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Dataset Card for [Dataset Name]

Dataset Summary

MS COCO is a large-scale object detection, segmentation, and captioning dataset. COCO has several features: Object segmentation, Recognition in context, Superpixel stuff segmentation, 330K images (>200K labeled), 1.5 million object instances, 80 object categories, 91 stuff categories, 5 captions per image, 250,000 people with keypoints.

As of now, there is only the 2014 subset (with Karpathy annotations and splits), but feel free to contribute the 2017 subset of COCO!

Supported Tasks and Leaderboards

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Languages

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Dataset Structure

Data Instances

Each instance has the following structure:

{
    'image': <PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=640x480 at 0x7F69C1BA8550>,
    'filepath': 'COCO_val2014_000000522418.jpg',
    'sentids': [681330, 686718, 688839, 693159, 693204],
    'filename': 'COCO_val2014_000000522418.jpg',
    'imgid': 1,
    'split': 'restval',
    'sentences': {
        'tokens': ['a', 'woman', 'wearing', 'a', 'net', 'on', 'her', 'head', 'cutting', 'a', 'cake'],
        'raw': 'A woman wearing a net on her head cutting a cake. ',
        'imgid': 1,
        'sentid': 681330
    },
    'cocoid': 522418
}

Data Fields

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Data Splits

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Dataset Creation

Curation Rationale

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Source Data

Initial Data Collection and Normalization

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Who are the source language producers?

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Annotations

Annotation process

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Who are the annotators?

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Personal and Sensitive Information

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Considerations for Using the Data

Social Impact of Dataset

[More Information Needed]

Discussion of Biases

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Other Known Limitations

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Additional Information

Dataset Curators

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Licensing Information

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Citation Information

[More Information Needed]

Contributions

Thanks to @VictorSanh for adding this dataset.

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