# COCO 2017 image captions in Vietnamese

The dataset is firstly introduced in [dinhanhx/VisualRoBERTa](https://github.com/dinhanhx/VisualRoBERTa/tree/main). 
I use VinAI tools to translate [COCO 2027 image caption](https://cocodataset.org/#download) (2017 Train/Val annotations) from English to Vietnamese. 
Then we merge [UIT-ViIC](https://arxiv.org/abs/2002.00175) dataset into it. 
To load the dataset, one can take a look at [this code in VisualRoBERTa](https://github.com/dinhanhx/VisualRoBERTa/blob/main/src/data.py#L22-L100) or [this code in Velvet](https://github.com/dinhanhx/velvet/blob/main/velvet/dataset/coco.py).

I provide both English original and Vietnamese version (including UIT-ViIC). 

⚠ Note:
- UIT-ViIC splits are originated from `en/captions_train2017.json`. Therefore, I combine all UIT-ViIC splits then I merge into `vi/captions_train2017_trans.json`. As a result, I get `captions_train2017_trans_plus.json`.
- `vi/captions_train2017_trans.json` and `vi/captions_val2017_trans.json` are VinAI-translated from the ones in `en/`.
task_categories:image-to-text task_ids:image-captioning language:vi language:en license:unknown coco coco-2017-vi Vietnamese arxiv:2002.00175 region:us
{"language": ["vi", "en"], "license": "unknown", "task_categories": ["image-to-text"], "task_ids": ["image-captioning"], "pretty_name": "COCO 2017 image captions in Vietnamese", "source-datasets": ["ms coco"], "tags": ["coco", "coco-2017-vi", "Vietnamese"]}
TAGS
#task_categories-image-to-text #task_ids-image-captioning #language-Vietnamese #language-English #license-unknown #coco #coco-2017-vi #Vietnamese #arxiv-2002.00175 #region-us 

# COCO 2017 image captions in Vietnamese

The dataset is firstly introduced in dinhanhx/VisualRoBERTa. 
I use VinAI tools to translate COCO 2027 image caption (2017 Train/Val annotations) from English to Vietnamese. 
Then we merge UIT-ViIC dataset into it. 
To load the dataset, one can take a look at this code in VisualRoBERTa or this code in Velvet.

I provide both English original and Vietnamese version (including UIT-ViIC). 

 Note:
- UIT-ViIC splits are originated from 'en/captions_train2017.json'. Therefore, I combine all UIT-ViIC splits then I merge into 'vi/captions_train2017_trans.json'. As a result, I get 'captions_train2017_trans_plus.json'.
- 'vi/captions_train2017_trans.json' and 'vi/captions_val2017_trans.json' are VinAI-translated from the ones in 'en/'.
# COCO 2017 image captions in Vietnamese

The dataset is firstly introduced in dinhanhx/VisualRoBERTa. 
I use VinAI tools to translate COCO 2027 image caption (2017 Train/Val annotations) from English to Vietnamese. 
Then we merge UIT-ViIC dataset into it. 
To load the dataset, one can take a look at this code in VisualRoBERTa or this code in Velvet.

I provide both English original and Vietnamese version (including UIT-ViIC). 

 Note:
- UIT-ViIC splits are originated from 'en/captions_train2017.json'. Therefore, I combine all UIT-ViIC splits then I merge into 'vi/captions_train2017_trans.json'. As a result, I get 'captions_train2017_trans_plus.json'.
- 'vi/captions_train2017_trans.json' and 'vi/captions_val2017_trans.json' are VinAI-translated from the ones in 'en/'.
TAGS
#task_categories-image-to-text #task_ids-image-captioning #language-Vietnamese #language-English #license-unknown #coco #coco-2017-vi #Vietnamese #arxiv-2002.00175 #region-us 
 # COCO 2017 image captions in Vietnamese

The dataset is firstly introduced in dinhanhx/VisualRoBERTa. 
I use VinAI tools to translate COCO 2027 image caption (2017 Train/Val annotations) from English to Vietnamese. 
Then we merge UIT-ViIC dataset into it. 
To load the dataset, one can take a look at this code in VisualRoBERTa or this code in Velvet.

I provide both English original and Vietnamese version (including UIT-ViIC). 

 Note:
- UIT-ViIC splits are originated from 'en/captions_train2017.json'. Therefore, I combine all UIT-ViIC splits then I merge into 'vi/captions_train2017_trans.json'. As a result, I get 'captions_train2017_trans_plus.json'.
- 'vi/captions_train2017_trans.json' and 'vi/captions_val2017_trans.json' are VinAI-translated from the ones in 'en/'.
passage: TAGS
#task_categories-image-to-text #task_ids-image-captioning #language-Vietnamese #language-English #license-unknown #coco #coco-2017-vi #Vietnamese #arxiv-2002.00175 #region-us 
# COCO 2017 image captions in Vietnamese

The dataset is firstly introduced in dinhanhx/VisualRoBERTa. 
I use VinAI tools to translate COCO 2027 image caption (2017 Train/Val annotations) from English to Vietnamese. 
Then we merge UIT-ViIC dataset into it. 
To load the dataset, one can take a look at this code in VisualRoBERTa or this code in Velvet.

I provide both English original and Vietnamese version (including UIT-ViIC). 

 Note:
- UIT-ViIC splits are originated from 'en/captions_train2017.json'. Therefore, I combine all UIT-ViIC splits then I merge into 'vi/captions_train2017_trans.json'. As a result, I get 'captions_train2017_trans_plus.json'.
- 'vi/captions_train2017_trans.json' and 'vi/captions_val2017_trans.json' are VinAI-translated from the ones in 'en/'.