README.md

---
annotations_creators:
- machine-generated
language_creators:
- found
language:
- en
license:
- unknown
multilinguality:
- monolingual
size_categories:
- 100K<n<1M
source_datasets:
- extended|other-guesswhat
task_categories:
- visual-question-answering
task_ids:
- visual-question-answering
paperswithcode_id: compguesswhat
pretty_name: CompGuessWhat?!
dataset_info:
- config_name: compguesswhat-original
  features:
  - name: id
    dtype: int32
  - name: target_id
    dtype: int32
  - name: timestamp
    dtype: string
  - name: status
    dtype: string
  - name: image
    struct:
    - name: id
      dtype: int32
    - name: file_name
      dtype: string
    - name: flickr_url
      dtype: string
    - name: coco_url
      dtype: string
    - name: height
      dtype: int32
    - name: width
      dtype: int32
    - name: visual_genome
      struct:
      - name: width
        dtype: int32
      - name: height
        dtype: int32
      - name: url
        dtype: string
      - name: coco_id
        dtype: int32
      - name: flickr_id
        dtype: string
      - name: image_id
        dtype: string
  - name: qas
    sequence:
    - name: question
      dtype: string
    - name: answer
      dtype: string
    - name: id
      dtype: int32
  - name: objects
    sequence:
    - name: id
      dtype: int32
    - name: bbox
      sequence: float32
      length: 4
    - name: category
      dtype: string
    - name: area
      dtype: float32
    - name: category_id
      dtype: int32
    - name: segment
      sequence:
        sequence: float32
  splits:
  - name: train
    num_bytes: 123556580
    num_examples: 46341
  - name: validation
    num_bytes: 25441428
    num_examples: 9738
  - name: test
    num_bytes: 25369227
    num_examples: 9621
  download_size: 105349759
  dataset_size: 174367235
- config_name: compguesswhat-zero_shot
  features:
  - name: id
    dtype: int32
  - name: target_id
    dtype: string
  - name: status
    dtype: string
  - name: image
    struct:
    - name: id
      dtype: int32
    - name: file_name
      dtype: string
    - name: coco_url
      dtype: string
    - name: height
      dtype: int32
    - name: width
      dtype: int32
    - name: license
      dtype: int32
    - name: open_images_id
      dtype: string
    - name: date_captured
      dtype: string
  - name: objects
    sequence:
    - name: id
      dtype: string
    - name: bbox
      sequence: float32
      length: 4
    - name: category
      dtype: string
    - name: area
      dtype: float32
    - name: category_id
      dtype: int32
    - name: IsOccluded
      dtype: int32
    - name: IsTruncated
      dtype: int32
    - name: segment
      sequence:
      - name: MaskPath
        dtype: string
      - name: LabelName
        dtype: string
      - name: BoxID
        dtype: string
      - name: BoxXMin
        dtype: string
      - name: BoxXMax
        dtype: string
      - name: BoxYMin
        dtype: string
      - name: BoxYMax
        dtype: string
      - name: PredictedIoU
        dtype: string
      - name: Clicks
        dtype: string
  splits:
  - name: nd_valid
    num_bytes: 13510589
    num_examples: 5343
  - name: nd_test
    num_bytes: 36228021
    num_examples: 13836
  - name: od_valid
    num_bytes: 14051972
    num_examples: 5372
  - name: od_test
    num_bytes: 32950869
    num_examples: 13300
  download_size: 6548812
  dataset_size: 96741451
configs:
- config_name: compguesswhat-original
  data_files:
  - split: train
    path: compguesswhat-original/train-*
  - split: validation
    path: compguesswhat-original/validation-*
  - split: test
    path: compguesswhat-original/test-*
- config_name: compguesswhat-zero_shot
  data_files:
  - split: nd_valid
    path: compguesswhat-zero_shot/nd_valid-*
  - split: nd_test
    path: compguesswhat-zero_shot/nd_test-*
  - split: od_valid
    path: compguesswhat-zero_shot/od_valid-*
  - split: od_test
    path: compguesswhat-zero_shot/od_test-*
---

# Dataset Card for "compguesswhat"

## Table of Contents
- [Dataset Description](#dataset-description)
  - [Dataset Summary](#dataset-summary)
  - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
  - [Languages](#languages)
- [Dataset Structure](#dataset-structure)
  - [Data Instances](#data-instances)
  - [Data Fields](#data-fields)
  - [Data Splits](#data-splits)
- [Dataset Creation](#dataset-creation)
  - [Curation Rationale](#curation-rationale)
  - [Source Data](#source-data)
  - [Annotations](#annotations)
  - [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
  - [Social Impact of Dataset](#social-impact-of-dataset)
  - [Discussion of Biases](#discussion-of-biases)
  - [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
  - [Dataset Curators](#dataset-curators)
  - [Licensing Information](#licensing-information)
  - [Citation Information](#citation-information)
  - [Contributions](#contributions)

## Dataset Description

- **Homepage:** [https://compguesswhat.github.io/](https://compguesswhat.github.io/)
- **Repository:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
- **Paper:** https://arxiv.org/abs/2006.02174
- **Paper:** https://doi.org/10.18653/v1/2020.acl-main.682
- **Point of Contact:** [Alessandro Suglia](mailto:alessandro.suglia@gmail.com)
- **Size of downloaded dataset files:** 112.05 MB
- **Size of the generated dataset:** 271.11 MB
- **Total amount of disk used:** 383.16 MB

### Dataset Summary

CompGuessWhat?! is an instance of a multi-task framework for evaluating the quality of learned neural representations,
in particular concerning attribute grounding. Use this dataset if you want to use the set of games whose reference
scene is an image in VisualGenome. Visit the website for more details: https://compguesswhat.github.io

### Supported Tasks and Leaderboards

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Languages

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

## Dataset Structure

### Data Instances

#### compguesswhat-original

- **Size of downloaded dataset files:** 107.21 MB
- **Size of the generated dataset:** 174.37 MB
- **Total amount of disk used:** 281.57 MB

An example of 'validation' looks as follows.
```
This example was too long and was cropped:

{
    "id": 2424,
    "image": "{\"coco_url\": \"http://mscoco.org/images/270512\", \"file_name\": \"COCO_train2014_000000270512.jpg\", \"flickr_url\": \"http://farm6.stat...",
    "objects": "{\"area\": [1723.5133056640625, 4838.5361328125, 287.44476318359375, 44918.7109375, 3688.09375, 522.1935424804688], \"bbox\": [[5.61...",
    "qas": {
        "answer": ["Yes", "No", "No", "Yes"],
        "id": [4983, 4996, 5006, 5017],
        "question": ["Is it in the foreground?", "Does it have wings?", "Is it a person?", "Is it a vehicle?"]
    },
    "status": "success",
    "target_id": 1197044,
    "timestamp": "2016-07-08 15:07:38"
}
```

#### compguesswhat-zero_shot

- **Size of downloaded dataset files:** 4.84 MB
- **Size of the generated dataset:** 96.74 MB
- **Total amount of disk used:** 101.59 MB

An example of 'nd_valid' looks as follows.
```
This example was too long and was cropped:

{
    "id": 0,
    "image": {
        "coco_url": "https://s3.amazonaws.com/nocaps/val/004e21eb2e686f40.jpg",
        "date_captured": "2018-11-06 11:04:33",
        "file_name": "004e21eb2e686f40.jpg",
        "height": 1024,
        "id": 6,
        "license": 0,
        "open_images_id": "004e21eb2e686f40",
        "width": 768
    },
    "objects": "{\"IsOccluded\": [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], \"IsTruncated\": [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], \"area\": [3...",
    "status": "incomplete",
    "target_id": "004e21eb2e686f40_30"
}
```

### Data Fields

The data fields are the same among all splits.

#### compguesswhat-original
- `id`: a `int32` feature.
- `target_id`: a `int32` feature.
- `timestamp`: a `string` feature.
- `status`: a `string` feature.
- `id`: a `int32` feature.
- `file_name`: a `string` feature.
- `flickr_url`: a `string` feature.
- `coco_url`: a `string` feature.
- `height`: a `int32` feature.
- `width`: a `int32` feature.
- `width`: a `int32` feature.
- `height`: a `int32` feature.
- `url`: a `string` feature.
- `coco_id`: a `int32` feature.
- `flickr_id`: a `string` feature.
- `image_id`: a `string` feature.
- `qas`: a dictionary feature containing:
  - `question`: a `string` feature.
  - `answer`: a `string` feature.
  - `id`: a `int32` feature.
- `objects`: a dictionary feature containing:
  - `id`: a `int32` feature.
  - `bbox`: a `list` of `float32` features.
  - `category`: a `string` feature.
  - `area`: a `float32` feature.
  - `category_id`: a `int32` feature.
  - `segment`: a dictionary feature containing:
    - `feature`: a `float32` feature.

#### compguesswhat-zero_shot
- `id`: a `int32` feature.
- `target_id`: a `string` feature.
- `status`: a `string` feature.
- `id`: a `int32` feature.
- `file_name`: a `string` feature.
- `coco_url`: a `string` feature.
- `height`: a `int32` feature.
- `width`: a `int32` feature.
- `license`: a `int32` feature.
- `open_images_id`: a `string` feature.
- `date_captured`: a `string` feature.
- `objects`: a dictionary feature containing:
  - `id`: a `string` feature.
  - `bbox`: a `list` of `float32` features.
  - `category`: a `string` feature.
  - `area`: a `float32` feature.
  - `category_id`: a `int32` feature.
  - `IsOccluded`: a `int32` feature.
  - `IsTruncated`: a `int32` feature.
  - `segment`: a dictionary feature containing:
    - `MaskPath`: a `string` feature.
    - `LabelName`: a `string` feature.
    - `BoxID`: a `string` feature.
    - `BoxXMin`: a `string` feature.
    - `BoxXMax`: a `string` feature.
    - `BoxYMin`: a `string` feature.
    - `BoxYMax`: a `string` feature.
    - `PredictedIoU`: a `string` feature.
    - `Clicks`: a `string` feature.

### Data Splits

#### compguesswhat-original

|                      |train|validation|test|
|----------------------|----:|---------:|---:|
|compguesswhat-original|46341|      9738|9621|

#### compguesswhat-zero_shot

|                       |nd_valid|od_valid|nd_test|od_test|
|-----------------------|-------:|-------:|------:|------:|
|compguesswhat-zero_shot|    5343|    5372|  13836|  13300|

## Dataset Creation

### Curation Rationale

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Source Data

#### Initial Data Collection and Normalization

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

#### Who are the source language producers?

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Annotations

#### Annotation process

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

#### Who are the annotators?

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Personal and Sensitive Information

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

## Considerations for Using the Data

### Social Impact of Dataset

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Discussion of Biases

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Other Known Limitations

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

## Additional Information

### Dataset Curators

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Licensing Information

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Citation Information

```
@inproceedings{suglia-etal-2020-compguesswhat,
    title = "{C}omp{G}uess{W}hat?!: A Multi-task Evaluation Framework for Grounded Language Learning",
    author = "Suglia, Alessandro  and
      Konstas, Ioannis  and
      Vanzo, Andrea  and
      Bastianelli, Emanuele  and
      Elliott, Desmond  and
      Frank, Stella  and
      Lemon, Oliver",
    booktitle = "Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics",
    month = jul,
    year = "2020",
    address = "Online",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/2020.acl-main.682",
    pages = "7625--7641",
    abstract = "Approaches to Grounded Language Learning are commonly focused on a single task-based final performance measure which may not depend on desirable properties of the learned hidden representations, such as their ability to predict object attributes or generalize to unseen situations. To remedy this, we present GroLLA, an evaluation framework for Grounded Language Learning with Attributes based on three sub-tasks: 1) Goal-oriented evaluation; 2) Object attribute prediction evaluation; and 3) Zero-shot evaluation. We also propose a new dataset CompGuessWhat?! as an instance of this framework for evaluating the quality of learned neural representations, in particular with respect to attribute grounding. To this end, we extend the original GuessWhat?! dataset by including a semantic layer on top of the perceptual one. Specifically, we enrich the VisualGenome scene graphs associated with the GuessWhat?! images with several attributes from resources such as VISA and ImSitu. We then compare several hidden state representations from current state-of-the-art approaches to Grounded Language Learning. By using diagnostic classifiers, we show that current models{'} learned representations are not expressive enough to encode object attributes (average F1 of 44.27). In addition, they do not learn strategies nor representations that are robust enough to perform well when novel scenes or objects are involved in gameplay (zero-shot best accuracy 50.06{\%}).",
}
```


### Contributions

Thanks to [@thomwolf](https://github.com/thomwolf), [@aleSuglia](https://github.com/aleSuglia), [@lhoestq](https://github.com/lhoestq) for adding this dataset.