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---
dataset_info:
features:
- name: image
dtype: string
- name: medium
dtype:
class_label:
names:
0: Albumen photograph
1: Bronze
2: Ceramic
3: Clay
4: Engraving
5: Etching
6: Faience
7: Glass
8: Gold
9: Graphite
10: Hand-colored engraving
11: Hand-colored etching
12: Iron
13: Ivory
14: Limestone
15: Lithograph
16: Marble
17: Oil on canvas
18: Pen and brown ink
19: Polychromed wood
20: Porcelain
21: Silk and metal thread
22: Silver
23: Steel
24: Wood
25: Wood engraving
26: Woodblock
27: Woodcut
28: Woven fabric
- name: museum
dtype: string
- name: museum_id
dtype: string
- name: subset
dtype: string
- name: width
dtype: int32
- name: height
dtype: int32
- name: product_size
dtype: int32
- name: aspect_ratio
dtype: float32
configs:
- config_name: default
data_files:
- split: train
path: data/dataset.csv
download_mode: reuse_dataset_if_exists
download_size: ???
features:
image: string
medium: int64
museum: string
museum_id: string
subset: string
width: int32
height: int32
product_size: int32
aspect_ratio: float32
dataset_size: ???
pretty_name: MAMe Dataset
size_categories:
- 10K<n<100K
task_categories:
- image-classification
tags:
- image
- artwork
- museum
---
## MAMe Dataset: Museum Artworks Medium
The MAMe Dataset is an image classification dataset focused on the recognition of mediums in artworks and heritage held by museums (e.g., Oil on canvas, Bronze or Woodcut).
The classes considered in the MAMe dataset comprise a wide variety of mediums according to both interpretations of the term. These can range from simple material aspects (e.g., Bronze, Silver or Gold) to complex, high-level techniques (e.g., Faience, Woodblock or Woven fabric). The variety of relevant features in MAMe requires both attention to detail and to the overall image structure.
---
### Paper
- Journal Version: [Materials in Art and Museum Environment (MAMe): A Dataset for Art Material Recognition](https://link.springer.com/article/10.1007/s10489-021-02951-w)
- ArXiv Version: [MAMe: A Dataset for Multi-class Classification of Materials in Artworks](https://arxiv.org/pdf/2007.13693)
---
### Dataset Variants: TODO
- **MAMe_small**: A toy version of the dataset, optimized for quick experimentation and lighter storage needs.
- **MAMe_original**: The original version of the dataset, meant for detailed tasks requiring precision in material classification.
---
### Dataset Description
The MAMe dataset contains thousands of artworks from three different museums, and proposes a classification task consisting on differentiating between 29 mediums (i.e. materials and techniques) supervised by art experts.
- **Curated by**: HPAI
- **License**: The MAMe dataset is available for non-commercial research purposes only.
### Citation
If you use this dataset, please cite the following journal paper:
```bibtex
@article{pares2022mame,
title={The MAMe dataset: on the relevance of high resolution and variable shape image properties},
author={Par{\'e}s, Ferran and Arias-Duart, Anna and Garcia-Gasulla, Dario and others},
journal={Applied Intelligence},
volume={52},
number={12},
pages={11703--11724},
year={2022},
publisher={Springer},
doi={10.1007/s10489-021-02951-w}
}
```
For accessibility purposes, you can also reference the ArXiv version:
```bibtex
@article{pares2020mame,
title={The MAMe Dataset: On the relevance of High Resolution and Variable Shape image properties},
author={Par{\'e}s, Ferran and Arias-Duart, Anna and Garcia-Gasulla, Dario and Campo-Franc{\'e}s, Gema and Viladrich, Nina and Labarta, Jes{\'u}s and Ayguad{\'e}, Eduard},
journal={arXiv preprint arXiv:2007.13693},
year={2020},
url = {https://arxiv.org/pdf/2007.13693}
}
```
---
### Dataset Card Authors
[Ferran Parés]([email protected]), [Anna Arias-Duart]([email protected]), [Dario Garcia-Gasulla]([email protected])
### Dataset Card Contact
For more information or questions about this dataset, please contact the [HPAI organization](https://hpai.bsc.es). |