Datasets:

dali-does
/

clevr-math

	---
	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.