region:us
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viewer: false
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# 

## Overview
- `Vision question Answer (VQA) dataset`: VQA is a new dataset containing open-ended questions about images. 
These questions require an understanding of vision, language and commonsense knowledge to answer.
- `Reference`: Split into small-train & small-val dataset from https://huggingface.co/datasets/Graphcore/vqa validation dataset

## Dataset Structure

### Data Instances

A data point comprises an image and its object annotations.

```
{'question': 'Where is he looking?',
 'question_type': 'none of the above',
 'question_id': 262148000,
 'image_id': 'images/COCO_val2014_000000262148.jpg',
 'answer_type': 'other',
 'label': {'ids': ['at table', 'down', 'skateboard', 'table'],
  'weights': [0.30000001192092896,
   1.0,
   0.30000001192092896,
   0.30000001192092896]}}
```

### Data Fields

- `question`: the question to be answered from the image
- `question_type`: 
- `image_id`: the path to the image the question refers to
- `answer_type`: 
- `label`: the annotations
  - `ids`: 
  - `weights`: 

  
### Data Splits

- `Training dataset` (1169)
- `Val dataset` (100)


## Usage
```
from datasets import load_dataset
dataset = load_dataset("SIS-2024-spring/coco_vqa_small_dataset")
```