README.md

---
annotations_creators:
- machine-generated
language:
- en
language_creators:
- machine-generated
license:
- cc-by-4.0
multilinguality:
- monolingual
pretty_name: CLEVR-Math - Compositional language, visual, and mathematical reasoning
size_categories:
#- 100K<n<1M
source_datasets: [clevr]
tags:
- reasoning
- neuro-symbolic
- multimodal
task_categories:
- visual-question-answering
task_ids:
- visual-question-answering
---

# Dataset Card for CLEVR-Math

## Table of Contents
- [Table of Contents](#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)
- [Considerations for Using the Data](#considerations-for-using-the-data)
  - [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:**
- **Repository:*https://github.com/dali-does/clevr-math*
- **Paper:*https://arxiv.org/abs/2208.05358*
- **Leaderboard:**
- **Point of Contact:*dali@cs.umu.se*

### Dataset Summary

Dataset for compositional multimodal mathematical reasoning based on CLEVR.

#### Loading the data, preprocessing text with CLIP

```
from transformers import CLIPPreprocessor
from datasets import load_dataset, DownloadConfig


dl_config = DownloadConfig(resume_download=True,
        num_proc=8,
        force_download=True)

# Load 'general' instance of dataset
dataset = load_dataset('dali-does/clevr-math', download_config=dl_config)

# Load version with only multihop in test data
dataset_multihop = load_dataset('dali-does/clevr-math', 'multihop',
                                download_config=dl_config)


model_path = "openai/clip-vit-base-patch32"
extractor = CLIPProcessor.from_pretrained(model_path)
def transform_tokenize(e):
  e['image'] = [image.convert('RGB') for image in e['image']]
  return extractor(text=e['question'],
                           images=e['image'],
                           padding=True)

dataset = dataset.map(transform_tokenize,
                      batched=True,
                      num_proc=8,
                      padding='max_length')

dataset_subtraction = dataset.filter(lambda e:
        e['template'].startswith('subtraction'), num_proc=4)
```


### Supported Tasks and Leaderboards

Leaderboard will be announced at a later date.

### Languages

The dataset is currently only available in English. To extend the dataset to other languages, the CLEVR templates must be rewritten in the target language.

## Dataset Structure

### Data Instances

* `general` containing the default version with multihop questions in train and test
* `multihop` containing multihop questions only in test data to test generalisation of reasoning


### Data Fields


```
features = datasets.Features(
  {
    "template": datasets.Value("string"),
    "id": datasets.Value("string"),
    "question": datasets.Value("string"),
    "image": datasets.Image(),
    "label": datasets.Value("int64")
  }
)
```

### Data Splits

train/val/test

## Dataset Creation

Data is generated using code provided with the CLEVR-dataset, using blender and templates constructed by the dataset curators.


## Considerations for Using the Data

### Other Known Limitations

[More Information Needed]

## Additional Information

### Dataset Curators

Adam Dahlgren Lindström - dali@cs.umu.se

### Licensing Information

Licensed under Creative Commons Attribution Share Alike 4.0 International (CC-by 4.0).
### Citation Information

[More Information Needed]

```
@misc{https://doi.org/10.48550/arxiv.2208.05358,
  doi = {10.48550/ARXIV.2208.05358},
  url = {https://arxiv.org/abs/2208.05358},
  author = {Lindström, Adam Dahlgren and Abraham, Savitha Sam},
  keywords = {Machine Learning (cs.LG), Computation and Language (cs.CL), Computer Vision and Pattern Recognition (cs.CV), FOS: Computer and information sciences, FOS: Computer and information sciences, I.2.7; I.2.10; I.2.6; I.4.8; I.1.4},
  title = {CLEVR-Math: A Dataset for Compositional Language, Visual, and Mathematical Reasoning},
  publisher = {arXiv},
  year = {2022},
  copyright = {Creative Commons Attribution Share Alike 4.0 International}
}
```

### Contributions

Thanks to [@dali-does](https://github.com/dali-does) for adding this dataset.