---
language:
- en
- th
- ru
- ja
- it
- de
- vi
- zh
- ar
- es
license: cc-by-4.0
size_categories:
- 100K<n<1M
task_categories:
- image-to-text
pretty_name: multilingual-coco
dataset_info:
  features:
  - name: cocoid
    dtype: int64
  - name: filename
    dtype: string
  - name: en
    sequence: string
  - name: th
    sequence: string
  - name: ru
    sequence: string
  - name: jp-stair
    sequence: string
  - name: it
    sequence: string
  - name: de
    sequence: string
  - name: vi
    sequence: string
  - name: cn
    sequence: string
  - name: jp-yj
    sequence: string
  - name: ar
    sequence: string
  - name: es
    sequence: string
  - name: image
    dtype: image
  splits:
  - name: train
    num_bytes: 13852882321.001
    num_examples: 82783
  - name: val
    num_bytes: 811780220
    num_examples: 5000
  - name: restval
    num_bytes: 5123622277.68
    num_examples: 30504
  - name: test
    num_bytes: 823623386
    num_examples: 5000
  download_size: 20265033594
  dataset_size: 20611908204.681
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: val
    path: data/val-*
  - split: restval
    path: data/restval-*
  - split: test
    path: data/test-*
---

# Multilingual Common Objects in Context (COCO) Dataset

This dataset is a collection of multiple language open-source captions of [COCO](https://cocodataset.org/) dataset. 

The split in this dataset is set according to [Andrej Karpathy's split](https://www.kaggle.com/datasets/shtvkumar/karpathy-splits) from `dataset_coco.json` file. The collection was created specifically for simplicity of use in training and evaluation pipeline by non-commercial and research purposes. The COCO images dataset is licensed under a Creative Commons Attribution 4.0 License.

# Multilanguage Feature's Code and Sources

If you use any part of the dataset, we recommend that you directly cite the original source for each language in this collection.

## English `en`

English caption is retrieved from the original [COCO dataset repository](http://images.cocodataset.org/annotations/stuff_annotations_trainval2017.zip)’s annotation file.

```
@misc{lin2015microsoftcococommonobjects,
      title={Microsoft COCO: Common Objects in Context}, 
      author={Tsung-Yi Lin and Michael Maire and Serge Belongie and Lubomir Bourdev and Ross Girshick and James Hays and Pietro Perona and Deva Ramanan and C. Lawrence Zitnick and Piotr Dollár},
      year={2015},
      eprint={1405.0312},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/1405.0312}, 
}
```

## Thai `th`

Thai captions were a part of Romrawin Chumpu’s work at NECTEC. This work is partially supported by the Program Management Unit for Human Resources & Institutional Development, Research and Innovation (PMU-B) [Grant number B04G640107]. <br> The captions were translated from English to Thai using google translate API. 

## Russian `ru`

Source: [AlexWortega/ru_COCO: Translated coco dataset with "facebook/wmt19-en-ru" model](https://github.com/AlexWortega/ru_COCO) <br> The captions were translated by using `facebook/wmt19-en-ru` model.

## Japanese STAIR `jp-stair`

Source: [STAIR Captions](https://stair-lab-cit.github.io/STAIR-captions-web/) <br> The captions were translated from English to Japanese using machine translation. 

```
@InProceedings{Yoshikawa2017,
  title     = {STAIR Captions: Constructing a Large-Scale Japanese Image Caption Dataset},
  booktitle = {Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)},
  month     = {July},
  year      = {2017},
  address   = {Vancouver, Canada},
  publisher = {Association for Computational Linguistics},
  pages     = {417--421},
  url       = {http://aclweb.org/anthology/P17-2066}
}
```

## Japanese YJ `jp-yj`

Source: [yahoojapan/YJCaptions](https://github.com/yahoojapan/YJCaptions) by Yahoo Japan. <br> Total captions of this Japanese version is around 26k captions. 

## Italian `it`

Source: [crux82/mscoco-it: A large scale dataset for Image Captioning in Italian](https://github.com/crux82/mscoco-it) <br> The captions were obtained through semi-automatic translation from English to Italian. 

## German `de`

Source: [Jotschi/coco-karpathy-opus-de · Datasets at Hugging Face](https://huggingface.co/datasets/Jotschi/coco-karpathy-opus-de) <br> The captions were translated by using [Helsinki-NLP/opus-mt-en-de · Hugging Face](https://huggingface.co/Helsinki-NLP/opus-mt-en-de) model. 

## Vietnamese `vi`

Source: [dinhanhx/coco-2017-vi · Datasets at Hugging Face](https://huggingface.co/datasets/dinhanhx/coco-2017-vi) <br> The captions were translated by VinAI from English to Vietnamese.

```
@software{dinhanhx_VisualRoBERTa_2022,
	title        = {{VisualRoBERTa}},
	author       = {dinhanhx},
	year         = 2022,
	month        = 9,
	url          = {https://github.com/dinhanhx/VisualRoBERTa}
}
```

## Chinese `cn`

Source: [li-xirong/coco-cn: Enriching MS-COCO with Chinese sentences and tags for cross-lingual multimedia tasks](https://github.com/li-xirong/coco-cn) <br> We selected only human generated dataset. 

## Arabic `ar`

Source: [canesee-project/Arabic-COCO: MS COCO captions in Arabic](https://github.com/canesee-project/Arabic-COCO) <br> The captions were fully translated with Google's Advanced Cloud Translation API.

## Spanish `es`

Source: [carlosGarciaHe/MS-COCO-ES: MS-COCO-ES is a dataset created from the original MS-COCO dataset. This project aims to provide a small subset of the original image captions translated into Spanish by humans annotators. This subset is composed by 20,000 captions of 4,000 images.](https://github.com/carlosGarciaHe/MS-COCO-ES) <br> The captions were translated by human.