and Soricut, Radu},
  booktitle = {Proceedings of ACL},
  year = {2018},
}