Add dataset README with metadata

README.md

@@ -18,65 +18,6 @@ task_categories:
 task_ids:
 - multi-label-image-classification
 pretty_name: MER - Mars Exploration Rover Dataset
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
-  - split: val
-    path: data/val-*
-  - split: test
-    path: data/test-*
-  - split: few_shot_train_10_shot
-    path: data/few_shot_train_10_shot-*
-  - split: few_shot_train_15_shot
-    path: data/few_shot_train_15_shot-*
-  - split: few_shot_train_1_shot
-    path: data/few_shot_train_1_shot-*
-  - split: few_shot_train_20_shot
-    path: data/few_shot_train_20_shot-*
-  - split: few_shot_train_2_shot
-    path: data/few_shot_train_2_shot-*
-  - split: few_shot_train_5_shot
-    path: data/few_shot_train_5_shot-*
-dataset_info:
-  features:
-  - name: image
-    dtype: image
-  - name: label
-    sequence: int8
-  - name: feature_name
-    sequence: string
-  splits:
-  - name: train
-    num_bytes: 189511167.738
-    num_examples: 1762
-  - name: val
-    num_bytes: 48685102.0
-    num_examples: 443
-  - name: test
-    num_bytes: 78350787.0
-    num_examples: 739
-  - name: few_shot_train_10_shot
-    num_bytes: 12072390.0
-    num_examples: 128
-  - name: few_shot_train_15_shot
-    num_bytes: 16781171.0
-    num_examples: 175
-  - name: few_shot_train_1_shot
-    num_bytes: 1499051.0
-    num_examples: 16
-  - name: few_shot_train_20_shot
-    num_bytes: 21623151.0
-    num_examples: 220
-  - name: few_shot_train_2_shot
-    num_bytes: 2605778.0
-    num_examples: 30
-  - name: few_shot_train_5_shot
-    num_bytes: 6184131.0
-    num_examples: 67
-  download_size: 380702168
-  dataset_size: 377312728.73800004
 ---
 
 # MER - Mars Exploration Rover Dataset
@@ -87,7 +28,7 @@ A multi-label classification dataset containing Mars images from the Mars Explor
 
 * **License:** CC-BY-4.0 (Creative Commons Attribution 4.0 International)
 * **Version:** 1.0
-* **Date Published:** 2025-05-14
+* **Date Published:** 2025-10-22
 * **Cite As:** TBD
 
 ## Classes
@@ -132,13 +73,6 @@ The dataset contains the following classes:
 - **few_shot_train_20_shot**: 220 images
 - **few_shot_train_2_shot**: 30 images
 - **few_shot_train_5_shot**: 67 images
-- **partition_0.01x_partition**: 19 images
-- **partition_0.02x_partition**: 33 images
-- **partition_0.05x_partition**: 81 images
-- **partition_0.10x_partition**: 184 images
-- **partition_0.20x_partition**: 361 images
-- **partition_0.25x_partition**: 447 images
-- **partition_0.50x_partition**: 878 images
 
 ## Few-shot Splits
 
@@ -159,27 +93,6 @@ Few-shot configurations:
 - **20_shot.csv**
 - **2_shot.csv**
 - **5_shot.csv**
-## Partition Splits
-
-This dataset includes the following partition splits:
-
-- **partition_0.01x_partition**: 19 images
-- **partition_0.02x_partition**: 33 images
-- **partition_0.05x_partition**: 81 images
-- **partition_0.10x_partition**: 184 images
-- **partition_0.20x_partition**: 361 images
-- **partition_0.25x_partition**: 447 images
-- **partition_0.50x_partition**: 878 images
-
-Partition configurations:
-
-- **0.01x_partition.csv**
-- **0.02x_partition.csv**
-- **0.05x_partition.csv**
-- **0.10x_partition.csv**
-- **0.20x_partition.csv**
-- **0.25x_partition.csv**
-- **0.50x_partition.csv**
 ## Format
 
 Each example in the dataset has the following format:
@@ -187,8 +100,8 @@ Each example in the dataset has the following format:
 ```
 {
   'image': Image(...),  # PIL image
-  'labels': List[int],  # Multi-hot encoded binary vector (1 if class is present, 0 otherwise)
-  'feature_names': List[str],  # List of feature names (class short codes)
+  'label': List[int],  # Multi-hot encoded binary vector (1 if class is present, 0 otherwise)
+  'feature_name': List[str],  # List of feature names (class short codes)
 }
 ```
 
@@ -202,10 +115,10 @@ dataset = load_dataset("Mirali33/mb-surface_multi_label_cls")
 # Access an example
 example = dataset['train'][0]
 image = example['image']  # PIL image
-labels = example['labels']  # Multi-hot encoded binary vector
+label = example['label']  # Multi-hot encoded binary vector
 
 # Example of how to find which classes are present in an image
-present_classes = [i for i, is_present in enumerate(labels) if is_present == 1]
+present_classes = [i for i, is_present in enumerate(label) if is_present == 1]
 print(f"Classes present in this image: {present_classes}")
 ```