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--- |
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dataset_info: |
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features: |
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- name: image |
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dtype: string |
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- name: medium |
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dtype: string |
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- name: museum |
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dtype: string |
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- name: museum_id |
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dtype: string |
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- name: subset |
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dtype: string |
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- name: width |
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dtype: int32 |
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- name: height |
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dtype: int32 |
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- name: product_size |
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dtype: int32 |
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- name: aspect_ratio |
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dtype: float32 |
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config_name: default |
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splits: |
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- name: train |
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download_size: ??? |
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dataset_size: ??? |
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configs: |
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- config_name: default |
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data_files: |
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- split: train |
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path: data/dataset.csv |
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download_mode: reuse_dataset_if_exists |
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pretty_name: MAMe Dataset |
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size_categories: |
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- 10K<n<100K |
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task_categories: |
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- image-classification |
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tags: |
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- image |
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- artwork |
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- museum |
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--- |
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## MAMe Dataset: Museum Artworks Medium |
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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). |
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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. |
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--- |
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### Paper |
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- 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) |
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- ArXiv Version: [MAMe: A Dataset for Multi-class Classification of Materials in Artworks](https://arxiv.org/pdf/2007.13693) |
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--- |
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### Dataset Variants: TODO |
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- **MAMe_small**: A toy version of the dataset, optimized for quick experimentation and lighter storage needs. |
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- **MAMe_original**: The original version of the dataset, meant for detailed tasks requiring precision in material classification. |
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--- |
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### Dataset Description |
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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. |
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- **Curated by**: HPAI |
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- **License**: The MAMe dataset is available for non-commercial research purposes only. |
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### Citation |
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If you use this dataset, please cite the following journal paper: |
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```bibtex |
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@article{pares2022mame, |
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title={The MAMe dataset: on the relevance of high resolution and variable shape image properties}, |
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author={Par{\'e}s, Ferran and Arias-Duart, Anna and Garcia-Gasulla, Dario and others}, |
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journal={Applied Intelligence}, |
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volume={52}, |
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number={12}, |
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pages={11703--11724}, |
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year={2022}, |
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publisher={Springer}, |
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doi={10.1007/s10489-021-02951-w} |
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} |
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``` |
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For accessibility purposes, you can also reference the ArXiv version: |
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```bibtex |
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@article{pares2020mame, |
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title={The MAMe Dataset: On the relevance of High Resolution and Variable Shape image properties}, |
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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}, |
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journal={arXiv preprint arXiv:2007.13693}, |
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year={2020}, |
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url = {https://arxiv.org/pdf/2007.13693} |
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} |
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``` |
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--- |
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### Dataset Card Authors |
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[Ferran Parés]([email protected]), [Anna Arias-Duart]([email protected]), [Dario Garcia-Gasulla]([email protected]) |
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### Dataset Card Contact |
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For more information or questions about this dataset, please contact the [HPAI organization](https://hpai.bsc.es). |
