license:openrail region:us
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.
@article{DBLP:journals/corr/LinMBHPRDZ14,
  author    = {Tsung{-}Yi Lin and
               Michael Maire and
               Serge J. Belongie and
               Lubomir D. Bourdev and
               Ross B. Girshick and
               James Hays and
               Pietro Perona and
               Deva Ramanan and
               Piotr Doll{\'{a}}r and
               C. Lawrence Zitnick},
  title     = {Microsoft {COCO:} Common Objects in Context},
  journal   = {CoRR},
  volume    = {abs/1405.0312},
  year      = {2014},
  url       = {http://arxiv.org/abs/1405.0312},
  eprinttype = {arXiv},
  eprint    = {1405.0312},
  timestamp = {Mon, 13 Aug 2018 16:48:13 +0200},
  biburl    = {https://dblp.org/rec/journals/corr/LinMBHPRDZ14.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}
---
license: openrail
---

Usage:

```
from datasets import load_dataset
coco_dataset = load_dataset("nyanko7/coco-hosted")
```

Each instance has the following structure:

```
{
    'image': <PIL.JpegImagePlugin.JpegImageFile>,
    '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
}
```