Add dataset card

README.md

@@ -1,23 +1,96 @@
 ---
-dataset_info:
-  features:
-  - name: image
-    dtype: image
-  - name: label
-    dtype: string
-  - name: gesture_type
-    dtype: string
-  - name: label_id
-    dtype: int64
-  splits:
-  - name: train
-    num_bytes: 756277434.197
-    num_examples: 28431
-  download_size: 803008855
-  dataset_size: 756277434.197
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
+license: mit
+task_categories:
+- image-classification
+- zero-shot-image-classification
+language:
+- en
+tags:
+- bharatanatyam
+- mudra
+- hand-gestures
+- indian-classical-dance
+- computer-vision
+size_categories:
+- 10K<n<100K
 ---
+
+# Bharatanatyam Mudra Dataset
+
+## Dataset Description
+
+The Bharatanatyam Mudra Dataset contains **28,431 images** of hand gestures (mudras) from Bharatanatyam, a classical Indian dance form. The dataset was collected from 15 volunteers in a studio environment and includes both single-hand and double-hand gestures.
+
+### Dataset Statistics
+- **Total Images**: 28,431
+- **Single Hand Gestures (Asamyukta Hastas)**: 15,396 images across 29 classes
+- **Double Hand Gestures (Samyukta Hastas)**: 13,035 images across 21 classes
+- **Total Classes**: 50 different mudras
+
+## Dataset Structure
+
+The dataset is organized into 50 classes representing different mudras:
+
+### Single Hand Gestures (Asamyukta Hastas) - 29 classes
+- Pathaka, Tripathaka, Ardhapathaka, Mayura, Katrimukha
+- Ardhachandran, Aralam, Shukatundam, Mushti, Sikharam
+- Kapith, Katakamukha_1, Katakamukha_2, Katakamukha_3, Suchi
+- Chandrakala, Padmakosha, Sarpasirsha, Mrigasirsha, Simhamukham
+- Kangulam, Alapadmam, Mukulam, Chaturam, Bramaram
+- Hamsasyam, Hamsapaksham, Tamarachudam, Trishulam
+
+### Double Hand Gestures (Samyukta Hastas) - 21 classes
+- Anjali, Kapotham, Karkatta, Swastikam, Pushpaputam
+- Shivalinga, Katakavardhana, Kartariswastika, Sakata, Shanka
+- Chakra, Samputa, Pasha, Kilaka, Matsya
+- Kurma, Varaha, Garuda, Nagabandha, Khatva, Berunda
+
+## Data Fields
+
+- `image`: PIL Image of the mudra
+- `label`: String label of the mudra name
+- `label_id`: Numerical ID for the label
+- `gesture_type`: Either "single_hand" or "double_hand"
+
+## Usage
+
+```python
+from datasets import load_dataset
+
+# Load the dataset
+dataset = load_dataset("samarth/bharatanatyam-mudra-dataset")
+
+# Access the data
+train_data = dataset["train"]
+print(f"Number of samples: {len(train_data)}")
+print(f"Features: {train_data.features}")
+
+# Example: Get first image and label
+sample = train_data[0]
+image = sample["image"]
+label = sample["label"]
+print(f"Label: {label}")
+```
+
+## Applications
+
+This dataset can be used for:
+- Hand gesture recognition and classification
+- Cultural heritage preservation through AI
+- Computer vision research on hand pose estimation
+- Educational applications for learning Bharatanatyam
+- Transfer learning for other hand gesture datasets
+
+## Citation and Acknowledgments
+
+This data was collected as part of Ph.D. work done under the guidance of **Dr. Sunil T.T**, Professor, College of Engineering, Attingal, Thiruvananthapuram, Kerala, India.
+
+For original-sized images or additional information, please contact: **Jisha Raj R** at jisharajr@gmail.com
+
+## License
+
+This dataset is available under the MIT License.
+
+## Ethical Considerations
+
+This dataset was collected with the consent of volunteers in a controlled studio environment. The dataset represents traditional Indian cultural practices and should be used respectfully, particularly in research and educational contexts.