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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
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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
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Contributions
Thanks to @VictorSanh for adding this dataset.
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