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--- |
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license: other |
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license_name: conceptual-captions |
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license_link: >- |
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https://github.com/google-research-datasets/conceptual-captions/blob/master/LICENSE |
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task_categories: |
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- image-to-text |
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size_categories: |
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- 1M<n<10M |
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--- |
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# Dataset Card for Conceptual Captions (CC3M) |
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## Table of Contents |
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- [Dataset Description](#dataset-description) |
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- [Dataset Summary](#dataset-summary) |
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- [Additional Information](#additional-information) |
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- [Dataset Curators](#dataset-curators) |
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- [Licensing Information](#licensing-information) |
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- [Citation Information](#citation-information) |
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## Dataset Description |
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- **Homepage:** [Conceptual Captions homepage](https://ai.google.com/research/ConceptualCaptions/) |
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- **Repository:** [Conceptual Captions repository](https://github.com/google-research-datasets/conceptual-captions) |
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- **Paper:** [Conceptual Captions: A Cleaned, Hypernymed, Image Alt-text Dataset For Automatic Image Captioning](https://www.aclweb.org/anthology/P18-1238/) |
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- **Leaderboard:** [Conceptual Captions leaderboard](https://ai.google.com/research/ConceptualCaptions/competition?active_tab=leaderboard)https://ai.google.com/research/ConceptualCaptions/leaderboard?active_tab=leaderboard |
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- **Point of Contact:** [Conceptual Captions e-mail](mailto:conceptual-captions@google.com) |
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### Dataset Summary |
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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. |
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### Usage |
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This instance of Conceptual Captions is in [webdataset](https://github.com/webdataset/webdataset/commits/main) .tar format. It can be used with webdataset library or upcoming releases of Hugging Face `datasets`. |
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...More Detail TBD |
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### Data Splits |
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This dataset was downloaded using img2dataset. Images resized on download if shortest edge > 512 to shortest edge = 512. |
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#### Train |
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* `cc3m-train-*.tar` |
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* Downloaded on 2021/12/22 |
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* 576 shards, 2905954 (of 3318333) samples |
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#### Validation |
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* `cc3m-validation-*.tar` |
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* Downloaded on 2023/12/13 (original validation set download in 2021 was corrupted) |
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* 16 shards, 13443 (of 15840) samples |
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## Additional Information |
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### Dataset Curators |
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Piyush Sharma, Nan Ding, Sebastian Goodman and Radu Soricut. |
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### Licensing Information |
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The dataset may be freely used for any purpose, although acknowledgement of |
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Google LLC ("Google") as the data source would be appreciated. The dataset is |
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provided "AS IS" without any warranty, express or implied. Google disclaims all |
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liability for any damages, direct or indirect, resulting from the use of the |
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dataset. |
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### Citation Information |
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```bibtex |
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@inproceedings{sharma2018conceptual, |
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title = {Conceptual Captions: A Cleaned, Hypernymed, Image Alt-text Dataset For Automatic Image Captioning}, |
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author = {Sharma, Piyush and Ding, Nan and Goodman, Sebastian and Soricut, Radu}, |
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booktitle = {Proceedings of ACL}, |
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year = {2018}, |
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} |
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``` |
