Update README.md

README.md

@@ -1,68 +1,47 @@
-pretty_name: MAMe Dataset
-task_categories:
-  - image-classification
-size_categories:
-  - 10K<n<100K
-language:
-  - en
-tags:
-  - image
-  - artwork
-  - museum
-configs:
-  - config_name: mame_dataset
-    data_files:
-      - path: data/dataset.csv
-        description: "Main dataset file containing all splits (train, val, test)"
-      - path: data/images/small.zip
-        description: "ZIP file containing all image files"
-      - path: data/labels.csv
-        description: "File containing label mappings"
+---
 dataset_info:
   features:
     - name: image
       dtype: string
-      description: "Filename of the image (e.g., '1234.jpg'). The actual image file is located in data/images/small.zip"
     - 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
+            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
-      description: "Indicates whether the sample belongs to 'train', 'val', or 'test' split"
     - name: width
       dtype: int32
     - name: height
@@ -70,4 +49,116 @@ dataset_info:
     - name: product_size
       dtype: int32
     - name: aspect_ratio
-      dtype: float32
+      dtype: float32
+configs:
+  - config_name: default
+    data_files:
+      - split: train
+        path: data/dataset.csv
+    download_mode: reuse_dataset_if_exists
+    download_size: ???
+    features:
+      - name: image
+        dtype: string
+      - name: medium
+        dtype: int64
+      - 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
+    dataset_size: ???
+    splits:
+      - name: train
+        num_bytes: ???
+        num_examples: ???
+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).