---
language:
- pt
size_categories:
- 10K<n<100K
task_categories:
- text-to-image
- image-to-text
- text-generation
pretty_name: nocaps Portuguese Translation
dataset_info:
  features:
  - name: image
    dtype: image
  - name: image_coco_url
    dtype: string
  - name: image_date_captured
    dtype: string
  - name: image_file_name
    dtype: string
  - name: image_height
    dtype: int32
  - name: image_width
    dtype: int32
  - name: image_id
    dtype: int32
  - name: image_license
    dtype: int8
  - name: image_open_images_id
    dtype: string
  - name: annotations_ids
    sequence: int32
  - name: annotations_captions
    sequence: string
  - name: image_domain
    dtype: string
  splits:
  - name: test
    num_bytes: 3342886710.0
    num_examples: 10600
  - name: validation
    num_bytes: 1422203749.0
    num_examples: 4500
  download_size: 4761190122
  dataset_size: 4765090459.0
configs:
- config_name: default
  data_files:
  - split: test
    path: data/test-*
  - split: validation
    path: data/validation-*
---


# 🎉 nocaps Dataset Translation for Portuguese Image Captioning

## 💾 Dataset Summary

nocaps Portuguese Translation, a multimodal dataset for Portuguese image captioning benchmark, each image accompanied by ten descriptive captions
that have been generated by human annotators for every individual image. The original English captions were rendered into Portuguese
through the utilization of the Google Translator API.

## 🧑‍💻 Hot to Get Started with the Dataset

```python
from datasets import load_dataset

dataset = load_dataset('laicsiifes/nocaps-pt-br')
```

## ✍️ Languages

The images descriptions in the dataset are in Portuguese.

## 🧱 Dataset Structure

### 📝 Data Instances

An example looks like below: 

```
{
  'image': <PIL.JpegImagePlugin.JpegImageFile image mode=L size=732x1024>,
  'image_coco_url': 'https://s3.amazonaws.com/nocaps/val/0013ea2087020901.jpg',
  'image_date_captured': '2018-11-06 11:04:33',
  'image_file_name': '0013ea2087020901.jpg',
  'image_height': 1024,
  'image_width': 732,
  'image_id': 0,
  'image_license': 0,
  'image_open_images_id': '0013ea2087020901',
  'annotations_ids': [0, 1, 2, 3, 4, 5, 6, 7, 8, 9],
  'annotations_captions': [
    'Um bebê está parado na frente de uma casa.',
    'Uma menina com uma jaqueta branca e sandálias.',
    'Uma criança está parada na frente de uma casa.',
    'Uma criança está vestindo uma camisa branca e parada em uma calçada lateral.',
    'Um garotinho está de fralda e com uma camisa branca.',
    'Uma criança usando fralda e sapatos está na calçada.',
    'Uma criança veste uma camisa de cor clara durante o dia.',
    'Uma criança parada na calçada com uma camisa.',
    'Foto em preto e branco de uma menina sorrindo.',
    'um bebê fofo está sozinho com camisa branca'
  ],
  'image_domain': 'in-domain'
}
```

### 🗃️ Data Fields

The data instances have the following fields:

- `image`: a `PIL.Image.Image` object containing the image.
- `image_coco_url`: a `str` containing the URL to the original image.
- `image_date_captured`: a `str` representing the date and time when the image was captured.
- `image_file_name`: a `str` containing the name of the image file.
- `image_height`: an `int` representing the height of the image in pixels.
- `image_width`: an `int` representing the width of the image in pixels.
- `image_id`: an `int` containing the unique identifier of the image.
- `image_license`: an `int` representing the license type of the image.
- `image_open_images_id`: a `str` containing the identifier for the image.
- `annotations_ids`: a `list` of `int` containing the unique identifiers of the annotations related to the image.
- `annotations_captions`: a `list` of `str` containing the captions describing the image.
- `image_domain`: a `str` indicating the domain of the image. It can be: `in-domain`, `near-domain` or `out-of-domain`.


## 📋 BibTeX entry and citation info

```bibtex
@misc{bromonschenkel2024nocapspt,
  title        = {nocaps Dataset Translation for Portuguese Image Captioning},
  author       = {Bromonschenkel, Gabriel and Oliveira, Hil{\'a}rio and Paix{\~a}o, Thiago M.},
  howpublished = {\url{https://huggingface.co/datasets/laicsiifes/nocaps-pt-br}},
  publisher    = {Hugging Face},
  year         = {2024}
}
```