license:apache-2.0 region:us
# VQA

## What is VQA?
VQA is a new dataset containing open-ended questions about images. These questions require an understanding of vision, language and commonsense knowledge to answer.
- 265,016 images (COCO and abstract scenes)
- At least 3 questions (5.4 questions on average) per image
- 10 ground truth answers per question
- 3 plausible (but likely incorrect) answers per question
- Automatic evaluation metric

## Dataset
Details on downloading the latest dataset may be found on the [download webpage](https://visualqa.org/download.html).

## Usage
```python
from datasets import load_dataset

raw_datasets = load_dataset(
                "vqa.py", 
                "base",
                cache_dir="huggingface_datasets", 
                data_dir="data",
                ignore_verifications=True,
            )

dataset_train = raw_datasets["train"]

for item in dataset_train:
    print(item)
    exit()
```

v2 = v2.real + v2.abstract (v2.abstract == v1.abstract)
v1 = v1.real + v1.abstract
v2.abstract.balanced.bin
```
@InProceedings{balanced_vqa_v2,
author = {Yash Goyal and Tejas Khot and Douglas Summers{-}Stay and Dhruv Batra and Devi Parikh},
title = {Making the {V} in {VQA} Matter: Elevating the Role of Image Understanding in {V}isual {Q}uestion {A}nswering},
booktitle = {Conference on Computer Vision and Pattern Recognition (CVPR)},
year = {2017},
}
```

```
@InProceedings{balanced_binary_vqa,
author = {Peng Zhang and Yash Goyal and Douglas Summers{-}Stay and Dhruv Batra and Devi Parikh},
title = {{Y}in and {Y}ang: Balancing and Answering Binary Visual Questions},
booktitle = {Conference on Computer Vision and Pattern Recognition (CVPR)},
year = {2016},
}
```

```
@InProceedings{{VQA},
author = {Stanislaw Antol and Aishwarya Agrawal and Jiasen Lu and Margaret Mitchell and Dhruv Batra and C. Lawrence Zitnick and Devi Parikh},
title = {{VQA}: {V}isual {Q}uestion {A}nswering},
booktitle = {International Conference on Computer Vision (ICCV)},
year = {2015},
}
```
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license: apache-2.0
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